What they do and how machine learning fits in

‘…physics and neuroscience are in some ways the most fundamental subjects: one is concerned with the external world out there, and the other with the internal world in our minds’.

Demis Hassabis, a co-founder of DeepMind. FT.com

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The development of technologies that study and affect the ‘internal world in our minds’ is fuelled by investment activity, among other things. In the summer of 2016, CB Insights, an investment database, published a review of 17 startups that boost the brain. In just two years, in June 2018, Neuronetics, the most well-funded startup from the list, went public. Other companies from that list raised substantial investment rounds. For example, Lumosity ($11M), Headspace ($32M), Thync ($6M) and others. Only one startup went out of business reportedly. That, what is happening at the intersection of tech and neuroscience looks exciting.

This article represents a wider and deeper overview of startups that hack the brain*. It also highlights how machine learning (ML) is/may be applied to this grand challenge. I hope this article will be useful for data scientists, who are thinking about where to apply their expertise, as well as for researchers and healthcare professionals, who want to identify technologies beneficial for their research/patients.

In this article I divide 44 startups into three groups: 1) companies that provide diagnostics capabilities, 2) those who build tech for various interventions and affect/stimulate brain, and lastly, 3) companies who contribute predominantly to brain research and development of brain interfaces. See chart 1.

Within each group, startups are aligned around the core principles that their tech is based on. For example, measuring blood flow, tracking electrical activity of the brain, or testing for certain proteins. In the Appendix, you may find information on how this data was collected.

Selected brain tech startups*

I. Diagnostics

Tech by NeuroSky, BrainScope, and iota Biosciences

Electroencephalography(EEG), a technology to record electrical activity of the brain, is one of the most popular diagnostics tools. Among startups that build on EEG are:

A novel way of diagnostics is based on analysing human-smartphone interaction. Mindstrong relies on ‘…a set of digital biomarkers from human-smartphone interactions that correlate highly with select cognitive measures, mood state, and brain connectivity’.

Among various diagnostics approaches, there are approaches that are measuring fluid volumes, blood flow and oxygen levels, properties of a tissue, and even motions of the skull. Startups that apply these approaches are:

Blood tells a lot about brain health, and some startups study it to diagnose injuries and other conditions. For example:

Machine learning for diagnostics

It appears that brain diagnostic applications rely heavily on machine learning. The core of EEG software is interpretive models that help to identify and quantify categories of mental or emotional states. These algorithms ‘…can be as simple as a mathematical formula to as complex as a machine-learning model that maps to users’ personal opinions about how they feel while engaged in a given activity’.

Machine learning also allows skull motion patterns to be recognised and associated with various brain pathologies. Algorithms ‘…differentiate between the bioimpedance profiles of various brain pathologies’.

On top of that, machine learning methods are used ‘…to show that specific digital features [of human-smartphone interaction] correlate with cognitive function, clinical symptoms, and measures of brain activity’. Therefore, a new way of diagnosis becomes available.

II. Interventions

Startups go beyond diagnostic and build tech for affecting the brain. I divide various types of interventions into two large groups, namely:

  1. Technology-driven, when different types of stimulation are applied to the brain by a device. Nerves and the brain itself may be stimulated by electrical impulses, magnetic waves, low temperatures and even light. These and other stimuli affect various parameters of the brain, for example, blood flow, release of neurotransmitters, etc.;
  2. Technology-enabled, where a patient/user tries to manage his/her state by changing behaviour, meditating or applying other practices that do not involve stimulation by a device. These interventions may be enabled by neurofeedback, a type of biofeedback that ‘…uses real-time displays of brain activity to teach self-regulation of brain function’.

II. 1. Technology-driven interventions

Tech by NeuroSigma, MicroTransponder, and Aleva Neurotherapeutics

Affecting blood flow, temperature

Affecting release of some chemicals, e.g. hormones, neuromodulators, neurotransmitters

Other types of stimulation

II.2. Technology-enabled interventions: biofeedback and other techniques

Tech by Muse, MindMaze, and Headspace

Neurofeedback

Training self-awareness is another way how technologies can help to manage brain function

Machine learning for interventions

There are at least three ways how machine learning may be applied to hacking the brain, namely:

  1. To identify the right time for an intervention/simulation;
  2. To customise a stimulation itself for needs of an individual patient;
  3. To translate raw data into actionable insights that are required for neurofeedback.

Selecting the right time for stimulation is an important task. Sensor fusion algorithms may be applied to recognising indented movement of a patient and selecting the right moment for electrical stimulation. GTX Medical and NeuroSigma develop devices that send stimulating signals based on real-time feedback from body worn sensors and implanted sensors respectively. Seizure detection is an element of a pulse generator by AspireSR.

Parameters of an intervention themselves are not easy to define and programme.

Machine learning is vital for translating raw signals that are sent by the brain into meaningful insights that allow neurofeedback.

III. Research

Tech by Inscopix, Synchron, and Ctrl-labs

There are at least two wide research themes approached by neurotech startups. Some startups work on making brain more visible, while others try to connect it with the outside world.

