Longevity

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Unlocking the brain's longevity potential:

Longevity Neurotech

Table of Contents:

Foreword by NTX Services

Executive summary

Introduction: Biologically aging brain – shifting the focus to neurotechnology?

Part 1: Brain monitoring technologies and neurofeedback

Part 2: Neuromodulation

Part 3: Neuroimaging

Part 4: Brain computer interface 

Part 5: Advancing neurotechnologies

Part 6: Investing in neurotechnologies

Part 7: NTX Services industry view

Trailblazers

References

Author

Natasza Klas

Scientific Researcher
Market Intelligence Unit, Longevity.Technology
Contributor

Daragh Campbell

Head of Research
Market Intelligence Unit, Longevity.Technology

Neurotechnology – or Neurotech – while still an emerging industry, has attracted both major capital investments, and extensive media coverage in recent years. As tech relentlessly searches for the next “big tech platform” in the aftermath of the smartphone era [1], we propose that the answer may lie within our own minds. At NTX Services, we define Neurotechnology as any technological intervention that interacts with the brain or central nervous system either directly or indirectly, and as Neurotech attempts to integrate human and machine to enhance both, applications of the technology are broad ranging.

Often described as a new field, Neurotech is actually based on decades of academic research, previously held back from commercialization at scale due to technological limitations, and slow changes in government policies and regulations. Although humans have been researching the brain and its bioelectrical signals since the 1600s [2], the first major breakthrough in Neurotech was the invention of the electroencephalogram (EEG) by Hans Berger in 1929 [3]. Since this initial invention, several key developments have influenced the evolution of the industry until 2016, when Neuralink was founded [4]. Elon Musk backed this early venture, touting the idea of merging biological and machine intelligence and declaring in a Vanity Fair article “for a meaningful partial-brain interface, I think we’re roughly four or five years away,” [5] thus bringing the concept of brain implants and (by extension) Neurotech in general into mainstream conversations.

As Neurotech lies at the intersection of neuroscience, engineering (electrical, mechanical, software) and AI/Data Science, it has been influenced by innovations in these ancillary industries. Beyond the innovative startups in the industry today, large medical device manufacturers like Medtronic have also had a huge impact on the field of Neurotechnology, by paving the path forward for many of today’s startups since the 1960s and are likely to remain important players through new product development and through M&A activity.

Not only does Neurotechnology encompass a wide variety of technologies, but it can also be applied to a diverse array of industries. Due to its broad applications, this field could play a critical role in improving the human experience across multiple dimensions. Today, Neurotech is used predominantly in Healthcare applications, but it also has documented use cases in the Entertainment, Defense, Automotive, Wellness and Financial Services industries.

Given both the breadth and depth of applications, investor interest in Neurotechnology has been rising steadily over the past ten years. NTX Services’ extended industry view shares the breakdown in deal activity, sources of capital, types of technologies and end applications over the past ten years to give readers a sense of the maturity of the industry, sources of capital and applications that have attracted the most capital over the past ten years.

Despite the enormous potential of Neurotechnology, consumer adoption has been historically low for a number of reasons for both Consumer and Clinical applications. Companies producing consumer-facing products can find reaching their target market challenging, while companies producing clinical products and solutions can face difficulties in development and distribution. However, these limiting factors are slowly evolving due to structural trends like the increased consumerization of healthcare, recent improvements in the reimbursement landscape for digital medicine services and a drive towards increased personalization.

As with many novel technologies, several key policy changes have helped Neurotech companies grow and expand worldwide, such as the launch of the BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative in the US in 2013 [6]. and the Advanced Research Projects Agency for Health (ARPA-H), which was recently approved by the US Congress with a $1-billion-dollar budget [7]. Similarly [8], China also launched a similar initiative, the China Brain Project, with a budget of approximately US$ 15.8 billion.

Beyond national-level projects, supra-national projects are also underway. For example, the International Brain Initiative whose signatories include Japan, South Korea, the US, Australia, and newer members China and Canada was established in 2017 [9].

As nations develop policies regarding, and engage with, the Neurotechnology industry, regulators are not far behind. The FDA is a global leader on the regulation of medical devices and products, often setting a precedent that equivalent institutions in other countries tend to follow. As such, the FDA has had a clearly delineated Standards and Guidance for Neurological Devices (which issues guidelines related to biocompatibility, animal studies, sterility, pyrogenicity, etc.) publicly available since 2019 [10]. In addition to this general standard, the FDA also issued a guideline titled Implanted BCI Devices for Patients with Paralysis or Amputation on May 20, 2021 [11], reflecting the importance the US has given to Neurotech solutions and recognizing the unique issues of different devices and their therapeutic uses.

As Neurotechnology applications can not only collect data from the brain, but also directly affect brain function, there are a number of ethical issues that arise with continued industry growth. The two primary issues are privacy concerns, and the “Black Box” problem that can arise from heavy reliance on AI applications. Industry players are currently taking a proactive approach to these issues by engaging with discussions on Neuro Ethics.

Some general trends in the Neurotech industry are the exploration of new avenues to use neural implants, and an overall increase in patenting activity. Traditionally, neural implants have only been used to treat brain injuries and restore function to damaged components of the brain; recently however, researchers have been exploring the use of neural implants to treat major mental health conditions like major depression, OCD, addiction, pain, and more [12]. The OECD reported that between 2008 to 2016, investors in the US filed for 7,775 patents in Neurotechnology, reflecting the pace of innovation in this industry [13]. The same report stated that China filed 3,226 patents in the same time period, underscoring the point that continued innovation in this industry is a global undertaking, not a local one.

The future of Neurotechnology is bright and dynamic due to the continual development of new devices, novel applications, and the continued growth of Neurotech companies across both invasive and non-invasive applications. The field is likely to continue exploring multi-modal applications of technologies in order to improve the human experience. Some examples of this in the non-invasive devices space are the partnership between Muse and RendeVR that will explore the connection between virtual reality (VR) and Neurotech to improve care for seniors [14], and Snap’s recent acquisition of NextMind, which aims to drive the company’s long-term augmented reality (AR) research and develop future models of Snap’s AR glasses [15].

Future projects and research will also look to minimize risks associated with implantable devices and reduce invasive procedures to simple out-patient procedures. Companies like Neurosoft Bioelectronics and Inbrain Neuroelectronics in Europe are already looking to explore safer materials and form factors (such as implantable electrode materials, shape, size and placement) to use in invasive procedures that may reduce side-effects associated with traditional invasive technologies. Companies like Precision Neuroscience are developing products that can be placed beneath the skull or under the skin in a simple out-patient procedure, which could feasibly reduce hesitancy towards implantable solutions among prospective patients.

In addition to improving invasive solutions, the Neurotech industry is also coming up with new and/or improved non-invasive solutions to complex problems, through both hardware and/or software innovations. As big tech players like Meta are making breakthroughs in non-invasive thought-to-text solutions through its Facebook Reality Labs in the US [16], similar efforts are also underway in countries like Russia [17].

Companies like CortexBCI and Neeuro in Asia are developing therapeutics that help address the challenge of the acute shortage of home healthcare workers for widespread conditions that impact quality of life like Cerebral Palsy and ADHD, while companies like Evoked Response, NeuroGeneces and BrainKey aim to improve consumer wellness and empower the consumer to take their health into their own hands in the US.

The industry will also continue the development of consumer devices that improve human performance that can be easily integrated into a consumer’s daily life, such as the headphone-based device by Eno in Canada that aims to improve focus for knowledge workers.

As startups continue to create new products in the field, there will also be an increase in the number of companies like AE Studio in the US and mBrainTrain in Europe that look to improve data collection, processing, and algorithms for both research institutions and startups. These companies provide value-add through hardware and/or software solutions, thereby improving both the quality of novel solutions and reducing the cost of developing these solutions for emerging companies and/or research institutions in the field.

Finally, it is likely that there will be greater M&A activity in the Neurotech industry, though it is still too early to address the possibility of a broader industry consolidation. To this day, Neurotech has been thought of as emerging tech – as such, capital raises remain the dominant deal activity in this sector.

That said, it is worth noting that Headspace’s acquisition of Ginger. in 2021 at US$ 3 billion was the single largest deal in the Neurotech industry that year [18]. Industry pioneers like Blackrock Neurotech are also starting to make strategic investments in companies whose product portfolio can improve or further develop their own solutions [19]. NTX Services’ own review of M&A Activity in Neurotech also suggests that this type of activity has been increasing over the past decade.

As this field continues to emerge and grow, it is likely that many more strategic investors will become involved as they begin exploring the benefits of adding this novel technology into their existing service portfolios and/or products, and thereby help in taking the Neurotech industry and its products and solutions mainstream. This should also naturally also improve exit opportunities for startups in the field.

Adam Sefler,
CPA, CFA

Co-Founder & Chief Executive Officer

Radhika Gupta, MBA, CFA
Chief Operating Officer

Pawel Soluch PhD Study
MSc Neuropsychology Principal

  • The human lifespan has increased considerably; however, despite this rise in life expectancy, the same cannot be said for healthspan or the proportion of life a person spends in good health. This is largely due to an unmatched progress made in treating chronic age-related disease, including those affecting the brain. As life expectancy rises, there is a growing number of people living with debilitating neurodegenerative diseases, brain injury and damage, psychiatric conditions and mental health disorders.
  • Dementia is one of the leading threats to healthy old age and a key contributing factor to the rising healthcare pressures and costs associated with increasing life expectancies. Cases of dementia alone are estimated to rise to $78 million by 2030 and 139 million by 2050, leading to a global cost of $2.8 trillion by 2030. Similarly, after the age of 45 the risk of stroke doubles with every decade and 70% of strokes occur after the age of 65.
  • The economic, societal and individual impact of an aging population that experience neurological disorders is already significant and will increasingly place heavy demands on society and health care systems.
  • As the rise in neurological conditions forms the biggest threat, and, as the current treatment strategies for disorders related to the biologically aging brain mostly consist of symptoms management, it is essential to shift the focus elsewhere, and neurotechnology could offer the needed avenue to address this crisis.
  • Neurotechnology offers a unique solution in the face of an aging population, and the associated rise in neurological conditions, because it can improve detection and diagnosis of the conditions, facilitate their treatment, and maybe even provide a solution for their prevention.
  • Defined as the assembly of methods and technologies developed to help understand and improve brain function, neurotechnology brings together the fields of neuroscience, engineering and technology. It can be categorised into 5 main branches: Neuromodulation, Neuromonitoring/feedback, Neuroimaging, BCI and Advancing Neurotechnologies.
  • The recent developments in neurotechnology are becoming more sophisticated and are opening more opportunities to understand the changes that occur in the brain with age and to address the many neurological conditions which are resistant to pharmacological or therapeutic interventions.
  • Neurotechnologies are increasingly being translated from clinical setting into portable, cost and user-friendly at home devices. These advances could allow people to monitor their own brain waves and interface their brains with external devices creating a whole new market for neurotech: wearable devices targeted to the consumer that encompass markets such as the wellness industry, neuro-gaming, neuro-sport and ed-neurotech.
  • Although neurotechnologies can drastically improve our lives, they also raise many ethical issues which will have to be carefully managed to ensure that we can enjoy their benefits in a safe way.

The human lifespan has increased considerably, largely due to better health care and hygiene, healthier lifestyles, sufficient food, improved medical care and reduced child mortality [20]. However, despite this rise in life expectancy, the same cannot be said for healthspan or the proportion of life a person spends in good health.

This is largely due to an unmatched progress made in treating chronic age-related disease including those affecting the brain [21]. As life expectancy rises, there is a growing number of people living with debilitating neurodegenerative diseases, brain injury and damage, psychiatric conditions and mental health disorders.

This will lead to a large financial cost to the government and society and an enormous emotional cost to family and the individual.

Healthcare and societal burden of an aging population

The increase in lifespan is leading to major demographic shifts in the world, which are likely to have a significant consequence on healthcare systems, the economy and society.

About 5 years ago, for the first time, the number of people over 65 started to outnumber the children under 5 years of age; this was driven by both falling fertility rates and an increase in life expectancy.

As people become increasingly less likely to have children, the elderly population have smaller family networks to care for them; in addition, this further driven by higher rates of migration of younger family members [22].This means that increasingly, elderly people may need to depend on social support, with increasing numbers being admitted to specialised care facilities. Consequently, the working population will end up paying more to support the elderly and higher costs of healthcare, social care and retirement programmes [23].

To sustain this long-term, there may eventually be a need for workers to extend their working lives for longer and retire later in life to mitigate some of the pressures societies will face. In some cases, the misconceptions associated with the older work force and their work performance compared with younger workforces can lead people to feel pressured to retire earlier. To encourage workers to stay in work longer, these perceptions will need to change [23].

As the demand for healthcare rise with age, countries will have to allocate more money to healthcare spending and reconsider how healthcare is delivered (Figure 1) [24-26]

Aging population and epidemiological transition

The “epidemiologic transition” describes the change where chronic and degenerative diseases are becoming the leading causes of death, overtaking infectious and acute diseases [22]. Death rates from dementia are continuing to rise, whereas the death rate for stroke, heart disease and some cancers have seen a decline [27].

Dementia is one of the leading threats to healthy old age and a key contributing factor to the rising healthcare pressures and costs associated with increasing life expectancies. Cases of dementia alone are estimated to rise to 78 million by 2030 and 139 million by 2050, leading to a global cost of $2.8 trillion by 2030 [28].

Presently, no cure exists for dementia and, as it is a degenerative disease, the patient will experience worsening of symptoms with time leading to increasing need for dependency [29]. The impact the condition has on an individual is vast and has a major impact on the person’s quality of life affecting various domains of the person’s life as shown in Figure 2. As dementia is a progressive condition, with time, it will amount increasing cost as people will eventually require constant care which creates a huge societal burden and economic cost [22].

Worldwide, dementia disproportionately impacts women with the overall burden of diseases being ~60% higher in women and with women making up 65% of the total death toll [30].

Although the death rate has decreased, increased lifespan and increasing prevalence of hypertension, diabetes, obesity and cardiovascular diseases has led to increase incidence of stroke [31]. After the age of 45 the risk of stroke doubles with every decade and 70% of strokes occur after the age of 65. The impact that stroke will have on an individual’s life can massively vary, however, of those that do survive [32, 33]:

  • Nearly 50% will experience moderate to severe neurological deficit.
  • 50% will become chronically disabled.
  • 30% cannot walk unassisted.
  • 25% become dependent on assistance in their daily activities.

The sudden and often unforeseen nature of stroke often leaves the person and their family unprepared for the disability that follows and the extensive rehabilitation process. The loss of independence is a major contributor to the poor quality of life following a stroke and often leads to development of emotional changes and mood disorders [34]. The NHS Long Term Plan predicts that the number of stroke survivors living with a disability will increase by a third by 2035 [35].

The economic, societal and individual impact of an aging population that experience neurological disorders is already significant and will increasingly place heavy demands on society and health care systems.

The biologically aging brain and its changes.

Physical and Physiological changesIndications
Neurodegenerative∙ Parkinson’s
∙ Amyotrophic lateral sclerosis
∙ Alzheimer’s disease and other dementias
∙ Lewy body dementia
Neurological∙ Stroke
∙ Chronic pain conditions
∙ Sleep disorders
Deafness and Auditory∙ Age-related hearing loss
∙ Tinnitus
∙ Auditory neuropathy
Blindness / visual∙ Glaucoma
∙ Macular degeneration
∙ Diabetic retinopathy
∙ Cataract

Hallmark of brain aging

Genetics
  • Glial cell activation and inflammation
  • Mitochondrial dysfunction
  • Impaired adaptive stress response signalling
Environment
  • Impaired molecular waste disposal
  • Oxidative damage
  • Dysregulated neuronal calcium homeostasis
Lifestyle
  • Stem cell exhaustion
  • Impaired DNA repair
  • Aberrant neuronal network activity

Longevity is determined by a complicated interplay of three main factors: genetic, environmental and lifestyle. Whilst DNA may be seen as the ‘master code’ for health and longevity, there are many modifiable factors that impact the rate of aging such as supplementation, exercise, diet, sleep and exposure to environmental factors.

These three things impact the body at a cellular and molecular level. Your genetic code is written into every cell of the body and can determine our risk for certain diseases and disorders, both mental and physical. Subsequent studies have continued to find connections between our genetic profiles and our likelihood of developing health problems, such as Alzheimer’s disease.

However, this is only half the story – lifestyles and the environments can directly impact our genetics and many other components at a cellular level. The relationship is dynamic, as our genetics can also determine our response to lifestyle and environmental changes.

Each day of our life we are exposed to these three factors. Theoretically, this exposure begins to accumulate damage, compromise quality control systems and flip us into a state of decline. In 2018, Mattson and Arumugam described the adaptive and pathological modifications associated with the accumulation of damage as the “10 hallmarks of brain aging” (Figure 3).

These subclinical changes at the molecular level begin as early as our 20s and 30s. As we continue to age, the cellular and molecular changes result in physical and physiological changes (Table 1) , which eventually causes the functional capabilities of the brain to decline progressively [36]. Although these changes begin early in life, the brain remains malleable well into adulthood, which means with earlier detection, and therefore intervention, these changes could be slowed or stopped altogether.

Brain Volume• A loss of volume of around 5% per 10 years.
• After the age of 40 and the rate of loss accelerates over 70.
Cognitive Function• Declines from middle ages onwards.
• Episodic memory first affected.
• Sematic memory affected later in life.
• Older adults show loss of brain hemisphere dominance as a compensatory mechanism for decline in function.
Neurotransmitter Levels• Dopamine decline of 10% per decade leading to decline in cognition and motor function.
• Loss of serotonin and BDNF leading to loss in synaptic plasticity and reduced neurogenesis.
• Loss of oestrogen in women can affect cognitive process and predisposition to Alzheimer’s.
Vasculature• Reduced efficiency of the cerebrovascular impairs delivery of glucose and oxygen.
• Increased cerebrovascular pressure due to inefficiency of cardiovascular system leading to atrophy and grey matter volume.
• Poor capillary growth leading to poor response to increased metabolic demand leading to loss of neurogenesis.

As individuals enter their sixth, seventh and eighth decades, they become increasingly susceptible to the development of a neurodegenerative disorder, with Alzheimer’s disease and Parkinson’s disease being the most common.

Consequences of accumulating changes in the brain with age

From Figure 4, it is clear this is not a unidirectional process; how we age is dynamic. 

However, due to the natural aging process, people tend to change the way they live with age and typically become less physically active, may have smaller social networks and become less cognitively active than they once were [37]. This can become a vicious circle of decline, as changes in daily activities can accelerate the brain aging process.

Accumulatively, the brain damage incurred because of these changes can greatly increase the risk of developing diseases of the central nervous systems; those most seen in the elderly population are Alzheimer’s disease, Parkinson’s disease, other types of dementia and stroke which can also lead to conditions such as epilepsy as well as sleep disturbances and mood disorders [31].

It highlights the complexity of symptoms often experienced by the patients, the difficulty, the additive risk of having one of these conditions and the difficulty in management and the need for polypharmacy.

Figure 4: Diagram representing the interconnectedness between neurological disorders, mood disorders and sleep disorders.

The biologically aging brain: what is the solution?

There is a growing recognition that solutions must be found to extend not only lifespan, but longevity to keep people healthy for longer. Given the increasing pressure countries face, now is a better time than ever to start focusing on novel solutions.

As the rise in neurological conditions forms the biggest threat, and as the current treatment strategies for disorders related to the biologically aging brain mostly consist of symptoms management, it is essential to shift the focus elsewhere, and neurotechnology could offer the needed avenue to address this crisis [38].

It holds the potential to ensure that with an increasing lifespan, there is a matched increase in health span.

What is neurotechnology?

Neurotechnology is an assembly of methods and technologies developed to help understand brain function, enable visualisation of its processes and help to repair or improve its function. The focus is on creating an interface between the nervous system and technological devices (Figure 5) [39]. Although neurotechnology is not a new industry, it has been increasingly gaining traction in recent years and the solutions it provides will continue to expand.

Advances in neurotechnology will provide greater insight into normal brain function and a better understanding of diseases and disorders of the nervous system [40-43].

The field is seeing rapid advancements driven by progress in fields of neuroscience, computing, AI, imaging, material technology [44, 45]

Neurotechnology has the potential to provide both diagnostic tools that can detect changes at the earliest possible stage and therapeutic interventions that open an opportunity of targeting many of the changes at the same time, while overcoming some of the limitations that pharmacological treatment currently presents.

Relying on pharmaceutical intervention, Neurotech devices offer a promising alternative or at least an adjunct to pharmacological treatment [46, 47].

Many advances have already been made the field of neurotechnology, and these technologies are already offering a way of diagnosis and treatment of some neurological disorders and mood disorders. Some of the technologies have helped to shape the path for neurotechnologies in development today.

Neurotechnology in the future

Thus far, most of the focus has been placed on adjusting brain function with the therapeutic options neurotechnology has to offer. However, it might one day be feasible to develop devices that not only correct brain function but also augment its activity [48]. This is largely driven by the developments in bi-directional communication between the neurotech device and the neural network of the brain.

 In a one-directional relationship the device sends a signal to the target which leads to an action; a bi-directional relationship would allow information from the target to be sent back to the brain.  This opens the prospect of not only a shared understanding for both the brain and artificial interface, but also cognitive enhancement.

Consequently, humans could become more like computers/machines and computers could become more like humans. As each one can continually learn from the other, the advances made in our understanding of the brain would likely expand at an unprecedented speed [49].

Neurotechnology offers a unique solution in the face of an aging population

Neurotechnology offers a unique solution in the face of an aging population, and the associated rise in neurological conditions, because it can improve detection and diagnosis of conditions, facilitate their treatment – and maybe even provide a solution for their prevention.

PreventionDiagnosticTreatment
Neurotechnologies have been developed that help us monitor the impact of our lifestyles and environments on our brain healthThe major problem with neurological diseases associated with aging is that they typically present when a lot of the underlying damage has already occurred. Advances in imaging have already allowed for earlier detection of these conditions.Neurotechnology could play a big part in helping to better understand the pathophysiological changes that occur in humans and therefore determine better treatment targets and possible even screen for these targets.
Neurotechnologies may help in our understanding of the pathology and early detection of pathology through better screening, but it could also help to modify neuronal activity (neuromodulation) at early stages of disease to halt its progression and prevent manifestation of symptoms.With further advances in in neurotechnology we could see myriad new diagnostic methods coming to the market allowing the possibility of early detection of pathological changes, allowing us to halt their progression before it is too late. The technologies could offer a way to better predict outcomes and monitor any signs of progression.With techniques such as neurostimulation and neurofeedback, there could be a range of technologies that could treat the clinical indications of brain aging.

Why tech and not pharma?

The treatment of neurological conditions typically focuses of pharmacological treatment, particularly in the early stages, but also includes psychotherapy and rehabilitation. However, at best, the treatments available can control the symptoms or halt progression of the disease, but don’t provide a reversal of the physiological and pathological damage that has occurred, and no treatment offers a cure [50]. In addition, the pathophysiological changes underlying these conditions happen at different levels and often present in a multitude of ways.

As in the cases of neurodegenerative disorders, disease progression often leads to other symptoms or conditions, including epilepsy, mood disturbances and sleep disturbances. Therefore, patients are required to take multiple drugs to target each one of the symptoms which can lead to an accumulation of unpleasant side-effects.

One roadblock to development of successful treatment is identification of appropriate targets which is in part due to the lack of convincing animal models of neurodegenerative disorders use in pre-clinical trials. Mimicking the pathophysiological changes in these conditions can be difficult, and comparing the physical manifestation between animals and humans is often questionable – 500 neuroprotective therapies that were seen as successful in rodent models of stroke subsequently failed in human clinical trials [51, 52]. Neurotechnology could play a big part in helping to better understand the pathophysiological changes that occur in humans and therefore determine better treatment targets and possible even screen for these targets.

Development of new pharmacological strategies is also limited due to the presence the blood brain barrier in the neurovascular system (BBB) [53]. The BBB is a selectively permeable biological barrier which helps to protect the brain from possibly damaging solutes found in the circulating blood. However, this also means that in development of pharmacological treatments, one must consider bypassing this protective mechanism which creates an additional hurdle in development [54].  Apart from the poor access to the brain, other things must be considered in pharmacological treatment development, namely the first-pass metabolism, the half-life of the treatment and the possible side effects that they may produce [53].

Neurotechnology categories

For this report, Longevity.Technology has focused on the key technologies that underscore the broader categories of neurotech such as:  Neuromodulation, Neuromonitoring/feedback, Neuroimaging, BCI and the technologies that will facilitate, enhance and advance the use of neurotechnologies (Figure 6).

BCIAdvancing neuro-technologiesNeuro-modulationNeuroimagingNeuro-monitoring / feedback
A direct communication pathway between the brain’s electrical activity and an external device, most commonly a computer or robotic limb.Other technologies that will facilitate, enhance and advance the use of neurotech-nologies.The alteration of nerve activity through targeted delivery of a stimulus, such as electrical stimulation or chemical agents, to specific neurological sites in the body.The methods for the scanning of the brain and spinal cord’s
physiological functioning, including the assessment of its anatomical physiological
integrity.
The use of real-time displays that measure brain waves to produce a signal that can be used as feedback to teach the self-regulation of brain function.

The current developments in each of the categories will be discussed in detail in part 2, exploring their potential in improving outcomes of disorders associated with the biologically aging brain and normal brain aging.

Brain monitoring technologies and neurofeedback

Brain cells communicate with one another through rapid electrical impulses and these electrical impulses ultimately underlie all of our thoughts, behaviours and emotions.  

Without measuring the electrical activity of the brain, it would be impossible to gain a full appreciation of the brain function which is why efforts have been made to develop neuromonitoring techniques to measure this electrical activity.  

Since their early development, brain monitoring techniques, have played an important role in diagnosing of several brain disorders. In recent years there has been an increasing interest in using these technologies to understand the biologically aging brain and the associated age-related brain disorder.  

Ultimately any process or disorder affecting the brain will lead to changes in the electrical activity of the associated neurones and this can be recorded. The ability to visualise the brain signal is not only limited to diagnostic purposes but also has therapeutic application in neurofeedback. 

EEG at a glance

  • Potential for: Diagnostic/Treatment
  • CNS or PNS: CNS
  • Strengths: long history of clinical use, functional measure, good temporal resolution
  • Weaknesses: poor spatial resolution, artefacts
  • Invasiveness: non-invasive
  • Usability ease: high
  • Safety: high
  • Security: moderate
  • Cost: low

EEG and its potential for neurodegenerative diseases

Electroencephalogram (EEG) is a non-invasive method for measuring brain activity. It consists of electrodes which are fixed on a cap. The EEG head piece is placed on the scalp and can record the underlying electrical activity of the brain in real time. The signal is recorded from each electrode and is amplified before feeding into a computer where it is processed [55].

Most well known as a diagnostic tool for conditions such as epilepsy and sleep disorders, EEG is emerging as a new tool to facilitate both diagnostics and neuromodulation in aging related neurodegenerative diseases.  

EEG as a brain aging diagnostic tool

Neurodegeneration is associated with widespread and progressive changes in the brain’s network affecting its electrical signalling. Changes in the electrical activity of neurons, as seen on EEG, have been shown in early stages of neurodegenerative diseases such as Alzheimer’s disease, and this opens the possibility of using EEG for earlier detection of such changes and therefore earlier intervention. There is also the same potential for Parkinson’s disease, where characteristic EEG changes have also been identified [56, 57]. 

In addition to diagnosing indications, EEG could also be used as a biological age tool for the brain. Whilst everyone might develop a degree of cognitive decline with age, for some this cognitive decline will be far greater and faster than for others [58]. For example, as sleep is a predictive factor of cognitive decline, recording brain activity during sleep with EEG could be a biomarker of brain health. This is further emphasised by a study that sleep data collected using EEG, combined with machine learning, could be used to predict life expectancy. Further research is required to validate preliminary results, but the research so far points towards EEG being a promising diagnostic tool in aging. 

EEG as a neuromodulation device for Alzheimer’s disease 

EEG is proving to be a useful tool in neurofeedback, a therapeutic technique, which could offer a novel treatment approach. Neurofeedback allows patients to directly visualise their neural events, for example using an EEG, and through operant conditioning, patients can learn to modulate their neuronal activity (Figure 7) [59]. This has already been demonstrated by Dr Singh and her group in schizophrenic patients [60]. The study demonstrated that EEG-Neurofeedback interventions were associated with significant improvements in working memory, speed of processing, and reasoning and problem solving in patients with schizophrenia. Furthermore, these effects persists four weeks after the treatment ended. Dr Singh is now hoping to do the same in patients with mild cognitive decline and Alzheimer’s disease, in her on-going clinical trial [61].

Figure 7.EEG as neurofeedback for Alzheimer’s disease: allowing the patient to visualise their neural events can help them, learn how to change, and modulate their neural activity.

EEG is a well-established technology in clinical use 

One of the main strengths of EEG is that the technology has been used for many years as a diagnostic tool for epilepsy, as well as sleep disorders. As a well-established diagnostic tool used clinically which provides a high level of confidence over its safety and acceptability, therefore, gaining relevant approval for new EEG technologies from bodies such as the FDA is likely to be easier [62, 63]. For innovators this paves an easier pathway to widescale market use. The success and widespread clinical use of EEG also stems from its relatively low cost, portability, and participant friendly use [58, 64].

Transitioning EEG from clinical to commercial domain

As EEG technology is continually being improved, there is a move towards commercial use of the technology with portable, wireless and affordable EEG headsets now available commercially [65].

The EEG has several advantages that allow for easy transition from a clinical setting to a commercial one: EEG is non-invasive and the EEG acquisition is completely painless, giving it an advantage in terms of usability, especially with recent developments in dry electrodes [38, 48-50]. The technology is extremely safe and poses no significant risk and has no contraindications for its use [69].

Furthermore, EEG has been in use for nearly a century making it a well-established technology. Together with the non-invasiveness of EEG means that translation to consumer grade devices can be achieved at a comparatively lower cost compared to other neurotechnologies. The prices of the currently available consumer grade EEG headsets on the market ranges from $150 to $800 dollars, compared to clinical grade headsets which can cost between $1000 and $25,000+ [61, 70].

