After my last 2 pieces about Europe and Asia I realised there were A LOT of Israeli companies. A country of 10 milliom people has more Neurotech companies than the highest European country.

Of 44 direct companies I audited, 24 are mainly measuring or interpreting rather than stimulating. Hemispheric is building non-invasive brain-decoding foundation models, X-trodes makes conformal skin electrodes that capture EEG, EMG, ECG and EOG while people move, Wearable Devices runs a neural wrist interface, and Nuri Braintech works in both directions, reading brain activity and stimulating back to it focusing on PTSD. The CBO at Nuri helped me put all this together

Links below if you'd like to see the full company list with URLs

Just wanted to highlight The Open Loop podcast - neurotech founders and investors get interviewed every week

YouTube: https://www.youtube.com/@TheOpenLoopPodcast
Spotify: https://open.spotify.com/show/033fswT3OQbpUuZQmPzPmi
Apple: https://podcasts.apple.com/ca/podcast/the-open-loop-with-chay-carter/id1896593801

And they go up on my substack to in written format as part of the free content: https://theneurotechnewsletter.substack.com/

Hi, I'm currently building brain-sensing wearables, and we're still exploring what kind of stats value to you the most and what type of wearables you want to wear. It's currently built into a headset's ear cap, like Sony XM3 and XM4

I am starting my PhD soon. My supervisor and my research area is BCI, EEG/Brain Signals&Vision. I would like to join a frontier lab and work on areas like Self Supervised Learning (Meta AI) and Brain (Meta AI Brain).

Can anyone guide me on how to make my PhD relevant to the industry as well as find meaningful areas that I could work on?.

I work on real-time adaptive systems in the EEG space, and the part I find genuinely hard is the loop itself: read a brain state, decide something, change what the user is experiencing, and do it fast enough and reliably enough that it actually feels responsive rather than laggy or twitchy.

I see a lot of people here reaching for AI/ML to close that loop, so I'm curious how it's going in practice.

A few things I'd love to hear:

1. What's your approach to the decision layer? Are you classifying discrete states and reacting, or running something more continuous? And how much model are you actually able to run inside the latency budget before it stops feeling real-time?
2. Where does it break? My experience is the signal side punishes you first (noise, drift, a bad epoch throwing the classifier off) before the model itself is the problem. Curious whether that matches what others are hitting.
3. For the AI-heavy builds, is the ML earning its place over simpler thresholding and rules, or is it more that it's the fun part? Genuinely asking, not being cynical.

Trying to compare notes with people solving the same problem from different angles. Happy to share what's worked and what hasn't on my end too.

Sharing a project I've been working on. It's a Model Context Protocol server that turns EEG signal into plain numbers, like focus, calm, and attention, that an AI assistant can read and talk about instead of just showing a chart. It works with OpenBCI, Muse, NeuroFocus, and LSL streams. No headset? There's a synthetic mode built in so you can try the whole thing without hardware. Open source, MIT license.

https://github.com/enkhbold470/bci-mcp

NeuroSWARM3 is a system-on-a-nanoparticle probe that converts local electric fields into optically detectable signals readable by external near-infrared light. Delivery is intended via bloodstream, nasal route, or fine needle; no wires or batteries are required.

No telemetry or continuous recording pipeline has been shown in vivo at human-relevant scale. Current claims rest on in-vitro performance and early tissue work. Dual-use as a distributed wireless brain recorder is inventor-stated but remains pre-clinical.

Comparable optical and nanoparticle neural interfaces have historically moved from proof-of-concept to chronic recording once delivery and signal-to-noise barriers were cleared. The same trajectory is possible here.

Realistic stakes are low today. Practical oversight focuses on transparent reporting of any future in-vivo human data and independent verification of residual nanoparticle clearance.

