What do control theory and neuroscience have in common? Shared origins in cybernetics — and, lately, “poor cousin” status next to ML. To reconnect them, we’ve been organizing workshops at this interface, most recently at the Flatiron Institute. Thanks to all who joined!
A cautionary note on biological inference from connectome-constrained networks trained in supervised settings: model selection based on task performance alone does not reliably recover the true biological circuits or underlying mechanisms Led by @ckaraneen biorxiv.org/content/10.6...
biorxiv.org
Applications are open for the Junior Theoretical Neuroscientists Workshop, July 21–24, 2026, at the Center for Computational Neuroscience, @flatironinstitute.org. Apply by April 15, 2026. Acceptance includes travel, lodging, and meals: simonsfoundation.org/event/jrwork...
A biologically plausible algorithm for learning local predictive directions in nonlinear dynamical systems. Applied to natural videos, it learns both temporal and spatial filters that resemble those of retinal neurons. Cosyne poster 2-109, presented by Marco Zenari
Self-supervised learning from natural dynamical stimuli yields a circuit that resembles the Drosophila motion detector, reproducing both its directional selectivity and characteristic synaptic weight structure. By Abdelrahman Sharafeldin and Erik Schomburg at Cosyne poster 2-137
A more biologically plausible controller neuron model: ReLU emerges as the optimal solution to a reach–avoid, rather than stabilization, objective, solved with a multi-step policy in a potentially stochastic setting. Poster 1-142 at Cosyne presented by Abel Sagodi, happening now
#FlatironCCN researchers drew on lessons from neurobiology to enhance artificial systems using a new type of computational component that is more akin to real brains: https://www.simonsfoundation.org/biological-brains-inspire-a-new-building-block-for-artificial-neural-networks/ #science
Biological Brains Inspire a New Building Block for Artificial Neural Networks
Biological Brains Inspire a New Building Block for Artificial Neural Networks on Simons Foundation
simonsfoundation.org
ReSU: A novel biologically inspired computational primitive for dynamical data. Now at AAAI board 489
Why do we stop smelling odors that linger? In our new @prxlife.bsky.social paper with @pfrancois.bsky.social, @gautamreddy.bsky.social, and Massimo Vergassola, we develop a manifold learning theory of this olfactory habituation process in fluctuating environments. 🔗 doi.org/10.1103/q62z... 🧵🔽
Joint junior faculty position in Computational Neuroscience, between Ctr for Computational Neuroscience at @flatironinstitute.org and the CUNY Graduate Center @thegraduatecenter.bsky.social . Application deadline: 16 Jan 2026! www.simonsfoundation.org/flatiron/car... cuny.jobs/new-york-ny/...
Careers
Careers on Simons Foundation
simonsfoundation.org
Move over ReLU 🚀 Meet **ReSU** (Rectified Spectral Unit): a biologically inspired, self-supervised unit for learning from dynamical data. A backprop-free multilayer ReSU network learns predictive features and recapitulates *Drosophila* vision. To appear at AAAI: arxiv.org/abs/2512.23146
A Network of Biologically Inspired Rectified Spectral Units (ReSUs) Learns Hierarchical Features Without Error Backpropagation
We introduce a biologically inspired, multilayer neural architecture composed of Rectified Spectral Units (ReSUs). Each ReSU projects a recent window of its input history onto a canonical direction ob...
arxiv.org
Delighted to talk at Brown about our self-supervised neuronal algorithm for modeling biological circuits—and challenging backprop along the way. Thanks to @leokoz8 for the kind invitation! youtu.be/AF3Uhrm__U4?...
CCBS Seminar: “What does the neuron do? A self-supervised dynamical model for neuroscience and AI"
YouTube video by Brown University
youtu.be
Biological neurons cluster dynamical stimulus trajectories to predict what’s coming and infer what just happened. If you’re at NeurIPS, stop by our poster #2107 — on display now until 2pm
Interested in algorithmic neuron models and learning rules at the intersection of neuroscience, AI, dynamical systems, and control theory? Working towards a PhD in neuroscience, physics, EE, or math? Apply for a summer internship with us: apply.interfolio.com/177775 At NeurIPS? Feel free to DM me.
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Interested in algorithmic neuron models and learning rules at the intersection of neuroscience, AI, dynamical systems, and control theory? Have a PhD in neuroscience, physics, EE, or math? Consider joining us: apply.interfolio.com/173400 If you’re at NeurIPS, feel free to DM me.
Apply - Interfolio {{$ctrl.$state.data.pageTitle}} - Apply - Interfolio
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An exciting opportunity!
Simons Foundation@simonsfoundation.org · 8mo agoInviting apps for a workshop to develop a project focused on a mechanistic understanding of canonical cortical computations at the circuit level. Deadline is 1/5/2026: https://www.simonsfoundation.org/simons-foundation-now-accepting-applications-for-workshop-on-canonical-cortical-computations
The brain survives by predicting the future. We suggest that single neurons cluster trajectories with common futures. But when observations are noisy, retrospection helps. Even individual neurons may look backward—like LGN lagged cells and olfactory bulb mitral cells: dailyneuron.com/how-sensory-...
How Sensory Processing Works: Neurons May Predict the Future and Remember the Past - Daily Neuron
New research on sensory processing suggests neurons are self-supervised learners that group stimuli by common pasts or futures to make sense of the world.
dailyneuron.com
The neuron as a controller and a few other thoughts. Thanks to the GreyMatters podcast for hosting me: open.spotify.com/episode/1ox9...
Neural Network: Dmitri Chklovskii
Spotify video
open.spotify.com