However, these headsets are not used for diagnostic or preventative screening purposes largely due to the poorer sensitivity provided by these commercially available headsets [68]. The development of at home headsets that have the necessary accuracy to detect network changes associated with various neurological conditions will undoubtedly increase the cost of the development of such devices and up their price point.

Furthermore, interpreting EEG data can be a hurdle, as often the there is a large volume of data which can be difficult to understand by someone other than a skilled clinician. Here, future developments in software, algorithms and machine learning could help to facilitate automated interpretation of the results (Table 2) [71]. 

Table 2. Technological improvements in EEG 

Improving resolutionEEG provides excellent temporal resolution (1-4 milliseconds), but it does suffer from poor spatial resolution making it difficult to determine the precise brain area generating the neuronal activity [72].Biomedical engineers and neurotechnology companies are already working to develop high density EEG systems to be use alongside a more precise assessment of head anatomy [72]. Sufficient scalp coverage is vital to allow for better localisation of the neuronal activity and better signal quality [68]
Improving artefactsEEG is that it can produce many artefacts, and these could become even more pronounced and unpredictable in real-world settings compared to clinical setting [73]. Artefacts often develop form systemic non-neuronal sources such as motion, muscle contractions, and eye movements. 
Developing improved sensors and signal amplifiers will help to counteract this problem in the future. This could also mitigate some of the other environmental factors and conditions that can affect EEG readout (low blood sugar, use of sedatives, caffeine consumption and lights) [75,76].
Improving UsabilityTo prevent low signal-to-noise ratio, wet electrodes are normally used which require application of gel like substance to the electrodes before placement on scalp [77]. This can make the procedure unpleasant and prove challenging especially when used on elderly patients with dementia [66]. It is also likely a barrier to user-friendly home-based use as application. Neurotechnology companies are now continually researching and improving the development of dry-contact electrodes that do not sacrifice the signal-to-noise ratio of the data [73, 78].

Neurotechnology: Electrocorticography (ECoG) 

ECoG at a glance

  • Potential for: Diagnosis and Treatment
  • CNS or PNS: CNS
  • Strengths: Approved for clinical use, functional measure, great spatial and temporal resolution
  • Weaknesses: Surgery required, no long-term implant studies, risk of seizure
  • Invasiveness: Invasive
  • Usability ease: High
  • Safety risk: High
  • Security risk: High
  • Cost: High

Unlike EEG, which records neuronal electrical signals non-invasively via the surface of the scalp, ECoG is an invasive recording modality where macroelectrodes are placed directly on the surface of the brain [79].

ECoG Provides Much Greater Spatial Resolution than EEG.

ECoG offers a functional assessment of the brain by recording its electrical activity in real time. Due to its direct placement on the cortical region, ECoG offers superior spatial resolution as the electrical signal is recorded directly from the surface of the brain [80]. 

Another advantage of direct contact with the cortical surface is that the signal quality is greatly enhanced, allowing for measurement of higher frequency activity and therefore better signal localisation, which is unaffected by movement artefacts compared with EEG [81, 82]. Therefore, ECoG can decode the activity of multiple areas of the brain at the same time, helping to map out communication between regions of the cortex [80]. The result could be used to develop, for example, motor and sensory maps of an individual finger. 

ECoG and its potential for neurodegenerative diseases 

As ECoG provides a more detailed view of the function of neuronal networks than EEG, it greatly enhances our understanding of the brain and could lead to the discovery of new functional biomarkers of diseases. 

ECoG is already used clinically in medically intractable epilepsy to help and locate the specific region of focal epilepsy. Identifying the specific origin of seizure allows for subsequent precise surgical removal of the seizure foci. ECoG is also often used in combination with direct electrical stimulation (DES) to facilitate mapping of the various cortex regions during surgery to prevent resection of cognitively vital brain regions [83]. 

The potential of ECoG lies in its adaption for BCI  

As ECoG has the ability to record precise signals with high temporal and spatial resolution, it can locate specific functions in the brain whether speech, movement, or vision. This paves the way for it becoming the preferable technology for development of BCIs. ECoG will aid the development of closed-loop DBS -BCI systems where signals recorded from the surface of the cortex are decoded and then used as input commands to modulate the activity of the same region of the brain where the signal was initially recorded [83]. This could provide a basis for treatment of essential tremor, Parkinson’s disease and epilepsy.

The challenges to ECoG uptake will remain in its safety risk.

As ECoG is an invasive technology that requires it to be placed during a surgical procedure, there are higher risks than with EEG technologies (Table 3). 

There is currently a lot of effort being placed on creating ways to minimise the risk of infection and pave the way for development of fully implantable devices for home use and on selecting materials that will withstand the test of time and minimise adverse effects [84, 85].  

In addition, there is a wave of ECoG devices making their way to clinical trials which offer new advancements on the older technologies including smaller electrode size and higher electrode density [86]. This will overall improve the usability of the technology for individuals and help transition from clinical to commercial use. 

Table 3. Challenges, consequences and solutions for ECoG 

Challenge Consequences Solution 
General risk of surgery∙ Risk of anaesthetic use
∙ Deep vein thrombosis
∙ Infection
∙ Damage to the brain tissue
∙ Performing awake craniotomy where possible 
∙ Standard preoperative and postoperative care including venous thromboembolism prophylaxis, antibiotic prophylaxis and regular monitoring
ECoG placement on the brain surface∙ Risk of seizures 
∙ Damage to the underlying tissue with unpredictable changes in function and/or behaviour 
∙ Development and use of soft, flexible, and elastic ECoG electrodes
Wear and tear of electrodes/ battery in wireless devices∙ Batteries overheating/ leaking 
∙ Loss of function of electrodes over time
∙ Longitudinal studies (animal/clinical trials) to validate long-term safety and duration of safe implantation. Continual development and improvement in materials and battery used

Neurotechnology: Electromyography (EMG)

EMG at a glance

  • Potential for: Diagnosis and Treatment
  • CNS or PNS: PNS Strengths: Application in biofeedback
  • Weaknesses: Complex signal to interpret, training may be required, affected by individual differences in physiology and biology,
  • Invasiveness: Invasive and non-invasive available
  • Usability ease: Moderate
  • Safety risk: Low
  • Security risk: High
  • Cost: Moderate

Electromyography (EMG) is a device that measures the electrical activity produced by muscle cells. The EMG sensor detects the electrical signals generated by muscle fibres of a motor unit enabling analysis of muscle activity [87]. In a clinical setting EMG is a useful diagnostic procedure that can evaluate the health of muscles and the nerves that control them by recording these signals and translating them into graphs or numbers that can be interpreted by qualified doctors. 

There are two types of EMG:

Surface EMG (sEMG):
Intramuscular EMG (iEMG):

SEMG measures electrical activity of the muscle by using electrodes placed directly on the skin surface. It is suitable for the measurement of large and easily accessible muscles. Excitation level is measured from a large area containing several motor unit populations. Although sEMG is non-invasive and the placement of the electrodes does not require a lot of technical knowledge, the signal produced is complex and requires technical knowledge. Environmental conditions are also known to impact signal quality. This makes it difficult to analyses sEMG data and for this very reason the technology is not widely used in clinical setting to help make definitive diagnosis [88].

IEMG is an invasive method which allows for the study of deep muscle and muscle that have a small cross-sectional area. This is technically challenging and requires special skills to insert the electrodes. The signal produced is of much higher amplitude and less complex due to lack of converging signal from multiple locations making it easier to interpreted. The major advantage of iEMG is the specificity or higher spatial resolution of the signal provided which is superior to that of sEMG. However, the invasiveness may be less tolerable for individuals and particularly elderly and those with cognitive decline. The test is painful and can cause destruction of muscle fibres, With this in mind iEMG is the less likely candidate to enter the consumer market and will likely remain within the clinical domain [88].

SEMG: user-interface applications

SEMG is generally more widely used for non-clinical and non-diagnostic purposes, particularly in the user-interface domain for wearable devices to provide better insight into individuals wellbeing and health (Table 4). Most people reported that they are open to the idea of sEMG providing better awareness about their physiological state which could be used to give recommendations or advice about health and wellbeing if they easily fit into their daily needs and habits [89].

The application of sEMG is diverse and there is likely to be new areas of application emerging in the future. 

Table 4. How sEMG can be used for insight into health and wellbeing 

sEMG sensors Function 
In devices such as smartwatches can classify hand gesturesFunctions can be executed depending on hand gesture and posture
Placement on muscle groups such as legsCan be used to provide information in physical activity performance
Placement on the trapezius muscle in the neckCan reveal information about stress levels 
Placement on the faceHas been used to help people with disabilities control a mouse cursor

Changes to the neuromuscular system with age? 

During the aging process there are numerous changes that occur in the neuromuscular system including changes in motor unit size, properties, and morphological changes, as well as alterations to the input from the nervous system [90]. As a result, elderly people often struggle to perform daily activities such as rising from seated position, walking up and down the stairs, or taking a shower, greatly impacting their independence and quality of life. 

EMG can help to identify frailty early on 

The EMG is a useful investigative tool that could reveal relevant information about the electrical properties of muscle that could be used to assess physical decline, reduced functional performance, disability and frailty in older adults [91].

Frailty is best thought of in terms of a spectrum, ranging from healthy to pre-frail to frail. Exercise interventions may prevent those who are pre-frail from becoming frail. However, the success of exercise interventions depends on where on the spectrum a person lies and typically for those in at the far end of the frailty spectrum, exercise interventions may lead to worsening of their condition and consequently lead to more adverse events such as falls and/or fractures.  

Early detection at the pre-frail stage is essential to prevent further progression of physical impairment. Assessment of the function of the motor system through EMG could help to detect and measure progression of motor decline and assess the success of those exercise interventions [92].

Combining EMG with biofeedback to improve motor performance

Furthermore, EMG can be a useful tool for combination with biofeedback. Biofeedback refers to the procedure where a person is provided information or feedback about their biological state and function which enables them to make appropriate changes to improve function or personalise intervention [93].

In the case of EMG, important information about motor function could be used to improve or recover motor performance for example through more targeted physiotherapy or electrical stimulation. This has already shown to be successful in stroke patients where EMG-biofeedback was used in combination with electrical stimulation [94].

Some challenges of sEMG in the commercial domain.

sEMG easily be translated to the consumer domain as it is non-invasive, can be adapted for use during everyday activities and will be more tolerable by the user. However, several things would need to be considered with regards to the everyday use of sEMG including:

  • Data interpretation: the sEMG software would have to be developed in a way that the user can interpret and understand the data. 
  • Positioning of electrodes: the signal produced by sEMG is likely to be affected by human errors such as the correct positioning of electrodes and how good the skin to electrode contact is. 
  • User specific differences: the technology will have to be adapted to user specific difference such as fat composition. 

This can further hinder the quality of the signal making data interpretation more difficult, and devices being developed might need to integrate a component which protects the users from any errors and misinterpretation of information [95].

Future developments in EMG

A major development in the EMG field is improving the signal acquired through sEMG by using multielectrode HD-sEMG recording techniques which could allow detection of pathological changes at much finer level. Although they are still in the experimental stage and not widely available, they do hold great potential both for clinical application and consumer market [96].

GSR at a glance

  • Potential for: Prevention
  • CNS or PNS: PNS
  • Strengths: Monitoring wellbeing, improve independence and quality of life
  • Weaknesses: Detects heightened emotional state but not the type of emotion
  • Invasiveness: Non-invasive
  • Usability ease: High
  • Safety risk: Low
  • Security risk: Low
  • Cost: Low

What is galvanic skin response (GSR) 

Galvanic skin response (GSR) is an “electrodermal” signature of the sympathetic nervous innervation of the skin. GSR can be measured on the skin surface and predominantly reflects the unopposed action of sudomotor sympathetic nerves on secretory channels of eccrine sweat glands. 

Sweat secretion is vital for regulation of body temperature and for sensory detection, however changes in sweat gland activity are also associated with emotional stimulation. When a person experiences a heightened emotional state, the sympathetic system will be activated, leading to increase in sweat gland activity and therefore increase in skin conductance that can then be measured [97]. From there the signal can be accurately transmitted to a device where it can be stored. 

Galvanic skin response does not reflect a single psychological process, but an array of processes like attention, habituation, arousal, anticipation and cognitive effort, making it a valuable tool for behavioural and neuroscientific research in many subdomains of psychology and related disciplines. In marketing, it has been primarily used as a measure of arousal. 

GSR is most known today as a component of polygraph tests. To a lesser extent, GSR has also been explored for control; for example, GSR has been used to detect emotional responses to game events, and these responses are then reflected in the games avatar. It could also be adapted to, for example, gauge frustration and driving stress. 

How is GSR applicable in healthy aging?

GSR application to aging and longevity is likely to be mainly within the wellness domain, improving the quality of life of the users and potentially lowering healthcare costs and the need for care. 

For example, falls in elderly are common and associated with morbidity and mortality as it is estimated that about one in three elderlies over the age of 65 experience a fall each year [98]. GSR based wearables measure stress levels that are the result of unsteadiness or instability felt by the user, reducing the risk of imminent fall [98, 99]. GSR wearables could also be used to detect increasing stress levels caused by manifestations or worsening of a health condition, quickly alerting a family member or healthcare provider to act. Lastly, as GSR signal measurements reflects the skin resistance and conductance, which is indicative of water content in the skin, feedback to the user about their hydration level could help maintain healthy hydration levels.

GSR potential and drawbacks

Although GSR could be used in both clinical and commercial domains, it is not likely to become a solitary diagnostic or therapeutic tool. Nonetheless it has a lot of promise for application in monitoring wellbeing of the user and could be a useful adjunct to other forms of monitoring of the overall health state.  

One major drawback of this technology is in the fact that although it can detect heightened emotional states it does not provide any indication about the type of emotion driving this change. Emotional arousal is a broad state which can range from joy to rage to disgust and to depict the exact emotion causing a change in GSR, would require the use of additional devices or means of measurement [100, 101] 

On the other hand, in comparison with other technologies where the output data is difficult to interpret, GSR data is straightforward and easy to interpret. Furthermore, GSR is simple to use and a relatively cheap device, making it a cost-effective tool that provides real-time information that can be acted upon [102].

Neuromodulation is a well-established area of healthcare technology which has been in use for many years and has led to novel approach to treatment and therapy.

Recent focus in research has largely concentrated on identifying new applications of the neuromodulatory technologies currently available.

In recent years, efforts have been made to transition this technology from clinical settings to home-use devices to further advance patient care and even allow for personalised therapy.  

Neuromodulatory devices and treatments can be life changing for patients and with increasing expansion of possible applications and further developments in neurotechnology, this area will see large growth in the coming years. 

Neuotechnology: transcranial direct current stimulation (tDCS)

TDCS at a glance

  • Potential for: Treatment
  • CNS or PNS: CNS
  • Strengths: Widely used and approved for clinical use in depression, easy technology to use
  • Weaknesses: Many factors which can interfere with efficacy, cannot target deep brain structures, poor spatial resolution, no standard measure of intervention success.
  • Invasiveness: Invasive and non-invasive available
  • Usability ease: High
  • Safety risk: Moderate
  • Security risk: Moderate
  • Cost: Low

Transcranial direct current stimulation (tDCS) involves the application of a weak electrical current to stimulate specific parts of the brain to modulate neuronal excitability, firing rates and overall cortical activity [103].  

The procedure is non-invasive and involves the placement of two electrodes on the scalp of the individual undergoing the treatment before a current is applied which flows between the two electrodes, passing through the brain to complete the circuit (Figure 8) [104, 105].

Figure 8. The application of positive anodal current is believed to increase the probability of neurons firing thereby stimulating behaviours or function associated with the underlying cortical region. The negative cathodal current decreases the likelihood of neurons firing, therefore, inhibiting those behaviours and functions [105].

The exact mechanism of tDCS is still being investigated, there is an understanding that tDCS produces changes in the neuronal pathways in the brain. 

Currently, tDCS is mainly used in the treatment of depression in a clinical context and it is well tested in terms of safety and efficacy for this use [106]. Commercially, tDCS handsets are available to buy for personal use with claims of helping to improve cognitive performance and mood [107].

More research is needed into the potential benefits of tDCS, however, as a neurotechnology it offers several advantages over other brain stimulation techniques. The main advantages include its low cost, portability of the device for possible home use and a well-established safety and tolerability [108, 109].

TDCS for neurodegenerative disorders

With age, the neural pathways that are activated when undertaking a certain task differ from the neural pathways activated in the young. It is believed that this is due to a reorganisation event of neural pathways to compensate for less robust neural networks. tDCS has been shown to have restorative potential, by creating a more youthful activation pattern in the brain of elderly people matched with improvement in task performance.  

Heightened excitability of neurons is also observed in those with mild cognitive impairment and Alzheimer’s disease, possibly to compensate for the cortical atrophy. These changes in excitability are thought to be early drivers in development of Alzheimer’s disease and therefore, targeting this abnormal activity early on using negative cathodal currents could prove beneficial to slow down or halt progression [110].

Secondly, Alzheimer’s disease has also been associated with loss of neurons and synapses, however, the aged brain does retain the ability to undergo neuroplasticity to a degree which could be targeted tDCS on a molecular level has been shown to modulate or induce neuroplasticity, therefore, it could be used to modify the neuronal networks [102, 103, 111].

Another study found that tDCS in Alzheimer’s patients improved overall cognitive performance, as well as depressive symptoms and quality of life. Importantly the effects of the treatment were still present 3 months following the stimulation period [112]. 

Many factors can influence tDCS efficacy.

There are some factors that can influence the efficacy of the stimulation which could prove difficult to fully mitigate. This can make the target effect difficult to predict which could lead to ineffective or unwanted outcomes (Table 5).

Table 5 Factors that influence efficacy of tDCS efficacy

Anatomical featuresFeatures such as the thickness of the skull, and its composition, can impact how the current is distributed across the cortical surface leading to difference in experienced benefits across different individuals
Targeted regionThe targeted region has to be found on the surface of the cortex as the electrical signals cannot penetrate deep into the brain
Hair thicknessThe targeted region has to be found on the surface of the cortex as the electrical signals cannot penetrate deep into the brain
Age of the brainThe biologically aging brain undergoes a great deal of structural and neuronal network changes and therefore the elderly may require adjustments in stimulation parameters used as the determination of target region becomes more difficult to predict 
State of targeted networkThe state of the underlying network at the time of receiving the treatment can also lead to differing outcomes. Simple factors such as alertness levels or the amount of caffeine in the system could change the baseline of underlying neuronal excitatory potential 

Due to the reasons in table 5, spatial resolution of tDCS is generally poor and often limited by the size of the electrodes used. Application of the current may be affecting a large portion of the brain including undesired brain regions. Future focus on improving the technology should be in delivery of more focal stimulus [113].

Lastly, unlike pharmacological treatment, where the dose and outcomes can be measured, there are no clearly standardised markers of completion of successful treatment with tDCS and therefore no way of determining the correct protocol of treatment [114]

Commercial tDCS may be a more desirable treatment option

Although the technology is relatively easy to use and is inexpensive and non-invasive, the major challenge of tDCS use is the number of treatments needed to achieve a desired result. Studies have shown that effects of tDCS are cumulative and multiple daily applications are necessary to achieve meaningful effect, which likely underlies the network changes needed [114]. Typically, in a clinical setting the treatment is given over a 5-to-9-week period requiring 30-39 sessions in that time [115, 116].

To accommodate a wider access and use, there will certainly be pressure to adapt this technology for at home use [117]. In fact, Flow Neuroscience has already developed the first medically approved tDCS device for home use. Such development will facilitate greater usability and compliance with treatment, helping the users to experience the full benefits of treatment.

How safe is tDCS technology?

At present, there is no FDA approved tDCS for clinical use in the US, and internationally regulatory approvals vary across countries. No consensus about safety has been achieved, and no definitive guidance for therapeutic treatment has been established [114]. Nonetheless, no study has reported any adverse effects with use of 1-2 mA tDCS other than mild side effects. Side effects are typically mild, temporary and generally well tolerated [105, 111].

It is important to remember that the safety of tDCS devices has been mostly demonstrated for short-term use only and the long-term effects of tDCS brain stimulation remain largely unknown. Similarly, any risk associated with repeated stimulation over a long period of time has not been assessed. As tDCS has neuromodulatory potential, the risk of maladaptive plasticity will have to be determined [111]. More long-term follow us studies are required to fully understand the effects of continued tDCS use [118].

Neurotechnology: transcranial magnetic stimulation (TMS)

TMS at a glance

  • Potential for: Treatment
  • CNS or PNS: CNS
  • Strengths: FDA approved for presurgical motor and language mapping and treatment of refractory major depression. Potential for many other treatments
  • Weaknesses: TMS has been thought to cause seizure induction
  • Invasiveness: Non-invasive, technician required, wall-powered and large
  • Usability ease: Low
  • Safety risk: Moderate
  • Security risk: Moderate
  • Cost: High

Transcranial magnetic stimulation is a neurophysiology technique that can non-invasively indue a controlled current pulse to a cortical target.  

The transmission of a large, brief pulse of current through loops of copper wire which causes a fluctuating magnetic field targeted to the brain. The magnetic pulses induce an electrical current in the brain, stimulating the cells into activity.  

TMS is becoming frequently adopted to treat medication-refractory depression, and the FDA has cleared 2 TMS devices for psychiatric applications. The growing therapeutic effect of TMS upon psychiatric practice is exemplified by the fact that hundreds of clinics in the United States now use an FDA-approved TMS system to treat depression. TMS has also been established as a tool in presurgical language and motor mapping (Table 6).

Table 6. Established applications of TMS

Presurgical motor mappingTMS can target cortical regions defined by the individuals own brain MRI and thereby systematically probe motor responses. It can therefore be used to assess what areas of cortex can be safely removed during tumour resection. TMS is able to perform these functions with accuracy profiles similar to those observed with invasive cortical mapping approaches. FDA approved.
Presurgical language mappingTMS was first thought as a good tool to probe language, following its ability to induce speech arrest. Due to TMS being a non-invasive technique, it is well suited to evaluate language areas in patients that cannot sit still during mapping. Navigated transcranial magnetic stimulation for mapping language areas is becoming increasingly used in presurgical planning.
Treatment of refractory major depressionRepeatedly administered TMS, when delivered to the dorsolateral prefrontal cortex, has been establish as a treatment for certain forms of medication refractory major depressive disorder. The efficacy of TMS in treating depression has been supported by large randomised, sham-controlled trials and several meta-analyses.

Potential applications of TMS in neurological diseases

The efficacy of TMS as a diagnostic or therapeutic tool in other neurologic contexts has yet to be confirmed. While TMS has not been FDA-approved as a treatment modality for neurologic disease, studies are underway to explore the potential therapeutic use of TMS for a diverse array of neurologic disorders (Table 7).  

Some of these applications will be beneficial in an aging population. Age is the largest risk factor for the development and progression of Parkinson’s disorder, and high frequency TMS is being explored as a treatment option. Further, epidemiological studies reports have demonstrated that increased age is a risk factor for chronic pain, which is another potential target for treatment with TMS. 

Table 7. Potential applications of TMS.

Treatment of epilepsyLow frequency or continuous theta burst TMS can suppress cortical activation. Reductions in seizure frequency following rTMS have been demonstrated in many but not all randomised sham-controlled trials. There is currently no FDA approval for the use of TMS in the treatment of epilepsy.
Treatment of stroke rehabilitiationIn addition to enhancing motor recovery after stroke, other preliminary studies have shown promising results using similar TMS paradigms to improve aphasia and hemispatial neglect following stroke. Issues surrounding patient characteristics, timing of the TMS intervention, and effective stimulation parameters will need to be determined for both FDA approval and widespread clinical use to treat deficits following stroke.
Treatment of movement disordersMulticentre trials are currently underway to better define the effectiveness of TMS for motor symptoms in Parkinson’s Disorder, as a first step toward possible FDA approval. There are mounting data from sham-controlled studies to support the use of high-frequency rTMS to premotor and primary motor cortices in improving bradykinesia and freezing in Parkinson disease.
Treatment of chronic painTMS could be effective in decreasing chronic pain in patients with neuropathic pain, fibromyalgia and complex regional pain syndrome. Ongoing studies are aimed at defining the target and parameters of stimulation, in addition to patient characteristics that predict response. It is thought that the effect sizes in patients who do response to TMS could be substantial.

TMS a clinical or at-home treatment?

TMS is primarily only available in clinics, where treatment is administered by a trained technician. A course of TMS treatment can cost between $6,000 and $12,000 in a clinical setting. Devices being designed for at home use are normally tDCS treatments that do not use the electromagnetic coil that is placed on the forehead during TMS clinical treatment. The difference between TMS and tDCS are described in Table 8

Table 8. TMS vs tDCS

TechnologyTMStDCS
Clinical or consumerClinicalClinical and at-home devices
UsabilityWall-powered and largeBattery operated, small and easily transported
Operated byTechnician requiredSelf-operated
Current transmittedShort, high-power electrical wavesSustained, lower power electromagnetic wave
FDA approvedFDA approved for major depressive disorderNot FDA approved for mood disorders

Safety of TMS

TMS has been linked to mild symptoms such as mild transient headache and mild neck and facial discomfort, thought to be caused by muscle contraction induced through stimulation. Hearing loss, transient mood and cognitive changes have also been reported but are uncommon.

However, worryingly, TMS has been thought to cause seizure induction. Consequently, established safety parameters regarding stimulation intensity and duration are required. With these in place, seizures are exceedingly rare.

Neurotechnology: deep brain stimulation (DBS)

DBS at a glance

  • Potential for: Treatment
  • CNS or PNS: CNS
  • Strengths: DBS is only approved for use in three conditions: Parkinson’s disease, dystonia and tremor but could also treat a range of other diseases. Potential for future closed-loop DBS
  • Weaknesses: Programming, cost, side effects, stimulation lead migration and pulse generator battery life
  • Invasiveness: Minimally invasive
  • Usability ease: Low
  • Safety risk: High
  • Security risk: High
  • Cost: High

DBS involves the delivery of electric current to an electrode implanted in a brain structure or nucleus of interest. The physiological effects of DBS are complex and can occur at the molecular, cellular, local and network levels.

The main components of a DBS system include the intracranial electrode and implantable pulse generator (IPG), linked with a connecting wire.

DBS placement occurs during a minimally invasive surgery procedure, where DBS system normally targets specific areas such as the subthalamic nucleus (STN), globus pallidus pars internus (GPi) and the nucleus ventralis intermedius (VIM) of the thalamus. DBS is only approved for use in three conditions: Parkinson’s disease, dystonia and tremor.

However, it has been suggested to be therapeutic in a number of neurological diseases (Figure 9).

Figure 9. Potential diseases and psychiatric disorders that could be treated using DBS [101]

DBS in neurodegenerative diseases: Parkinson’s 

Parkinson’s disease (PD) is a neurodegenerative condition that is predicted to reach 8.7 million patients by 2030. Currently, the annual sales estimates of DBS devices for PD is approximately US$200–300 million worldwide, but the coming years promise a further surge in sales. 

Motor symptoms of PD include tremor, rigidity, bradykinesia and postural instability whilst non-motor features often occur prior to the development of the motor symptoms and become worse as the disease progresses. Non-motor symptoms include memory dysfunction, impaired decision making, dementia, sleep disturbance, psychiatric changes and memory dysfunction. 

DBS is normally used as a therapy for PD when medications are no longer effective. Many studies have evaluated DBS efficacy in PD patients. As with many neuromodulatory techniques, exactly how DBS works is not fully understood. However, it is believed it regulates the abnormal electrical signalling patterns in the brain that are characteristically irregular in Parkinson’s disease. The STN and GPi are the most common targets for PD, and which is targeted is dependent on patients’ clinical profile and needs. 

Although highly effective in providing persistent symptom improvement even 5 to 10 years after surgery, there are challenges to using DBS as a treatment (Table 9). Furthermore, chronic DBS has created a new phenotype of PD: patients in whom bradykinesia, tremor, rigidity, on–off fluctuations and dyskinesias are improved, but who continue to present with progressive gait, speech and cognition problems. Gait problems, in particular, become important and difficult to manage at late stages of the disease [119].

Table 9. DBS Challenges and future solutions [120, 121]

DBS Challenges DBS solutions 
ProgrammingTherapeutic stimulation is rendered ineffective by disease progression, environmental factors, mechanical factors and behaviourally induced changes in network activity. As a result, additional sessions are required to manually adjust stimulation settings. Active research is being conducted in closed-loop stimulation, in which ‘smart’ stimulation is delivered using neurophysiology feedback from deep nuclei local field potentials or cortical phase amplitude coupling.
CostAs additional sessions may be required, the procedure can be very costly and time consuming because only a fraction of the stimulation parameter space can be practically explored during each session.Advancement of imaging software allows surgical planning preoperatively and remotely, reducing operating room time.
Stimulation lead migrationLead migration involves the unintended displacement of the DBS lead after surgery. 
Lead migration is reported to constitute 1.6% of hardware related complications in DBS. DBS leads were reported to migrate by greater than 3 mm in 10% of cases tested. This may degrade the effectiveness of the stimulation, requiring the need to constantly adjust stimulation to these changes.
New targeting methods are being developed and trialled including intraoperative computed tomography and MRI to guide lead placement, high-field MRI (3T) and reconstruction (susceptibility-weighted phase imaging) to better visualise anatomic targets, diffusion tensor imaging tractography to visualise neural network through specific regions of a target, and processing software for microelectrode recordings data to analyse local field potentials and efficiently triangulate surgical location.
Side effectsIn DBS, stimulation induced side effects are mainly caused by continuous stimulation and stimulation field spread beyond target areas. 
Stimulation side effects include drooling, flushing dysarthria and ocular deviation.
Stimulation protocols such as interleaving and stimulating multiple electrode contacts with different frequencies are techniques that help to optimise symptom control and minimise stimulation side effects.
Pulse generator battery lifeShortening of pacemaker battery life are mainly as a result of continuous stimulation and poor stimulation focusRechargeable batteries and wireless charging. Closed-loop DBS will only stimulate in response to changing biomarkers, saving battery life.

