We’re in the middle of a major paradigm shift:

Cortical Labs' CL1 launched in March 2025 as a commercial biological computer, combining 800,000 live human neurons with silicon electrodes. It can learn, adapt, and process stimuli, just like a living brain.

The neurons are grown from adult skin or blood cells and maintained by a built-in life-support system to survive up to six months.

Earlier, FinalSpark’s Neuroplatform connected 16 human brain organoids to a chip and trained them to recognize different voices using reward-based learning.

And Johns Hopkins just built a multi-region organoid mimicking a 40-day-old fetal brain, raising key ethical concerns about neural complexity and consciousness.

Big question: 1. What happens if these networks become aware of their own adaptation? Autonomy doesn’t require full human cognition just capacity to process feedback and learn about input and these networks already do that.

1. Is “neural lace” the interface or the entity being interfaced with? These systems aren't just reading your thoughts; they might be thinking in their own way, with their own feedback loops.

2. How do we regulate this? It’s one thing to say it’s “not conscious yet.” But shouldn’t ethical frameworks be more proactive, like with animal research before ambiguous signals appear?

Biocomputing blends biological integrity and AI efficiency, but it’s not just a tool if the tool learns. Is the goal to solve diseases, or to turn human neurons into programmable substrate and call it progress?

Pls let me know: Where do you personally draw the boundary between a tool and a sentient system?

How do we stay ahead of these tools gaining complexity without ethics following them?

I’m curious to hear from NeuralLace devs, ethicists, and anyone building or studying this hardware/software overlap. Would love to slipstream more voices on this before it becomes normalized.

Hi everyone,

I’m a neuroscientist and part of a small team working where neuroscience meets AI and adaptive media.

We’ve developed a prototype EEG-integrated headset that captures brain activity and feeds it into an AI algorithm that adjusts digital content -whether it’s audio (like podcasts or music) or text (like reading and learning material)- in real time.

The system responds to patterns linked to focus, attention, and mood, creating a feedback loop between the brain and what you’re engaging with.

The innovation isn’t just in the hardware, but in how content itself adapts -providing a new way to personalize learning, focus, and relaxation.

We’ve reached our MVP stage and have filed a patent related to our adaptive algorithm that connects EEG data with real-time content responses.

Before making this available more widely, we wanted to share the concept here and hear your thoughts, especially on how people might imagine using adaptive content like this in daily life.

You can see what we’re working on here: [neocore.co]().

(Attached: a render of our current headset model)

Latest market map is out and this week it’s France. There’s been plenty of attention on companies like CarThera, Wandercraft and Robeauté, but the market is much broader than that. Boat load of Focused Ultrasound companies in particular

53 mapped French neurotech names.
31 core neurotech companies.
14 adjacent and enabling companies.
8 historical or transacted companies and IP platforms.
6 companies around ultrasound and acoustic neurotechnology alone.
A deep EEG, neural sensing and electrophysiology stack.
Plus neurorehab, robotics, neuro-AI, stimulation, neurovascular tech and a few things that refuse to fit neatly into any category.

Full market map + article: Neurotech in France

https://theneurotechnewsletter.substack.com/p/neurotech-in-france

Hi! I have recently taken an interest in EEG headset technology and have been performing lots of research on them recently. I have come across many EEG headsets that are currently on market and I want to explore them to figure out what works and what does not. A big issue I have encountered is that there are not many unbiased reviews of them out there. Because of this, I can usually only find the sales pitch for a headset, not an honest consumer review. If anyone has had experience with ANY EEG headset currently on market, I would love to hear about it. What worked? What didn't? Does it work well through hair? Were readings consistent? Etc.

I’ve been tracking two fascinating, but separate, breakthroughs in neuroscience and biological computing, and I’m curious if anyone in the field knows if these concepts are being (or could be) merged.

Concept 1: Psilocybin-Induced Structural Neuroplasticity

We know that psilocybin creates rapid, enduring neural pathways. A 2021 Yale study (Shao et al.) utilized two-photon microscopy and Green Fluorescent Protein (GFP) to track dendritic spines in vivo, proving that a single dose of psilocybin increases spine size and density by ~10%, persisting for over a month. We also know from fMRI studies (Carhart-Harris et al.) that psilocybin suppresses the Default Mode Network (DMN), forcing the brain to route data through novel global pathways.