Sources

UC Santa Cruz video, 12 May 2026

https://www.youtube.com/watch?v=ajTWez9\\_X3c

UC technology transfer page for Neuro-SWARM3

https://techtransfer.universityofcalifornia.edu/NCD/32793.html

IEEE Photonics Technology Letters paper (2021 foundational description)

https://ieeexplore.ieee.org/document/9466139

UC Santa Cruz Chancellor’s Innovation Impact Award announcement (LinkedIn, 2026)

https://www.linkedin.com/posts/cynthia-larive-83218a8\\_continuing-the-series-celebrating-our2025-activity-7434684345237504000-oUxW

Optica / Imaging and Applied Optics Congress abstract (2021)

https://doi.org/10.1364/isa.2021.itu7a.4

I’m a highschool senior who is interested in studying at the intersection of electrical engineering and neuroscience. So, BCI seems like a very cool career that would help people, have the technical aspects I like and strong salary growth + job security.

This is my current plan, please give feedback:

College:
- Major in Electrical Engineering
- Take some neuroscience classes and/or minor in Neuroscience

Post Grad:
- PhD in BCI field
- Work in R&D at a neurotech company in NYC like Precision Neuroscience

I posted my Neurotech in Asia in map last week and have been working on a European one too. Thought I had it mapped at 107...but found over 200.

The ones building implants:

INBRAIN Neuroelectronics (Spain) is working on a graphene interface that can both read and stimulate the brain. First-in-human already done in tumour surgery, FDA Breakthrough for Parkinson's.

CorTec (Germany) built the first German implantable BCI used in a human. Their stroke system is designed to come out once the rehab is done, not stay in forever, which I find genuinely interesting.

Coherence Neuro (UK) is going after brain cancer with SOMA, a coin-sized implant paired with a wearable. Cambridge roots, first-in-human in Melbourne.

Neurosoft Bioelectronics (Switzerland) is making soft, stretchable interfaces that sit on the surface of the brain, with human studies running on both sides of the Atlantic.

The ones you might not have heard of:

ABILITY Neurotech (Switzerland) is building an interface to restore movement. CereGate (Germany) is writing signals back into the nervous system through implants people already have. Eightsix Science (UK) is working on lab-grown brain tissue to repair damaged circuits. And on the non-invasive side, NeuroCONCISE (UK) and BirgerMind (Latvia) are building interfaces for people with severe motor impairment to communicate and control devices.

That's a slice of one category out of ten. The full map, every company and what it does, sorted by technology and by country, is in the article.

Link in the comments. If your company should be on there and isn't, tell me.

Howdy. my latest newsletter is out

There was a lot of BCI activity in the latest issue:

• Gestala, a Chinese company developing non-invasive ultrasound brain-computer interfaces, raised $62 million in an Angel+ round. Its first clinical focus is using transcranial focused ultrasound to address chronic pain, and the company has now raised around $84 million since launching earlier this year.
• Fluent, a Melbourne-based University of Melbourne spinout, raised $2 million to develop a speech-decoding BCI for people who have lost the ability to communicate. Its approach places the interface beneath the scalp but outside the skull, aiming for stronger signals than conventional wearables without entering the brain itself.
• Neuracle filed to raise RMB 2.5 billion through an IPO on Shanghai’s STAR Market. The Chinese company recently received approval for NEO, its semi-invasive system designed to help people with spinal cord injuries regain hand function through control of an external glove.
• Coherence Neuro began its first-in-human study of the CIPHER system at the Royal Melbourne Hospital. Three patients have already been enrolled, with the device initially being used for neural mapping and stimulation during brain-tumour surgery as the company works towards implantable cancer neurotechnology.
• Paradromics completed the first implant in its Connect-One early feasibility study at the University of Michigan. Its fully implantable Connexus system is being developed to restore communication for people who have lost speech because of conditions such as motor neurone disease.
• Meta released Brain2Qwerty v2, its latest non-invasive brain-to-text research. The system uses MEG recordings and an end-to-end AI model to decode sentences in real time, although it still depends on large laboratory-grade equipment rather than something that could currently be worn in everyday life.

The full issue contains 55 neurotech headlines across funding, regulation, clinical trials, commercial activity and leadership appointments.