The future for DBS and PD: Closed-loop DBS

The future of neuromodulation is believed to be individualised patient-specific programming and stimulation delivered based on neurophysiologic feedback. Although DBS can help with some PD symptoms, its current systems are poorly suited to cope with the dynamic nature and progressiveness of PD. Closed-loop DBS has the potential to adapt to the progression of the diseases: the stimulation parameters will be adjusted based on characteristic changes in biomarkers. Biomarkers for closed-loop DBS include neurophysiological signals, like electrical and metabolic activity recordings, and external body signals from EMG. Closed-loop systems would allow real-time adjustment of therapy according to quantifiable brain response.

Modern biomedical imaging technologies have vastly advanced our understanding of the brain and have provided much valuable evidence of the functional and structural changes that take place during aging and in neurodegenerative diseases.

The brain is the most challenging structure to image, because of the complexity of its highly coordinated system. However, through imaging we can further our understanding of the biologically aging brain and the sources of pathophysiological changes which could enable earlier detection of diseases [122, 123]. The brain imaging modalities can be categorised into:

  1. Functional brain imaging
  2. Structural brain imaging

Functional brain imaging

FMRI at a glance

  • Potential for Diagnostic
  • CNS or PNS: CNS
  • Strengths: Great image quality image produced within 1 second
  • Weaknesses: Person required to remain still during recording
  • Invasiveness: Non-invasive
  • Usability ease: Low
  • Safety risk: Low
  • Security risk: Low
  • Cost: High

Neurotechnology: functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) is a variation of conventional MRI which is intended to measure brain activity and assess brain function.

The transfer of information between neurons during brain activity requires a higher level of energy consumption. This is associated with increased blood flow to provide sufficient oxygenated blood to the highly metabolically active region of the brain. fMRI detects brain activity by measuring the changes in the amount of oxygen in the blood and the amount of blood flow. The blood oxygenation level dependent (BOLD) is the most used technique for indirectly measuring brain activity using fMRI.  

When a particular brain region becomes highly active, there will be an increase in oxygen consumption in this region which will lead to a drop in oxygenated haemoglobin and an increase in CO2 and deoxygenated haemoglobin. The blood vessels in this region will respond to this rise in CO2 by dilating the blood vessels, a process called cerebrovascular reactivity (CVR). This allows for an increase in cerebral blood flow (CBF) to the region and therefore an increased supply of oxygen [124, 125]. This rise in oxygenated arterial blood flow leads to an increase in presence of oxyhaemoglobin which increases the ratio of oxyhaemoglobin to deoxyhaemoglobin found in the blood (compared to the surrounding tissue which is not metabolically active) [126]. Deoxyhaemoglobin in weakly magnetic whereas oxygenated haemoglobin is not, as a result when measured with fMRI, the deoxyhaemoglobin will reduce the amount of signal from the tissue that fMRI can measure, and oxyhaemoglobin will in increase the signal intensity [125, 126]. This change in ratio of oxy- to deoxy-haemoglobin is the principle behind BOLD.

FMRI for early detection of neurodegenerative diseases 

FMRI can measure the function of the brain, something that cannot be achieved with other imaging techniques. This can provide novel ways to evaluate the impact of neurodegenerative disease and it could also be instrumental in understanding the biologically aging brain.  With its ability to show insight into vascular physiology and metabolic process (Table 10), fMRI is a great candidate for detection of pathophysiological changes before they manifest structurally or clinically [126].  

FMRI can help assess the transition from mild cognitive impairment to Alzheimer’s 

A brain area which has received a great deal of interest in Alzheimer’s disease is the medial temporal lobe (MLT). The MTL contains vital brain regions related to memory formation and studies have shown that this area is often one of the first to sites which demonstrates neuropathological changes in Alzheimer’s disease. Previous studies of memory tasks measured with fMRI have pointed to this region as being the most characteristically impaired in early Alzheimer’s, typically showing reduced activity.  

Furthermore, previous studies have also pointed out that there is a phase of abnormal MLT hyperactivation at the transition from mild cognitive impairment to Alzheimer’s disease which could be interpreted as a compensatory mechanism of this region, trying to keep up the normal memory performance of the individual. Importantly, this hyperactivation can be seen with the use of fMRI and could form an important functional biomarker helping to facilitate early diagnosis of Alzheimer’s [127].

Table 10. Changes in CVR and CBF can be reflected in BOLD fMRI signal [122].

fMRI detection ofIndications
Cerebral blood flow (CBF):
Cerebral circulation is the movement of blood through a network of cerebral arteries and veins supplying the brain. The volume of blood in circulation is called the cerebral blood flow.
Cognitive decline:
Reduced cerebral blood flow can account for any age-related loss of brain volume, common in cognitive decline.

Neurodegeneration:
CBF is recognised as a biomarker for neurodegeneration but it still lacks specificity as the underlying mechanism could either be vascular or neural in origin. 
Cerebrovascular reactivity (CVR):
CVR is the compensatory mechanism that reflects the change in blood flow in response to vasoactive stimulation which can be achieved by, for example, asking an individual to hold their breath.
Blood brain barrier permeability:
CVR decline is also observed concurrently with increased permeability of BBB.

Cognitive decline:
Loss of CVR can be seen in aging and in cerebrovascular diseases and has been associated with cognitive decline.

Alzheimer’s:
Extracellular beta amyloid plaques settle in the walls of blood vessels causing compromised vascular function. FMRI CVR is reduced in patients with plaques and this plaque accumulation is present in 95% of Alzheimer’s patients. This could potentially be a biomarker of early stage Alzheimer’s. 

PET at a glance

  • Potential for: Diagnostic
  • CNS or PNS: CNS
  • Strengths: Patient does not have to remain still during the recording, patient can perform tasks during the recording
  • Weaknesses: Less accessible in hospitals, image takes 40 second to be produced, requires injection of radioactive isotope.
  • Invasiveness: Minimally invasive
  • Usability ease: Low
  • Safety risk: Moderate
  • Security risk: Low
  • Cost: High

Neurotechnology: positron emission tomography

Positron emission tomography (PET) is an imaging modality that measures the physiological function of the brain by looking at things such as blood flow, metabolism, neurotransmitters, pathological aggregates and radioactively labelled drugs [128].

A small amount of radioactively labelled isotope is incorporated into a molecule such as glucose which is injected into the peripheral vein. The radioactively labelled glucose will spread through the body and become metabolised emitting a positron.  

The positron quickly pairs with an electron mutual annihilation ensues, emitting two gamma photons. These photons are detected by the PET scanner revealing where in the body the metabolism took place [129]. Over time, enough events are detected to reconstruct an image. 

PET can also be used to look at blood flow and oxygen consumption in different parts of the brain, in stroke and Alzheimer’s, and can track neurotransmitters such as dopamine in Parkinson’s disease [128].

PET scan for earlier detection of Alzheimer’s disease

PET scan has the ability to reveal pathological and physiological changes in vivo and with an increasing emphasis being placed on the need for earlier detection of Alzheimer’s related changes, diagnosis with the help of PET scan could form a viable diagnostic metric. 

To facilitate the study of Alzheimer’s related brain changes using PET scan, many radiotracers have been developed to study Tau, a protein which forms the neurofibrillary tangles, one of the fundamental hallmarks of Alzheimer’s disease [130]. 

Development of PET ligand that bind Tau

Previous studies have identified a strong association between Tau presence and pathology and loss of neurons and synaptic activity which correlated with disruptions in cognition [131, 132]. Further PET studies using high ligands which bind Tau have revealed the following [130]:

  • Tau retention strongly overlaps with regions affected by brain atrophy and increased rate of metabolism and wore cognitive performance [133].
  • Tau can be used to distinguish Alzheimer’s dementia from other types of dementia including frontotemporal dementia and vascular dementia [134].
  • Elevated baseline Tau levels are associated with accelerated decline over time [135].

Presence of Tau detected through PET scanning can form an important predictive biomarker of cognitive decline and cognitive change over time. With further studies it could become a viable biomarker to help in diagnosis of Alzheimer’s at earlier stages and it could be a useful prognostic factor to track development of the disease [130].

Tau accumulates in all aging brains

Tau is not only associated with pathological brain aging and neurodegenerative diseases such as Alzheimer’s; recent studies have shown that Tau is present to varying degrees in the medial temporal lobe (MTL) of all aging brains. The higher the amount of Tau present in this region the greater the decline in memory, especially episodic memory which codes new information.  

However, many people who do have Tau present in the MTL do not go on to develop Alzheimer’s, the reason being that it is when Tau is found more globally outside the MLT that it could lead to a more global decline seen in neurodegenerative diseases. 

Furthermore, Tau accumulation is only one of many pathological changes and it is likely that the very precise accumulation of varying types of damage is what leads to the development of Alzheimer’s. Nonetheless, PET scan can be used to help qualify and monitor the accumulation of tau to help determine the risk of development of more advanced cognitive decline and could place tau at the forefront of development of novel therapeutic approaches that target its formation early on to help halt further progressions. 

FMRI or PET as a functional imaging modality – which one performs better? 

The two imaging modalities are similar in that they both provide functional information rather than simply structural. However, the information they can reveal also differs and the type of imaging modality used will largely depend on what is being investigated. Nonetheless, apart from the clinical question being addressed, other aspects of the two technologies have to be taken into account such as the spectral possibilities and other practical aspects as discussed below [122, 127, 128, 137].:

Spectral differences:
  • FMRI provides superior image quality overall.
  • PET scan has lower resolution of images compared to fMRI: PET scan resolution is 5-10 mm3 compared to <3 mm3.
  • FMRI usually produces the image as quickly as 1 second but PET scan takes 40 seconds, therefore, the ability to determine when precise brain regions are activated and hold long, they remain active is much better with fMRI.
Practical differences:
  • FMRI is non-invasive as opposed to PET which requires an injection of radioactive isotope.  
  • The use of radioactive isotopes limits how often the scan can be done. 
  • PET scan is advantageous because the person does not have to remain still during the recording as is required during fMRI which can be beneficial when working with elderly patients, Parkinson’s patients and those with cognitive decline. 
  • Patients are performing cognitive tasks such as recalling items for memory tasks.  
  • As MRI is one of the main imaging modalities in all hospitals, fMRI is far more widely accessible than PET scanners.  
  • PET scanners in general are far more expensive than fMRI.

Ultrasound at a glance

  • Potential for: Diagnostic and Therapeutic
  • CNS or PNS: CNS
  • Strengths: Developments of at-home devices under way, provides structural and functional information
  • Weaknesses: No radiation as opposed to other imaging techniques
  • Invasiveness: Non-invasive
  • Usability ease: Moderate
  • Safety risk: Low
  • Security risk: Low
  • Cost: Moderate

Neurotechnology: ultrasound 

The ultrasound is a non-invasive device that uses sound waves for diagnostic or therapeutic purposes [138].

Diagnostic
Used for clinical purposes mainly to visualise internal organs and other structures of the body to help in the diagnostic process.

  • A transducer sends a beam of soundwaves with frequencies above those of human hearing, these will reflect off the internal structure of interest and the echo signal can be analysed converting it into an image known as a sonogram.

Therapeutic
Used to produce an effect such as pushing tissue or dissolving blockages.

  • A therapeutic ultrasound also utilises soundwaves but instead of producing an image the soundwaves interact with the tissue to produce an effect such as moving or pushing tissue, heating the tissue, dissolving clots or other blockages and even helping to deliver drugs to specific location .

Understanding and targeting the biologically aging brain with ultrasound

Similarly, presence of micro emboli can cause damage within the cerebral vasculature and has been linked with increased risk of vascular cognitive impairment.  Both the atherosclerotic plaques and damage induced by micro emboli can be detected with the use of a transcranial doppler ultrasound [139].

Furthermore, functional transcranial doppler ultrasound has been shown to detect neurovascular changes of small vessel disease, or before these changes are detectable with an MRI scan.

Transcranial doppler ultrasound could be a novel approach to detecting pathological changes at an earlier stage of disease process which could allow for development of strategies that target the disease process at a time where the disease can be stopped or reversed [139].

Before viable biomarkers can be established

Although these studies show promise, before viable biomarkers can be established, more studies are needed to assess the vascular changes that contribute to the development of conditions such as dementia, especially as these early studies indicate a potential for this tool across a wide range of neurodegenerative conditions [140].

One possible downside is the lack of development in the technology over the years, nonetheless, rising awareness of the potential application across a spectrum of neurodegenerative disease could help to drive interest in this technology for brain related diseases. Although transcranial doppler does not provide the special resolution possible with other imaging modalities such as FMRI or PET scan, it provides much better temporal resolution of 5ms. In addition, it is easy to apply and operate, it does not use any harmful radiation and is resistant against any movement related artefacts [139].

Are at-home ultrasound scanners possible? Enter Vscan

At present the use of ultrasound is mainly within the clinical domain and for research purposes however, consumer orientated portable at home ultrasound devices could be possible. One example is the Vscan, a low cost, miniature ultrasound scan capable of anatomical and functional imaging [141].

However, as the field of ultrasound use for neurological related disease is still in its infancy it has not been established if these scanners will be able to detect the changes in the brain and its vasculature. The Vscan is currently in clinical use and the cost is far lower than the more traditional ultrasound scanner [141]. These developments make it possible that patients could use similar devices from their home. 

The barriers to at home ultrasound scanners.

Nonetheless, some have argued that the unsupervised use of these devices by patients at home, is dangerous and irresponsible, noting that it takes years of training to use an ultrasound scanner [142]. There are also a number of side effects associated with use of ultrasound which are shown below (Figure 10):

Figure 10. Ultrasound Side Effects

Others argue that if made possible, ultrasound scanners could be a valuable tool for people to use at home to monitor for development of breast cancer and the use of this technique for home use should be explored [142]

What does the future hold for ultrasound?

In the future the rise of AI will likely drive the use of ultrasound forward with new capabilities emerging that have not yet been considered. At present it is already enabling crisper images and more efficient data collection [143].

Structural brain imaging

Structural brain imaging allows us to visualise the various structures of the brain and any physical abnormalities that may affect them. This is particularly useful when looking at the physical changes that occur due to the accumulation of damage with aging, and can allow us to diagnose, and track the progression of, certain brain aging pathologies. 

MRI at a glance

  • Potential for: Diagnostic
  • CNS or PNS: CNS
  • Strengths: No radiation,
  • Weaknesses: Noisy acquisition, longer image acquisition
  • Invasiveness: Non-invasive
  • Usability ease: Low
  • Safety risk: Moderate
  • Security risk: Low
  • Cost: High

Magnetic resonance imaging (MRI) is a modality which uses a strong magnetic field and radio waves to create detailed images of organs and tissues of the body. 

The magnetic field forces protons in the body to align with the field and when a radiofrequency current is pulsed through the patient, the protons are stimulated and spin out of their equilibrium position. When the radiofrequency is turned off the MRI sensors are able to detect the energy released as the protons return to their equilibrium position and realign with the magnetic field. The time it takes for the protons to return to their original position is dependent on the types of molecules, and therefore the type of tissue. This information is then translated into an image [144]. 

MRI can reveal structural changes associated with neurodegenerative disease

There is a large amount of heterogeneity between individuals in terms of changes to brain structure with age, most likely as a result of differences in genotype, environment and lifestyle, as well as disease [145].

Therefore, MRI may be a viable modality which could help in the development of an index of disease, or the risk of developing a disease by comparing healthy brain aging MRI images to those of pathological aging [145].

In the last decade, studies have helped to establish many structural changes that occur in the brain with aging that have furthered our understanding of the pathophysiology but developments in MRI scanners and software have simultaneously facilitated measurement with increasing levels of detail and precision [146]. Some of the changes found are described below:

Brain atrophy in Alzheimer’s
this is typically in the medial, basal and lateral temporal lobe and medial parietal cortex [147].

Cortical thinning
This has also been shown to be a marker of Alzheimer’s disease and can even be used to detect amyloid positive individuals before symptoms become apparent and it can be a marker to indicate severity of the disease. Furthermore, different pattern of atrophy in the hippocampal region can help to distinguish between the different types of neurodegenerative disease [147]

Abnormal iron deposition
This has been reported in Alzheimer’s disease, Parkinson’s disease and other neurodegenerative disorders. The rise in cortical iron deposition has been shown to be predictive of cognitive decline in individuals with Amyloid pathology [147].

Brain atrophy and lesion index to quantify structural changes in the biologically aging brain. 

The Brain Atrophy and Lesion Index (BALI) has been developed to summarise some of the most common structural changes in the biologically aging brain which can be detected with MRI scan and could be used to track the changes [148].

BALI score for brain aging
  • Grey matter lesions
  • Subcortical dilated perivascular spaces
  • Lesions in the basal ganglia and surrounding area
  • Periventricular lesions
  • White matter lesions
  • Lesions in the infratentorial compartment
  • Global atrophy

The BALI score has been shown to be significantly related to age and dementia progression and has been validated by numerous studies. The BALI score is particularly useful as it recognises that some of the above-mentioned changes may hold little meaning on their own, but a specific combination and degree of the above-mentioned changes may translate to significant effects [149].

3D MRI

MRI and CT images are two-dimensional.  For a truly impactful imaging presentation, a brain viewed in three dimensions can provide a more comprehensive picture of injury location and the extent of brain injury.  This could be imperative in neurodegenerative diseases as well. A study by Zhang et al., investigated 3D texture as a possible diagnostic marker of Alzheimer’s disease. The results suggested that 3D texture could detect the subtle texture differences between tissues in Alzheimer’s disease patients [150].

The future for MRI: 7-Tesla MRI for higher resolution and the potential for transportation

Clinical 7-tesla MRI was approved by the FDA in late 2017 for several uses of scans in the knee and brain. The 7-Tesla MRI is an ultra-high field MRI which provides enhanced detail in cortical imaging. The more powerful magnet of the 7T allows clinicians to take higher resolution images meaning if those scans can identify the subtle abnormalities, clinicians can present a stronger hypothesis to surgeons to operate. The cortex, the outermost layer of the brain, primarily made up of grey matter, is only 2 to 3mm wide. Normal 3T scanners can resolve details of the brain as small as 1mm. But the power of the 7T allows clinicians to see these cortical abnormalities more clearly. 7T MRI already resulted in gains, researchers say, for both neuroscience and clinical applications: for example, clinicians can guide electrodes for deep-brain-stimulation treatments more accurately. 

However, 7T MRI is not a cheap method and technically challenging. 

The amount of signal that can be obtained from an object is strongly dependent on the strength of the magnetic field applied. Imaging at lower resolutions can reduce the cost size and weight of the MRI scanner, as well as shortening imaging times. A company called Hyperfine has developed a portable, easy-to-use MRI. To date, a main application of the Hyperfine scanner has been for stroke and it is also being looked at for use in Multiple sclerosis [151]. 

It is thought that the low dose radiation stimulates adaptive protective systems which act to reverse, stop or delay cell and tissue damage in Alzheimer’s. Although the efficacy of CT in improving cognitive function is supported by increasing number of studies, the mechanisms underlying it are not known and future studies are required to better understand this underlying process. Although pilot studies are beginning to emerge, more is needed to validate the efficacy of these results and assess the long-term outcomes and the appropriate and safe doses and whether the benefits outweigh the risks of radiation [152, 153]. 

Neurotechnology: computer tomography

CT at a glance

  • Potential for: Diagnostic
  • CNS or PNS: CNS
  • Strengths: Cheaper imaging modality, less concern about motion artefacts than MRI
  • Weaknesses: Risk of ionizing radiation and iodinated contrast agents.
  • Invasiveness: Non-invasive
  • Usability ease: Low
  • Safety risk: Moderate
  • Security risk: Low
  • Cost: High

Computer tomography (CT) uses a rotating X-ray machine to create cross-sectional or 3D images of any part of the body. The technique is non-invasive and allows the examination of bones, internal organs and tissues. The patient passes through the doughnut-like CT scanner as the source of X-ray rotates around the patient shooting narrow beams of X-ray through the body part. The data is sent to a computer which reconstructs all the individual snapshots into a cross sectional image [154]. 

CT scans are widely used within the clinical setting for diagnostic purposes including helping in diagnosis of stroke, identification of brain lesions and malignancies and in guiding the diagnosis of Alzheimer’s disease [155]. However, evidence has been emerging that the radiation from CT scan could also provide therapeutic benefits.

Treatment of Alzheimer’s with CT – case studies

Recent evidence from multiple case studies has suggested that the low dose radiation received during a CT scan can lead to noticeable improvement in the symptoms of patients with Alzheimer’s disease, including retuning of memory, improvements in motor function and language function which were previously diminished [156, 158, 158].

It is thought that the low dose radiation stimulates adaptive protective systems which act to reverse, stop or delay cell and tissue damage in Alzheimer’s. Although the efficacy of CT in improving cognitive function is supported by an increasing number of studies, the mechanisms underlying it are not known and future studies are required to better understand this underlying process. Although pilot studies are beginning to emerge, more is needed to validate the efficacy of these results and assess the long-term outcomes and the appropriate and safe doses and whether the benefits outweigh the risks of radiation [152, 153].

Table 11. Comparison between MRI and CT scan

MRICT
Excellent sensitivity and variable specificity. Detailed pictures of soft structures.Good sensitivity and very good specificity, but less detailed in comparison to MRI. Detailed pictures of bony structures.
High costModerate cost
Patients with metal or medical implants are not able to undergo MRICT scan can be performed with no risk to medical implants
Long imaging timeShorter imaging time
Excellent anatomical detail for surgeonsExcellent characterisation of mineralised matrix

Brain imaging with the patient in mind

Out of all the neurotechnologies available, brain imaging is likely to remain one of the most expensive and for this reason less accessible within the consumer domain and will remain largely constrained to the clinical domain.

Although there has been progress in the development of the technologies in terms of their ability to produce increasingly better and quality images and easier analysis of the images, the big developments have come using brain imaging to further our understanding of the brain function and disease rather than any technological advances. Appreciating the functional and structural changes that occur in the brain with disease or during ‘healthy’ aging can help in identifying diseases earlier on for more successful interventions, in identifying novel targets and creating improved therapies.

Brain imaging does come with its challenges especially when using it in the elderly population. Firstly, MRI scans for example do have contraindications for their use including having implants such as pacemakers, insulin pumps, cochlear implant, and deep brain stimulators to name a few. Many of the elderly people may have co-morbidities which may prevent them accessing this modality. Furthermore, the scan can take a long time to complete, requiring the patient to remain still and this can prove challenging in population who are cognitively impaired.

The lengthy time it takes to complete a scan and the high cost and technical demand associated with brain imaging might also be a limiting factor in research and studies, limiting the number a participants that can take part. This could be a barrier to large scale studies where the evidence tends to provide the most robust findings.

The idea that humans could control a computer with their minds might seem too far-fetched for many. However, with the emergence of brain computer interface (BCI) this is no longer simply science fiction but a very possible reality.

BCI is not a new idea; in fact, research in this area was already underway in the 1970s. Since then, the applications for the technology have significantly expanded.  This is largely driven our increasingly detailed understanding of the brain thanks to other technologies notably brain imaging and electrical recording of brainwaves.  

Having the ability to pinpoint the specific location associated with a particular function and understand the underlying neuronal activity has allowed the development of BCIs to gain momentum. 

Neurotechnology: brain computer interface (BCI)

BCI at a glance

  • Potential for: Treatment
  • CNS or PNS: CNS
  • Strengths: Augmentation of human brain function
  • Weaknesses: Surgery required, no long-term implant studies, risk of seizure, user training required
  • Invasiveness: Invasive and non-invasive available
  • Usability ease: High
  • Safety risk: High
  • Security risk: High
  • Cost: High

A brain computer interface (BCI) is a computer-based system which establishes a direct connection between the brain and an external device facilitating communication between the two. A BCI acquires brain signals, and a suite of algorithms analyses them and translates them into commands that are relayed to a device. The device carries out the desired action in real time, reflecting the intention of the individual (Figure 12) [159]. The emerging field has many applications from rehabilitation to augmentation of human function [160].

Brain Computer Interface (BCI) system consists of:
  1. Signal acquisition – a means of recording the electric, magnetic or metabolic activity of the brain [160].
  2. Processing pipeline – that extracts meaningful features from the signal and translates them into a command based on brain signals received [160].
  3. A computer or device – that generates the command [160].

Barriers to widespread BCI adoption

BCIs have extraordinary potential and could transform the field of medicine, offering new ways to prevent, diagnose and treat various neurological conditions to improve quality of life and allow people to function in good health for longer. On a broader scale BCIs could also challenge the very definition of what it means to be human and a very careful consideration will be required across the whole of society to determine where to draw the line and when the risk outweighs the benefits. One important aspect to consider is that the  Data collected by BCI devices could be sensitive and stigmatising and needs to be carefully monitored for possible interference or inception. Although at present, these devices cannot be used to decipher someone’s thoughts, person specific information about treatment, particular brain abnormality, neurological or mental health condition could be obtained which could be used for malicious purposes. 

The brain is a complex structure and ultimately assessing or measuring any structural, functional or electrical changes will lead to equally complex outputs.

The field of neurotechnology advances this complexity of data will increase and with developments of home-based neurotechnological devices it will become ever more imperative that we can make sense of this data.

To achieve this, and to allow neurotechnology to continue advancing, technologies such as AI may need to be implemented alongside neurotechnologies. Furthermore, the enhancing technologies themselves have the potential to revolutionise our understanding of brain function and facilitate the development of new treatments.

Technology: AI

“The science of getting computers to act without being explicitly programmed”

Stanford University

Artificial intelligence (AI) is a branch of computer science that aims to develop computers that are capable of intelligent behaviour. Through AI, a computer can find patterns in data in a way that mimics the reasoning of humans [163]. There are three main subsets of AI: 

AIMimics the intelligence or behavioural patterns of humans or any other living entity.
Machine learning (ML)ML involves the use of algorithms which help a computer to learn without continually needing direct instructions. It can then find hidden insights without needing to be programmed on where to look and what conclusions to draw from the data [163, 164].
Deep learning (DL):DL is modelled after a human brain; therefore, it can carry out some of these more complex tasks . DL involves creating multi-layered data processing which is not linear and therefore can deal with increasingly abstract data [165].

AI will aid in the development of neurotechnologies for brain aging

Scientific research often requires a deep level of understudying of the underlying processes to make sense and make use of data. AI, on the other hand, is one of the most attractive technologies out there, as it has the ability to identify patterns in complex data without requiring any prior understanding of the biological process [166]. 

Many of the technologies discussed in this report generate vast amounts of aging data. However, with increasing data there comes increasing complexity. The analysis and practical use of the information generated in this vast amount of data can become difficult and therefore technologies such as AI can hugely impact the field of brain aging (Tables 13 and 14).

Table 12. Examples of how AI can aid aging neurotech

NeurotechnologyAdvancements with AI
MRIAI will also shape the evolution in workflow, by automating many of the tasks currently carried out by humans at far greater speed.  Computers will be able to understand, interpret, and label medical diagnostic images after learning from examples and help overcome some of the challenges posed by a shortage of MRI radiographers. AI is bringing new opportunities to make MR faster, more productive, and more quantitative [314, 315].
EEGAI methods have the potential to automate clinical EEG analysis. Machine learning (ML) and deep learning (DL) algorithms, are increasingly being applied to EEG data for pattern analysis, classification, and brain-computer interface purposes. DL models can use the large amounts of data from EEG recordings to learn important features from raw and minimally processed data inputted into the DL models. ML algorithms, by first learning on training data, can then apply the learned parameters to new and previously unseen data [316-318].
TMSTranscranial magnetic stimulation (TMS) plays an important role in treatment of mental and neurological illnesses. However, at present it is difficult to target specific brain regions accurately. In addition, TMS is very time consuming and expensive. AI could be used to facilitate personalised treatment planning and targeted stimulation. Professor Raj Gururajan and his team are working to develop an AI model that can inform treatment decisions by recognising patterns from data collected after previous treatments. This could save both the patient and health systems’ time and money, while improving patient outcomes [319].
BCIAdvanced AI algorithms such as ML can aid in improving BCI system’s performance and in achieving better outcomes by allowing BCI to achieve real-time or near-real-time modulation of training parameters and subsequent adjustments in response to active real-time feedback. The, algorithms can also learn from previous data and make adjustments based on what they have done in the past [320, 321].
Identifying biomarkers of brain aging
Since neural data is incredibly complex, the development of more powerful methods to interpret huge volumes of neural data will be the key to finding signal patterns that can be used as biomarkers.

Recently ML was used on data from structural MRI to help estimate chronological age and to establish that this ‘brain-predicted age can be used as a biomarker of individual differences in the brain aging process and therefore predict cognitive impairment and development of Alzheimer’s disease.

ML has been shown to detect neurodegenerative diseases before progressive symptoms worsen which can improve patients’ chances of benefiting from successful treatment.

Why choose AI? 

AI will solve many other problems that go beyond its use for diagnostic and therapeutic purposes. Humans occasionally make mistakes and, in rare cases, these mistakes can be fatal. AI could be the answer to reducing human error because, unlike humans, computers can be trained to achieve far greater accuracy when they are programmed with highly specific algorithms. The better the data which is used for algorithm training, the better the outcomes.

Another way that AI outperforms humans is that it can process data much faster leading to a higher rate of results that can be applied. Lastly, humans are rarely able to separate the emotion from decision making which can lead to biased decision making; AI can allow for unbiased decision making leading to more accuracy [168]. Taking all this into account AI has enormous potential to transform healthcare by facilitating decision-making, reducing the number of errors and speeding up processes.  

But is AI all good? 

“Garbage in, garbage out” is a highly used cliché in machine learning circles. Anyone who works with artificial intelligence (AI) knows that the quality of the data goes a long way toward determining the quality of the result. But “garbage” is a broad and expanding category in data science – poorly labelled or inaccurate data, data that reflects underlying human prejudices, incomplete data. Users must ensure that the ML model is trained on “good” data and that what you are feeding the model is also “good” data.  

Furthermore, the creation of AI is very complex and this is associated with huge costs to a company [167].  As the demand for the technology grows due to expanding of possible applications, this will drive the cost even higher. 

