Alex Williams

@itsneuronal.bsky.social

Asst Prof at NYU + Flatiron Institute Computational + Statistical Neuroscience https://neurostatslab.org/

If at CCN, please check out three posters from our lab today. In the morning session: A62 - Deep Learning Models of Attention Reveal Peripheral Encoding as a Bottleneck for Selective Listening Through Cochlear Implants, by Annesya Banerjee

What does synapse position buy a neuron? We trained a dendritic network to place its own synapses on a covariance task. It clustered correlated inputs onto shared branches, and shuffling that placement destroyed performance while every weight stayed intact. Preprint: arxiv.org/abs/2607.24503 🧵-->

Synaptic clustering emerges from learning and supports covariance discrimination

Functional synapse clusters (FSCs) are synapses with correlated presynaptic activity that are colocalized on the same neuronal dendritic branch. FSCs have been observed after learning in cortical and ...

arxiv.org

New preprint led by @rgast.bsky.social- part 1 of Richard's ongoing effort to make a better firing rate model: developing mean-field models that can be fit to biological data to capture both the dynamics of neural populations and the underlying physiological heterogeneity that sculpt those dynamics.

Richard Gast@rgast.bsky.social · last wk.

The Ott-Antonsen ansatz revolutionized our understanding of coupled oscillator systems with heterogeneous oscillators. We developed a multi-ensemble method that increases the applicability of the OA ansatz to empirical data substantially arxiv.org/abs/2607.09516, as we demonstrate on neural data.

Tremendously excited to announce that I will be joining @rockefeller.edu as an Assistant Professor and Head of Lab starting in January 2027! My group will be broadly focused on theoretical neuroscience, and mathematical problems in neural computation in the large.

Rockefeller campus image from https://commons.wikimedia.org/wiki/File:Rockefeller_University_Campus_aerial_2.jpg, licensed under the Creative Commons Attribution-Share Alike 2.5 Generic license.

1/ We work hard to factor "noise" out of behavior. But the brain doesn't. Strip away noise and you may miss what the brain evolved to do I wanted to share this pre-Bluesky paper where we found premotor (M2) corticostriatal circuits encode a broad history of behavior, beyond just action + reward 👇

Information normally considered task-irrelevant drives decision-making and affects premotor circuit recruitment - Nature Communications

Prior experience is used by the brain to guide adaptive behaviour during decision making. Here, the authors show that mice also selectively use information learned through recent and longer-term exper...

nature.com

Our new paper is out this week in Nature Neuroscience! www.nature.com/articles/s41... We built a BCI that works with the brain's natural geometry — and we found that people could learn to play a video game with their brains in <1 hr of training. This efficiency is groundbreaking & here's why:

Human learning of noninvasive brain–computer interfaces via manifold geometry - Nature Neuroscience

Busch et al. use nonlinear neural manifolds to help humans gain rapid control over a noninvasive brain–computer interface, allowing them to learn how to play a video game with real-time fMRI neurofeed...

nature.com

Even if they don't dismiss the evidence of its existence, a big chunk of neuroscientists don't seem to get a key question that representational drift raises. The whole point is that responses reconfigure *without* loosing representational fidelity. This means *of necessity* that any geometric/

Posting for Vibhu Sahni: Due to unforeseen circumstances the Burke Neurological Institute will have to terminate its research operations 5/22. There are international postdocs on visas who are looking for new homes. Please reach out to Vibhu if you can help

New preprint from my lab! We study how reinforcement learning & selective attention interact. To do so, we built a set of models describing different ways that value & reward prediction error can modulate top-down attention. We compare model outcomes to monkey data from a color value learning task

bioRxiv Neuroscience@biorxiv-neursci.bsky.social · 4mo ago

Modulation of feature attention by reward prediction error explains value learning behavior https://www.biorxiv.org/content/10.64898/2026.04.10.717847v1