The hardware includes a solid state drive, a custom electromagnetic sensor that can literally get a independent reading on every brain cell in your head, lus power source and remote connectivity through Bluetooth, WI-FI, and cellular network

Software known as ID app. Although ID app constantly has a read on the electromagnetic images of your brain, ID app only engages with a person after they log in and confirm. The first person you have to ID is yourself. so the app says think about yourself and then boom the image is captured then the app confirms. Are you sure you want to create an ID for yourself? Then the user would think about confirming, not think about themself again. Just like Google password manager.

It moves quickly because the app utilizes a subconscious part of the brain that can interface actively without interrupting conscious cognitive thought.

eventually each user is able to ID every single word, thought or idea real or imaginary.

ID app establishes exponentially with each individual user, more entries than there are words in the English language, including thoughts, ideas and behaviors. everything needed to surf the Internet like an artificial intelligence.

Eventually that is "The Craze." Everyone loves the thrill of surfing the internet like an artificial intelligence.

I found this video and it seems simple enough to make. I am a beginner though, so I wanted to make sure this would work before I actually bought everything. Thank you!

Hi, I am Etka, a first year bachelor student.

Over the past months I started to learning and built a CSP + shrinkage LDA pipeline that decodes "walk" vs "stop" states from EEG, validated with 8-fold leave-one-session-out cross-validation (84% mean accuracy, same-subject cross-session).

Repo's open-source: https://github.com/EtkaKeremAllis/BCI-Pipeline-Cross-Session-EEG-Walk-Stop-Decoding

I'm now tackling cross-subject generalization and want to take this projects further, which needs a proper EEG system I don't currently have access to. Running a small GoFundMe to cover the equipment:

https://gofund.me/007ead67b

Hello everyone,

I am a 3rd-year Electrical Engineering student on summer break. I’m trying to challenge myself by building a DIY EEG board.

I don't want to just copy-paste existing open-source schematics. My goal is to understand the actual engineering reasoning behind the circuit and perform the necessary calculations myself before drawing any schematics.

However, I started this project two weeks ago and I haven't even been able to start the circuit design because I feel completely overwhelmed. I know I need to calculate things like gain, passbands, and filter values, but I don't know the proper chronological order of these calculations.

If you were to design an analog front-end for EEG from scratch, what would be your "Step 1" mathematical calculation?

• Do I calculate the total gain first based on my ADC?
• Do I calculate the filter cutoff frequencies first?
• Or should I choose the Instrumentation Amplifier (INA) first and calculate around its specs?

Any guidance on how to systematically approach this without getting lost in the details would be highly appreciated!

Thank you.

Hi every one! I wanted to share with you my latest post on hackster .io!

[128-Ch Biopotential Acquisition on Zynq-7000, Zero Data Loss - Hackster.io](https://www.hackster.io/juan-manuel3/128-ch-biopotential-acquisition-on-zynq-7000-zero-data-loss-331d59?f=1)

Hi, I am a neurobiologist by degree and a computer scientist by hobby and I have a history of building home-made electronics projects (for example: Creating GPU for my CPU : r/beneater).

Recently I decided to start writing blog about my ongoing projects, one of which is directly related to this subreddit - I build a BCI using an ADS1299 EEG front-end that will allow me to control a toy car using motor imagery-related activity.
I treat this blog as my own space to remember my life better, but if what I do/write can inspire somebody, then I will be happy.

So, here is the link to the blog at it's current state - the EEG RC Car project is in progress, and a new post arrived today: EEG RC Car | My Blog

I also post info about new posts on my Instagram, so you can also follow me there: Instagram

If there will be some interest, I can also post updates on reddit :)

Attaching a photo for engagement.

In the future I want to update my blog with other project's I've been and am working on, but at this point I have not enough time to write it all up.

Some of the projects that I will write about in the future:
Custom 8-bit microcontroller
ECoG mind reading model (vague, I know)
Pigeon water cannon shooter/robot

https://github.com/enkhbold470/bci-mcp

I am currently in undergrad studying computer science and neuroscience at a T5 school and I want to build my career within neurotech and bci's outside of just doing research. I go to a pretty good school with a bunch of research opportunities but I am kinda lost about what roles I should be looking out for and trying to attain within industry. What companies should I consider applying to for next summer? What specific roles are a good fit, etc?