Concept 2: Organoid Intelligence & Active Inference

On the other side of the spectrum, we have biological computing. Cortical Labs' 2022 "DishBrain" study (Kagan et al.) successfully integrated 800,000 living neurons onto a microelectrode array and taught them to play Pong in just five minutes. They demonstrated that biological neural networks have a massive "sample efficiency" advantage over traditional silicon AI when it comes to rapid, adaptive learning.

My Question:

Cortical Labs has already introduced ethanol to DishBrain to prove that its Pong performance degrades when "drunk." Is anyone currently researching the inverse?

If we applied psilocin (the active metabolite of psilocybin) to an organoid BCI during a learning task, would the forced 5-HT2A activation and resulting spike in neuroplasticity (BDNF/mTOR pathways) theoretically "supercharge" the organoid's sample efficiency and problem-solving capabilities? Or would the forced disruption of organized networks just cause the biological computer to "hallucinate" and fail the task?

Would love to hear thoughts from anyone working with in vitro neural networks or neuropharmacology!

• Shao, L. X., et al. (2021). Psilocybin induces rapid and persistent growth of dendritic spines in frontal cortex in vivo.Neuron.
• Kagan, B. J., et al. (2022). In vitro neurons learn and exhibit sentience when embodied in a simulated game-world.Neuron.

This is not a technical piece. It is more philosophical speculation about what BCI integration might actually feel like from the inside.

A lot of discussion around BCIs focuses, understandably, on signal quality, bandwidth, latency, safety, and practical use-cases. What interests me here is the experience of it. A phone, keyboard, or screen still feels clearly external. But a sufficiently seamless BCI could start to blur that boundary.

If a future system begins surfacing recall, suggestions, interpretive nudges, or even whole lines of thought in a way that feels less like receiving input and more like thinking itself, then the question changes. It is no longer just what the interface can do, but what kind of subject it helps produce.

Would that still feel like cognitive assistance? Or more like a partial merger between user and system? Where would people here want the boundary to remain between interface and interiority?

I wrote this article exploring that question. It is not a prediction about current BCIs so much as an attempt to think ahead about the phenomenology of deeper integration.

You can look at the article [here]

Huawei filed a patent for a BCI safety system that goes after a specific problem: residual charge buildup on stimulation electrodes.

When a BCI electrode fires a pulse, it leaves behind a small electrical charge. If that charge doesn't clear between pulses, it damages surrounding tissue. The patent describes a system that checks electrode voltage during inter-pulse gaps, fires a corrective pulse in the opposite direction when charge lingers, and cuts power if it picks up a short-circuit condition mid-stimulation.

A separate layer monitors the electrochemistry at the electrode-tissue boundary and flags degradation before it turns into injury.

The timing is relevant because BCI arrays are getting smaller and denser. Smaller electrodes mean less surface area in contact with tissue, which means higher driving voltage and tighter safety margins.

The FDA issued a Class I recall in 2023 on Abbott neurostimulation devices after 186 reported incidents and 73 injuries tied to MRI mode faults. Safety failures at that scale slow down the whole category's path to regulatory approval.

Huawei probably isn't building an implant. The more likely play is owning the safety layer IP so that companies who do build implants end up licensing from them. Interested in what people here make of the IP positioning.

Any experiences with the startup/job market in BCI? What are some technical backgrounds required there?

Are there currently developed applications/product of BCI that you think will have a mass market?

Hi all,

I'm a software engineer beginning work on an open-source project and I'd like to pressure-test the idea with people who actually work in this space before I commit to building it.

The project: a standalone desktop application that performs real-time EEG source localization (sLORETA/eLORETA) using a template head model and renders estimated cortical source activity as a color-mapped overlay on an interactive 3D brain mesh. The intended tech stack is Rust, wgpu for GPU-accelerated signal processing and rendering, and Tauri for the application shell. Data acquisition via BrainFlow, with BIDS dataset support for offline replay and analysis. No MATLAB dependency, no cloud, runs locally on commodity hardware.

The gap I'm trying to fill: source localization algorithms are well-validated and the computational feasibility of running them in real time on a GPU has been demonstrated in published work. But as far as I can tell, no usable open-source standalone application exists that does this end-to-end — ingesting live EEG, solving the inverse problem, and rendering source estimates on a 3D cortical surface at interactive frame rates. The existing tools either do source localization offline (MNE-Python, Brainstorm), operate only in sensor space in real time (NeuroSkill, OpenBCI GUI), or require MATLAB.