Hearing aids, walking frames, wheelchairs – there are numerous examples of how technology has restored or replaced function to assist aging populations. If the natural sensors of the human body are impacted by disease, then why not use electrical signals to modulate the nervous system? We already know of some success stories – cardiac pacemakers control an individual’s heartbeat with only a few contact sites, cochlear implants restore hearing and deep brain stimulation can suppress tremors in Parkinson’s disease patients.

Clinical applications of neurotechnology offer alternatives to pharmaceutical approaches and devices for diseases that to date, are often fatal. The need for neurotechnologies is not only driven by humanitarian desire, but also by the need to alleviate the considerable economic and social burden of aging societies.

The cost of neurological disorders already exceeds those associated with cardiovascular diseases and cancer [in the same population]. And it is not only healthcare expenses that contribute to this burden. The impact of neural diseases can also cause a loss of productivity in the workplace and have a significant impact on families.

With these driving factors, it is no wonder that the importance of neurotechnology (neurotech) is being recognised internationally by governments, and countries with accentuated aging population problems are at the forefront of those focusing investment in this field.

US BRAIN InitiativeUS$1.8 billion since 2013 plus $500 million a year until 2023
EU Human Brain Project€1 billion over 10 years (launched in 2013)
China Brain ProjectA 15-year project established in 2016
Korea Brain Initiative51.3 billion KRW committed to brain research in 2021 alone
Australian Brain InitiativeAU$500 million over 5 years, launched in 2016
Japan Brain/MINDS40 billon Yen from 2014-2024
Canadian Brain Research StrategyCA$230 million invested in brain research from 2011 – 2019

An analysis prepared by KTN [170] concluded that when comparing brain related investments (of which an increasing proportion is based around neurotechnology) relative to a country’s GDP, Australia and Korea are investing heavily in brain-related research. The US is the largest investor in absolute terms, investing $1.8 billion in its BRAIN initiative so far and committing a further $500m a year until 2023. 

As government initiatives increased, the number of neurotech longevity companies launching also increased substantially between 2010 and 2018.  

Number of NeuroTech startups with a Longevity focus, by year

Of the new neurotech companies founded, 80% of those with a longevity focus are based in either North America (59%) or Western Europe (21%), with both these locations offer attractive sources of an advanced neurotech ecosystem and significant investment capital opportunities.

Geographic location of NeuroTech startups with a Longevity focus, %

Although the number of startups in the period 2019 to 2021 reduced, in part due to the COVID19 pandemic, investment into neurotech companies with a longevity focus stayed strong in the same period.

Capital invested in NeuroTech companies with a Longevity focus, US$B
Deal count in NeuroTech companies with a Longevity focus

In terms of trends, it is worth noting that 2016’s exceptional total investment of >US$20b was dominated by a single US$17.2b deal by Abbot, accounting for 85% of the total funding that year. (Similarly 2017’s total was skewed by a US$8.09b deal.)

There were 425 successful deals in the year of 2020, raising a total of $8.61b. Although deal count was lower in 2021, on average, individual deals were of greater value, and y-o-y total deal value increased by 30% to $11.26b.In terms of the breakdown of deal types in 2021, it is clear there were larger sums closed in both early-stage and late-stage venture capital rounds in comparison with previous years. Not only does this reflect the growing interest in neurotech in terms of Venture Capital, but may also suggest that several neurotech companies might be approaching IPO in the near-term.

Early Stage VC (in M)
Later stage VC (in M)

The top deals of 2021 are presented in Table 15. At the top of the list in terms of size, Ginger agreed to merge with Headspace in a US$3b deal to accelerate digital mental health support in Q3 of 2021 [171]. Elon Musk’s Neuralink, founded in 2016 with the aim to develop BCI’s for therapeutic use in patients, raised US$205m from Google and other funds in a Series C fundraising, following a presentation by the company of the technology being used in pigs in late 2020. HeartCare Medical, focused on reducing the mortality rate and improving the prognosis of stroke, has commercialised four products since it was founded in 2015 and listed on 20 August 2021, raising US$145m [172]. 

Table 14. Top neurotech deals of 2021

CompanyTotal raised (in US$m)Last financing size (in US$m)Valuation at last financing (in US$m)Deal TypeIf capital raise, then round
Ginger23630003000Merger/Acquisition
Neuralink3632052105Later Stage VCSeries C
HeartCare Medical (HKG: 06609)117145854IPO
Huma (Other Healthcare Technology Systems)210130600Later Stage VCSeries C
Pear Therapeutics (NAS: PEAR)3961251600PIPE
NeuroPace (NAS: NPCE)553102390IPO
Woebot Health130100230Early Stage VCSeries B
ONWARD (Therapeutic Devices) (AMS: ONWD)16387442IPO
Cala Health12277228Later Stage VCSeries D
Happify Health11973435Later Stage VCSeries D

Neurotechnology applications extend further than medical devices.

Currently the field of neurotech is represented mostly by medical device and research industries, but the neurotechnologies that are being developed also have potential for application in other industries. These non-medical applications could also be pulling early adopters of neurotechnology and help drive the demand for neurotechnology products.

Consumer devices

Although traditionally designed to be used in clinical and research settings, the recent advances in neurotech translate to more portable, cost and user-friendly devices. These advances could allow people to monitor their own brain waves and interface their brains with external devices. This has created a whole new market for neurotech: wearable devices marketed directly to the consumer. There are a number of different markets where neurotech wearables have potential to be a disruptive technology, which are discussed below.

A. Wellness industry

Individuals already monitor a wide range of characteristics of their bodies using wearables, including heart rate, sleep, and movement patterns. Most of these wearables are worn below the neck – watches, chest straps, rings – but what if a new option were worn on the head? There have recently been several consumer grade neural devices introduced to the market that are targeted towards general wellness such as focus, sleep, meditation and working memory.  

Most consumer devices are EEG headsets packaged in an ergonomic design that also has the wearable form factor for the consumer. Generally, the number of sensors in a consumer grade tends to be lower than research grade, and dry electrodes are used to facilitate faster and easier set up for the user.  

Consumer-operated neuroimaging headsets could also enable the development of a widescale database of the broad population’s neural data which could help produce powerful findings related to neurological disease. The public sharing of data opens the door for scientists to probe un-investigated scientific questions, but clearly individual privacy rights would need careful protection….  

Consumer devices escape FDA regulation despite claims of reducing stress or improving focus or aiding sleep. While these may sound like clinical benefits, such products can qualify as “general wellness” devices provided they are low risk and can avoid claims about diagnosing or treating specific diseases or health conditions [173].

B. Neuro-Gaming

The gaming sector is a good example of this. Current interaction patterns between gamer and computer are restricted by mouse, keyboard, gamepad and console. But advances in BCI could allow the interpretation of neurological signalling which could provide quicker and more sensitive actions when playing such games. It is thought that these types of games could also improve physiological factors such as brainpower, health and cognitive skills. The concept of neuro-gaming technology is still relatively new, however the rapid developments happening in both the software and the technologies mean that neurogames could offer exciting additional challenges via multiple actions. It is predicted that the neuro-gaming technology market will register a CAGR of 12% over 2021-2026 [174].

C. Neuro-sporT

Another potential market for neurotech is the sport industry. Neurotechnology offers the potential to modulate and stimulate the brain which could prime high-speed decision making, which could be useful in many sports from boxing to cricket. It could aid in developing muscle memory faster by accelerating neuroplasticity. There is even evidence emerging that stimulating the vestibular nerve with a low-level current could tweak fat storage [175]. Neuro-sport is an emerging market for neurotechnologies and one that could totally disrupt how we play and see sport.

D. Ed-Neurotech

If we can use neurotechnologies to enhance cognition, focus and attention, it is not farfetched to believe that one day we may be using neurotechnologies to augment the education process. Technologies such as brain imaging are already being used by “ed-neurotech” researchers to produce insights for policymakers and practitioners. Furthermore, EEG headbands have been used to study students brain-to-brain synchrony, and even visualise the brain focusing [176, 177].

“The implications for learning are obvious. When we know what you think, we know whether you are learning, optimise that learning, provide relevant feedback, and also reliably assess. To read the mind is to read the learning process… We are augmenting the brain by making it part of a larger network … ready to interface directly with knowledge and skills, at first with deviceless natural interfaces using voice, gesture and looks, then frictionless brain communications and finally seamless brain links [178].”
Donald Clark, founder of the AI-based online learning company Wildfire Learning.

Business and neurotechnologies

Neurotechnologies could be sold to a range of different businesses for different needs. The field of neuromarketing allows the study of the brain’s response to both marketing and advertising. For example, BitBrain has developed a neurotechnology solution to measure emotions of consumers during product development to allow companies to design better strategies adapted to a customer’s need [179] . Furthermore, neurotech could be applied by businesses in the workplace to boost employee engagement and focus, which could be particularly useful as the world shifts to a new way of remote working after the COVID-19 pandemic.

Military and neurotechnology

In the United States, programs within the Defense Advanced Research Projects Agency (DARPA), Intelligence Advanced Research Project Activity (IARPA), and several branches of the military are examining ways that brain science can be employed to augment warfighters’ and intelligence operators’ performance, and alter adversaries’ capabilities with regards to key cognitive and physical tasks. Similar projects are being conducted by other NATO and Non-NATO Military Alliance (NNMA) nations, as well as North Korea, Iran, Russia and China [180].

Challenges for neurotech

Future regulation surrounding neurotech

The fascinating aspect of neurotechnology is that, in a certain sense, human beings and machines can be “fused” together to a degree previously unheard of. The ability to record, stimulate and create closed feedback loops within the brain creates obvious ethical, regulatory and societal concerns. Clinical neuortechnologies are currently regulated by the United States Food and Drug Administration (FDA) Center for Devices and Radiological Health (CDRH) in the US. 

How will the ethical use of these technologies be policed? If not regulated, could these technologies be used to enhance cognition, change personalities or alter perceptions? If we had access to vast amounts of brain data, could we categorise people by intelligence or temperament? What if it doesn’t work, stops working or has unwanted effects? 

There are clearly risks to unregulated neurotechnologies, and these risks should not be ignored given the speed at which the technology is advancing and the amount of money invested in the sector (US$74.3b in the last decade).

Broad use of neural data

The use of consumer neurotech devices will enable the collection of large amounts of neural data, way beyond what is possible in a research or clinical setting. If this data is shared, it could be useful in managing neural diseases, however, there are concerns that it could also be used to draw unwanted inferences about individuals. This concern currently exists mostly in the corporate, employment and insurance sectors. The potential for neural data to be used against individuals has been raised before, prompting calls for stronger data protections. These could include obtaining informed consent from individuals to use or share their data, anonymising datasets, and requiring companies to disclose how neural data are managed. Further concerns include the data being leaked online, sold to third parties, or subjected to uses to which the consumer did not consent.

These concerns are like those raised with genetic data, where there is now legislation in place such as the Genetic Information Non-discrimination Act (GINA) to limit discrimination based on genetic data [181]. 

For neurotechnology to gain wide public acceptance, there must be a framework in place to protect users’ neural data.

Potential safety risks

The risk of inducing maladaptive plasticity with neurotechnologies is expected to be small in clinical scenarios where a medical professional is likely to monitor a patient’s progress and change the intervention at the first signs of any side effects. For consumer devices, however, end users might not be aware of this potential risk and unknowingly cause harm to themselves. While this risk is likely to be small for well-defined applications (such as improving meditation), this risk could be exacerbated with open-ended do-it-yourself kits. Consumers can freely change the parameters of a device (such as stimulation strength) or use the device well beyond what was intended or studied. For these reasons, some researchers have proposed that consumer-grade neural training devices should be regulated like medical devices [182]. 

Other ethical challenges and potential future recommendations, as set out in neuroethics [183], are described in Table 16.

Table 15. Potential ethical challenges for neurotechnologies and recommendations.

ChallengeDescriptionRecommendation
Brain data privacyNeural data can provide access to information proximal to one’s identity. It is one of the few remaining domains where invasions of privacy haven’t been realised. Concerns around access to this data include: Unauthorised access, consent to share data, consent to brain modulation, making inferences based on large data to assess populations, fraud and identity theft.Create defaults that require an active opt-in to share brain data. Encrypt brain data along its full arc, from brain recording site to output device. Restrict sharing of brain data.
BiasThe assumptions, values, and limitations underlying research, whether they are appropriate or inappropriate, intentional or unintentional, that could create projections of what is considered “normal” brain function and what is not.Recognise the role of bias within a research team or company, but also to communicate to others how these biases affect an intervention or product. Actively counteract bias by seeking end user feedback or creating bias checklists. 
Promote equitable access to neurotechnologies.
EnhancementEnhancement (or augmentation) interventions are those that “improve human form or functioning beyond what is necessary to sustain or restore good health”.Scientists and ethicists should work alongside companies to ensure that neurotechnologies are developed with appropriate ethical foresight.
SafetyRegulation focused on the long-term effects of emerging technologies, such as neurotechnologies for brain stimulation, often requires decision-making under considerable uncertainty, given the lack of longitudinal observations and dataImprove informed consent for neurotechnology.
Commercial responsibilityAs some neurotechnologies do not fit into the traditional medical regulatory frameworks, there could be conflict between company interests and the goal of ensuring safety of participants and the public good.Create a broad international commission designed to meet regularly and assess neurotechnology developments with the aim of providing ethical guidance and shared commitments to responsible innovation.
Identity and AgencyFeatures sometimes ascribed to personality – impulsivity, conscientiousness, neuroticism, openness, or agreeableness – may be altered through neural interventions. Building on existing human rights frameworks, establish “neurorights” (mental liberty, mental privacy and mental integrity).

Calls for neurotech regulation

There are a number of initiatives specific to neurotechnology that are currently emerging;

  • At the end of 2019, the Organisation for Economic Cooperation and Development (OECD) released its first formal recommendation on responsible innovation in neurotechnology, the first published international standard in this domain.  
    In the document, the OECD recognised that mental and neurological disorders are increasingly recognised as major causes of death, remain untreated and impose significant economic and social welfare costs that Neurotechnology could aid. However, it highlighted the need for sharper scrutiny into the ethical, legal, and social challenges raised by novel neurotechnologies from governments, companies and researchers  
  • The neurorights initiative from Columbia University was initiated to engage the United Nations, regional organisations, national governments, companies, entrepreneurs, investors, scientists and the public at large to raise awareness about the human rights and ethical implications of neurotechnologies [185].  
  • In September 2021, the UN’s international bioethics committee issued a draft report that found there were “few regulations on neurotechnology outside of regulation on medical devices”, and warned of a plethora of risks, including “neurosurveillance” at school or work. UN Secretary-General António Guterres specifically mentioned neurotechnology as one of the frontier issues that needs to be taken care of in the next six years [186]. 
  • In 2021 the EPSRC, in partnership with MRC, invited proposals for Network Plus grants that build capability for responsible research across the breadth of neurotechnologies [187].

Regulations are likely to increase and the rate at which that happens is unpredictable. Some are wary of moving too quickly to regulate neurotech which could stifle innovation and instead preach that consumer based neurotech start-ups should be encouraged to develop privacy conscious and ethically minded products. Others favour strict regulation, fearing that neurotech may become the next Facebook or Theranos. However, for now, the rules of neurotechnology remain unwritten.

About NTX Services

NTX Services is the exclusive partner of NeuroTechX, the largest international community of neurotechnology experts and enthusiasts, with an international presence in over 100 countries, and ~20,000 members in the online community.

The company offers consulting and recruiting services to neurotech companies at various life stages internationally. Since inception, it has worked on projects for clientele in the US, Canada, the EU and Asia, reflecting the international nature of its services and the evolution of the field itself.

Specifically, NTX Services’ projects range from preparing strategic marketing plans, to comprehensive go-to-market strategies, to regulatory roadmaps to translating business plans into full financial models on the business side. On the technical side, it has also advised on a variety of topics ranging from product features and roadmaps to planning for optimal clinical trials, etc.

NTX Services has actively engaged in projects ranging from consumer-grade EEG headsets to VR-based solutions, to purely software-based solutions to invasive solutions. It has examined use cases ranging from consumer grade applications (Iike wellness, meditation, sleep) to clinical applications (like quadriplegia, depression, stroke rehabilitation and more).

The information in this Foreword is based on a review of ~1,600 companies (ranging from startups to larger medical device companies like Medtronic) in neurotech across ~90 countries, working on a wide variety of different technologies and applications. It is also informed by conversations with players across the entire ecosystem in neurotech (including company founders and executives, investors, academia, etc) and with players in collaborative industries (for example pharma, fitness, entertainment and more). Due to the confidential nature of NTX Services’ work, the company has intentionally limited the facts in this Foreword to published data (databases or news items), although the opinions expressed are its own. As the field itself is vast, this Foreword is intentionally focused on bigger picture ideas.

If you’re curious about neurotechnology or the type of work NTX Services does, please visit their website or contact them directly through [email protected]

NTX Services Foreword

Neurotechnology (neurotech), while still an emerging industry, has attracted both major capital investments, and extensive media coverage in recent years. As tech relentlessly searches for the next “big tech platform” in the aftermath of the smartphone era [188], NTX Services proposes that the answer may lie within our own minds.

Often described as a new field, neurotech is actually based on decades of academic research, which has often been held back from commercialisation at scale due to technological limitations, and slow changes in government policies and regulations. NTX Services defines neurotechnology as any technological intervention that interacts with the brain or central nervous system either directly or indirectly.

To contextualise current neurotechnology innovations, a sense of the history and key developments in the field must first be appreciated.

The history of neurotechnology

Although people have been researching the brain and its bioelectrical signals since the 1600s [189], the first major breakthrough that led to a true understanding of the way the brain functions was the invention of the electroencephalogram (EEG) by Hans Berger in 1929 [190].

Berger’s invention of the EEG was significant as it allowed people to go from broadly measuring and monitoring brain signals to conducting more precise analyses of different brain waves. The creation of the EEG was a generative moment in the field that has had a lasting impact on modern neuroscience. As EEG readings were visualised on a screen through a computer, this device could be considered as a rudimentary brain computer interface (BCI); Given that BCIs are a critical part of modern neurotechnology, it is important to provide a working definition: a BCI is a system that measures central nervous system (CNS) activity, and converts it into artificial output that replaces, restores, enhances, supplements, or improves natural CNS output – thereby changing ongoing interactions between the CNS and its external or internal environment [191].

Otfrid Foerster and Hans Altenburger further leveraged Berger’s work with EEG by performing the first invasive EEG recording only five years later [192].

The history of Neurotechnology

1600sScientists begin researching the brain and bioelectric signals.
1929Hans Berger discovered EEG.
1934Foerster and Altenburger published results from 30 intraoperative EEG recordings in different areas of the brain.
1937Wilder Pinfield and Herbert Jasper combined cortical stimulation with EEG recording, establishing an interdisciplinary approach in the Montreal Neurological Institute (MNI).
1940sWarren McCollough and Walter Pitts created a computational model for neural communication networks, paving the way for neural network connection research.
1957Frank Rosenblatt created the Perceptron at Cornell’s Aeronautical Lab.
1960sMarvin Minsky and Seymour Paper discovered two major problems with the computational systems that processed neural networks. This stagnated neural network research.
1980sCT and MRI recordings were invented.
The cochlear implant became the first implantable brain device to gain widespread adoption.
David E. Rumelhart and James McClelland started the focus on connectionism in computer systems.
1988Dr. Phil Kennedy created the modern day BCI.
1990sSupport vector machines overtake neural networks in popularity.
2000sThe advent of deep learning.
2004BrainGate implanted a device into the motor cortex of Matthew Nagle’s brain, allowing him to move a prosthetic arm.

Building on this discovery, doctors Wilder Penfield and Herbert Jasper successfully combined the EEG recording technique with cortical stimulation and established the use of an interdisciplinary approach in the Montreal Neurological Institute (MNI) in 1937, which quickly cemented Montreal, and the MNI in particular, as a global leader in neuroscience [193].

In the 1940s, Warren McCollough and Walter Pitts created a computational model for neural communication networks based on mathematics and algorithms labelled “threshold logic” [194]. This system paved the way for neural network connection research to split into two distinct approaches, one of which focuses on biological processes in the brain, while the other relates to the application of neural networks to artificial intelligence (AI).

This work was the base for Frank Rosenblatt’s Perceptron in 1957 at Cornell University [195]. The Perceptron was the world’s first artificial neural network that explained how the brain processes and distinguishes between different visual stimuli. This device introduced the concept of what is now considered to be a form of unsupervised machine learning (ML), as it allowed a system to perform classifications based on data categorisation and pattern recognition.

Due to limits in the processing power of computers at the time, research on neural networks stagnated in the 1960s and 1970s [196]. Following this period of relative inactivity, a number of significant neurotechnology innovations emerged in the 1980s that formed the basis of many of the tools that are still used today.

Non-invasive technologies like computerised tomography (CT) scans and magnetic resonance imaging (MRI) recordings provided brain imaging with much higher spatial and general image resolution than what was previously possible. Additionally, other non-invasive technologies that tracked biological data (like EEG, galvanic skin response (GSR), pulse and eye tracking, etc.) started being used for non-medical purposes (like the analysis of human reactions to stimuli).

Contemporaneously, cognitive science researchers like David E Rumelhart and James McClelland began working on connectionism using computer systems, particularly in relation to language learning models [197]. Connectionism is a research movement that sought to explain intellectual abilities using artificial neural networks [198].

The Neurotechnological boom of the 1980s also benefited invasive therapies; the cochlear implant, an in-ear device used to improve and restore hearing, became the first neural implant to gain widespread adoption [199].

In the 1990s, traditional ML became a more popular research approach than neural networks with the emergence of more complex algorithms that could both analyse and classify data and perform regression analysis [200]. These algorithms also improved the predictive power of hardware and software-based solutions.

Implantable BCIs (as described in mainstream media today) started with Dr Phil Kennedy in 1998 [201]. Kennedy was a neurologist that treated Johnny Ray, a Vietnam War veteran who suffered from a brainstem stroke. The brainstem is the main communication pathway between the brain and the spinal cord, and through this, the whole body. Therefore, when the brain stem is damaged, people can lose the ability to breathe, touch, or move, while still retaining their ability to think, and their consciousness – a condition known as being “locked in.”

Kennedy was able to successfully restore this communication using invasive electrodes. This procedure took 12 hours, and required the placement of electrodes, which were encased in two glass cones, into the cortical area of the brain that controlled movement of the left hand. In this way, Ray could imagine moving his left hand, thus causing neurons in the area to fire with greater frequency, and allowing the electrical impulse passing through the axons could to then be intercepted and directed through the electrodes to an external receiver that would translate the signal for Ray’s computer. From there, the signals could be used to move a cursor on Ray’s computer that could help him communicate and express his feelings [202].

Other invasive technologies that made significant progress in the 1990s include deep brain stimulation (DBS) and vagus nerve stimulation (VNS), therapies that electrically stimulate specific brain areas through implanted electrodes [203], which have brought relief to individuals suffering from otherwise intractable brain disorders such as Parkinson’s and epilepsy [204].

Progress in neurotechnology continued through companies like BrainGate, which was one of the first to successfully implant a device into the motor cortex of a subject’s brain back in 2004, thus allowing the subject to move a prosthetic arm, open email, and even play video games [205]. Dr John Donoghue (of BrainGate) realised that the problem lay in the unresponsiveness of the subject’s actual motor neurons due to the disrupted pathway between the brain and the rest of the body, and used this to inform the development of the implantable treatment.

Most recently, Neuralink was founded in 2016 [206]. Elon Musk backed this early venture, touting the idea of merging biological and machine intelligence and declaring in a Vanity Fair article “for a meaningful partial-brain interface, I think we’re roughly four or five years away” [207], thus bringing the concept of brain implants into mainstream conversations.

As neurotechnology lies at the intersection of neuroscience, engineering (electrical, mechanical, software) and AI/Data Science, developments in these fields are key to its continued innovation.

Below are some examples of recent advancements in these fields that have been driving innovation in the past decade.

Advancements in our understanding of neuroscience

Most closely tied to neurotechnology, advancements in the fields of psychology and neuroscience have led to new and improved neurotech devices and applications.

Specific examples include:

  1. A deeper understanding of neuroplasticity and the knowledge that the brain is malleable even in adulthood led to the development of brain game companies aimed at improving “brain fitness” by training the brain [208].
  2. Better understanding of memory formation and recollection led to the formation of digital health companies that aim to improve memory [209].
  3. Further developments of therapeutic techniques like cognitive behavioural theory (CBT) that led to the development of AI powered chatbots targeting conditions like depression through automated CBT [210].
  4. The formation of institutions like the Allen Institute in 2003, which is engaged in mapping all the various regions of the brain, to gain greater understanding about the human brain and its various functions [211].

Neurotechnology has also been advanced by seminal neuroscience studies on mice. For example, neuroscientists were able to activate individual neurons in live and alert mice using optogenetics (a method of controlling cells in living tissues with light and genetics) [212]. When replicating this research seven years later, the same team was able to optogenetically activate cells in the human visual cortex to trigger hallucinations, which could provide insight into hallucination-causing mental illnesses such as schizophrenia, Alzheimer’s and more [213].

Advancements in AI and data science

Advancements in AI and data science have also been crucial to the development of the field, as these methods can be used to predict or analyse neural recording data [214].

These advancements have led to several neurofeedback applications which leverage algorithms to interpret brain signals and provide feedback to users for a variety of purposes, including focus and meditation.

Furthermore, existing devices have been using AI algorithms to improve their function. For example, certain DBS devices that stimulate neural regions and modify neural activity can now leverage AI algorithms to manage the frequency of stimulation for optimal treatment, potentially reducing any unnecessary stimulation [215].

Advancements in engineering & computing

The great number of innovations and improvements in hardware and software engineering over the past couple decades has also been critical in developing the field of neurotechnology. An example of this is the fact that advances in semiconductor manufacturing have led to a dramatic improvement in the quality of sound for cochlear implants [216].

Similarly, advancements in graphics processing units (GPUs) allowed for the creation of massively parallel processors that are optimized for the computational burden of training large neural nets, which have contributed to many of the neurotech products on the market today [217].

The industry also continues to benefit from improvements in miniaturisation, improved wireless connectivity, and more, to this day.

What technologies are typically classified as neurotechnology?

The numerous and diverse applications of neurotechnology are partly due to the fact that neurotech encompasses a wide variety of technologies and allows for the collection of many different types of data.

EEG data, the most commonly used form of brain data, is typically gathered via non-invasive, low spatial resolution techniques that record cortical activity from an array of extracranially-placed electrodes. EEG devices are typically portable, and can observe regional brain activity in real time, enabling a wide range of applications in consumer wellness like meditation, attention, and focus. EEG solutions are also often used in medicine to address and monitor conditions ranging from ADHD to ALS. However, the practicality of EEG solutions come with some drawbacks including: (1) low signal to noise ratio (meaning that artefacts such as ancillary movements like grinding of the jaw can influence the data quality gathered), and (2) lower spatial resolution relative to imaging techniques like MEG and fMRI (more on this below).

Imaging techniques like fMRI and fNIRS are non-invasive, and derive insights based on blood flow and oxygenation to various parts of the brain. The main drawback of these techniques is that they use proxy measures (e.g., blood flow) to assess neuronal activity.

Clinically, ultrasound technology is becoming increasingly prevalent as a superior alternative as it can reach deep brain regions, has a high spatial resolution, and is adaptable for closed loop therapies. However, such technologies have not yet been commercialised at scale.

Brain stimulation (referred to as neurostimulation or neuromodulation) is another key application enabled by a wide range of stimulation techniques like DBS, implanted microelectrodes, endovascular electrodes (EE), optogenetics, VNS, repetitive transcranial magnetic stimulation (rTMS), transcranial electrical stimulation (tES) and transcranial focused ultrasound stimulation (tFUS) that stimulate specific reactions in the brain, pushing applications beyond purely diagnostic to therapeutic.

