Neurotech monthly. June 2021

Progress in quantum tech & MEG, pipelines for EEG & fMRI, TMS startups raise capital, insights from a crowdfunding prospectus

The third issue of the astrocyte* newsletter is here. Among other things, it covers:

Neurotech reading list

  • MEG - scanning while moving, how quantum tech improves MEG, and MEG vs. fMRI;
  • tools - preprocessing/processing pipelines for EEG, fMRI;
  • improving EEG with data science - a plugin for NNs to handle missing EEG channels, a CNN for solving the EEG inverse problem in a distributed dipole model.

Startup/Corporate news

a) Investments: two TMS companies raised capital, big rounds for Synchron and Precision Neuroscience;

b) Other news: the CE Mark for a BCI software, FDA 510(k) Clearance for a minimally invasive cEEG system.

My interpretations/comments are in italic.

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I. Reading List

Tech Stack

Using a 90 channel (45-sensor) whole-head OP-MEG system and concurrent motion capture, we recorded auditory evoked fields while participants were… standing up and making large natural head movements continuously throughout the recording.

There are already MRI scanners with lower maximum field strengths that do not require a protected room or building. Although these scanners have limited resolution quality of resultant MRI images due to a lower signal-to-noise ratio, they have a market.

OP-MEG systems may move in a similar direction when systems that don’t require shielding will be created for some use cases where a lower resolution works just fine.

Quantum physics gives brain-sensing MEG scanners a boost - … the development of optically pumped magnetometers (OPMs) has been key. These are quantum enabled magnetic field sensors that offer similar sensitivity to SQUIDs but without the need for cryogenics. … OPMs can be mounted directly on the surface of a human head, increasing sensitivity by removing the thermally insulating gap and getting the sensor closer to the brain. This also allows the sensor array to move with the head, making the MEG measurement resilient to subject motion.

I’d advise neurotech entrepreneurs to carefully monitor adjacent fields and prepare to apply to neurotech what were achieved there.

On OP-MEG and speech tracking:

Brain Modelling as a Service: The Virtual Brain on EBRAINS. The Virtual Brain (TVB) is now available as open-source cloud ecosystem on EBRAINS, a shared digital research platform for brain science.

There’s always a debate about what to build first - applications or tools. It’s fantastic that projects like this offer tools to researchers/entrepreneurs (here) and allow them to focus on doing research/building applications.

Data Science

Google and Harvard map brain connections in unprecedented detail. The end result, which Google calls the H01 dataset, is one of the most comprehensive maps of the human brain ever compiled. It contains 50,000 cells and 130 million synapses, as well as smaller segments of the cells such axons, dendrites, myelin and cilia.

In the recent neurotech landscape, I highlighted that neurotech startups feel less pressure from tech giants than ‘traditional’ software companies that fearlessly compete with them. However, tech giants are building neuro datasets and at some point, may increase their activity in the market. Therefore, those who consider launching a neurotech startup should probably move faster.

In this article, we present SynthSR, a method to train a CNN that receives one or more [MRI] scans with spaced slices, acquired with different contrast, resolution and orientation, and produces an isotropic scan of canonical contrast (typically a 1 mm MP-RAGE).

In fMRI, researchers have many degrees of freedom in the way that they can process the data… Here we show, using three popular whole-brain dynamical models, that different choices during fMRI preprocessing can dramatically affect model fits and interpretations of findings.

EPOS: EEG Processing Open-Source Scripts. Since the replication crisis, standardization has become even more important in psychological science and neuroscience. As a result, many methods are being reconsidered, and researchers’ degrees of freedom in these methods are being discussed as a potential source of inconsistencies across studies. With the aim of addressing these subjectivity issues, we have been working on a tutorial-like EEG (pre-)processing pipeline to achieve an automated method…

Something built for research purposes may transform/be plugged into a developer tool that fuels neurotech adoption.

Positive for reproducibility, therefore for wider neurotech adoption.

Robust learning from corrupted EEG with dynamic spatial filtering. We propose dynamic spatial filtering (DSF), a multi-head attention module that can be plugged in before the first layer of a neural network to handle missing EEG channels by learning to focus on good channels and to ignore bad ones.

It’s an attempt to overcome the limited computing power of consumer-grade EEG devices that may boost adoption.

ConvDip: A Convolutional Neural Network for Better EEG Source Imaging. Artificial neural networks have been previously used successfully to find either one or two dipole sources. We present ConvDip, a novel convolutional neural network (CNN) architecture, that solves the EEG inverse problem in a distributed dipole model based on simulated EEG data.

Other Themes

A brain-computer interface that evokes tactile sensations improves robotic arm control. We supplemented vision with tactile percepts evoked using a bidirectional brain-computer interface that records neural activity from the motor cortex and generates tactile sensations through intracortical microstimulation of the somatosensory cortex.

I’m a big believer in bidirectional BCIs that allow personalisation for stimulation and other purposes. Personalisation is a powerful driver of consumer/enterprise tech and should be emphasised in neurotech too.

II. Startup/Corporate News


Precision Neuroscience Raises $12M to Develop Next Generation Brain-Computer Interface Technology (🇺🇸). A very minimalistic website tells us - ‘Our integrated platform – delivery, device, and data – will help deliver the next frontier of medicine’.

I’d highlight the ‘integrated platform’ part, and it seems that multiple startups aim to build ‘the Apple of neurotech’.

Synchron Secures $40M in Series B led by Khosla Ventures to Launch U.S. Clinical Trials of Minimally Invasive Brain Computer Interface (🇺🇸/🇦🇺).

Synchron is building a minimally invasive system, and therefore may have a wider adoption, probably by millions of people. Compare it to ‘traditional’ DBS systems that were implanted to 200K+ patients, according to some estimates.

Actipulse Neuroscience (🇺🇸) that develops a neuromodulation treatment for depression, launched a crowdfunding campaign. I’d encourage you to dive into their prospectus for some exciting details, for example:

  1. The company is profitable, raised only $140K from investors, but has already 210+ hospital-setting neuromodulation devices currently in use;
  2. Business model: 1) patient direct use with our at home device (post FDA approval); 2) shared-revenue for our hospital-setting device.

Greenbrook TMS Announces Completion of US$23.5 Million Private Placement(🇺🇸). The company runs outpatient mental health service centres and provides magnetic stimulation therapy.

It’s not a neurotech company per se, but learning about it could help neurotech entrepreneurs to gauge the scale of an opportunity. Greenbrook provided more than 510,000 TMS treatments to over 14,000 patients. According to Pitchbook, a database, Greenbrook’s revenues grew from $6.7M in 2016 to $43M in 2020.

Trials & Other Announcements

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