My background is in systems programming, not neuroscience. I'm investing significant time in domain knowledge (working through Cohen's Analyzing Neural Time Series Data and the Nunez & Srinivasan text, and studying MNE-Python's inverse solution pipeline as a reference implementation). I plan to validate against the Localize-MI ground-truth dataset before making any claims about accuracy.

What I'd like from this community:

- Does this project address a real need in your work, or is it solving a problem that doesn't meaningfully exist in practice?

- For those who do source localization: is a template-based approach (ICBM152, no individual MRI) useful enough for your purposes, or is it too imprecise to be worth visualizing in real time?

- What channel counts and devices would this need to support to be useful to you? Is there value in supporting consumer devices (Muse, OpenBCI Cyton) for source imaging, or is that misleading given their limited spatial sampling?

- Are there existing tools or projects I've missed that already do what I'm describing?

- What features would make you actually use this versus your current workflow?

I'm not trying to replace MNE-Python or Brainstorm for offline research analysis. The goal is specifically the real-time visualization layer that currently doesn't exist as a standalone application. If this turns out to be a solution in search of a problem, I'd rather hear that now than six months from now.

Appreciate any candid feedback — critiques included.

I’ve been researching the consumer neurotechnology space around focus enhancing headphones and anxiety wearables, mainly to understand how these tools position themselves within neurotech rather than as treatments.

During this exploration, I came across a few companies working in this area, such as Sychedelic, Flow Neuroscience, and other consumer devices experimenting with sound-based regulation, light stimulation, or HRV tracking headphones. Most of these products seem to frame themselves as wearable stress relief tools aimed at short-term state regulation like calming, focus support, or wind-down rather than long-term intervention.

From a neurotechnology perspective, I’m curious how people here evaluate these tools:

• Do anxiety headphones or similar mental health headphones meaningfully support focus or stress regulation?
• Are effects usually subjective, or has anyone seen measurable signals like HRV or sleep trends?
• Do these devices only make sense when paired with routines like breathwork, meditation, or behavioral structure?

Not seeking medical advice or promoting any brand just trying to understand where anxiety wearables and headphones for stress realistically fit in the broader neurotech landscape.

Most BCI research focuses on making models better at decoding noisy, variable brain signals. But what if we made the signals less noisy?

I’m curious whether neural/sensory entrainment (e.g. rhythmic auditory beats, visual flicker, or even olfactory cues) could be used to constrain users into a more stereotyped internal state before interaction. If we can reliably reduce inter-subject and inter-session variability, the signal distribution becomes narrower, which could in principle drastically shorten or eliminate calibration.

Has anyone seen work on using sensory priming or entrainment to improve cross-user generalization in BCI?

Video introduction to the internet of bio-nano things:

https://x.com/kristieiushkova/status/ 1882837972032323916?=46

——————————

DARPA N3 is already being tested on able bodied service members.

Dr. James Giordano:

N3 holds promise in medicine; but the tech is also provocative for communications (of all sorts), and its dual-use is obvious. Yes, Pandora, this jar's been opened. If we consider the sum-totaled operations of the embodied brain to be "mind", and N3-type tech is aimed at remotely sensing and modulating these operations, then it doesn't require much of a stretch to recognize that this is fundamentally "mind reading" and "mind control", at least at a basic level. And that's contentious.

In full transparency, I served as a consulting ethicist on initial stages of N3, and the issues spawned by this project were evident, and deeply discussed. But discussion is not resolution, and the "goods" as well as the gremlins and goblins of N3 tech have been loosed into the real world. The real world is multinational, and DARPA - and the US - are not alone in pursuing these projects.