The following graph describes the various technologies available within the realm of neurotechnology and their applications in more detail [218]:

MEG
Magneto-Electroencephalography

EEG
Electroencephalography

ECoG

Electrocorticography

DBS
Deep Brain Stimulation

Implanted Microelectrodes

EE
Endovascular Electrodes


fMRI
Function Magnetic Resonance Imaging

fNIRS
Function Near-Infrared Spectroscopy

fTCD/tFUS
Focused Transcranian Doppler/Transcranian Focused Ultrasound Stimulation


Optogenetics

VNS
Vagus Nerve Stimulation Noninvasive: tVNS or nVNS

rTMS
Repetitive Transcranial Magnetic Stimulation

tES (tACS, tDCS)
Transcranial Electrical (AC or DC) Stimulation


DBS (deep brain stimulation)
An invasive technique that modulates brain activity with surgically implanted electrodes embedded deep in the brain. DBS electrodes monitor neural activity and deliver electrical impulses, usually to the globus pallidus, nucleus ventralis intermedius thalami, or subthalamic nucleus.
Chronic pain, cluster headache, dystonia, epilepsy, essential tremor, huntington’s, major depression, MS, OCD, Parkinson’s, substance abuse, TBI
ECoG (electrocorticography)
An invasive, high-throughput technique for measuring neuronal activity with a patch or strip of electrodes applied directly on the brain’s surface. ECOG measures synchronized postsynaptic action potentials from large populations of cortical pyramidal neurons.
Epilepsy diagnosis, Spinal cord injury, Locked-in Syndrome, Speech and movement synthesis from neural decoding, Movement disorders
EE (endovascular electrodes)
A miniature mounted electrode array that is passed intravenously into the cerebral vasculature and placed in close proximity to specific brain regions.
Restoring voluntary motor impulses to control digital devices in patients with severe paralysis
EEG (electroencephalography)
Non-invasive, low spatial resolution technique used for recording cortical activity from an array of electrodes placed extracranially via neuroimaging or via portable devices. EEG measures several bands of neural oscillations (delta, theta, alpha, beta, gamma, and mu waveforms) to observe regional brain activity in real time.
ADHD, ALS, Chronic pain, Computer control, Consumer wellness, Electrooculography, Epilepsy, Sleep disorders, Stroke rehabilitation, Widely used in diagnostics and monitoring
Implanted microelectrodes
Tiny electrodes (thickness under 50pm) delivered via craniotomy, used in electrophysiology for recording neural signals and/or stimulating the brain.
ALS, Epilepsy, Blindness/ocular injury, Locked-in Syndrome, Major depression, OCD, Peripheral nerve injury, Memory, Movement disorders, Spinal cord injury, Stroke
MEG (magneto-electroencephalography)
A technique that uses magnetometers and gradiometers to amplify and record electromagnetic fields created by large groups of neurons. SQUID-MEG (conventional MEG) requires superconducting elements in a supercooled environment. Optically pumped MEG (OP-MEG) and other atomic magnetometers sense magnetic fields at “room temperature”.
SQUID-MEG – Epilepsy, Stroke, TBI

OP-MEG – Consumer use for arousal, attention, emotion, learning, & memory, Sleep and concentration studies
Optogenetics
A stimulation method that can activate preselected neurons and circuits using light. Targeted cell types are genetically modified to produce light-sensitive proteins called opsins. These proteins trigger action potentials when the targeted cells are exposed to a specific wavelength of blue light.
Neural circuit research, Reversible disease models, Structure-function mapping, Vision restoration
rTMS (repetitive transcranial magnetic stimulation)
Noninvasive neurostimulation technique that uses a wire coil to produce a magnetic field that penetrates through the skull. The magnetic field induces small electrical currents that stimulate targeted areas of the brain under the coil.
Auditory hallucination, Borderline personality disorder, Bipolar disorder, Major depression, OCD, PTSD, Parkinson’s, Schizophrenia, Smoking cessation, TBI
tES (tACS, tDCS)
[transcranial electrical (AC or DC) stimulation]

Noninvasive neurostimulation technique that uses a wire coil to produce a magnetic field that penetrates through the skull. The magnetic field induces small electrical currents that stimulate targeted areas of the brain under the coil.
Amblyopia, Alzheimer’s, Cancer, Consumer DIY kits, Epilepsy, Intraoperative imaging, Major depression, Mild TBI, Parkinson’s, Stroke, Sleep, Substance abuse
VNS (vagus nerve stimulation)
Noninvasive: tVNS or nVNS

Device that delivers electrical impulses to the vagus nerve via an implanted electrode or a noninvasive wearable clip or handheld device. VNS alters levels of neurotransmitters such as serotonin, norepinephrine, GABA, and glutamate (all brain chemicals that affect mood). The amount of stimulation is set by a magnetic wand by a doctor or adjusted by the patient in the case of tVNS/nVNS.
Alzheimer’s, Cancer, Chronic pain, Depression, Epilepsy, Migraines, Parkinson’s, PTSD, Stroke
FMRI (functional magnetic resonance imaging)
Imaging technique that uses magnetic fields to detect changes in cerebral blood flow as a marker for brain activity. Specifically, fMRI measures deoxygenated to oxygenated blood ratio in the brain (which have different magnetic susceptibility) to identify neurons that are firing (active neurons consume more oxygen), revealing which structures of the brain are active at a given moment.
Bipolar disorder, Brain tumors, Chronic pain, Epilepsy, Major depression, Memory studies, Schizophrenia, Widely used in diagnostics and monitoring
FNIRS (functional near-infrared spectroscopy)
A neuroimaging technique that measures haemoglobin concentration in specific brain regions using a near-infrared light source (-6501000nm) and a detector that measures photon signal intensity. Blood oxygenation alters the signal and this fluctuation is used as a biomarker for brain activity.
Deafness, Depression, Mental arithmetic, Motor execution, Motor imagery, Music imagery, Stroke, TBI
FTCD/tFUS (focused transcranial doppler/transcranial focused ultrasound stimulation)
FTCD is an imaging technique that uses a probe to transmit ultrasound pulses into the brain to determine velocity changes in blood flow that may correspond to neural activation. FUS delivers low-intensity pulsed ultrasonic waves to the brain to directly modulate specific neuronal pathways. FUS should be distinguished from high-intensity ultrasound, which is ablative.
fTCD – Alzheimer’s, Cerebrovascular disorders, (Language, face and colour processing, intelligence studies), Tobacco dependence

tFUS – ALS, Anxiety, Coma recovery, Depression, Essential Tremor/Parkinson’s, Mild cognitive impairment, Pain

Large Medical Device companies paved a pathway for new(er) Emerging Technology

As this report will show, start-ups have, and will continue to, influence the industry significantly – these companies tend to display the most growth, and produce more novel innovations and discoveries than larger established corporations. That said, it is worth noting that this industry was shaped by large Medical Device companies, particularly through their production and distribution of neurostimulators.

In the early 1960s, Medtronic introduced the first commercially available cardiac pacemaker, which was eventually adapted to treat chronic pain in the latter half of the decade. Upon witnessing growing interest in nervous system stimulation, Medtronic and Cordis (then, Avery Laboratories) developed the first-generation of neurostimulators [219]. In 1975, Medtronic trademarked the term “DBS,” and neurostimulation technology evolved further, even extending to the spinal cord. Following NeuroMed’s introduction of a series of spine stimulators, other major players continued developing therapeutic technologies like electrodes and microelectronics, and remained focused on implantable devices. These large companies also influenced the United States’ Food and Drug Administration’s (FDA) development of standards and regulations in the medical device market. Other companies like Johnson & Johnson, St. Jude (now, Abbott), Boston Scientific, Nevro, NeuroPace, and many more began joining the neurological device market. Eventually, companies developing and producing non-implantable stimulators also began appearing in the field. These companies made transcutaneous electrical nerve stimulation (TENS) devices available on the mass-market (like Bayer’s Aleve TENS Device), and produced TMS and tES devices(which are usually only available by prescription from a medical professional). In recent years these products have been referred to as “bioelectronic medicine” and/or as “Neurotech devices.”

Thus, large medical device manufacturers have had a huge impact on the field of Neurotechnology. These companies were the first to adopt the discoveries of modern neurosurgery and neurology, influenced the establishment of medical device regulations, and have accelerated the development of implantable technologies. Today, these products are approved for the treatment of various conditions like chronic pain, Parkinson’s disease, tremor, dystonia, epilepsy, depression, and more. Despite the major uptick in the number of successful Neurotechnology startups, big companies will undoubtedly continue to be active participants in this industry, primarily in the form of new implementations and acquisitions.

Neurotechnology has applications across a wide variety of industries

Not only does Neurotechnology encompass a wide variety of technologies, but it can also be applied to a diverse array of industries. As the Co-Founder of TransTech (a partner organization of NTX Services), Nichol Bradford recognized: “[these industries] ha[ve] the largest Total Addressable Market (TAM) in the world. Everyone has a brain, everyone has a heart, and we all long for happiness – whether we know it or not” [220].

Indeed, one of the greatest benefits of Neurotech is that it can have applications ranging from healthcare to entertainment to defense to wellness to automotive to insurance and more. As Neurotechnology can be used across so many industries, this field could play a critical role in improving the human experience across multiple dimensions.

Given its roots in neuroscience, Neurotechnology has since been used successfully across the healthcare industry for both research and therapeutic purposes.      

Because the human brain plays a key role in the consumption of entertainment content, Neurotech also has clear applications in this sector. Neurotech has been used in gaming to improve a player’s reflexes, and can even measure a player’s response to external stimuli and use that information to adapt the game to their state of mind. Similarly, the principle of “adaptive content” (defined as content that “relies on collecting various data points about each…user, interpreting the collected data and replacing parts of the content with user-centric data”) [221] can be applied across a number of fields in entertainment like music, movies, gaming, etc. NTX Services is currently aware of projects where researchers are exploring adapting the film experience to a user’s state of mind in real time. If successful, these efforts could take current rudimentary adaptive content (like Netflix’s series Black Mirror) to the next level and personalize entertainment content to a viewer’s mental state in real time.

Neurotechnology also has a number of practical defense applications; in fact, many of the advancements in Neurotech in the United States of America (US) can be attributed to the Defense Advanced Research Projects Agency (DARPA), which funds and research Neurotechnology applications. As one might expect, most Neurotech defense applications are confidential, but one public example of this particular application is the Spark Defense product created by Spark Neuro, that “provide(s) unparalleled neuroscience-based artificial intelligence tools to counter violent extremism, enhance intelligence gathering, and assess cognitive performance and health” [222].

As integration of man and machine applications are explored extensively by Neurotech startups, the automotive industry is not far behind the curve. In sharp contrast to autonomous driving projects, some large automotive manufacturers like Daimler (Mercedes-Benz) and Nissan [223], are exploring applications that range from using that technology to enhance driver performance, to integrating a driver’s thoughts with the vehicle to improve the driving experience [224]. One example of this can be seen in the collaboration between Mind Maze and Andretti Autosport in the 2022 NTT IndyCar Series, which shows how Neurotech can help improve “safety and human performance in motorsport” [225].

One more example of the diverse applications of Neurotechnology is its use in both the Wellness, and Financial Services industries. When applied in Wellness, Neurotech is often used to improve meditation, focus, and sleep, and typically takes the form of a direct-to-consumer (B2C) business model.These Wellness applications can also be integrated into existing corporate wellness or employee benefits programs to provide a greater value proposition to employees.

Neurotech also has applications in the health insurance industry beyond its use as a therapeutic tool. As shown by Swiss Re, a global reinsurance firm, Neurotech wearables can be used to improve underwriting models by allowing the firm to collect data that helped them better understand loss ratios and improve premium pricing [226]. Neurotech can also be applied in high performance industries like investment banking and financial trading as certain technologies can be used to improve human performance either by enhancing focus or improving mental agility.

Investor interest in the industry is rising, demonstrated by an increase in the amount of capital invested and the variety of deals and geographies for this type of activity

Given both the breadth and depth of applications, investor interest in Neurotechnology is rising, particularly in the Health and Wellness sectors. Digital Health, which also encompasses some Neurotech applications, is starting to go mainstream – as demonstrated by Lux Capital’s launch of a Digital Health focused ETF [227].

A review of the amount of Capital invested in the Neurotech industry, and the number of deals is supportive of the view that investor interest in the field is rising over the past decade.

A Review of Deal History in Neurotechnology (Capital invested in B)
Deal count history in neurotech

As the industry continues evolving, there is an increase in both the number and proportion of deals in later stage financing rounds, for example, through Later Stage Venture Capital activity (Series B and beyond), as well as exit activity like IPOs.

Beyond a basic understanding of Financing activity in the field, it is also important to get a sense of which technologies and applications are attracting the most capital.

Total Raised by Category (Past 10 Years Data)

Neurostimulation companies have received more than half the capital in the space over the preceding ten-year period. NTX Services believes this is partially explained by how established the technology is (through academic research, studies, etc.), the research and development (R&D) heavy nature of the companies in this field (reflecting a higher need for funds), and the established FDA regulatory pathway for the commercialization of technologies like DBS. It is worth noting that the majority of technologies that attracted Capital are typically applied as Therapeutics, not Diagnostics, suggesting some implicit preference on investor’s part.

It’s also worth noting that Suppliers (including suppliers to Research & Academia, Industrial Parts Suppliers like Electrode manufacturers, etc.) also benefit from increasing Investor interest, despite having a less consumer or patient facing role, as they drive innovation across multiple areas of the industry by either reducing the costs of R&D for their clients or by creating new products/services that drive continuous innovation. These companies also benefit from the growth of the industry as a whole as a result of increasing demand for their products.

Total CapitalRaised by Country in Neurotech (Past 10 years data)

A review of the source of Capital Invested in Neurotech, also yields interesting insights into attractive geographies for these companies.

Specifically, the US remains the single most attractive geography for Neurotech companies, accounting for > 75% of the capital invested in the space. This is partially influenced by the ease of establishing an investment vehicle and disbursing funds to early-stage companies in the US, the policies and programs established in the country that are supportive of Neurotech, and the quality of research at key institutions like the University of California at San Francisco, the University of California at San Diego, Rice University, etc.

Beyond the US, Germany, France, Israel, the UK, and Canada are also emerging sources of investment for companies in the field.

Total Raised by Use Case in Neurotech (Past 10 years Data)

Every technology should be created with a specific purpose, something well evidenced by looking at the end-applications for Neurotechnology. Over the past ten (10) years, solutions targeting Movement Disorders have attracted the most capital, followed by Neurological diseases, Mental Health applications, and Wellness applications.

A believer in Maslow’s hierarchy of human needs may have fun arguing that the order of preference for these companies reflects fundamental truths of the human condition (meaning that Physiological Needs (Movement Disorders, Neurological diseases), are followed by Belonging and Love Needs (Mental Health), then followed by Self Actualization and Transcendence (Wellness)).

Consumers are also slowly starting to see the value of Neurotechnology solutions in their everyday lives for both medical and wellness applications

Despite the enormous potential of Neurotechnology, consumer adoption has been historically low for a number of reasons for both Consumer and Clinical applications.

Companies producing consumer-facing products can find reaching their target market challenging, while companies producing clinical products and solutions can face difficulties in development and distribution.

Challenges in Consumer Applications

Business-to-Consumer (B2C) Neurotech companies typically have a difficult time with consumer education, resulting in lower-than-expected consumer adoption numbers. This challenge is partially due to the team composition of early-stage companies in the field, as they are typically composed of a strong engineering and science staff, but can lack diversified skill sets in the areas most relevant to successful consumer adoption (like Marketing and Sales).

However, this is slowly changing – NTX Services’ own conversations with companies in this space suggest that they are beginning to appreciate the value of identifying individuals with such transferable skills and are adjusting their recruiting strategies accordingly.

Some other factors affecting low consumer adoption of B2C Neurotech products are: (1) reliance on channels that are inappropriate to a specific target market, reflecting a weak understanding of consumer behavior, and (2) underestimating the resources required to successfully market consumer-facing products (both in terms of personnel and finances). Another specific consideration for B2C companies claiming some form of health benefit is the validity of such claims and aligning marketing messages to match the body of evidence gathered to support these claims. For example, the “Brain Training” company Lumosity settled Federal Trade Commission (FTC) charges in 2016 that alleged “[the platform] deceived consumers with unfounded claims that Lumosity games can help users perform better at work and in school and reduce or delay cognitive impairment associated with age and other serious health conditions” [228].

Finally, while many players are currently exploring B2B2C (Business to Business to Consumers) models to alleviate some of the complexities associated with B2C models, the extent of the success of such strategies remains to be seen.

Challenges in Clinical Applications

Low adoption of clinical products is often due to the dual complexity of both developing and distributing these products.

Most visible in companies developing implantable solutions, the R&D costs of developing and conducting clinical studies are often prohibitive for many early-stage companies. Further, pursuing FDA (and other health authority) approval can be both expensive and time consuming as that process may require additional personnel with the right expertise, and proof of both safety and efficacy. Moreover, despite the speed of approvals for COVID vaccines in the context of the pandemic, these institutions remain bureaucracies that are, by nature, reactive to novel technology.

Furthermore, obtaining insurance codes for reimbursement can also be a lengthy process that can be similarly slow, if not more so. Even when a specific insurance code is accepted, the actual reimbursement rate may be low as the conditions for meeting the “medical necessity” standard can be quite cumbersome on patients and/or caregivers, resulting in lower disbursement volumes in practice.

However, despite the historically low consumer adoption rates, there are several favorable trends for Neurotech companies amongst customers.

The Changing Landscape for Increased Adoption of Neurotech

Healthcare has become increasingly consumer-driven, which has contributed to growth in Digital Health start-ups and the influx of ‘big tech’ companies into Digital Health (largely through Telemedicine) – for example, Amazon launched the Amazon Care network in 2019 to offer digital health services in the US.

Consumers are also now starting to experience difficulties resulting from the shortage of healthcare workers (particularly home healthcare workers), which drives the need for user-friendly technological interventions that can help people safely diagnose, treat, and/or monitor their health at home.

These changes have provided an opportunity for Neurotech as a growing number of Digital Health solutions are being developed to treat neurological, mental health, and overall wellness issues.

Consumer demand for Neurotech interventions could also be supported by a recent improvement in the reimbursement landscape for technological solutions; an example of this is the addition of a new appendix to the 2022 CPT code set (a set of insurance codes that allow for the reimbursement for medical procedures, services etc.) that provides a taxonomy for digital medicine services [229].

Another trend that supports a potential increase in consumer demand for Neurotech solutions is the general trend of increased personalization in consumer experiences across industries. A 2019 McKinsey survey reported that 37% of CMOs surveyed stated that facial recognition and/or bio data are more likely to offer consumers a more tailored experience [230]. As Neurotech offers unique insight directly into consumers’ brains, this industry is particularly suited to personalizing the consumer experience by leveraging wearable solutions that gather an individual’s biometric data in real time.

Neurotech is going mainstream as traditional companies begin incorporating these solutions into their current or future Product/ Service Offering

There are many traditional companies across various fields that have identified the potential of Neurotech within their industry verticals.

Given the natural connections with Neurotechnology, several pharmacological companies like Otsuka [231], Merck (whose CVC arm has invested in Neurable – a “company that makes Neurotechnology easily accessible to everyone, everywhere”[232]), and AstraZeneca [234] have invested in neuroscience and Digital Health.

Meta (formerly Facebook) is also exploring “wrist-worn neural input devices” as a promising method of making their Project Aria a reality [235].

The entertainment industry is also starting to use Neurotech. For example: Spotify and Neuro-Insight have worked together to use brain information to enhance the consumer experience of Spotify listeners [236]. This is just one example of how Neurotechnology can be used to better understand and enhance the user consumer experience across a number of fields. Emotiv has been particularly successful in this endeavor as shown by both the partnership between Emotiv and Yves-Saint Laurent to enhance the consumer’s experience in selecting fragrances [237], and the Aki-Emotiv Superbowl Report [238] that reported on consumer responses to products during culturally significant live events.

Neurotech is also being used to enhance human performance across various industries; for example, the company Neurotracker, has developed a software solution that can be used by athletes to enhance their reflexes, and can be used by financial traders to increase cognitive flexibility [239].

The US Olympic Wrestling Team has even used one startups neuroscientifically composed music as an all-day companion to improve focus and improve sleep quality while training for the Olympics [240].

Neurotechnology can also have applications in industries like Banking and Insurance; as Corporate Wellness programs are starting to recognize Neurotech as a possible solution to the industry-wide problems of stress and burnout, factors that contributed to the Great Resignation during the COVID-19 pandemic (a widely documented global economic phenomenon where employees are leaving roles that are not aligned with their personal values or objectives) [241].

As with many great innovations, Neurotech has been supported by Government Policy across multiple countries, though the US has been at the forefront of this endeavor

Several key policy changes have helped Neurotech companies grow and expand worldwide.

One such change was the launch of the BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative in the US in 2013. This ambitious project aimed to recreate the success of the Human Genome Project, and is currently housed in the National Institutes of Health (NIH) [242].

Signaling further support for growing the Neurotechnology industry, the current Biden administration in the US has announced a new agency, the Advanced Research Projects Agency for Health (ARPA-H), which was approved by the US Congress with a $1-Billion-dollar budget. ARPA-H puts Neurotech at the forefront of its mission to make pivotal investments in breakthrough technologies and broadly applicable platforms, resources, and solutions that have the potential to transform important areas of medicine and health for the benefit of all patients [243].

Although it has been subject to some controversy [244], China also launched a similar initiative, the China Brain Project, with a budget of approximately USD 15.8 billion.

Further, a number of multinational initiatives have been launched; for example, the International Brain Initiative whose signatories include Japan, South Korea, the US, Australia, and newer members China and Canada, and which was established in 2017 [245].

Though more mitigated than others, European lawmakers have also expressed interest in the expansion of Neurotechnology developments and companies through Organization for Economic Co-Operation and Development’s (OECD) documents examining issues related to Neurotechnology.

Regulatory Pathways are adapting to this emerging technology

As nations develop policies regarding, and engage with, the Neurotechnology industry, a couple of noteworthy regulatory changes and debates on standardization have emerged, regarding parameters within which the industry must operate.

The FDA is a global leader on the regulation of medical devices and products, often setting a precedent that equivalent institutions in other countries (particularly Western countries) tend to follow. As such, the FDA has had a clearly delineated Standards and Guidance for Neurological Devices (which issues guidelines related to biocompatibility, animal studies, sterility, pyrogenicity, etc.) publicly available, even as a draft, from 2019 [246].

In addition to this general standard, the FDA also issued a guideline titled Implanted BCI Devices for Patients with Paralysis or Amputation on May 20, 2021 [247], reflecting the importance the US has given to Neurotech solutions, and recognizing the unique issues of different devices and their therapeutic uses.

In recognition of the value of novel technology that can improve the lives of people with irreversibly debilitating diseases or conditions, the FDA Breakthrough device designation aims to expedite the review of certain types of innovative technologies and accelerate their path to commercialization. The FDA Breakthrough Device designation is sometimes misunderstood as a way for products to gain approval without clinical data; however, this program only aims to accelerate the evaluation of therapeutic solutions. As with the standard pathway, manufacturers that want ‘pre-market’ approval (PMA) or ‘De Novo’ approval must conduct clinical trials. Using the Breakthrough Pathway would simply expedite the commercialization process. Other advantages of using this Pathway include the possibility of regular contact with the FDA, the opportunity to request feedback on trial protocols and to make appropriate changes if needed, and the possibility of bringing a product to market earlier (and then continue trials after approval). For example, Blackrock Neurotech (an implantable BCI device company) was granted Breakthrough Device designation for its MoveAgain BCI system in late 2021, and is targeting 2022 for commercialization of this device that aims to offer patients with some form of paralysis new possibilities for improved mobility and independence [248].

TechnologyNumber of Product Codes in the FDA
EEG22
TMS5
VNS2
DBS5
PNS5
The FDA Establishment Registration & Device Listing and Classification Databases were used to determine the number of product codes. The higher of the two were used in the table.

In addition to governmental regulation, the governing bodies of ancillary industries are also creating regulation on the uses and development of Neurotech. An example of this is the comprehensive Standards Roadmap developed by the Institute of Electrical and Electronics Engineers (IEEE), that outlines standards for brain-machine interfaces (BMI) [249]. Below is a table summarizing standardization priorities for a number of BMI aspects published by IEEE in 2020:

Standardization levelBackgroundPriorities
Sensor TechnologyHighEstablished standards for electromagnetic safety, biocompatibilityInteroperability
End effectorsHighElectrical/Mechanical safety

Standard for lexicon for prosthetics

Ongoing development on wearable robotics
Unified terminology

Communication across devices and processes

Standards to specify and measure performance of systems relying on shared control
Data ManagementMedium/LowCybersecurity standards in non-BMI applications

Community driven standards

EEG consumer devices
Cybersecurity/Privacy

Interoperability between data management platforms

Data annotation (in real life situation), Definition of meta data and closed-loop data
User NeedsLowExisting standards for human factors but seldom integrated in BMI design

Medical design device control
User requirement and needs of healthy and less severely affected patients

User needs (beyond direct user, e.g. caregivers, family)

Benchmarking of user needs fulfilling
Performance AssessmentLowCommunity driven approaches, focused on neural decoding performance

Benchmarking of individual BMI sub-components
Closed-loop evaluation

Integration of evaluation of human factors

Benchmarking of task-based performance and assessment of clinical use

As with many novel technologies, there are still many other ethical considerations for companies in the field to consider. The industry has thus far been proactive by actively debating and considering the ethical implications of their solutions through Neuro Ethics.

As Neurotechnology applications can not only collect data from the brain, but also directly affect brain function, there are a number of ethical issues that arise with continued industry growth. The two primary issues are privacy concerns, and the “Black Box” problem that can arise from heavy reliance on AI applications.

The question of data ownership is also a hotly debated topic across all fields of technology today and is especially relevant in Neurotech. As there has been relatively little regulation on this specific matter, European regulators have taken the lead on defining the scope of data ownership. The General Data Protection Regulation (GDPR) was passed by the European Union (EU) and stipulates special categories of data in Article 9.1; per the regulation, biometric data can be classified as sensitive data, and is afforded a higher level of protection. Brain data could potentially be interpreted as falling under that category [250].

As these policies develop across the world, “NeuroRights”, like “Genome Rights”, are likely to redefine rights related to an individual’s brain data. Neurotechnology, like most modern technologies, eventually risks attacks from hackers, opening the door to the possibility of third parties altering a person’s neural processes without their consent. Due to the concerning implications of this problem, Neurotech companies will have to consider cybersecurity early in their life cycle to protect both their end-consumers and themselves from such threats.

Furthermore, as regulations and policies continue to grow and evolve, a new field of law called NeuroLaw has emerged to try and manage the gaps in existing legal structures and protect individuals’ rights in the context of this emerging technology [251].

In any case, the adoption of self-regulation by Neurotech players could be an intelligent strategy as it would not only build trust among the general public, but also prepare them for upcoming regulation, which seems inevitable.

Another major issue to be addressed as Neurotech solutions increasingly rely on AI algorithms is the “Black Box” problem. Simply put, the “‘Black Box’ is a device, system or program that allows you to see the input and output but gives no view of the processes and workings between”[252]. AI-powered methods can provide effective predictions about brain activity. As some of those predictions can be unexpected, the fact that they have been obtained through methods which are often complex and opaque, can be a cause for concern [253]. Oftentimes, even those who develop these AI applications are not able to explain these methods reliably [254], and this inability to explain the mechanisms by which the “output” (i.e.: predictions, diagnoses, etc.) is reached raises major conceptual and ethical issues.

This issue becomes especially pronounced in the psychiatric context where there is an implicit power differential between the patient and the medical professional. If the “Black Box” is granted authority on diagnoses and treatment of patients, technological paternalism could ensue, which could take autonomy away from both patients and practitioners. Further, heavy use of AI without fully understanding how it generates its output could lead to blind reliance on these applications.

The current state of affairs in the industry is encouraging

Some general trends in the Neurotech industry are the exploration of new avenues to use neural implants, and an overall increase in patenting activity.

Traditionally, neural implants have only been used to treat brain injuries and restore function to damaged components of the brain; recently however, researchers have been exploring the use of neural implants to treat major mental health conditions like major depression, obsessive-compulsive disorder, addiction, pain, and more [255]. Further, Pannu forecasts that future neural implants will go beyond altering electrical impulses in specific areas, and will also release neurotransmitters to fix chemical imbalances in the brain that can cause mood disorders [256].

To give a sense of the pace of technological innovation in this space, patenting is also racing ahead across the globe. The OECD reported that between 2008 to 2016, investors in the US filed for 7,775 patents in Neurotechnology [257]. The same report stated that China filed 3,226 patents in the same time period, while European countries like Germany and France lagged behind in the number of patents filed (555 and 239, respectively).

NTX Services’ own review of patents in the space supports the OECD report, in that patenting seems to be growing at an exponential pace.

Number of Patent Applications in Neurotechnology Worldwide

A regional analysis of the source of these patents also yields interesting insights. As expected, the US is the main source of patents in the field. However, patents filed in China represent a growing proportion of the patent pool from 2010 onwards. Similar dynamics can be observed in more developed countries in Asia such as Japan and South Korea, suggesting that a North America-centric view of innovation in Neurotech could risk missing innovation which is currently more ‘under the radar’. It is also likely that some of these other countries could experience “technological leapfrogging” (referencing an adoption of advanced or state-of-the-art technology in an application area where immediate prior technology has not been adopted) [258] in Neurotechnology as they have for many different technology categories (e.g. smartphones, semiconductors etc.).

Trend in patent applications by country in Neurotech
Price Range (USD)Distribution of Patents filed in Neurotechnology
1-30K50%
30-300K35%
300-600K5%
600K-3M8%
3M2%

In addition to an increase in the number of patents being filed across the world, the value of the patents that are filed has also been increasing in recent years – though half the patents filed as of today in Neurotechnology remain valued under USD $30,000, reflecting, in our view, the maturity of the industry today.

How could this industry develop in the future?

The future of Neurotechnology is bright and ever evolving due to the development of new devices, novel applications, and the continued growth of Neurotech companies.

The future of this field is likely to continue exploring multi-modal applications of technologies in order to improve the human experience. Some examples of this in the non-invasive devices space are the partnership between Muse and RendeVR that will explore the connection between virtual reality (VR) and Neurotech to improve care for seniors [259], and Snap’s recent acquisition of NextMind, which aims to drive the company’s long-term augmented reality (AR) research and develop future models of Snap’s AR glasses [260].

Future projects and research will also look to minimize risks associated with implantable devices and reduce invasive procedures to simple out-patient procedures. Companies like Neurosoft Bioelectronics and Inbrain Neuroelectronics in Europe are already looking to explore safer materials and form factors (such as implantable electrode materials, shape, size and placement) to use in invasive procedures that may reduce side-effects related to tissue damage, scarring, and more., associated with traditional invasive technologies.

There is also a trend towards making devices and procedures as minimally invasive as possible – companies like Precision Neuroscience are developing products that can be placed beneath the skull or under the skin in a simple out-patient procedure, which could feasibly reduce hesitancy towards implantable solutions among patients. Similarly, there are novel innovations in the implantable space that are exploring technologies that could further optimize the balance between invasiveness and scope of application, to maximize effectiveness while decreasing risk and inconvenience.

In addition to improving invasive solutions, the Neurotech industry is also coming up with new and/or improved non-invasive solutions to complex problems, through both hardware and/or software innovations. As big tech players like Meta are making breakthroughs in non-invasive thought-to-text solutions through its Facebook Reality Labs in the US [261], similar efforts are also underway in countries like Russia [262].

Companies like CortexBCI and Neeuro are developing therapeutics that help address the challenge of the acute shortage of home healthcare workers for widespread conditions that impact quality of life like Cerebral Palsy and ADHD in Asia, while companies like Evoked Response, NeuroGeneces and BrainKey aim to improve consumer wellness and empower the consumer to take their health into their own hands in the US.

The Neurotech industry will also continue the development of consumer devices that improve human performance that can be integrated into a consumer’s daily life, such as the headphone-based device by Eno in Canada that aims to improve focus for knowledge workers.

