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Nima Dehghani

@neurovium.bsky.social

Computational neuroscience, Physics of Complex Systems, Bio-Inspired Intelligence, Foundations of Physical Computing https://neurovium.science/ https://compneuro.mit.edu/home

266 Posts1990 Follower1018 Folgt
Nima Dehghani@neurovium.bsky.social · last wk.

The paper might be hard to penetrate for some that are not familiar with the mathematics/physics machinery. But what this means for neuroscience (and why NeuroAI needs it)? See the companion that explains and unwraps it for computational/systems neuroscientists. 👇 neurovium.science/posts/pblog-...

When Does Matter Compute? Wave Memory, Closure, and the Architecture of Autonomous Physical Computation

Companion post to: Autonomous Physical Computation: A Categorical Closure Criterion for Physical and Neuromorphic Reservoirs. Nima Dehghani arXiv 2026. DOI: https://doi.org/10.48550/arXiv.2607.23902

neurovium.science

Nima Dehghani@neurovium.bsky.social · 2w ago

Week 4 of summer of papers! Here we go! 📣📷 📜 The central question: when does memory in matter become autonomous computation? 1/n 👇🧵 arxiv.org/abs/2607.23902

Nima Dehghani@neurovium.bsky.social · last wk.

I have decided to add the story behind papers to technical companion posts. Here is a starter: "When Prediction Shapes the Machine: Evolutionary Reservoirs, Chaos, and Structural Constraints What is under a reservoir's hood?" 👇 neurovium.science/posts/pblog-... Let me know if you want to see more📜

When Prediction Shapes the Machine: Evolutionary Reservoirs, Chaos, and Structural Constraints

Companion post to: Evolutionary Optimization Reveals Structural Constraints on Reservoir Architecture for Spatiotemporal Chaos Nima Dehghani arXiv 2026. DOI: https://doi.org/10.48550/arXiv.2606.22765

neurovium.science

Nima Dehghani@neurovium.bsky.social · 2mo ago

Week 3 of summer of papers! Here we go! 📣🎥📜 If a recurrent dynamical system is selected only for prediction, what structure does it evolve? Not just: can it predict complex timeseries (like Kuramoto-Sivashinsky)? But: what does prediction do to the machine? 1/n 🧵👇 arxiv.org/abs/2606.22765

Nima Dehghani@neurovium.bsky.social · 2w ago

Week 4 of summer of papers! Here we go! 📣📷 📜 The central question: when does memory in matter become autonomous computation? 1/n 👇🧵 arxiv.org/abs/2607.23902

Autonomous Physical Computation: A Categorical Closure Criterion for Physical and Neuromorphic Reservoirs

Physical reservoirs, neuromorphic devices, and wave-mediated systems often possess memory, feedback, and rich state-dependent dynamics, but these properties do not by themselves establish autonomous c...

arxiv.org

Nima Dehghani@neurovium.bsky.social · 2mo ago

Week 3 of summer of papers! Here we go! 📣🎥📜 If a recurrent dynamical system is selected only for prediction, what structure does it evolve? Not just: can it predict complex timeseries (like Kuramoto-Sivashinsky)? But: what does prediction do to the machine? 1/n 🧵👇 arxiv.org/abs/2606.22765

Evolutionary Optimization Reveals Structural Constraints on Reservoir Architecture for Spatiotemporal Chaos

Biological systems maintain function in fluctuating environments by transforming past stimulation into internal dynamical states that support future-oriented responses. Reservoir computing provides a ...

arxiv.org

Nima Dehghani@neurovium.bsky.social · 2mo ago

Perfect open sci + ed. Fueled by the curiosity of great students, backed by the generous support of @neuromatch.bsky.social (1.5 yr of serious compute beyond their Impact Scholar Program), MICrONS data funded by IARPA generated by @alleninstitute.org @jhuapl.bsky.social hosted by @dandiarchive.org

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Neuromatch@neuromatch.bsky.social · 2mo ago

From Neuromatch Academy ➡️ Impact Scholars Program ➡️ published paper 🎉 Just published: Harnessing cortical geometry, wiring, and function as inductive biases for recurrent neural networks 🤓 Full story and paper link: www.linkedin.com/feed/update/... #ComputationalNeuroscience #DeepLearning

Nima Dehghani@neurovium.bsky.social · 2mo ago

A key point of "Open Science" is that it enables the sci community to make advances that otherwise wouldn't have been possible. Thanks to @bingbrunton.bsky.social group who made the efforts to make the AJILE12 data available on @dandiarchive.org , we were able to develop a cool method. Try it!🫵

Nima Dehghani@neurovium.bsky.social · 2mo ago

How local is a “local” field potential? In our new paper 📜, we introduce Spatially Masked Regression (SMR), a reconstruction-based framework for asking how much of an electrode signal is locally redundant, and how much is embedded in broader distributed dynamics. 1/n 🧵👇 arxiv.org/abs/2606.11415

Nima Dehghani@neurovium.bsky.social · 2mo ago

new paper, #NeuroAI 📣📜 Can measured cortical organization be used as an inductive bias for artificial recurrent neural networks? In this work, we ask whether cortical geometry, wiring, and function can push RNNs learn. Not as metaphor, but as measurable structure! 1/n🧵👇 arxiv.org/abs/2606.14975