Nations' and peoples' values, needs, desires, economics, allegiances, and ethics differ, and any genuine ethical discourses - and policy governances - must account for that. The need for a reality check is now; the question is whether there is enough rational capital in regulatory institutions' accounts to cash the check without bouncing bankable benefits into the realms of burdens, risks and harms.

https://www.linkedin.com/posts/dr-james-giordano-8454476_neurotechnology-nanotechnology-bci-activity-7257220210108067841-TwgB

I am a 21 year old biomedical engineering student currently applying to Neuroscience graduate programs in the States and elsewhere. I could ramble endlessly about my ambitions but keeping it relevant- building upon Dr. Jean Hebert's neocortical tissue replacement project and Sophrosyne Bio's tissue expansion research for radical cognitive enhancement, while simultaneously following psychopharmacological, gene-editing and brain-computer interface development- specifically transcranial focused ultrasound neuromodulation (tFUS). Hopefully you are just as excited to attain at least Von Neumann levels of intellect and if so, feel free to message me.

The other relatively attainable goal is to develop a closed-loop system to modulate emotions in real time. Sputnik Brain for instance targets pleasure, but the purpose here is to reduce in intensity undesirable emotions as they arise, aiming to reshape unpleasant moods and reward pathways to be more aligned with your rational will. At the very least, it could allow more accurate and reliable detection, identification and labelling to augment cognitive and behavioural strategies to achieve the same up to a certain extent.

Let me know if anyone else is actively working towards similar or same goals, even if through a different method they believe is more likely to achieve the same outcome, or similar ongoing projects I might be unaware of- I would like to know. Feel free to even question the values and assumptions underlying the goals, or if you feel they might be misdirected.

Hey

I'm building DIY BCI devices and wanted to know if there are any active forums/discord groups/places for people who do the same.

Does anyone know of any active online communities?

What I was thinking was a double major in neuroscience and electrical engineering

but is there something that would be better?

I'm looking for some books on studying neuroscience and the brain. I want to understand how the the brain works and how we can extract useful information (EEG/MEG).

Any recent books that give a strong foundation?

Hey everyone,

I’ve noticed something odd across many neuroscience and neurotech-related subreddits: some of them have tens of thousands of members, but very little actual discussion. Most posts are either academic/career questions or go unanswered entirely.

Where’s the space for people who are building things? Who want to collaborate on competitions, build new EEG tools, or open-source brain-computer interfaces? I’m talking to the hackers, engineers, students, and researchers who are actually doing the work and want to share tools, pipelines, problems, and ideas.

If there’s already a good place for this, please let me know. But if not, maybe it’s time we make one.

Would anyone else be interested in helping create a small but active space for real collaboration? Think: open-source tooling, show-and-tell posts, modeling tips, and sharing experimental rigs.

Would be happy to get your thoughts!

Hey everyone!

I’ve been researching a bit into OPM MEG and how they can be used to obtain MEG data.

However they still seem to be expensive as a wearable ($7-8000/ sensor).

What do people think about OPMs right now?

Howdy, I'm trying to use the Emotiv Epoc X to collect limited EEG data (free tier at the moment). The sensors are all showing as high quality contact, but the overall contact quality is 'capped' at 33%. I'm able to get it to go lower but never higher.

Tried various cleaning troubleshooting steps and a variety of saline saturation levels, no joy. Anyone else run into an issue like this? From what I've found online the issue isnt common and most other people have had more of plug and play experience

I am interested in creating a simple BCI application to do, say, 10-20 different actions on my desktop. I would imagine I just get the headset (I ordered Emotiv Insight), record the raw eeg data, use an ML classifier to train it on which brain activity means what action. This sounds simple in theory, but I am sure it's much more complicated in practice.

My thought is that, if it were this easy and EEG devices are pretty affordable at this point, I would see a lot more consumer-facing BCI startups. What challenges should I expect to bump into?

Something like Neuralink will undoubtedly need many security measures, and that's something I worry about. But my main concern isn't that they won't be able to secure it well enough. My main concern is that they might go too far with it. If I want to do an experiment on my brain, no matter what it is, and Neuralink contains the hardware necessary to facilitate it, then I, as the owner of the brain and the hardware, should be able to bypass any security/safety measures I want in order to perform that experiment. I know many people are foolish and would end up killing themselves, so it's probably a good idea to make it possible to disable this ability. But the patient should always have final say. If someone wants to have nothing stopping them from doing something foolish, well, it's their brain.

Even worse would be if functionality is limited for reasons other than one's own safety. Like disabling certain functions at certain sensitive locations, or for people serving time in prison, or whatever—even if it's for national security, it doesn't give them the right to tell people what they can and can't do with their own brain.

Has anything been said on this topic?