As startups continue to create new products in the field, there will also be an increase in the number of companies like AE Studio in the US and mBrainTrain in Europe that look to improve data collection, processing, and algorithms for both research institutions and startups. Companies like these provide value-add through hardware and/or software solutions, thereby improving both the quality of novel solutions and reducing the cost of developing these solutions for emerging companies and/or research institutions in the field.

Finally, it is likely that there will be greater mergers and acquisitions (M&A) activity in the Neurotech industry, though it is still too early to address the possibility of a broader industry consolidation.

To this day, Neurotech has been thought of as emerging tech – as such, capital raises remain the dominant deal activity in this sector.

That said, it is worth noting that Headspace’s acquisition of Ginger.io (a company whose patent portfolio includes several methods patents for modeling and providing therapy for a range of mental health conditions like psychosis, depression etc.) in 2021 at US$ 3 Billion was the single largest deal in the Neurotech industry, i.e. not a capital raise or an IPO [263]. Industry pioneers like Blackrock Neurotech are also starting to make strategic investments in companies whose product portfolio can improve or further develop their own solutions [264]. NTX Services’ own review of M&A Activity in Neurotech also suggests that this type of activity has been increasing over the past decade.

M&A Activity in Neurotech is on the rise over the past 10 year period

M&A Activity in Neurotech is on the rise over the past 10 year period

As this field continues to emerge and grow, it is likely that many more strategic investors will become involved as they begin exploring the benefits of adding this novel technology into their existing service portfolios and/or products, and thereby help in taking the Neurotech industry and its products and solutions mainstream. This should naturally also improve exit opportunities for startups in the field.

AE Studio

Company Profile

Agency Enterprise (AE) is a software development and data science consultancy. Founded in 2016, AE has bootstrapped its way to over 140 employees that aim to use technology to increase human agency. No venture capital. No private equity. No outside shareholders. This allows a longtermist perspective for clients and employees that leads to unparalleled thought-partnership and creativity [265]. AE aspires to be visionaries and thought-leaders in human agency, BCI, Blockchain, and any other world-changing technology [266].

AE was born of the vision to increase human agency for end users through the technology the group develops for their partners and their wholly-owned and operated skunkworks companies. Running a highly collaborative agile process, these efforts are extended by investing heavily in the brain computer interface (BCI) space. BCI represents, to AE, the pinnacle of agency increasing tech with massive implications for users and the whole of humanity.  To ensure that the incentives of this technology aligned with long-term gains in human agency rather than short-term monetary incentive, the founders were determined to bootstrap their way in lieu of outside capital.

“Building products with human agency in mind results in happier, more satisfied customers who use their newfound agency to build a longer relationship with the product, refer connections, and better their lives. What’s good for the user is good for profit and growth.”

Judd Rosenblatt, CEO of AE

A proportion of the profits from its data science consulting business are channelled into “skunkworks” efforts—internal, ambitious, agency-increasing projects that AE’s software team ideate and lead. AE incubates skunkwork ideas, turning its world-class team into founders themselves. Some projects remain internal even after finding market fit. The team at AE scales them into full-fledged businesses, plowing profit into their BCI efforts, whilst others are sold, with the proceeds similarly finding a home in the BCI division.

In addition to multiple internal projects currently being incubated, one recent success has been the sale of ElectricSMS to Recharge, one of the industry’s largest subscription payment processors. The software allows users to pause or alter subscriptions without cancellation and without the dark patterns of conventional alternatives. Short-term loss, long-term gain in customer lifetime value! AE is also enjoying impressive growth in its online fitness video platform, Instill, which managed $200K in subscriptions from 13K users and over 2M+ minutes streamed in its first three weeks.

As a product and venture studio, skunkworks and other ventures enable AE to fund their ambitious BCI goals without the need for outside capital, ensuring incentives are aligned with long-term goals, maximizing the quality and quantity of positive outcomes.

By taking on a longtermist perspective, AE can make decisions with the products it develops internally, unbound by considerations of quarterly earnings and the like [265].

The company’s expertise in data science and software engineering best practices have allowed it to implement and improve upon the performance of state-of-the-art neuroscience and machine learning models. This expertise and experience led to AE’s win in the Neural Latents Benchmark Challenge [267].

The ability to think like founders in helping clients craft their software visions ensures that AE does not only deliver to specifications but also exceeds expectations with extraordinary, agency-increasing products.

AE’s innovative developer equity plan represents a unique approach to compensation that incentivizes its employees to collaborate and think about the long term with regards to adding value. It also greatly increases retention [268].

The company is also in the early stages of collaboration with multiple leading academic research labs and industry partners in the hardware space. Both will be necessary for developing its BCI software platform using data from human subjects.

Flagship Product Deep Dive

BCI applications can improve quality of life via neuroprosthetics, thought-to-text, and by replacing common devices like a keyboard and mouse with thought. Restoration of agency to those with severe disabilities will allow control of robotic limbs for motion and systems for communication. Ultimately, these disabilities will no longer preclude use of cell phones, computers, and other societal necessities.

AE is developing improved processes and standards for neural data, focusing on human agency and neuroethics with each piece of technology it develops. We offer grants to student groups to increase community engagement. We are open-sourcing tools for widespread and equitable access. We are baking user protections into the software based upon an evolving set of principles based broadly upon ethical priorities outlined in Nature [269]. AE is developing new methods for interpreting neurodata, including algorithms that reduce calibration time, and generalise across time and even between users and environments.

While AE’s BCI models are based upon well-researched academic ideas, they are actively and successfully improving the performance of these models through software engineering and data science best practices, ensuring robustness, transferability, reproducibility, and scalability. More broadly, by combining extraordinary creativity, communication, and product-focused design patterns, AE ensures that every delivered product delights and increases human agency.

AE has recently begun partnership discussions with leading academic groups to help them develop robust, state-of-the-art, scalable software solutions for decoding neural data.  Specifically, we are eager to partner with labs developing life-saving BCI systems to be tested with human participants.  More specifically, microelectrode arrays and ECoG are of interest currently, in the hopes of building an intellectual scaffold from which to develop the next generation of BCI software.

AE is aware of the vast implications for this technology and its potential effects on human agency. This driving force has brought the company together around the goal of becoming a leader in the BCI space—to ensure there’s an ethical voice at the table.

Evidence of safety and efficacy

AE will implement and deploy state of the art machine learning models. As an experienced provider of software engineering and data science solutions, it hopes to follow industry best practices for development, testing, and deployment at scale. Additionally, AE has experience handling sensitive data and delivering HIPAA-compliant solutions.

AE’s models will be tested in the context of academic research labs with human subjects, and it expects some of the findings to be published in peer-reviewed journals.

Future development

AE has already demonstrated its competence in software development and machine learning by winning the Neural Latents Benchmark Competition. It has begun working on its real-time neural decoding software platform, which it intends to open-source for use in the research community. AE is also working with potential partners to test this solution in human participants.

Neurotech companies on the software side are dependent upon data produced by neurotech hardware companies and academic research labs. This is often a stumbling block for neurotech software development. By building relationships with potential partners performing research on human participants and delivering production-quality ML software solutions, AE will continue to develop its software via data from state-of-the-art neurotech hardware.

Once it has done so, the real-time neural decoder’s application will be expanded to include work with several modalities of neural data to ensure the flexibility required for research labs to assemble the applications they desire.

Both industry and academic partnerships are currently being discussed to ensure the best research meets the best industrial software practices.

Target market

AE’s solution targets anyone who can benefit from a brain-computer-interface. Currently, this market would consist predominantly of the severely impaired seeking restoration of motion (e.g. neuroprosthetics) or capacity to communicate (e.g. thought-to-text).

As the technology matures, so too will its user base and applications. Ultimately, AE believes the technology will expand beyond restoration to augmentation, allowing seamless communication between human beings and machines. While that technological advance remains distant, the market for such a tool will be anyone who uses a personal computer.

Channels to market

AE’s current focus is to work in collaboration with neuroscience research labs performing brain-computer-interface research with human subjects (at no cost to the lab). Throughout the process, AE’s values of increasing human agency and ensuring ethical use of neural data will allow the company to offer its decoding solutions to the maximum number of individuals that stand to benefit from current hardware and software.

AE’s core values of maintaining a growth mindset, overcommunication, and taking increasingly-large A/B-tested baby steps ensures that we will continue improving their models and their understanding of human agency at every stage.

Additionally, AE is beginning partnerships with device manufacturers to incorporate its software solution into their systems – again, maximising the number of potential users who can benefit from the decoding AE can provide.

Success Factors

Team and Reputation

The AE team consists of a rich array of academics, ex-academics, ex-founders, and industry professionals [270]. These are just a few of its data scientists focused on BCI:

  • Dr. Darin Erat Sleiter holds a PhD in quantum physics from Stanford and has 15+ years of professional machine learning and software engineering experience across numerous fields of application.
  • Dr. Sumner Norman holds a PhD in Mechanical Engineering from UC Irvine and has served as a postdoctoral researcher in Caltech’s neural engineering laboratory for the past ~5 years.
  • Dr. Mike Vaiana holds a PhD in Computational Data Science and Engineering from the University of Buffalo and has four years of experience developing and delivering large scale machine learning solutions.
  • Dr. Robert Luke holds a PhD in Neuroscience from KU Leven, focusing on responses to cochlear implants and worked as a research fellow at Macquarie University for ~4 years before joining AE.
  • Dr. Diogo Schwerz de Lucena holds a PhD in Mechanical and Aerospace Engineering from UC Irvine and worked as a postdoctoral fellow at Harvard thereafter, developing robotic systems for home rehabilitation after neurologic injury.

Intellectual Property

  • Although only founded in 2016, AE is already demonstrating the skill of its machine learning researchers in modelling neural data by recently winning the Neural Latents Benchmark Challenge. Our IP strategy finds an analog with Red Hat (Linux) rather than traditional tech. We tend to open source a great deal of our tooling to develop in concert with the broader community. The principal goal lies in the development and deployment of public goods that increase human agency.
  • We are taking the best of modern machine learning, bringing that knowledge to the field of BCI, and developing specific IP to ensure that software can run in real-time, with less training, and remain robust over time
  • Specific IP consists of industrial best-practices for development of algorithms to process neural data, and the experience to scale and deploy efficiently. 

Funding

  • AE is a fully bootstrapped company. Foregoing any outside capital, it has been profitable since its founding in 2016 until today. This is because both its consulting and Skunkworks business are profitable and allow a long-term approach to BCI research and software development. Presently, AE’s headcount stands at ~14  We recently sold ElectricSMS, which we founded and incubated, to ReCharge for $6M and an undisclosed quantity of equity. 
  • We have offices in Venice, LA and in, Florianopolis Brazil, and have worked with clients on multiple continents, including recently a collaboration with the South China Morning Post (SCMP) to immortalise historical events via NFTs.
  • AE is currently growing on a global scale, with clients across the biotech space. From deploying cutting-edge computer vision algorithms to diagnose health conditions from in-home urine tests, to machine learning models from wearable health data to improve wellness, to classifiers of ischemia from cardiac and cranial sensing, AE deploys its data science expertise to improve human agency and human health.

BrainKey

Company profile

“The brain longevity data platform”

BrainKey’s platform applies AI to brain imaging and genetic data to provide actionable brain health insights.

The team designed BrainKey to be two-sided with a focus on ease of use so that both patients and physicians can understand brain health visually, get treatment recommendations in plain English and monitor changes over time seamlessly. For example, BrainKey’s AI can take a patient’s black and white brain MRI scans and translate them into 3D with 25+ regions that can be tracked over time.

BrainKey has an entrepreneurial team of Stanford PhDs and YCombinator alumni with over 100 neuroscience and AI publications [271]. The team developed BrainKey to be the 1st company to incorporate imaging, genetics, and demographics into a single patient report.

“Many of the technologies that are on the market today are focused on specific data types such as imaging or blood. It’s my belief that incorporating multiple datatypes is necessary to gain a full picture of the patient because the biology of brain aging is complex and can’t be fully understood with limited data.”

Owen Phillips, PhD – CEO of BrainKey

The BrainKey team is designing the platform so that it is well positioned to:

  • Detect dementia 10+ years before symptoms are present
  • Differentially diagnose from 100+ dementia types
  • Recommend personalized treatments from 1000s of combinations of medications and surgical interventions.   

BrainKey’s AI Drives Its Vision

BrainKey’s report and platform are powered by a novel AI system that BrainKey calls “3D AI” which fuses multimodal data to construct a high-dimensional representation of the patient, which is then compared to the larger BrainKey database to pinpoint brain abnormalities.

Although the underlying power of the platform is its AI technology, BrainKey is guided by the ethos that complex medical data must be made easily digestible to both patients and physicians for it to have real-world value.

“At BrainKey, we believe physicians and patients need to be able to pull out their phone and quickly understand – here’s what this data means and most importantly, here’s what we can do to get the best outcome”

Nathan Strong, PhD – CTO of BrainKey

Ultimately, the goal of BrainKey is to empower patients with their own health data.

“My own mother has had a version of dementia that should have been identified and treated years ago. But it was missed, and her outcome is worse for it. I was frustrated about her struggle for an early and precise diagnosis. But as a neuroscientist who has worked with some of the world’s leading neurologists and neurosurgeons, I’ve seen how tough it is to help patients with limited data. We can do better as a field. But to do so we need more data. We created BrainKey with the goal of pooling data from millions of patients to create a powerful new tool that can fundamentally improve how we identify, treat, and manage dementia. It’s a personal mission for me but it’s a global problem as 1 in 3 will experience dementia in their lifetime.”

Owen Phillips, PhD, CEO of BrainKey

Founding and Partnerships:

CEO and Founder of BrainKey, Owen Phillips [272], PhD, has 50+ publications [273] incorporating, imaging and genetic data with collaborators from top universities all over the world such as Stanford, UC London, Charité – Universitätsmedizin Berlin, and the University of Toulouse.

BrainKey emerged as a project of Owen’s while he was in a deep learning for genomics class as a post-doctoral researcher at Stanford University in 2018. BrainKey got off the ground in 2019 when the world’s top start-up accelerator YCombinator backed them [271]. Owen subsequently recruited key domain experts such as Stanford AI PhD, Nathan Strong and renown physicist Kevin Aquino, PhD to help build BrainKey’s infrastructure.

To expand on its competitive advantages BrainKey has collaborative projects with leading experts on specific subtypes of dementia. These collaborations include projects on dementia subtyping with UCSF and the SF VA, brain aging with UCLA, movement disorder subtypes with the University of Toulouse and autoimmune contributors to aging with Charité – Universitätsmedizin Berlin.

Flagship Product Deep Dive: BrainKey Platform

BrainKey’s goal is to be the primary platform for the early detection, support differential diagnosis and treatment planning of dementia. There are other companies competing in this area, but they tend to be focused on diagnostics using single specific data types such as imaging, blood/genetics or demographic or smartphone-based biomarkers. BrainKey fuses many specific data types into one. For example, BrainKey can:

  • Calculate BrainAge vs chronological age. An advanced BrainAge is associated with increased risk for dementia [274-278].
  • Measure the memory area of the brain (hippocampus) associated with early atrophy in Alzheimer’s disease volume loss with expert human accuracy from MRI scans [279].
  • Identify 20+ genes associated with hippocampal volume from genetic data.
  • Fusion of multimodal biomedical data with the patient’s demographic information (such as age, and sex) and compare it against the underlying BrainKey database to provide detailed information about a patient’s brain health back to the physician.

BrainKey’s platform is powered by its proprietary “Rollerblade” system. Rollerblade is their in-house HIPAA compliant cloud infrastructure to structure and deploy imaging and biomedical data at scale. (To learn more about Rollerblade, please see:  Rollerblade Data Analysis Engine [280]). Using the “Rollerblade” infrastructure, BrainKey developed an AI system that can reference different data types and create a single report that they call 3D AI. Built as containerized extensions of this are a number of specific analytical tools. A few of the highlights include:

In the near term, BrainKey’s go to market strategy is a B2B SaaS business model focused on high-end preventive health clinics. BrainKey’s analysis tools such as the BrainAge and BrainKey’s 3D visualization capabilities are a natural fit for physicians looking to offer their clients the most advanced solutions. BrainKey has already partnered with a number of high-end preventive health clinics such as Human Longevity/Health Nucleus and the Healthy Longevity Clinic [288, 289].

“The longevity and high-end preventive health space has been a great beachhead for us to enter the market. Getting our platform into the real-world and into the hands of physicians and patients has been invaluable for us to improve the product.”

Owen Phillips, PhD, CEO of BrainKey

Additional Channels: BrainKey is also pursuing B2B partnerships with pharmaceutical companies to assist in remote clinic trial recruitment and patient monitoring.

Evoked Response

Company Profile

Evoked Response is a music technology company with a twist – It has identified 12 different music variables that impact the brain in different ways, which, when applied as direct, non-invasive brain stimulation doesn’t just evoke an emotional response, but actually shifts mental state. Through its music, Evoked Response can supercharge focus and productivity, relaxation, sleep, and athletic activity. In representing a new frontier of digital wellness, the company’s core objective is to enable as many individuals as possible to experience the mental enrichment it can provide.

The original fundamental idea behind Evoked Response was born in 2000, when CEO Adam Hewitt, who has a self-proclaimed synaesthesia to music, went to a meditation retreat and was played a sound that instantly made him relax. Through this experience, and his skills as a programmer and musician, Adam developed the idea that music could “programme the brain”, which blossomed into a ‘neural programmer’ workstation, and the founding of “Transparent Corp” in 2003. This application was incredibly popular with scientists and universities, even at a time when the science of brain wave activity was still nascent, but there was a continued frustration that this type of programme wasn’t accessible to individual users.

Subsequently, backed with a National Science Foundation grant from the government, Adam created Brain.fm, a science-based music app for focus, sleep and relaxation, which he describes as a “real renaissance for the field in general”. Brain.fm has become an incredibly popular app, with a good attrition rate, and to date has generated US$6 million in revenue.

Adam is always looking at ways to improve his product, but recognised that the Brain.fm app was competing in the same sphere as many meditation and relaxation apps, which would limit accessing the more significant market he needed to meet his core value of “enriching the experience of as many individuals as possible through neuro-based music”. To target this much larger audience, in 2019 Evoked Response was developed as a B2B company with the aim of getting this unique technology into the hands of as many existing businesses, pharma companies and governments as possible.

To date, following over 20 years of technological development, Evoked Response has created 1000s of hours of music covering different conditions such as ADHD, insomnia, anxiety, mental fatigue, and the enhancement of Productivity, workflow, and fitness. The technology continues to be refined by the company through large scale, double-blind, internal studies. These studies use behavioural tasks to measure things such as attention, speed, and accuracy to hone the music for maximum enhancement in different target populations.

It has also already partnered with many wearables that usually contain EEG sensors to diagnose focus and sleep quality, but which also require a non-invasive intervention to improve what it is they are diagnosing. The Evoked Response team has also worked with the US Olympic Wrestling team to enhance athletic performance through its music as an all-day companion to manage Sleep, Wellness and Anxiety

Neurons in the brain communicate with each other, forming thoughts, emotions, and ideas using electrical impulses. Activities such as sleeping, working, or meditating, each have their own unique brainwave pattern. Evoked Response leverages neuro-musical synchronisation, to optimise brainwave patterns for each desired activity.

Driven by neuroscientific principles, the music is composed to enhance performance and productivity by inducing a state of focus, support overall wellness like sleep and even tackle mental health conditions like depression and PTSD.

The solution is backed by established scientific studies, internal research and a 4-step approach that ensures the expected results can be presented as a product to clients.

It is now well-established that music can modulate brain activity and induce different mental states [290]. Music is a non-invasive way to stimulate and depress brain activity, with the potential to reach and treat hundreds of people at the same time. Unlike other neurotech device-based solutions, , this technique doesn’t require a closed loop to have an impact on the individual listening to it.

Proof of concept has been demonstrated in:

Additional research by Evoked response has been backed by a National Science Foundation grant and is soon to be published in Nature magazine.

Evoked Response has just completed two internal trials with ADHD subjects that concluded the more an individual enjoys the music, the greater the enhancement in focus. This is a finding that has driven the company to develop further music in this area.

The company also has another ongoing trial that is focused on sleep and stress to aid those with insomnia.

Due to the accumulating in-house evidence, Evoked Response’s primary target market encompasses consumers wishing to improve productivity. With its study soon to be published in Nature, Evoked Response is set to enter the enhanced productivity market, valued at 75  billion USD, in a strong position.

The company also ecompasses several areas of the wellness market, valued at 1.5T USD, including improved mindfulness, fitness, health and sleep. A recent Sonos global survey showed that a majority of people already use music for their general wellness: ~75% reported that they listen to music to reduce stress, and that listening to music is key to producing their best work.

Evoked response has created meditation sessions ranging from 15-60 minutes to support the consumer wellness journey.
It also has created relaxation and anxiety reducing music for before/after stressful situations.

Consumers can use the music to aid in both getting to sleep and in maintaining a deeper, more restorative, sleep throughout the night.

Evoked Response have created simple and motivational workout music to support athletes and mainstream consumers.
The music can be used during a regular workout routine by a layperson to kickstart their motivation.

Evoked Response markets exclusively via B2B channels. Main channels include pharma companies, universities, hospitals, wearables, health and wellness apps, any kind of biosensors, businesses and athletic teams. Organisations can integrate the music into their physical technologies or digital applications, or Evoked Response can also create custom web and mobile solutions to empower any end-user to have streamlined access to neuro-music.

mBrainTrain

Company Profile

mbt is a mobile EEG company committed to bringing innovation in neuroscience. Since the company’s beginnings in 2012, they have established themselves as a technology enabler for the pioneers in brain research who want to widen the scope of research and help move the boundaries of neuroscience. Driven by the strong belief that there is much more potential in the human brain that hasn’t been unlocked, and that our lives would be much better if we got to know how the human brain works in real life, mbt delivers the promise of making the everyday brain tracking possible in the near future.

mbt do this by developing and marketing the cutting-edge brain research products for the neuroscientific labs around the world. mbt launched the first commercial mobile EEG product in 2014, and after years of work on hardware and software advancement, mbt has marketed the second generation of proprietary mobile EEG products. This is now their flagship product – Smarting PRO, which, mbt believe represents the new standard for EEG research in any setup a researcher can imagine.

mbt believe that human-machine interfaces should be designed such that they assist humans, make their lives better, and help them use the best of themselves and the world they live in. Applications are many, but just to name a few – mental health&wellness, safety at work, entertainment industry, etc.

The founders of mbt come from the scientific background, holding PhDs in Biomedical engineering. They started mbt with a short-term goal to make a simple, easy, and mobile EEG device which will walk EEG experiments out of the restricted laboratory conditions; and with the long-term mission to make everyday brain tracking possible in the same way as we track our heart rate today. It took them 2 years to reach their first goal – in 2014 Smarting was launched with the help of grant from The Innovation Fund of the Republic of Serbia.

The first market to conquer was Germany, where the founders had strong scientific contacts base after the PhD studies and Academia engagements in KU Leuven Belgium. German market has been advanced when EEG work is in question, and the new revolutionary device was warmly welcomed and further recommended to the wider European neuroscience community. The client base quickly spread across EU, USA and China as the parts of the world most active in brain research, but with the growing trend of brain research, the list of countries grows everyday – reaching to Turkey, Australia, Latin America and South Korea.

We exist to make brain tracking a part of our everyday and help people use the best of their lives”

mbt |mBrainTrain

Artificial intelligence (AI) is a branch of computer science that aims to develop computers that are capable of intelligent behaviour. Through AI, a computer uses math and logic to mimic the reasoning of humans [163]. There are three main subsets of AI: 

Today, ten years after foundation, mbt is in a unique position of technology know-how, with respectable client base in about 40 countries, and the ability to close the HW-SW products loop in-house.

mbt Smarting devices have been used worldwide, in research, from 2014 and their output has been widely reported [293]. mbt has also fielded consumer-looking equipment, that has already been used in research, verified scientifically and credited by corporate users. [294-296]

mbt has been awarded a number of local and European projects, and is currently hosting and training PhD students engaged on advanced [297], approaches for EEG signal processing – with corporate partners offer field-testing capabilities of work-based wearables in relevant environments. This makes it possible to field-test and verify assumptions of mbt solutions quickly and effectively.

mbt is a profitable company which is growing continuously and one of the key metrics is to grow on the market of research mobile EEG products.

Bogdan Mijovic, PhD, CTO: >10 years’ experience in neuroscience, product development, IP management. Published in top 5% neuroscientific journals. Also, co-founded Brainstorm, and BSTORM.

Ivan Gligorijevic, PhD, CEO: >10 years’ experience in neuroscience, sales, B2B partnerships, business strategy.

Pavle Mijovic, PhD, Head of Engineering: Research and Development, Biomedical Signal Processing, Customer Care & Support

Ana Jolic, Head of Sales – Sales, B2B enterprise solutions: Proven sales manager, with Academic and corporate client concluded contracts; experienced in negotiations, direct sales, and distributorship relations

mbt’s scientific advisors are at the forefront of mobile EEG work – they share user experience insights (leading to innovations) and disseminate work that often brings new clients.

Maarten De Vos, PhD, scientific advisor: professor of biomedical engineering at KU Leuven, Belgium.

Stefan Debener, PhD: professor of Neuropsychology, University of Oldenburg, Germany. World pioneer in fMRI and EEG fusion as well as mobile EEG.

What sets mbt apart from its competitors can be grouped into 3 points:

  1. hands-on domain experience and expertise of its management
  2. position of integrated system – mbt owns all its hardware and software development (and has in-house prototyping/development infrastructure)
  3. their approach to meaningful AI architecture design that is tuned to time-series data such as EEG – and is supported by Cambridge AI scientific advisors.

Submitted and granted patents include (apart from design patents) UK patent application: GB2018664.9 dated 29 November 2019, and one granted US patent: US10874356.

mbt have received funding from Eleven VC in 2015/2016 (120k EUR in total), as well as 25k EUR from an angel investor at about the same time [299].

mbts plans to raise further capital by seeking a strategic partner – someone in the domain that could pave the way for technology commercialization and testing as well.

Neeuro

Company Profile

Neeuro is a global company, founded in 2013 in Singapore, which specialises in the utilisation of Brain-Computer Interface technology to maximise the potential of users’ neurological agility and fitness.

One of its main products, the Neeuro Senzeband, is a headband equipped with dry-electroencephalography (EEG) sensors that can capture brainwave signals non-invasively. The seven sensors are distributed over the prefrontal cortex and two on the side. The prefrontal cortex plays a central role in executive functions such as planning complex cognitive behaviour, personality expression, decision making, and moderating social behaviour. The core technology, NeeuroOS, provides health care professionals, researchers, and third-party developers with an Artificial Intelligence (AI) driven platform that has the ability to analyse the brain signals and provide the user with meaningful insights and solutions to improve their brain function.

Neeuro’s vision is “To be the enabler that empowers every human’s mind.” Says Dr. Alvin Chan, Co-Founder and CEO of Neeuro. “A Platform Ecosystem for Brain Computing that Powers Mental Health Solutions.”

Neeuro was founded by Eddie Chau, current Chairman. As a serial entrepreneur, Eddie noticed the negative impact of poor sleep and high stress levels can have on people and became interested in finding a neurotechnology-based solution that could help users manage their mental health. He saw a great deal of potential that EEG data holds in this regard, but also its wider potential to help across all aspects of mental health. In addition, he saw that EEG data could be used to help the elderly, helping seniors suffering from stroke and cognitive decline, and in children with attention deficit hyperactivity disorder (ADHD). This is when Eddie Chau reached out to Alvin Chan, the co-founder, and CEO of Neeuro.

Alvin Chan was equally interested in the field and his, engineering and computer science background contributed to his fascination with the amount of data, and therefore information that can be obtained from EEG data. Eddie and Alvin were motivated by personal experience as well, as both had family members and friends who had suffered from conditions such as dementia or ADHD and had a first-hand understanding of the impact that these conditions can have on people’s lives.  With the rise of digital therapeutics which are, defined as “delivering evidence-based therapeutic interventions to patients that are driven by software to prevent, manage, or treat a medical disorder or disease”, they wanted to utilise these rising interests to specifically address disorders affecting the brain.

Neeuro’s major goal was to build neurotechnology products that can be home-based. With the end-user in mind, they understood that experiencing the full potential of the technology may be difficult for busy parents who cannot afford to take three days off to see a therapist or for the elderly who may also struggle to attend appointments due to their symptoms or do not have the nearby care to support them. Neeuro aims to bring solutions to solve these challenges within the home itself. The importance of home-based solutions became ever more apparent to the company in the light of the recent COVID pandemic, where access to care became difficult and the founders of Neeuro wanted to ensure that care delivered through their technology would not overburden the hospitals further. To make its products home and user friendly, they had to be easy and fun to use which is why Neeuro’s solution is to train the brain centres around gamification.

Neeuro stands out from its competitors by ensuring its solutions are always based on strong clinical evidence, long before they even make it onto the market and are commercialised. Its current products are backed by 10 years of work and 10 years of scientific publications. Furthermore, Neeuro’s extensive portfolio and an array of offerings empower digital therapeutics and brain fitness solutions are backed with clinical validated research by the Agency for Science, Technology and Research (A*STAR), an institute widely known as being at the forefront of Singapore’s research endeavours. In addition, Neeuro is working closely with neuroscientists as well as clinicians and the medical community, providing Neeuro with a strong vote of confidence in the potential of its technology.

In the next 5 years, Neeuro hopes to secure future partnerships with other solution providers integrating the Neeuro technology and algorithms into their products. Although its technology has potential across many different target markets, the major focus in the coming years is for Neeuro to grow its ADHD and senior/ageing market as there is a large increase in children being diagnosed with ADHD or inattentive symptoms and a rapidly ageing population. Their aim for both markets is to expand beyond the Singapore market and reach APAC, China, Europe and US.

“The Senzeband 2 is the ultimate “wearable for your mind”. This portable and non-invasive EEG headband device for capturing EEG brainwave signals consists of 7-dry electrodes, five of which are located over the prefrontal cortex and two on the sides. Using Neeuro’s machine learning algorithms, Neeuro SenzeBand 2 interprets these EEG signals measuring various mental states including:

After analysing the EEG signals SenzeBand 2 can provide biofeedback in real-time to drive interventions for several brain health challenges.

