Events

Title: When and How to Parallelize Seemingly Sequential Models   Abstract: Transformers have become the de facto model for sequential data in large part because they are well adapted to modern hardware:…

Initial Meeting! About: The ARNI Language & Vision Working Group aims to bring together researchers across neuroscience, cognitive science, computer science, and AI to collaboratively advance our understanding of how…

Title:A multimodal sleep foundation model for disease prediction Abstract: Sleep is a fundamental biological process with broad implications for physical and mental health, yet its complex relationship with disease remains poorly understood. Polysomnography (PSG)—the gold standard for sleep analysis—captures rich physiological signals but is underutilized due to challenges in standardization, generalizability and multimodal integration. To…

Herbert Zheng Wu Title: Neural Basis of Leader–Follower Dynamics in Cooperative Behavior Abstract: Cooperation allows social species to achieve outcomes that individuals cannot accomplish alone. Even in simple groups, cooperative behavior often depends on complementary social roles such as leaders and followers, yet the neural computations supporting these dynamic relationships are not well understood. Our lab investigates…

1) Charlotte onboarded vision and audio MNIST dataloaders. She's focusing on predictive coding for sequential tasks (e.g., audio data/moving MNIST). 2) Todd built a multi-modal predictive coding baselines showing that unsupervised representation learning is possible here. 3) Eivinas proposed a backprop based autoencoder and Hebbian based autoencoder (maybe Exponentiated Gradients?). 4) Nihal offered to onboard…

SueYeon Chung Title: Computing with Neural Manifolds: A Multi-Scale Framework for Understanding Biological and Artificial Neural Networks Abstract: Recent breakthroughs in experimental neuroscience and machine learning have opened new frontiers in understanding the computational principles governing neural circuits and artificial neural networks (ANNs). Both biological and artificial systems exhibit an astonishing degree of orchestrated information…

We are aiming to accelerate progress on the benchmark, and will demo a working prototype very soon. If you are interested in contributing to our project, we strongly encourage you to participate so that we can fix and implement our plan of action for the coming few months.

Title: Inter-area connectivity and the emergence of multi-timescale cortical dynamics Abstract: The brain generates behaviors spanning a wide range of timescales, from rapid sensory responses to the slow integrative processes underlying cognition. How does the anatomical connectivity of the neocortex give rise to such flexible, multi-timescale dynamics? In this talk, I will examine how the…

Continuation from prior meetings Zoom Link- Upon request @ [email protected]

Denise Cai Title: Dynamic neural ensembles support memory stability and flexibility across the lifetime Abstract: Creating stable memories is critical for survival. An animal relies on past learning to navigate its environment, avoid dangerous situations, and find needed resources. Because the environment is dynamic, stable memories must be updated with new information to enable responses…

Date and time: Monday, March 2, from 3–4 PM. Meeting Link: Upon request @[email protected] Speakers: Jorge Menendez, Research Scientist at CTRL-Labs, and Trung Le, postdoc in Prof. Chethan Pandarinath’s group. Title: A generic non-invasive neuromotor interface for human-computer interaction Since the advent of computing, humans have sought computer input technologies that are expressive, intuitive and…

Date: Wednesday, March 4, 2026 Time: 9:00 AM - 6:30 PM Location: Faculty Room, Low Memorial Library Address: 535 W. 116th Street, New York, NY 10027 - Visitor Information Overview How does a university learn and adapt as AI becomes woven into teaching, learning, and intellectual life? This program invites both celebration of innovative experimentation…