Proud to be a collaborator on this paper on compact deep neural network models of V4, with Ben Cowley (@benjocowley.bsky.social), Pati Stan, & Matt Smith, now finally out in print (by which I mean online).
Psyched to announce our COSYNE workshop on social behaviors (Mar 17th, Cascais). We have a stellar lineup of speakers on topics from animal cooperation and aggression to the social dynamics of LLM agents.
Co-organized with Libby Zhang (Allen Institute + UW).
cosyne-social-behavior.github.io
Can electrical microstimulation be used to steer cortical population activity on- and off-manifold? Our new preprint says yes — using data-driven control in macaque PFC. Joint work with @gbarzon.bsky.social, Anandita De, Isaac Moran, Conner Carnahan, and Luca Mazzucato.
The deadline to apply for the Brain Prize Cajal summer course in Computational Neuroscience has been extended to March 9! We’re excited for you to join us in sunny Lisbon! Please do not hesitate to send in an application and learn about computational neuroscience! @gjorjulijana.bsky.social
@cshlnews.bsky.social @princetonneuro.bsky.social
@cmu-neuroscience.bsky.social
#neuroAI #compneuro #neuroscience #visualcortex #closedloop #activelearning #modelcompression #distillation #pruning
www.cshl.edu/ai-monkey-br...
Thanks to NPR's All Things Considered Jon Hamilton for the interview!
www.npr.org/2026/02/25/n...
@npr.org #AllThingsConsidered #JonHamilton
Thanks to CV Starr, Pershing Square Innovation Fund, Simons Foundation, NIH, and NIH BRAIN Initiative for funding.
Data and code:
github.com/cowleygroup/...
doi.org/10.1184/R1/3...
We hope to add our V4 data to BrainScore soon!
Thanks to my wonderful collaborators:
Pati Stan (CMU)
Jonathan Pillow (Princeton) @jpillowtime.bsky.social
Matthew Smith (CMU)
This work has inspired myself and research group at CSHL to continue hunting for step-by-step computations of the brain both with closed-loop experiments and model compression.
"Compact deep neural network models of the visual cortex." B. Cowley, P. Stan, J. Pillow*, M. Smith*. Nature, 2026.
How do you build a V4 dot detector?
We dissected the compact model, finding a simple computation for dot size selectivity:
Search for corners of a dot while inhibiting large edges. If the activity overlaps *and* inhibition is low, there must be a small dot.
Future work: Map out these circuits!
What can the compact models tell us about feature processing in V4?
One class of V4 neurons that stuck out were "dot detectors." Perhaps there to build up "eye" detectors in IT?
We focused on a single V4 neuron dot detector whose response-maximizing images were...dots.
(a side note --- interestingly, DNN units from ResNet50-robust were *NOT* compressible. Perhaps these units have to do too much with too little.)
Each V4 neuron had unique feature selectivity. Can we compress a model predicting all 200 V4 neurons at once?
Yes, yes we could.
Our ensemble model was compressible.
ResNet50-robust was compressible.
V1, V4, IT populations were compressible.
Perhaps a V4 neuron is simpler than once thought.
My favorite experiment was optimizing a compact model to slightly perturb an image's pixels that causes the neuron to either excite or suppress its response.
These experiments gave us confidence the inner workings of the compact models likely matched that of real V4 neurons.
We went to work interrogating these compact models. And things got weird.
For example, we found a "palm tree" detecting V4 neuron whose response-maximizing natural and synthesized images were palm trees?!
To make sure this was real, we performed validation experiments.
A compact model is small enough to display *all* of its convolutional weights in one diagram!
To apply Occam's Razor, we used two types of model compression:
knowledge distillation: train a student model via a teacher model
pruning: remove any spurious filters
The result: Compact models 5,000x smaller than our ensemble model but with similar prediction power.
We focus on predicting V4 responses to natural images.
We first trained an ensemble DNN model in large-scale, closed-loop experiments in which the model chose the next stimuli to show (active learning).
This behemoth achieved great prediction. Yet, its computations were buried beneath 50M+ params.
DNN models of the brain are getting bigger. Are we replacing one complicated system in vivo with another in silico?
In new work, we seek the *smallest* DNN models of visual cortex, balancing prediction with parsimony.
It turns out these compact models are surprisingly small!
rdcu.be/e5H8G
NYU's Center for Neural Science is seeking a faculty candidate that would be jointly appointed with our Tandon School of Engineering. We are looking for post-doc applicants with neuroengineering or computational backgrounds.
apply.interfolio.com/182074
I was sure the illusion would break at some length: can't keep grow forever, right?
Wrong. My brain hurts.
Apply by May 7 for two early-career #neuro workshops at Janelia! Featuring joint sessions to foster collaboration between theory & experiment. 🧠 🤝
Theoretical Neuroscience→ janelia.news/THE26
Mechanistic Cognitive Neuroscience→ janelia.news/CNW26
@ratecoding.bsky.social @jvoigts.bsky.social
You have until March 3rd to apply for the Cajal summer school on Quantitative Approaches to Behavior and VR at Champalimaud! Come surf and track animals with us 🏄🪰🐟🚶
cajal-training.org/on-site/quan...
New preprint from the lab! Ábel Ságodi developed a theory of approximating dynamical systems that goes beyond finite time. #theoreticalNeuroscience
Follow @neurabel.bsky.social
Universal Approximation Theorems for Dynamical Systems with Infinite-Time Horizon Guarantees. . arxiv.org/abs/2602.08640
In case you missed these, here's a compilation (for a few giggles to end the week).
1. Instagram post by NYUmed comms (oops).
bsky.app/profile/andr...
sad day for primary visual cortex
Our paper is out in @natneuro.nature.com!
www.nature.com/articles/s41...
We develop a geometric theory of how neural populations support generalization across many tasks.
@zuckermanbrain.bsky.social
@flatironinstitute.org
@kempnerinstitute.bsky.social
1/14
We are hiring a research specialist, to start this summer! This position would be a great fit for individuals looking to get more experience in computational and cognitive neuroscience research before applying to graduate school. #neurojobs Apply here: research-princeton.icims.com/jobs/21503/r...
🚨 #CCN2026 Proceedings submissions are open!
CCN 2026 again features an 8-page Proceedings track (alongside extended abstracts). Accepted papers will appear in CCN-Proceedings (CCN‑P) with DOIs on OpenReview.