To produce a successful total solution, Digital Mental Health and Brain Fitness providers require the integration of AI platforms to interpret brain signals and harness the data to provide feedback on different mental states. Neeuro provides a solution through their NeeuroOS platform. It is an AI-driven platform and when coupled with Neeuro SenzeBand 2 it can help to address problems associated with ADHD, cognitive and stroke rehabilitation, and other neurological issues.

The full realm of possibilities through the NeeuroOS platform is indicated below:

Attention deficit hyperactivity disorder (ADHD), is one of the most common nerodevelopmental disorders of childhood leading to trouble paying attention, controlling impulsive behaviours or be overly active. ADHD has a negative impact on children leading to the becoming easily distracted and frustrated, social anxiety, difficulty following instructions and carless mistakes in homework. Parents are often left feeling challenged and clinicians are increasingly looking for alternative, non-pharmacological treatment options and a way to track progress.

Memorie is a collection of over 16 mobile games that help the different cognitive functions of the brain. These games are created to be fun and engaging mental exercises designed to enhance cognitive skills, enabling the user to ‘Think Faster, Learn Smarter and Remember Better’. When paired with the Neeuro SenzeBand 2, A user can track their brain fitness in quantifiable terms. Apart from receiving a game score, the user will also receive a ‘Brain’ score providing feedback on brain activity and cognitive function.

MEMORY:
improving working memory and well as comprehension and problem solving.

DECISION MAKING:
improving logic and reasoning skills to make more mindful decisions.

COGNITIVE FLEXIBILITY:
improving ability to shift attention from one task and another.

SPATIAL ABILITY:
understating reason and remembering the spatial relations among objects or space.

ATTENTION:
improving concentration and ability to process new concepts and complete daily tasks with more ease.

Learning to handle and cope with daily stress is essential in today’s world. When unchecked, chronic stress can lead to unwanted things that may negatively affect your health. That’s why Neeuro created Galini – a stress management solution that provides tailored relaxation and mindfulness experience. Galini comes with a suite of scientifically proven techniques that helps the user to achieve peace and clarity of mind. When used together with real time EEG recordings it can provide a dynamic interventions and measurements.

LISTEN AND REACH IDEAL RELAXATION FASTER:
(binaural beats) in Neeuro’s tracks, coupled with calming visualisations of peaceful scenes, can coax user’s mind into a state of deep relaxation.

BREATHE TO BETTER BALANCE MIND & BODY:
breathing techniques are designed to stimulate specific parts of the brain to modulate the mind and body and bring about a deep sense of peace.

MOVE TO CONTROL YOUR MIND:
Galini can guide the user through slow and deliberate movements while the screen interacts with you. This helps to regulate your focus and induce an increased awareness of your internal sensations and of the immediate environment.

Cogo Clinical Trial Data: Researchers from A*STAR Institute for Infocomm Research (I2R), Institute of Mental Health, and Duke-NUS Medical School in Singapore together with Neeuro ran clinical trials and pilots to test the efficacy of Cogo. Various trials were done to ensure there were no side effects, gaming addiction and operational ability as a home-based solution. One of the major trials involving 172 children with ADHD, 6-12 years showed that the children who received the 8-week intervention with Cogo showed significant improvement in their inattentive symptoms than those who did not receive the intervention. Furthermore, a study was done using fMRI brain scans from a group of these children that demonstrated Cogo helped re-normalize brain functional network topology among cognitive networks, associated with behavioural improvement and facilitate brain maturation in ADHD children. All these findings demonstrated evidence that showed value of BCI-based attention training game like Cogo as an attractive treatment strategy for ADHD.   

Memorie Clinical Trial Data:

Researchers from Geriatric Education and Research Institute (GERI), Khoo Teck Puat Hospital, National University of Singapore, in Singapore together with Neeuro ran a randomised controlled trial with 94 elderly healthy community dwelling adults (mean age 68.8 years) using Neeuro’s Computerized Cognitive training (CCT) application Memorie that is paired with SenzeBand. Results showed that it can be implemented in community settings to improve attention and executive functions.

Neeuro has ISO 13485 medical device standards. With its wellness products already in the market, Neeuro is working through the necessary regulatory approval, first within Singapore before expanding to other markets to further open channels in the medical industry.

Neeuro is currently working on an idea called Neeuro Cycle which can be thought of as the Peloton for seniors. Through Neeuro Cycle, Neeuro hopes to combine physical activity with brain training and further enhance the mind-body connection. Brain training largely focuses on improving everyday function. For example, the interactive game may require the elders to go to the supermarket. They will need to first cycle to the supermarket providing them the opportunity to exercise, after which they may need to recall the list of items they need to purchase once at the shop. These simulated real-life scenarios can help to improve daily aspects of the user’s life and help build confidence and independence. Neeuro’s focus on the senior market is particularly relevant at a time when the global population of Seniors is expected to triple by 2050.

As part of its NeeuroOS offering, Neeuro hopes to partner with other developers to integrate the Neeuro technology and algorithms into their products or to develop solutions to tackle different mental health challenges.

ADHD: Neeuro aims to provide a solution to improve inattentive symptoms both in children already diagnosed with ADHD but also in those who have not received an official diagnosis of ADHD, but may experience inattentive symptoms. The worldwide prevalence of ADHD in children aged 18 and under is estimated to be 7.2% with a higher prevalence in higher-income countries making it a large market with many opportunities. The ADHD therapeutic treatment market is estimated to reach US$25 billion by 2024 [305, 306].

Seniors/Aging Population: With a growing aging population Neeuro hopes to make seniors one of its key target markets. In 2015 there were around 901 million people aged 60 years and over worldwide and it is estimated that by 2050 this will rise to 2.1 billion [307]. Cases of dementia alone are estimated to rise to 78 million by 2030 and 139 million by 2050, leading to a global cost of $2.8 trillion by 2030 [308]. With the Silver Tsunami upon us, the market for the cognitive assessment and training industry is expected to grow.
By licencing its products and forming future partnerships in the wellness space, Neeuro hopes to indirectly expand its target markets and explore additional opportunities. 

Neeuro is focusing on the B2B model for two reasons. Firstly, it will enable Neeuro to scale quickly without incurring significant personnel costs, but rather focus on forming strong partnerships and distributors that can carry the product to the target markets. Secondly, the B2B route allows Neeuro to establish a strong branding around their company and product. Neeuro hopes that once they see through the success of B2B route they may consider the B2C route.

Dr. Alvin Chan:  the Co-founder, and CEO at Neeuro holds a PhD in Engineering specializing in Artificial Intelligence that has successfully exited his previous company, with a background in computer security, big data and neural networks. His fascination is finding insights or sense making from big data and continually looks for new technologies, ideas, and innovations to turn into business opportunities. His passion is to merge business ideas and technologies and turn them into successful products.

Eddie Chau:  the Founder, and Chairman at Neeuro is a serial entrepreneur with successful exits from his previous companies that is interested in all tech that makes a high impact in business and daily lives. He is on the board of several charitable and non-profit organisations including Mount Alvernia Hospital and Tsao Foundation in Singapore.

Professor Cuntai Guan: the scientific advisor at Neeuro is a world-renowned scientist in brain-computer-interface (BCI) research and a pioneer in medical applications using BCI. He is a Professor of Computer Science and Engineering at the Nanyang Technological University in Singapore. He has been on various leadership roles, including the Director of the Artificial Intelligence Research Institute of NTU, the head of the department in the institute of A*STAR, Singapore. He is a Fellow of IEEE in recognition of his contributions to BCI applications.

Strong partnerships with A*STAR Institute for Infocomm Research (I2R), Institute of Mental Health, and Duke-NUS Medical School in Singapore.

The Agency for Science, Technology and Research (A*STAR) in Singapore, one of Neeuro’s key investors have put in about 14 patents and intellectual properties for Neeuro as part of their agreement.

NeuroGeneces

Company Profile

NeuroGeneces is a neurotechnology company integrating sleep activity with neuroscience to provide non-invasive neuromodulation and brain health measurement.  Established in 2016, NeuroGeneces is developing an EEG sleep wearable that measures brain health biomarkers and unleashes the brain’s natural restorative powers of sleep.  The company’s core belief is that brain health is the next frontier in healthy aging, and everyone should have the opportunity to improve their brain health to live happier, healthier lives.  Its non-invasive, low-cost consumer headband analyzes EEG data to benchmark brain function over time against normal distribution to identify neurological changes and enable timely intervention.  

NeuroGeneces’ headband incorporates machine-learning algorithms and delivers closed-loop audio stimulation to enhance the natural restorative benefits of slow-wave sleep activity to promote healthy aging with improved memory consolidation, enhanced HRV, reduced cortisol, and normalized glucose metabolism. The light-weight, flexible form factor is being designed with input from users in order to maximize consumer comfort, an important differentiator from other sleep tech headbands on the market.

NeuroGeneces co-founder, Karen Crow’s, mother suffered from Alzheimer’s Disease and her son wrestled with a sleep disorder.  As she researched both conditions, Karen learned about the role of slow-wave sleep on cognitive impairment and neurodegenerative decline.  She further discovered how closed-loop audio stimulation can effectively enhance slow-wave activity to achieve targeted outcomes in memory improvement, heart rate variability (HRV) enhancement, stress resilience, and reduced neural inflammation.  Karen partnered with co-founder Jason Worchel, M.D., a neuropsychiatrist and recognized expert in neurostimulation. Together they launched NeuroGeneces to develop safe, natural, and clinically proven ways to improve memory and brain health. Their mission is to enhance brain health as we age, using neurotechnology to optimize the benefits of restorative sleep.

As Karen summarizes, “By the time my mother was diagnosed, the damage was done and there was very little that we could do to help her. My passion is to provide a low-cost, scalable product that each of us can employ to measure our own brain health, detect issues quickly and get timely interventions. NeuroGeneces wasn’t there in time to help my mother, but I hope it will help all of us avoid her fate.”

NeuroGeneces’ approach to the market is a unique and superior competitive solution for several reasons. Unlike most memory enhancement solutions, the company has focused on clinical research and proof of efficacy.  The company has completed a pilot study with the University of New Mexico to measure the impact of audio stimulation of slow-wave activity on memory retention.  Several additional studies, in early stages, will measure the impact of audio stimulation on stress resilience, mental health and glucose metabolism. 

NeuroGeneces’ Brain Age application is a novel solution and represents a new product category in brain health. This diagnostic component has tight synergy with neurological therapies. The headband combines EEG and deep learning to analyze and track biomarkers for cognitive diseases, using the resulting data to better inform and target neuromodulation or other interventions. The headband delivers personalized neurological therapies based on machine-learning algorithms that provide precisely timed stimulation to maximize biological effects and targeted behavioural effects. Additionally, NeuroGeneces has developed a novel, proprietary and growing dataset. Having a sizable proprietary database (both neurological and behavioural) with ongoing beta testing provides a distinct competitive advantage, allowing for quick iteration of algorithms to further enhance personalization and efficacy while also creating opportunities for new insights. NeuroGeneces has submitted a utility patent application directed to systems and methods of use for Sleep Performance and Brain Fitness for triggering audio stimulation.  Additional patent filings are underway to further document and protect the company’s intellectual property.

NeuroGeneces is well-positioned for success on its work on brain health measurement and neurostimulation applications.  Key drivers include world leading scientific advisors, a strong clinical partner, and support from key business networks. NeuroGeneces’ scientific advisors from UCSF and UNM bring expertise in neuromodulation, cognitive aging and sleep and its role on cognition, mental health, cardiovascular disease, inflammation and acute stress.   NeuroGeneces has a long-established partnership with the Psychology Clinical Neuroscience Center at the University of New Mexico to conduct wide-ranging clinical studies. As a Techstars backed company, NeuroGeneces leverages the resources and community of the Techstars network with its long and deep track record of building successful companies.

Flagship Product Deep Dive: Memory consolidation sleep headband

NeuroGeneces’ sleep headband and ML algorithms measure brain age to let users know how they compare to a healthy cohort with the same age/gender and track changes over time. There are no consumer products available today that measure brain health or brain age, and NeuroGeneces’ solution is significantly less costly and more accessible than MRI scans, requires no prescription, and puts individuals in charge of their own brain health.

Unlike most products in the memory enhancement market (i.e., brain supplements and training apps), NeuroGeneces has validated its efficacy in university-based trials. In addition, audio stimulation has no side effects – a claim memory drugs cannot make. Trial results demonstrated that audio stimulation enhanced slow oscillation (SO) spindle coupling and density, key metrics of brain aging. Strengthening SO-spindle coupling has profound anti-aging implications; no other brain or sleep enhancement product has been shown to have similar therapeutic effects.

Brain age is currently measured through MRI scans and has a mean absolute deviation (MAD) of 5.0 years to chronological age in healthy participants.   Because sleep EEG reflects functional changes in the brain, NeuroGeneces has been able to predict chronological age with a MAD of 4.2 years for healthy participants. NeuroGeneces’ headband is less expensive than MRI, can be self-administered, and can be repeated to mitigate internight variability and track changes over time. Thus, it can be used as a scalable screening device. NeuroGeneces’ personalized ML algorithms provide precisely timed audio stimulation to enhance memory consolidation.   University-based trials demonstrate strong biological effects as well as enhanced memory retention.

Brain age monitoring alerts users to unexpected changes or accelerated decline in brain function.  This early detection of potential neurologic problems is critical to enable early intervention, which is when they can be most impactful. Slowing cognitive decline during aging has profound impacts on quality of life.

Audio stimulation therapy strengthens restorative sleep. Restorative sleep directly improves the quality of life through cognitive, emotional, and physical effects. Enhancing cognitive functions and related executive functions improves almost every aspect of daily life. It supports the ability to learn, to develop new interests and to live independently. Restorative sleep is bidirectional with mental health. It improves mood, mitigates the emotional reactivity associated with stress, and is the most critical factor in supporting social functioning. Enhancing restorative sleep results in multiple physical health benefits, some of which are improved HRV, immune response, decreased inflammation, physiological homeostasis, synaptic plasticity, and insulin sensitivity. 

NeuroGeneces plans to launch as a consumer wellness product that meets the FDA requirements. The company intends to extend laboratory research and clinical testing beyond memory enhancement to validate the accuracy of brain age prediction and to quantify the impact of its audio stimulation on stress resilience and HRV and inflammation. At the conclusion of clinical trials, it will submit for software as a medical device and therapeutic device.

Evidence of safety and efficacy

NeuroGeneces conducted its first trial at the University of New Mexico using a prototype headband. This study was focused on measuring the impact of audio stimulation of slow-wave sleep on memory consolidation as well as the biological effects on micro-sleep features, specifically slow oscillation (SO) power, SO-spindle coupling and SO-spindle density, since these are key indicators of brain function atrophy and overall brain health.

In a within-subjects double-blind study, healthy adults ages 18-40 years old used the NeuroGeneces headband for a total 82 nights, consisting of 41 pairs of stim and sham nights. Each night and the following morning, participants completed an associative word-pair memory assessment.  The results from the stim nights were compared against those of sham nights, showing significant increase in slow oscillations of slow wave activity of 30% (p-value 0.001), and increases in S0-spindle coupling (8.9%, p-value 0.006) and SO-spindle density (10.0%, p-value 0.06). Memory improvement from one night of stimulation was 14% (p-value of 0.06).

These outcomes support the findings that NeuroGeneces’ headband effectively enhances memory consolidation and counters aging effects on brain function.

Future development

To date, the company has achieved several key milestones, all with limited outside funding. These include the development of a validated EEG-based headband prototype with machine-learning algorithms that accurately target and stimulate slow-wave activity. The first university pilot trial has been completed to measure the impact of audio stimulation on biological and behavioural (e.g., memory) effects.

Future product development efforts are focused on improvements to the headband form factor and adding more sensors, continued development of personalized algorithms for targeted outcomes of HRV and stress resilience and brain health scoring. 

The company plans to protect its IP through more patent filings and will continue to expand its partnerships for additional research trials and commercial channels.

Target market

NeuroGeneces’ headband with brain age scoring is targeted at health-conscious healthy adults who want to establish a brain health benchmark and monitor over time to quickly identify unexpected changes in brain function and seek timely intervention. This is particularly relevant for adults who have parents afflicted with Alzheimer’s Disease, dementia or other neurodegenerative diseases.

NeuroGeneces’ therapeutic audio stimulation applications are targeted at individuals with acute or chronic stress and seek to restore homeostasis to pre-stress levels before damage to the body and brain occurs. This includes millions of individuals in high-stress work or home environments, as well as those with traumatic stressors associated with PTSD and some mental health conditions like depression or schizophrenia.

Finally, audio stimulation of slow-wave activity is also beneficial for those who do not have significant sleep disorders but want to maximize the restorative benefits of sleep.

Channels to market

Initially, NeuroGeneces plans to market direct-to-consumer through online channels, as well as through health, fitness and longevity centers, health-oriented influence marketers, neurotechnology communities (e.g., NTX, OpenBCI, TransTech) and curated health device web sites. In the future, as more clinical studies are completed, the company will evaluate opportunities to develop additional sales and distribution partnerships and market directly to physicians.

Success Factors

Team and Reputation

  • NeuroGeneces’ management team brings over 100 years in senior level leadership with subject matter expertise in neuromodulation, artificial intelligence and data analytics, and proven business expertise in starting and scaling businesses, product design and manufacturing at top companies like Google, Facebook, Honeywell, and Everlywell.  The team boasts 6 exits, including 4 unicorns and IPOs in the direct-to-consumer health tech industries. 
  • As a pioneer in measuring brain age and closed-loop audio stimulation, the NeuroGeneces team has developed state-of-the-art deep learning algorithms to advance the neurotech field. The company has strong partnerships with key academic institutions to collaborate on research, apply innovative therapeutics into a suite of applications, and conduct clinical studies.
  • The team is driven by its passion to improve cognitive health and broaden the benefits of restorative sleep throughout the aging process. The team is excited to be pioneering the development of technologies to identify individuals at risk for neurodegenerative disease in a scalable, low-cost way, and to provide effective audio stimulation to strengthen and maintain healthy brain function.

Intellectual Property

  • The headband combines EEG and deep learning to analyze and track biomarkers for cognitive diseases, using the resulting data to better inform and target neuromodulation intervention. The headband delivers personalized neurological therapies based on machine-learning algorithms that provide precisely timed stimulation to maximize biological effects and targeted behavioural effects.
  • Additionally, NeuroGeneces has developed a novel, proprietary and growing dataset. Having a sizable proprietary database (both neurological and behavioural) with ongoing beta testing provides a distinct competitive advantage, allowing for quick iteration of algorithms to further enhance personalization and efficacy while also creating opportunities for new insights.
  • NeuroGeneces has submitted a utility application directed to systems and methods of use for Sleep Performance and Brain Fitness analytics to trigger stimulation..  Additional patent filings are underway to further document and protect the company’s intellectual property
  • The company plans to protect its IP through more patent filings and will continue to expand its partnerships for additional research trials and commercial channels.

Funding

  • NeuroGeneces is largely self-funded. The company has received several non-dilutive grants from U.S. Air Force (SBIR) and the New Mexico Economic Development Department.
  • To date, the company has accomplished its milestones with limited outside funding. The only two outside investors to date are Techstars and Esther Dyson, a former board member of 23&me and a notable leading angel investor in the digital technology and health tech arena.
  • The company is pursuing additional non-dilutive grants to fund these near-term research and development efforts and clinical trials and will raise equity financing to help support the product’s commercialization and launch.

Neurosoft Bioelectronics

Company Profile

Neurosoft Bioelectronics, a spin-out company from EPFL, the Swiss Federal Institute of Technology in Lausanne, is laser focused on developing new implantable electrode technologies to interface with the nervous tissue. With over 9 years of neurotech expertise, research, and development, the team at Neurosoft has developed small, thin implantable electrodes that can both stretch, flex and reducing dramatically the foreign body reaction and scarring associated with traditional implantable devices. These unique mechanical properties allow enhanced long-term performance, even in hard-to-reach areas such as the brain sulci and can reduce scar tissue formation around the electrodes. When implanted, these soft, thin, and flexible electrodes can both record and stimulate the brain, which Neurosoft believes may be able to help in indications such as tinnitus and epilepsy. Ultimately, the goal of Neurosoft is to leverage its technology and build fully implantable brain-computer interfaces to treat severe neurological disorders.

“Therapeutic outcomes from clinical neural implants are limited by their mechanical properties. Their stiff and rigid designs present a mechanical mismatch compared to the soft and curved tissues they interface with, thereby constraining the physiological motion dynamics of the nervous system. At Neurosoft Bioelectronics, we are addressing this issue by engineering elasticity in thin film materials to manufacture implantable electrodes that are much softer and flexible, and that can seamlessly interface with the nervous system.”

Founder of Neurosoft Bioelectronics, Nicolas Vachicouras, always dreamt about the possibilities of biomedical engineering since he learned about the mechanisms of the retina at high school. To pursue this dream, Nicolas threw himself into studies of microelectronics at EPFL and in 2012 he joined the Laboratory for Soft Bioelectronic Interfaces, ran by Professor Stéphanie Lacour, where he worked on soft microelectronics for neural interfaces. Inspired by the medical potential of these devices, he pursued various research projects in that field at EPFL and Harvard Medical School, and eventually started a PhD with Prof. Lacour on the translation of these technologies to the clinic. He initiated the start-up one year before the end of his PhD and in 2018 Ludovic Serex, a long-time classmate of Nicolas’, joined the team to share his expertise in microtechnologies (specifically cleanroom microfabrication).

Neurosoft is a pioneering company in soft bioelectronic interfaces. Other companies competing in this area tend to use plastic-based technologies which can be flexible but, due to the intrinsic rigidity of these materials, must be manufactured very thin and can have very sharp edges. When creating an interface with the brain, sharp edges and stiff materials can cause damage to brain vessels and put a patient’s safety at risk. Neurosoft Bioelectronics is one of the only companies in the world that are developing truly soft, stretchable, and flexible electrodes. This soft electrode technology can drastically reduce the risk of damaging neural structures, as the devices are 1000x softer and 2x thinner than current clinical electrodes. Additionally, they are MRI compatible and can easily be folded in the sulci, allowing unprecedented access to typically unreachable brain regions. Finally, the electrode sites integrated on the devices can be 100x smaller in surface area, providing high resolution for both recording and stimulation. Patients implanted with Neurosoft’s electrodes should benefit from the lower risk of scarring and device failure, avoiding complications which can require costly surgical device removal and re-implantation. Furthermore, the high resolution recording performance of these electrodes improves the ability to detect disease-related electrical biomarkers such as for epilepsy. Moreover the high-resolution stimulation reduces the risk of off-target stimulation which can typically lead to unwanted side-effects. Neurosoft Bioelectronics has a portfolio of 24 patents, including 11 granted in the USA, Europe and China, relating to its proprietary connector technology, its soft electrode technology and other specific embodiments of their technology. With more than nine years of research and development already completed, the level of expertise in this field will be hard for another company to emulate.

“Many of the technologies that are on the market today are all made with the same materials and techniques, regardless of what neurological target they have. It’s my core belief that having soft devices is a smarter way if you are interfacing with softer tissues, like the brain or spinal cord”

Nicolas Vachicouras, Founder and CEO of Neurosoft Bioelectronics

One of Neurosoft’s main goals is to treat severe tinnitus using cortical neuromodulation. To ensure this goal is met, the company have partnered with one of the leading experts in the world, Prof. de Ridder, who pioneered cortical neuromodulation for tinnitus,  and showed that there is strong scientific evidence of neuromodulation efficacy [312] when applied to tinnitus , but didn’t pursue this further when he lacked the correct electrode materials for interfacing with neural tissue. Other academic and research collaborations include partnerships with EPFL and Stéphanie Lacour’s laboratory, where most of the company’s infrastructure and manufacturing capabilities currently reside. The company also has a strong relationship with the Wyss Center, a private foundation that helps start-up companies in the field of neurotech and is known as one of the best neurotech incubators in Europe. Its soft electrode technology is also currently being tested with other clinical collaborators at Harvard Medical school and Massachusetts Eye and Ear Infirmary. To ensure it can collect data on its materials and devices, Neurosoft Bioelectronics has also made strategic relationships with various hospitals and clinics, including Utrecht medical centre, which is one of the largest epilepsy centres in Europe, the Geneva University Hospital (HUG) and the Lausanne University Hospital (CHUV).

Flagship Product Deep Dive: Soft ECoG and SOFT TINNIT

Neurosoft Bioelectronics has two main products in development, one for epilepsy and brain tumours, SOFT ECoG, and one for severe tinnitus, SOFT TINNIT.

SOFT ECoG

SOFT ECoG is an implantable subdural electrode that can come in various shapes and sizes, and each device can integrate up to 64 electrode sites. The devices are made of extremely soft and thin silicone membranes with a proprietary stretchable coating on top of the electrodes proving high electrochemical surface area for improved recording and stimulation capabilities.

The soft and stretchable devices can be placed on the brain either intraoperatively or for a maximum duration of 30 days. SOFT ECoG Subdural Electrodes connect to an external intra-operative monitoring unit outside of the body, preventing any need for any implantable active electronics. The device can be used for either recording or stimulation of the brain surface and can be used for two main indications: monitoring during brain tumour resection surgery and localization of epileptogenic regions in refractory epilepsy patients.

For use in brain tumour resection surgeries, the electrodes are placed intraoperatively and can either stimulate or record parts of the brain, effectively acting as neuronavigation tool. This ensures that the surgeon can identify critical regions during invasive surgeries and helps to prevent operative damage.

The SOFT ECoG device can also be used for patients with epilepsy. Epilepsy is one of the earliest applications of neurotech at large and is supported by a wide body of scientific literature. One-third of epilepsy patients do not respond to drug treatments and must undergo invasive surgery to remove the part of the brain that is tiggering the seizures. However, it can be difficult to identify, using traditional methods such as MRI, what exact area of the brain is causing the seizures.  In these cases, the implanted electrodes go over an area where the seizures are suspected to arise and then the patient remains in the hospital for an extended period and is monitored continuously. The device records seizures that happen spontaneously or, alternatively, the device can stimulate parts of the brain to elicit seizures. The brain activity that is recorded allows the clinician to triangulate where the seizure is coming from prior to surgery. The use of the device is under 30 days in both scenarios, so safety and performance are much easier to demonstrate for first-in-human trials and regulatory clearance. Neurosoft is targeting first-in-human testing for 2022. And expects FDA clearance in 2023 for SOFT ECoG implantation into a patient for under 30 days.

SOFT TINNIT

Late 2023 will be the year that Neurosoft Bioelectronics expects clinical proof-of-concept of its second product, SOFT TINNIT, an implantable brain-computer interface to treat severe tinnitus through cortical neuromodulation. Invasive neuromodulation has been used previously to suppress tinnitus, however, the studies had to be halted as the electrodes were not suitable as they were too rigid for the soft environment of the brain.

Neurosoft’s compliant materials enable manufacturing of implants that can achieve exceptional long-term bio-integration in the body, conforming to the static and dynamic mechanics of neural tissue. This could be particularly useful in cases such as tinnitus, where a prime neurological target is located in a hard-to-reach area in the depth of the Sylvian Fissure. Due to the flexibility of Neurosoft’s devices, that region could be accessed and stimulated to enable a therapy for the currently untreatable tinnitus.

Evidence of safety and efficacy

Neurosoft’s technology has been demonstrated in 18 peer-reviewed articles. To date, the soft bioelectronic material has been tested on various neurological targets in mice, rats, pigs, monkeys and human cadavers. Each study strengthens certain characteristics of the material.

  1. Stimulation reliability: The soft arrays could be easily handled during surgery and functioned over 1 month when implanted in mice for stimulation of the auditory brainstem. When inserted in human cadavers the soft arrays showed good electromechanical and electrochemical stability and a larger dynamic range compared to clinical auditory brainstem implants (Vachicouras et al. 2019). Long-term functionality for electrical stimulation of the spinal cord was also demonstrated in pigs (6 months) and monkeys (6 weeks) (Schiavone et al. 2018, Schiavone et al. 2020, respectively).
  2. Recording reliability: The ability to record with a higher resolution using micro-electrodes was demonstrated in a pig study (Fallegger et al. 2019). Further, the soft implants successfully extracted cortical states in freely behaving animals, making them suitable for brain-machine interface applications (Minev et al. 2015)
  3. Safety: In terms of safety, due to the soft material being more biocompatible, studies on the central nervous system have shown a reduction in scar tissue in comparison to other rigid electrodes for 6 weeks of implantation. This advantage was shown at the level of the spinal cord in rats, where the use of a soft material has proven to be beneficial, reducing the spinal cord compression which could instead be observed when using a more rigid material (Minev et al. 2015).

Future development

Advances in technology: Neurosoft Bioelectronics has had a lot of focus on continuously developing its soft electrodes, but it is now also focusing on integrating them with the active electronics for recording and stimulation to build a fully operational implantable Brain-Computer Interface.

Advances in software: On the software side, Neurosoft Bioelectronics has been gathering pre-clinical data in the context of various neurological disorders and is now working on projects to automatize the identification of biomarkers for neurological disorders such as epilepsy and traumatic brain injury. As Neurosoft starts gathering clinical data, Artificial Intelligence and machine learning are going to be a big component of its activities.

Future indications: The company is focusing on investigating its product for severe tinnitus but foresees the use of its cortical electrode for other disorders. In particular, due to the current anatomical targets, a natural progression for Neurosoft would be to investigate the products effectiveness for deafness, in patients who are not eligible for cochlear implant. Cases of tinnitus are usually linked to hearing loss. “There is a lot of things that we will learn in our journey with tinnitus, including patient management, that we believe can then be applied to deafness as an indication”, Nicolas.

Target market

Market size for SOFT ECoG:  Refractory epilepsy is the drug resistant type of epilepsy, impacting around 1 million in the US. Based on prevalence data, Neurosoft Bioelectronics estimates that around 180,000 patients in the US and in Europe could be candidates for a surgical procedure. For use in surgery for patients with brain tumours, Neurosoft estimates around 200,000 surgical candidates around the world. This equates to a market size of $400M.