  1. Higher resolution/better visibility. Inscopix and its microscope system allows studying the brain of a mouse at the cell level, constantly while an animal lives its normal life. 3Scan uses ‘…computer vision to extract spatial data from tissue samples. The results are detailed 3D representations of anatomical structures’;
  2. Brain interfaces. Stentrode by Synchron is implanted inside the brain in the motor cortex. It captures and sends signal to a wireless chest-implanted antenna that forwards it to an external receiver. The concept of ‘neural dust’ was proposed by Neuralink. The interface ‘… would consist of thousands of microscopic independent sensor nodes, and one ‘sub-cranial interrogator’ that connects and powers them’. Kernel explores ways of implanting microchips into human heads. Ctrl-labs develops a wearable device thatworks based on differential electromyography, i.e. measuring changes in electrical potential caused by impulses traveling from the brain to muscles.

Conclusion

Chart 2. Search trends for ‘mindfulness’ and ‘meditation’ by Google, and US EEG market size, by Statista.

After having reviewed these startups, I got amazed by several things:

  1. We have an astonishing chemical factory within our body, and being able to control it may help to fight various diseases with lesser reliance on drugs. Exploring different types of brain stimulation and brain research techniques brings us closer to the control deck of this factory;
  2. Growing interest to mindfulness and meditation (see chart 2) may increase the adoption of wearable EEG sensors and other devices for neurofeedback. Headspace, one of the most popular meditation apps, has more than 16M downloads, and even a share of its users may help to grow a small portable EEG market ($50M in the US in 2017, chart 2);
  3. Data generated from growing EEG adoption, coupled with data from human-mobile phone interaction, opens up new opportunities for diagnosis based on digital biomarkers;
  4. There is a risk that despite increasing interest to neurofeedback and mindfulness, some technologies will be pushing us to a rather passive role in the process of managing our mind, e.g. stimulation instead of meditation;
  5. I would expect that neurotech will have a massive effect on economy/business and business models. Imagine the demand for neurologists if brain implants become mainstream and surgeries to implant them could become routine? In 2004, European countries had 4.84 neurologists per 100K population. To compare — in 2007, OECD countries had 61 dentists per 100K on average. These figures are a bit outdated, but I believe they demonstrate the challenge I am talking about. Then imagine a situation when a doctor would ask to remotely tap into patient’s memories for a certain day and explore 24 hours’ worth of video, data on brain activity, etc. Would the infrastructure of mobile networks withstand that? These are just some obvious operational challenges, that do not even take into account some other effects such as influence on population healthcare, countries’ competitiveness, philosophical/ethical issues, etc.
  6. Currently we are at the very early stages of brain tech, just unlocking its value to healthcare, wellness and sports. However, horizontal platforms like NeuroSky and Ctrl-labs may help to bring brain tech to other markets, e.g. education, gaming/entertainment.

If you find this article encouraging, and, if you want to launch/join a neuro tech startup I would strongly advise you to team up/consult with someone with neuroscience or an adjacent background. What I see from my brief dive into the field is that computer science/data science/engineering expertise alone rarely lead to success.

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Many thanks to Viktoria Korzhova and Maria Kolesnikova for reviewing early drafts of this post.

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Data collection and sources

* This review covers privately owned companies that raised $10M or more, are engaged in neuroscience research and develop software/hardware products for healthcare professionals, researchers and consumers. Startups for CT/MRI are not included, as it is a theme on its own. Also, the review does not include analysis of pharma companies.

Data is taken from Pitchbook and CrunchBase. If these data bases provide contradictory data, Pitchbook’s data is used.

  1. https://www.crunchbase.com/organization/mindmaze

  2. Pitchbook

  3. https://www.crunchbase.com/organization/biodirection

  4. https://www.crunchbase.com/organization/interaxon

  5. https://www.crunchbase.com/organization/elminda

  6. https://www.crunchbase.com/organization/rythm

  7. https://www.crunchbase.com/organization/ceribell#section-overview

  8. https://www.crunchbase.com/organization/brainscope-company

  9. https://www.crunchbase.com/organization/brainco

  10. https://www.crunchbase.com/organization/nativis

  11. https://www.crunchbase.com/organization/neuropace

  12. https://www.crunchbase.com/organization/microtransponder

  13. https://www.crunchbase.com/organization/brainsgate

  14. https://www.crunchbase.com/organization/aleva-neurotherapeutics

  15. https://www.crunchbase.com/organization/mindstrong-health

  16. https://www.crunchbase.com/organization/thync

  17. https://www.crunchbase.com/organization/neurosigma

  18. https://www.crunchbase.com/organization/halo-neuroscience

  19. https://www.crunchbase.com/organization/humancharger

  20. https://www.crunchbase.com/organization/neosync

  21. https://www.crunchbase.com/organization/lumosity

  22. https://www.crunchbase.com/organization/headspace

  23. https://www.crunchbase.com/organization/happify

  24. https://www.crunchbase.com/organization/calm-com

  25. https://www.crunchbase.com/organization/neural-analytics

26https://www.crunchbase.com/organization/iota-biosciences

  1. https://www.crunchbase.com/organization/cerebrotech-medical-systems

  2. https://www.crunchbase.com/organization/synchron-inc

  3. https://www.crunchbase.com/organization/neuralink

  4. https://www.crunchbase.com/organization/luciole-medical

  5. https://www.crunchbase.com/organization/kernel-co

  6. https://www.crunchbase.com/organization/jan-medical

  7. https://www.crunchbase.com/organization/inscopix

  8. https://www.crunchbase.com/organization/functional-neuromodulation

  9. https://www.crunchbase.com/organization/ctrl-labs

  10. https://www.crunchbase.com/organization/3scan