Harnessing cortical geometry, wiring, and function as inductive biases for recurrent neural networks

How the wiring and functional organization of cortex shape recurrent computation remains a central question in both neuroscience and machine learning. Here, we leverage data released through the Machi...

arxiv.org

Nigel Goldenfeld@nigelgoldenfeld.bsky.social · 2mo ago

Eukaryotic evolution via massive HGT "Our relative timing estimates suggest early interactions between an Asgard archaea and a Planctomycete (bacterium) ... Thus, the prokaryotic-to-eukaryotic transition was probably a gradual and complex process, with a constant flow of HGT from diverse sources."

Ricard Solé@ricardsole.bsky.social · 2mo ago

How did complex cells emerge? In this groundbreaking paper, @tonigabaldon.bsky.social & co show that eukaryotes arose through multiple waves of ancient genetic exchange involving diverse bacteria (& giant viruses!) revealing a far more complex origin than we imagined. www.nature.com/articles/s41...

Nima Dehghani@neurovium.bsky.social · 2mo ago

How local is a “local” field potential? In our new paper 📜, we introduce Spatially Masked Regression (SMR), a reconstruction-based framework for asking how much of an electrode signal is locally redundant, and how much is embedded in broader distributed dynamics. 1/n 🧵👇 arxiv.org/abs/2606.11415

Spatially Masked Regression Reveals Local and Distributed Predictability in Electrophysiological Recordings

Neural recordings are often interpreted as local measurements, yet the signal at any one sensor can also reflect structured activity distributed across the broader network. This raises a basic questio...

arxiv.org

Nima Dehghani@neurovium.bsky.social · 2mo ago

See the paper card (for link and the blog) on the recent manuscript on inhibitory neurons across different layers of the cortex! ps...the universality paper (quoted tweet) will be a follow up on this one. neurovium.science/papers/Inhib...

Morphoelectric properties of inhibitory neurons shift gradually and regardless of cell type along the depth of the cerebral cortex

This work shows that cortical interneuron morphoelectric properties are organized by two separable axes: molecularly related, depth-independent cell-type structure and gradual, depth-dependent shifts ...

neurovium.science

Nima Dehghani@neurovium.bsky.social · last yr.

Chihuly gardens is my "pilgrimage" whenever I come to Seattle. The sacred beauty of colors and forms, this time in the "Chandelier" room resonated w the manuscript that Felipe Yanez & I are working on together: "The universality of form/function of cortical inhibitory neurons"...

The Transmitter @thetransmitter.bsky.social · 2mo ago

@macshine.bsky.social talks with @satra.bsky.social about the #OHBM2026 Abstract Atlas—a community-built tool that places every 2026 abstract inside the broader neuroscience landscape. Where does your work sit in the field? #neuroskyence www.thetransmitter.org/open-source-...

Finding your place in neuroscience

A new tool places every OHBM 2026 abstract inside a semantic map of the neuroscience literature, so you can find your neighbors.

thetransmitter.org

Nima Dehghani@neurovium.bsky.social · 2mo ago

Mistakes happen. That is part of the sci progress. What is most important is reproducibility, verification & honesty. That the authors shared their data and in essence agreed to be criticized is itself necessary. That they opted to retract is honorable. Use @dandiarchive.org to amplify this! 🧵👇1/5

The Transmitter @thetransmitter.bsky.social · 4mo ago

The authors of a Nature paper outlining a mechanism for multisensory memories in Drosophila melongaster have retracted the work after they were unable to replicate a set of imaging experiments. By @callimcflurry.bsky.social #neuroskyence www.thetransmitter.org/retraction/r...

Liset M. de la Prida@lmprida.bsky.social · 2mo ago

A must-needed benchmarking👇🏼 How much is methodological and how much is conceptual? A reason for us developing #rippl-AI github.com/PridaLab/rip... Don’t miss the next hackathon avant-FENS pre-fens-brainhack.github.io/brainhack2026/ with @acnavasolive.bsky.social & @mattiachini.bsky.social

The Transmitter @thetransmitter.bsky.social · 2mo ago

Differences stemmed from the way researchers defined concepts, to the algorithms they used to analyze the data, to the parameters they employed when implementing the algorithms, note @mattiachini.bsky.social and Gaelle Chapuis. #neuroskyence www.thetransmitter.org/reproducibil...

Nima Dehghani@neurovium.bsky.social · 2mo ago

Without any doubt, if given ownership, governments will try to use AI for surveillance, control and weapons. I completely disagree that the government should own AI companies. Should governments put guardrails that AI companies don't turn to monopolies or disrupt the society negatively? Yes 100%.

Blake Richards@tyrellturing.bsky.social · 2mo ago

Sanders' proposal for the government to take a 50% stake in AI companies is, IMO, a good idea. AI will be a critical piece of infrastructure, one which should be built with appropriate safe-guards and environmental planning. Trying to cancel AI is foolish - but leaving it to market forces is too.