arnau-m-l
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arnauya.bsky.social
arnau-m-l
@arnauya.bsky.social
Studying natural and artificial learning & intelligence using ai agents and brain machine interfaces at Harvard.

https://arnaumarin.github.io/
Pinned
New paper alert!

In here, we (@ldallap.bsky.social , @mavi_sanchez and co) tap the intrinsic geometry of data to classify brain states on Riemannian manifolds! A lightweight and more INTERPRETABLE alternative to conventional deep learning architectures! Paper: doi.org/10.1002/aisy...
Riemannian Geometry for the Classification of Brain States with Intracortical Brain Recordings
Geometric machine learning is applied to decode brain states from invasive intracortical neural recordings, extending Riemannian methods to the invasive regime where data is scarcer and less stationa...
doi.org
Riemannian Geometry for the Classification of Brain States with Intracortical Brain Recordings - Marin‐Llobet - Advanced Intelligent Systems - Wiley Online Library advanced.onlinelibrary.wiley.com/doi/full/10....
Riemannian Geometry for the Classification of Brain States with Intracortical Brain Recordings
Geometric machine learning is applied to decode brain states from invasive intracortical neural recordings, extending Riemannian methods to the invasive regime where data is scarcer and less stationa...
advanced.onlinelibrary.wiley.com
October 14, 2025 at 11:02 PM
New paper alert!

In here, we (@ldallap.bsky.social , @mavi_sanchez and co) tap the intrinsic geometry of data to classify brain states on Riemannian manifolds! A lightweight and more INTERPRETABLE alternative to conventional deep learning architectures! Paper: doi.org/10.1002/aisy...
Riemannian Geometry for the Classification of Brain States with Intracortical Brain Recordings
Geometric machine learning is applied to decode brain states from invasive intracortical neural recordings, extending Riemannian methods to the invasive regime where data is scarcer and less stationa...
doi.org
October 14, 2025 at 11:01 PM
Reposted by arnau-m-l
Now out in Advanced Intelligent Systems: Exploiting underlying data geometry, we classify brain states efficiently using Riemannian manifolds. A lightweight and interpretable alternative to DNNs. Spearheaded by
@arnauya.bsky.social!

Check it out: advanced.onlinelibrary.wiley.com/doi/10.1002/...
Riemannian Geometry for the Classification of Brain States with Intracortical Brain Recordings
Geometric machine learning is applied to decode brain states from invasive intracortical neural recordings, extending Riemannian methods to the invasive regime where data is scarcer and less stationa...
advanced.onlinelibrary.wiley.com
October 14, 2025 at 12:05 PM
Reposted by arnau-m-l
An AI Agent for cell-type specific brain computer interfaces https://www.biorxiv.org/content/10.1101/2025.09.11.675660v1
September 17, 2025 at 4:15 PM
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...
Should neuroscientists ‘vibe code’?
Researchers are developing software entirely through natural language conversations with advanced large language models. The trend is transforming how research gets done—but it also presents new…
www.thetransmitter.org
September 10, 2025 at 8:58 AM
Reposted by arnau-m-l
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...
An autonomous AI agent for universal behavior analysis
Behavior analysis across species represents a fundamental challenge in neuroscience, psychology, and ethology, typically requiring extensive expert knowledge and labor-intensive processes that limit r...
www.biorxiv.org
May 20, 2025 at 1:33 PM
Reposted by arnau-m-l
Nature Reviews Neuroscience

Neural manifolds: more than the sum of their neurons

www.nature.com/articles/s41...
Neural manifolds: more than the sum of their neurons - Nature Reviews Neuroscience
In this Journal Club, Juan Gallego discusses a 2014 article that provided a first causal hint that neural manifolds may not only be a convenient way to interpret neural population activity.
www.nature.com
April 26, 2025 at 12:46 PM
Reposted by arnau-m-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...
Neural models for detection and classification of brain states and transitions - Communications Biology
A deep learning self-supervised hybrid CNN-autoencoder model is used to detect brain states and transitions, like wakefulness, slow oscillations and microarousals, during the emergence from anesthesia...
doi.org
April 11, 2025 at 11:32 AM
rdcu.be/ehyfl
Finally we see our work published! w/ Arnau Manasanch, @ldallap.bsky.social and Mavi Sanchez-Vives!
Neural models for detection and classification of brain states and transitions
Communications Biology - A deep learning self-supervised hybrid CNN-autoencoder model is used to detect brain states and transitions, like wakefulness, slow oscillations and microarousals, during...
rdcu.be
April 13, 2025 at 12:53 PM
Reposted by arnau-m-l
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
April 9, 2025 at 6:15 AM
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!!!
February 13, 2025 at 5:16 AM
Reposted by arnau-m-l
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
No More Adam: Learning Rate Scaling at Initialization is All You Need
In this work, we question the necessity of adaptive gradient methods for training deep neural networks. SGD-SaI is a simple yet effective enhancement to stochastic gradient descent with momentum (SGDM...
arxiv.org
December 20, 2024 at 7:00 PM
Reposted by arnau-m-l
Best quote from the trailer " I admit that I literally really understand nothing of this"
December 16, 2024 at 7:10 PM
Reposted by arnau-m-l
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/
BI 199 Hessam Akhlaghpour: Natural Universal Computation | Brain Inspired
braininspired.co
November 27, 2024 at 6:27 PM
Reposted by arnau-m-l
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
Adaptive Intelligence: leveraging insights from adaptive behavior in animals to build flexible AI systems
Biological intelligence is inherently adaptive -- animals continually adjust their actions based on environmental feedback. However, creating adaptive artificial intelligence (AI) remains a major chal...
arxiv.org
November 26, 2024 at 9:21 AM
Reposted by arnau-m-l
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
November 24, 2024 at 4:45 PM