SOFT TINNIT: Tinnitus is a common disorder (affecting 10-15% of the population) which consists in the perception of a loud ringing or buzzing noise which has no external source. While many manage to tolerate the sound, it is estimated that 7-9 million people have severe forms of the disorder, which significantly affects the social well-being and health of millions of people world-wide. It is estimated that close to 500’000 patients attempt to commit suicide every year due to the tinnitus. A high-profile case of this was the suicide of CEO Kent Taylor, whose son said The tinnitus had progressively worsened to the point that it sounded like a jet airplane taking off in your ear 24 hours a day, seven days a week” when interviewed about his father’s death in Fortune [313]. This number may be even higher in the future, as nearly 15% of COVID patients surveyed described having the symptoms of tinnitus. In terms of an addressable market, Neurosoft Bioelectronics estimates there would be roughly 170,000 patients in the US and Europe that could benefit and who would be willing to use SOFT TINNIT. Based on a rough price for the device, Neurosoft estimates a market size of over $3B for US and Europe.

Future markets: Neurosoft’s electrodes offer a safer type of ECoG that can locate specific functions in the brain whether speech, movement, or vision. Neurosoft has the potential to apply its technology to a range of further neurological disorders such as deafness, blindness or tetraplegia.

Channels to market

For its first product, SOFT ECoG, Neurosoft Bioelectronics is looking at a B2B model selling to hospitals and neurosurgeons. Neurosoft is currently looking for distributors and partners in both the EU and US markets. For its second product, SOFT TINNIT, Neurosoft Bioelectronics seeks a strategic partnership with large ENT/Audiology/Neuro companies which could be either a licensing deal or acquisition.

Success Factors

Team and Reputation

  • Neurosoft’s C-suite has a strong breadth of knowledge in the scientific areas of neuroprosthetics and bioelectronics;
  • Nicolas Vachicouras, PhD, is co-founder and CEO of Neurosoft. Nicolas has 9-years’ experience in neuroprosthetics and a PhD in application of microelectronics to soft neural interfaces from the laboratory of Prof. Stéphanie P. Lacour at EPFL. He holds a Certificate of Advanced Studies in the management of medtech ventures;
  • Ludovic Serex, PhD, is co-founder and COO of Neurosoft with  7 years’ experience in microfabrication and holds a PhD in microfluidics and microelectronics;
  • Florian Fallegger, PhD, is a co-founder and advisor for Neurosoft and holds a PhD in microelectronics with a strong focus on soft neural interfaces. He developed and improved a large part of the technology used in the company during his PhD.
  • The scientific advisory team includes Prof. Dirk de Ridder, MD PhD, who is the developer of the “burst” stimulation design for brain and spinal cord implants, commercialised by Abbott. Furthermore, he is recognized as the world-leading expert in tinnitus, pioneering cortical neuromodulation for its treatment. His years of experience and his world-wide collaborations have resulted in the publication of over 250 scientific articles and more than 30 scientific book chapters;
  • The advisory panel also includes tinnitus and neuromodulation expert, Dr. Christian Hauptmann. Dr. Hauptmann is an experienced neuroscientist and developer with over 20 years of international experience in several start-up companies and universities, with more than 48 patent filings and 55 scientific publications. Dr. Hauptmann developed several innovative neuromodulation techniques, both invasive and non-invasive and transferred these into medical devices.
  • Other key opinion leaders hold advisory positions at Neurosoft Bioelectronics, including Claude Clément, previous CTO of the Wyss Center with expertise in implantable medical devices and in particular brain-computer interfaces, and Stéphanie Lacour, Professor at EPFL and Director of the Center for Neuroprosthetics, who is a world leading expert in soft bioelectronic interfaces.

Intellectual Property

  • Neurosoft Bioelectronics is one of the only companies in the world that are developing truly soft, stretchable, and flexible electrodes;
  • Neurosoft has 24 patents, including 11 granted patents relating to its soft electrode technology, in particular around its connector solutions, in addition to application-specific embodiments;
  • Neurosoft’s subdural electrodes can cover larger parts of the brain/cortex (more than 10x compared to a single Neuralink device), which is much more suitable for applications that require recording/stimulation of networks of neurons across different and/or large brain regions;
  • Its devices are less invasive than Neuralink as it does not penetrate any brain tissue, instead coating the surface of the neural tissue;
  • Neurosoft have demonstrated in vitro and in vivo that their devices can be used for recording and stimulation;
  • Neurosoft have a wide range of electrode sizes from mm sized down to hundred on microns. Having larger electrodes is important for efficient stimulation, while micro-electrodes are critical for high-resolution recordings in order to segment more precisely pathological tissues from healthy ones, for example in the context of epilepsy resection surgery;
  • Neurosoft devices are suitable to access sulci (which represent more than 50% of the cortex). Tinnitus is a good example of an application which requires access to a sulcus. Other basic functions of the brain are hidden in sulci such as part of the auditory cortex or the leg area in the motor cortex;
  • The materials used in a Neurosft device are 1000x softer than conventional electrodes, which has an impact on long-term biointegration;
  • Neurosoft’s surgical approaches are compatible with existing and known surgical approaches, which is important for faster adoption by neurosurgeons, as they don’t require specific tools;
  • Neurosoft hopes to have FDA clearance in 2023 for SOFT ECoG implantation into a patient for <30 days for its first indications of brain tumour surgery monitoring and pre-surgical epilepsy monitoring;
  • The company is currently further developing the technology for novel biomarkers in intra-op epilepsy and traumatic brain injury, as well as pursuing the technology as a therapeutic for severe tinnitus;
  • Proof-of-concept of the use of its product SOFT TINNIT will begin in 2023;

Funding

  • Neurosoft Bioelectronics has raised more than $5M to date, 90% is non-dilutive and 10% is convertible loans.
  • The biggest grant to date is from the EIC accelerator grant, which is around 2.5M Swiss francs.
  • The company is seeking to close a $12M Series A venture funding round in 2022.

Investment opportunity

Series A investment round
Equity investment $12,000,000
($6M in soft commitment)
Expected close Q3 2022
Milestones & Expected Deliverables 1. FDA 510(k) Certification of SOFT ECOG

2. CE Mark of SOFT ECOG under MDR

3. Breakthrough Designation of SOFT TINNIT with FDA

4. Proof of Concept Clinical Trial for Tinnitus in 10-15 patients with SOFT ECOG

5. Chronic electrodes: Finalise development of chronic electrodes for SOFT TINNIT

Funding so far >$5,000,000 in non-dilutive grants
(incl. $2.78M SERI funded EIC Accelerator Grant – Q1 2022)

+ $540,000 in convertible loans

+ $110,000 in founder capital

NexStem

Company Profile

NexStem, founded in 2020, focuses on the development and widespread application of state-of-the-art BCI solutions that are affordable and accessible to all. NexStem’s aim is to empower individuals to transcend their biological limits through sophisticated, yet innovative solutions.

For a long time, human evolution has been under the influence of nature and nature alone, however with recent advancements in the field of technology and the implementation of AI technology, it is becoming possible to continue human evolution by unlocking the mystery of the brain. NexStem aims to fully unlock the mind’s potential and redefine what it means to be human by bridging the gap between man and machine through their key product, the NexStem headset. The NexStem headset is an EEG recording device that is capable of recording brainwave signals from the surface of the skull, which can be used to interpret the underlying brain state of their users.

The development of an EEG solution that can be translated from a clinical setting to the consumer domain has been the major challenge in the development of EEG-based BCI devices, as most consumer-grade headsets lack the technical prowess of research-grade equipment. Developing EEG devices that are user-friendly, affordable for widescale access, and can cope with both the complexity and volume of EEG data has limited most consumer-grade devices from truly adding value to consumers’ lives.  NexStem has addressed many of these issues through its hardware and signature software development kit (SDK) to create solutions that can be applied across a wide range of health and wellbeing applications. NexStem has also been developing its solutions by leveraging its unique headset and platform, including transforming its headset into a communication device for non-verbal patients. Through accruing a large amount of brainwave data, NexStem hopes to eventually recreate a digital twin of the user’s brain.

Growing up, Deepansh and Siddhant, the founders of NexStem, had seen several amputees all making use of cumbersome prosthetics manipulated with strings that were often tied to the person’s chest. The idea was short lived as their use was not initiative or user-friendly. Siddhant quickly realized that there were, in fact, prosthetics available which utilized EMG signals; however, they were expensive, the signals acquisition was exceptionally slow, and the user experience was poor. The next logical step was to head to the signals’ source – the brain. This is how the idea of NexStem was born.

NexStem’s first device? A prosthetic arm controlled by a person’s thoughts.

NexStem’s first proof of concept was simplistic. If the person focused, the arm would close and when they stopped focusing, the arm would open back up. The second version took the idea to the next level and was centered around creating more control of finer motor skills. When the user thought “left,” the index finger would go up, and if they thought “right,” the middle finger would go up; when they clenched their jaw, the arm would reset, and if they moved their tongues, then the complete hand would open or close depending on how it was set up.   

Since these early products, NexStem has grown and advanced their products extensively. Today, NexStem develops superior software solutions that can translate EEG signals at the highest quality and provide this as the premise to develop BCI solutions that are controlled simply with one’s thoughts. In short, the human brain becomes a part of the Internet, inserting the human into the Metaverse.  

Going forward NexStem hopes to continue to improve its headset to expand its application in the consumer domain with the hope that eventually the headset will gain the efficacy and accuracy of a medical device that can be used within the clinical domain.

Flagship Product Deep Dive: NexStem Headset and NexStem Wisdom SDK.

The NexStem headset is a 16-channel EEG device that measures brainwave signals across the skull, ranging from the prefrontal cortex to the occipital lobe, providing complete coverage of cortical brain activity. Their headset design is user-centric, and designed with every day, extended use in mind. It is a lightweight product, lined with padding and memory foam to ensure user comfort throughout the day. The headset also uses dry EEG electrodes, that are polymer-based ensuring that they are soft and do not dig into the skull; compared to (more common) wet-EEG electrodes often utilised in clinical EEG devices. With such a solution, NexStem hopes that users will be more inclined to wear their headsets for extended periods, hence leading to a larger volume of collected data.

From a technical perspective, the headset offers a unique combination of characteristics when compared to other consumer-grade EEG devices available on the market today

  • A high sampling rate of 1000 Hz (i.e., almost 4 x higher than most consumer-grade EEG devices on the market today).
  • An over-the-head form factor that can be easily incorporated into the user’s everyday life.
  • Wireless connectivity and Cloud storage allow users to easily access and manage their data.
  • Active electrodes to help reduce the impact of muscle artifacts on the signals.
  • Polymer dry electrodes provide a comfortable user experience as well a quick plug and play setup.
  • 16 channels which allow capturing of signals from the major centres in your brain.
  • Real-time data acquisition reflects changes in users’ brain activity in real-time.

Another major advantage with NexStem’s NexStem headset is its affordability, currently, at one-third that of other EEG headsets with similar specs.

NexStem Wisdom Software Development Kit (SDK).

NexStem Wisdom is a software development kit (SKD) that complements the high-performance hardware manufactured by NexStem. The NexStem Wisdom SDK is a tool that consists of pre-trained high accuracy Machine Learning (ML) models that can be used to analyse a variety of bio signals in a single platform.

A unique feature of the Wisdom SDK is that algorithms can be developed on the platform through a drag-and-drop feature that facilitates the development of novel solutions without writing a single line of code. This feature is intended to allow neuroscience researchers to develop and test solutions, thereby fostering continuous innovation on the device. Other devices on the market provide SDK, however, they often require developers to write their own code, limiting the target audience to developers with sufficient coding experience and expertise. NexStem’s drag-and-drop feature opens the definition of “developer” to include any individual/researcher and ensures a high degree of fidelity between the researcher’s hypothesis and the final, executed algorithm.

NexStem has invested in providing high degrees of signal processing quality by developing Hardware and Software filters which can reduce the amount of noisy data often produced by EEG recordings, and therefore enhance the recorded biological signal. Overall, this is meant to improve the signal-to-noise ratio and, as well as the predictive power of the machine learning algorithms developed. Overall, NexStem’s algorithms will allow the prediction of relevant information based on a user’s unique state of mind (and thoughts).

NexStem’s Cerebral Palsy Communication Device (CP Product).

NexStem is currently working on developing a Communication Device for non-verbal patients affected by Cerebral Palsy. The product aims to address communication issues for the ~ 250,000 (annual numbers) of non-verbal patients in the US today.

Current Status:

As part of the NexStem Wisdom solution, NexStem has implemented a P300 speller. This is a type of BCI system that utilises EEG signals to allow a patient to spell out words by simply focusing their gaze on characters in a matrix of letters and numbers that appear on a screen. NexStem is working on improving and adapting this feature and developing a complete Hardware and Software solution for Cerebral Palsy patients.

 Current communication devices on the market that try to achieve the same goal often rely on bulky, expensive equipment that measure eye muscle movements rather than brain signal data. Consequently, these devices struggle to distinguish between a person’s unintentional eye blinks or movements and can therefore provide limited value to patients as they cannot accurately distinguish intention.  In addition, CP can result in involuntary eye gazing and facial twitches that limit the usefulness of a device that tracks eye-gazing alone. NexStem’s product will overcome that limitation by recording brain signals directly from the intact visual cortex, providing a more seamless user experience and far more accurate output.

Future development

NexStem has several aims for the near future:

Optimising the design to expand applications: Optimizing the design to ensure that users can wear the headset comfortably for extended periods. This will allow for the collection of large amounts of data that will benefit the user both in the assessment they receive and also be benefit to developers and researchers using the anonymized data to establish new solutions. The aim is to make the headset as slim as possible over time so that the headset can be worn comfortably at night allowing nightly sleep monitoring. Securing further collaborations with ecosystem partners and utilising their expertise will help to achieve this aim.

Creating a digital twin of the body: NexStem hopes to move beyond just the human brain by capturing a variety of complementary bio signals apart from EEG, such as ECG (electrocardiography), and incorporating these multiple inputs into their device to produce holistic health and wellness solutions. The next version of the NexStem which is in development will have its own OS (WisdomOS) based on Ubuntu operating system, with a graphics processing unit (GPU) accelerated filters and machine learning (ML) models embedded in its kernel, which will allow developers to develop BCI applications on the headset directly. This minimizes latency as well as speeds up the development process significantly. The v2 headset will also allow communicating with other bio-signal sensors like electrocardiography (ECG), photoplethysmography (PPG), electrodermal activity (EDA), electromyography (EMG), electrooculography (EOG) et cetera giving you real-time image of the person’s heart, muscle, brain, and eye activity all in one place.

Target market

Digital Heath: 

NexStem solutions aim to target three main subsets of this domain:

  1. Improving Health: Measuring EEG data can give a lot of information on a person’s mental health, sleep, wellbeing, stress, and focus. 
  2. Improving Mental Wellbeing:  EEG-based BCI devices can be used for neurofeedback and neurostimulation purposes helping to drive a person towards better mental health and wellbeing whilst providing a customisable approach based on a person’s needs. 
  3. Assistive Technologies: These are affordable and accessible to every person who may require their use. Examples of possible applications include AAC devices, prostheses, and wheelchairs[Reference: https://www.gminsights.com/industry-analysis/digital-health-market]. 

Cerebral Palsy:  

Cerebral palsy is a group of disorders that affect movement and muscle tone or posture. It’s caused by damage that occurs to the immature, developing brain, most often before birth, and is the most common motor disability in childhood Recent population-based studies from around the world report prevalence estimates of CP ranging from 1 to nearly 4 per 1,000 live births or per 1,000 children. As the disorder can affect the muscle associated with speech production, those affected often lose the ability to communicate vastly impacting their quality of life. NexStem’s solutions can be targeted at improving this aspect of cerebral palsy, by utilising the headset together with the wisdom SDK. The cerebral palsy treatment market is predicted to continue to grow in the next decade, from a market size value of $3166.82 million in 2020, to projected growth of $4,365.01 million by 2030 [References: https://www.cdc.gov/ncbddd/cp/data.html] https://www.alliedmarketresearch.com/cerebral-palsy-treatment-market-A13340]

Success Factors

Team and Reputation

Founders:

Siddhant Dangi: is the Co-founder, President and CEO of NexStem. 

Siddhant Dangi is the CEO and a co-founder of NexStem, a MedTech and robotics startup that creates non-invasive mind-controlled robotic solutions directed simply by one’s thoughts. Siddhant develops the algorithms behind the development of the machine learning and artificial intelligence models the company is unlocking in their quest to insert human and machine seamlessly.

Deeply passionate about improving the quality of life of humankind, his first link to seamlessly and non-invasively integrating the brain to devices was the analysis of multivariate time-series data using deep learning models and the creation of a hand-gesture controlled system for paralyzed and differently-abled people. Siddhant’s days are spent alongside his co-founder Deepansh Goyal, breathing life into the EEG data acquired from the award-winning NexStem Headset. In short, developing, designing, and architecting end-to-end Brain Computer Interfaces (BCIs).

Siddhant doesn’t spend his spare time playing golf. Instead, it is very likely that along with Deepansh, they are working on how you can use just your thoughts to perfect your golf swing.

Deepansh Goyal: is the Co-founder, Treasurer, and CTO at NexStem, 

Deepansh Goyal is co-founder, treasurer, and CTO at NexStem, a MedTech and robotics start-up that creates non-invasive mind-controlled robotic solutions directed simply by one’s thoughts. A robotics enthusiast and self-professed geek, Deepansh spends all his time immersed in working out how to merge the human brain and technology non-invasively.

His strong entrepreneurial spirit is well applied to steering NexStem’s research and development, design, and engineering efforts, as it creates life-changing advanced Brain-Computer Interfaces (BCIs).

A Bachelor of Engineering graduate from the Birla Institute of Technology and Science in Electrical and Electronics Engineering, his expertise in developing assistive technologies has played a crucial role in developing the award-winning NexStem Headset.

Partnerships and collaborations:

Divergence Neuro Technologies:

NexStem has partnered with Divergence Neuro to make the NexStem headset available in their store, with a primary focus on Canada. Divergence Neuro selected NexStem’s device due to its long battery life and high-quality technical performance relative to price.

The Divergence Neuro’s platform is marketed to clinical researchers to treat a variety of mental health conditions which is beneficial for NexStem as the usage of their headset by Divergence Neuro clients can provide NexStem with access to data to help improve their algorithms.

Furthermore, the high performance of the headset and SDK have attracted the attention of several notable organizations, including the University of Santa Clara’s neuroscience research, Purdue University, Illinois University, Wheeler’s School and MyNeurva Neurofeedback Clinics.

Funding

NexStem has raised two rounds of investment, the first one for 140k USD was led by BITS Spark Angels, a group of super angels including Raghu Sethuram (VP MSFT Azure), Rajiv Patel (President, TiE), Preethy Padmanabhan (Marketing Director, Freshworks) and Hemanshu Jain ([email protected] Diabeto and Khyaal).

The second of investment for 1.5 million USD was led by InfoEdge Ltd. Info Edge is a highly regarded tech-focused investment fund in India with a track record of four successful unicorn exits in the past four years.

Other investors like BITS Spark Angels and super angels like Alagu Periyannan (Founder @BlueJeans), Utsav Somani (CEO @ AngelList India), Anand Raghvan (VP Verizon TeleHealth) and Sundi Natarajan(Founder @Sparksoft Corporation) followed on with additional investments in this round.

Eno

Company profile

Eno, founded in Canada in 2016, is a mental fitness platform that coaches knowledge workers to improve their productivity and mental health.

Eno was created with the mission of building Fitbit for mental fitness, which led Eno to design its first product, Enophone: a mental fitness tracker that helps users maximize their productivity by discovering when they work best, taking better breaks, and avoiding their biggest distractions. By integrating EEG sensors into a premium over ear headphone, Enophone is the most accessible, easy to use neurotech product available.

Eno believes that the next big innovation in neurotech will not come from a lab, but rather from designing incredible experiences that consumers love and use every day. Eno has spent the last decade innovating in sensor technology, machine learning, and user experience to achieve their vision of building the most user-friendly neurotech product available. With Enophone, tracking your mental fitness is as easy as wearing headphones. As a result, Enophone collects more data per user than any other neurotech product in the world.

“Over the last decade, our physical fitness tools have become more precise and personalized than ever – every heartbeat, step, and calorie can be tracked and analysed to help us understand our performance and health. Why doesn’t this exist for our mental fitness?
At Eno we believe the road to unlocking your peak mental fitness begins by measuring what matters: how well you’re performing, what’s getting in your way, and whether you’re ready for more. We spent nearly a decade working with the latest innovations in neurotechnology to achieve this vision. The result is Enophone.”

To date Eno has shipped thousands of Enophones to users across 80+ countries. Eno was awarded Forbes 30 under 30, and the CES innovation award for its innovation in wearable technology. Furthermore, Eno is currently partnered with Onkyo-Pioneer, and backed by Real Ventures, SOSV, and Anges Quebec.

Identifying the problem

“If you can’t measure it, you can’t improve it.” 

Before Eno was founded, Jacob Flood, Eno’s co-founder and CEO, spent several years researching the psychology of mental fitness, and published a book on the science of productivity. During this time, he recognized a problem: there doesn’t exist any product that can measure and track your mental fitness. As a result, despite the $121B spent annually on mental fitness tools, there’s no way to tell if what you’re doing is improving your mental fitness or not. In essence: there’s no Fitbit for mental fitness.

Here, Eno provides a solution – with their technology, users can measure and track their mental fitness, providing data, insights, and guidance to help users improve their mental health and productivity over time. 

Providing a solution

Jacob Flood and David Doyon founded Eno to do for mental fitness what Fitbit did for physical fitness. 

Enophone is a brain-sensing headphone that allows users to measure and track their mental fitness. Enophone’s EEG sensors detect changes in brain activity in real-time and can extract 3 mental fitness scores:

  • Mental effort tracks the cognitive demands of your task, to gauge how hard you are working.
  • Readiness tracks the impact of cognitive fatigue, to gauge whether you should take a break.
  • Efficiency tracks how focused or distracted you are while you work.

Eno’s software turns this data into meaningful and actionable insights, helping the everyday knowledge worker understand how their daily habits and routines impact their mental fitness.  

For knowledge workers seeking to improve their mental health and productivity, Enophone helps understand your mental fitness and the build better work habits.

Flagship Product Deep Dive: Enophone.

Enophone

The Enophone is the ultimate mental fitness tracker. It is one of the only neurotechnology products available that can be comfortably worn all day, in any environment, to help users track their mental fitness.

Enophone combines research-grade EEG into premium over-ear headphones. Eno intentionally chose as this form factor as it has several benefits over others (e.g., headbands, glasses, or VR headsets set).

  • Firstly, a headphone is a product that consumers are already familiar with and use for several hours daily. Thus, a headphone-based neurotech device can easily be incorporated into a user’s daily life. 
  • Secondly, because Enophone aims to improve user’s productivity while working, users will wear the device while sitting down without minimal movement – this helps to produce multiple hours of high-quality EEG recordings without muscle artefacts diluting the quality of EEG data recorded and interpreted. 
  • Thirdly, headphones are comfortable and appealing to wear, meaning that users are more likely to wear them for long periods, generating a large amount of data. This is vital when implementing AI technology, as the success of AI-based insights relies on feeding the platform with large enough datasets. The more data, the quicker the platform can learn and the better the quality of insights produced for the user. 

Simply wearing the Enophone – just like any other headphone – will automatically track, analyse, and report on users’ mental fitness to provide clear and actionable insights that can be applied to improve mental health and performance.

Enophone tracks three mental fitness scores that provide a clear, varied, and actionably summary of a user’s mental health and productivity:

  • The mental effort score tracks the cognitive demands of your tasks, to indicate how hard your mind is working. Your mental effort score can help you identify when your mind is operating at peak performance throughout the day and narrow down which tasks are the most cognitively demanding.
  • The readiness score tracks the accumulation of mental fatigue, visualizing how ready you are for high-effort tasks. The readiness score will help you identify when you should keep working, and when to stop and take a break.
  • The efficiency score tracks how focused or distracted you are throughout your session. Your efficiency score helps identify which apps are most distracting and highlight behaviours that may be impacting your focus.

By tracking their neural data and app usage, users can learn what time of day they are the most focused, which apps are most distracting, and when they should take a break. Users can also visualize each of these trends over time, helping them set future goals and experiment with their daily routine and work habits.

To achieve the goal of creating the most seamless and premium mental fitness tracker, Eno partnered with Onkyo. As pioneers in audio manufacturing, Onkyo supported the design and engineering of the audio technology, ensuring Enophone is not only a “fantastic mental fitness tracker”, but also a high-quality noise-cancelling headphone.

As part of their solution, Eno has also developed audio content to help users improve their productivity:

  • Neuro-adaptive focus music offers audio soundscapes that adapt to changes in the user’s brain, to help them focus or relax.
  • Guided meditations offer real-time feedback that quiets when your mind is calm, and lets you know when you’re distracted.
  • Short-form audio podcasts provide mental fitness coaching, to help educate users on the science of mental fitness

Evidence of safety and efficacy

Although the data is not yet published, Eno has demonstrated the following:

  1. Eno measures the overall efficacy of Enophone by how it increases the amount of deep, focused work users achieve each week by using their product. Their latest internal data demonstrates that Enophone users achieve an increase in time spent on focused work of 24% monthly throughout the first 6 months of use. 
  2. Enophone has demonstrably replicated industry-standard tests for EEG signal quality, including Auditory Steady-State Response, Steady-State Visually Evoked Potential, and Alpha Blockade experiments. 
  3. In a study using Enophone, during a response inhibition (impulse control) task, Eno identified a set of statistically significant metrics that explain 65% of the variance in cognitive workload across all participants. 

Future development

Because users can comfortably wear Enophone for several hours every day, Eno’ users can collect 100x more data than is possible with any other neurotech product. As a result, by 2023 Eno will have the largest neural dataset in the world. This wealth of data enables Eno to extract trends and insights over long periods that were previously impossible with consumer neurotechnology.

Eno is prioritizing the design of new software features aimed at leveraging this unique dataset to help users understand and improve their mental fitness.

Eno currently has several features in development, which will be released throughout 2022. These include the following:

  • Tracking of additional neural states, including mental effort, readiness, and efficiency.
  • Visualizations of behavioural insights and trends, to help users discover when they work best, identify their biggest distractions, and learn to take better breaks.
  • Neuro-adaptive meditations and brain-training games, designed to help users strengthen their mental fitness.
  • Audio content designed to educate users about the science of mental fitness.

These new features will help provide users with data, insights, and guidance to improve their mental health and productivity. 

Target market

Enophone is designed for and by knowledge workers seeking to improve their mental fitness. This direct B2C approach allows Eno to prioritize the end-user, designing the best experience for them. Eno aims to become the category-defining brand in the $121B mental fitness industry, by doing for mental fitness what Fitbit did for physical fitness.

Eno also provides a software development kit (SDK) that researchers and healthcare providers may use to integrate Enophone’s EEG sensors and mental fitness data into their products. Several third-party applications are currently in development following this model. 

Channels to market

Enophone can currently be purchased via direct e-commerce at https://enophone.com

Eno is currently expanding its omnichannel distribution strategy, including technology retailers (Amazon, BestBuy) and corporate wellness distributors. 

Success Factors

Team and Reputation

Founders

Jacob Flood (CEO): is a McGill engineer and Forbes 30 under 30, with 10 years of experience researching the science of productivity. Before Eno, Jacob founded a SaaS edtech company and authored the book Study Smart on the psychology of productivity. Jacob has audited minors in tech entrepreneurship and computer science, and previous experience in satellite manufacturing.

David Doyon (CTO): is a McGill engineer and Forbes 30 under 30, completing his honours thesis on biomimetic design. David has 4 years of hands-on experience in Shenzhen’s manufacturing ecosystem. Before Eno, David spent several years manufacturing surgical tools, and in aircraft failure prediction. 

Advisory Board

Eno works with an advisory board that help design and validate their neurotechnology. This includes:

Dr. Antony Passaro: neuroscience researcher specializing in EEG signal processing and neuro-adaptive training. Leader in applied neurotech for US Army and Deloitte.

Dr. Ian Robertson: professor of neuroscience at trinity college Dublin and an international authority on cognitive rehabilitation. 

Curt Steinhorst: CEO of Focuswise, and an expert on the psychology of productivity and attention. Author of Can I have your attention,

Partners

Onkyo-Pioneer: Global leader in manufacturing headphones, helping to design Eno’s high-quality audio.

Eno is backed by Real Ventures, SOSV, and Anges Quebec.

Location Advantages

Eno operates from three locations which highly reflect the global nature and strengths of the company:

  1. Montreal, Quebec, Canada which holds a strong reputation for neuroscience research and developments in AI, with the Canadian government allocating a substantial budget to AI-related initiatives. 
  2. Shenzhen, China due to its reputation as the manufacturing capital for electronic devices.
  3. San Francisco, California, USA due to its strong technology ecosystem.

Intellectual Property

Eno’s core technology, as well as the neuro-adaptive focus music, are covered by USPTO provisional patents. Eno intends to continue investing in, and patenting innovations that will allow them to create “the world’s most advanced mental fitness tracker”.

Funding

Eno has raised $4.8m to date from institutional and public sources. Notable investors include Real Ventures, SOSV, and Anges Quebec. These funds have enabled Eno to design and engineer its first product Enophone and deliver it to thousands of customers across 80+ countries. 

Eno’s priority is now to scale its commercialization strategy. The ambition is for Eno to become the category-defining brand in the $121B mental fitness space and do for mental fitness what Fitbit did for physical fitness. Eno is eager to connect with any institutional or angel investor who believes in their mission and feels they can support Eno’s commercialisation. 

Eno is currently prioritizing the growth of its first product Enophone. It is closely monitoring the growth of its user engagement metrics (e.g., 25% monthly growth for the past 6 months) and revenue (e.g., 24% monthly growth for the past 12 months). 

Eno intends to raise their next equity round in late 2022.

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