An AI Agent for cell-type specific brain computer interfaces https://www.biorxiv.org/content/10.1101/2025.09.11.675660v1

An in-depth perspective piece discussing the transformative impact of AI coding tools in neuroscience research, featuring my work on SpikeAgent and AI interfaces for neural data analysis. @zuwan-lin.bsky.social
www.thetransmitter.org/craft-and-ca...

Great work! I realized there was a Zenodo link but I can't find it. How can I locate it?

We are very excited to share a preprint for our BehaveAgent, the first fully autonomous AI agent for universal behavior analysis. BehaveAgent is the result of rewarding work with ‪Zuwan Lin and the amazing team in JiaLiu's lab at @harvard.edu . 1/6

www.biorxiv.org/content/10.1...

Nature Reviews Neuroscience

Neural manifolds: more than the sum of their neurons

www.nature.com/articles/s41...

I'm not entirely sure I understand what you mean - but essentially, in the paper we found that by making it a dual-classification problem (+ the clustering with high-confidence samples) we could refine the classifications of MA states (which, can be challenging to distinguish with the other states)

Check out our fully-open source code below!
github.com/arnaumarin/L...

A deep learning self-supervised hybrid CNNautoencoder model is used to detect brain states and transitions, like wakefulness, slow oscillations and microarousals, during the emergence from anesthesia in cortical local field potentials
doi.org/10.1038/s420...

rdcu.be/ehyfl
Finally we see our work published! w/ Arnau Manasanch, @ldallap.bsky.social and Mavi Sanchez-Vives!

Llobet, et al.: Riemannian Geometry for the classification of brain states with intracortical brain-computer interfaces https://arxiv.org/abs/2504.05534 https://arxiv.org/pdf/2504.05534 https://arxiv.org/html/2504.05534

Agents meet neuroscience.

www.biorxiv.org/content/10.1...

github.com/LiuLab-Bioel...
!!!!

Check out our last paper on completely automatizing spike sorting using AI agents!
Not only makes the whole process human-free, but also provides an additional layer of information and interpretation that is completely unachievable by any other methods..

Link to the GitHub below!!!

This paper looks interesting - it argues that you don’t need adaptive systems like Adam to get good gradient-based training, instead you can just set a learning rate for different groups of units based on initialization:

arxiv.org/abs/2412.11768

#MLSky #NeuroAI

also here!!!
Beniaguev, D., Segev, I., & London, M. (2021). Single cortical neurons as deep artificial neural networks. Neuron, 109(17), 2727-2739.

Best quote from the trailer " I admit that I literally really understand nothing of this"

not necessarily the 'universal computation' but at least its a common language across subjects in neuro. I mean, we can't be sure we record the single-cell resolution same neurons from our very limited (and very downsampled) number of neurons.

𝗪𝗵𝗮𝘁 𝗶𝗻 𝘁𝗵𝗲 𝗯𝗿𝗮𝗶𝗻 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝘀 𝘂𝗻𝗶𝘃𝗲𝗿𝘀𝗮𝗹 𝗰𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻?
Maybe not neurons, perhaps RNA??
Great episode of Brain Inspired with Hessam Akhlaghpour.
Do dynamical systems and/or RNNs implement universal computation? This discussion alone would be worth having.
#neuroscience
braininspired.co/podcast/199/

Alright #neuroAI 😉 crew and those in #AI #ML perhaps interested in brain-inspired models and what’s next (not just foundation models please!). Here is my vision/roadmap of the next steps. A reflection & projection wrapped into a Perspective. Feedback very much welcomed. 🧠🧪👩‍🔬

arxiv.org/abs/2411.15234

Juan! Love the list so far. I’d love to join if there’s room still :)

I *just* made a neurotech industry starter pack and added you to it.

Looks like it’s all organic so far due to the cool biohybrid work you just dropped!

go.bsky.app/N2LreWi

i was wondering the same