15 papers
Attractor Geometry of Transformer Memory: From Conflict Arbitration to Confident Hallucination
Qiyao Liang, Risto Miikkulainen, Ila Fiete
Language models draw on two knowledge sources: facts baked into weights (parametric memory, PM) and information in context (working memory, WM). We study two mechanistically distin…
Mean-field theory of rich oscillatory dynamics in low-rank recurrent networks with activity-dependent adaptation
Bowen W. Zheng, Earl K. Miller, Ila R. Fiete
We develop a dynamical mean-field theory for random recurrent networks with low-rank structure and firing-rate-driven adaptation. When the random connectivity is strong enough to g…
B[FM]: Brain Foundation Model via Flow Matching with SplitUNet
Jaedong Hwang, Kathleen Zhang, Wei Dai +5
EEG foundation models can learn generalizable representations from large-scale EEG corpora to enable single-backbone transfer across diverse clinical and brain-computer interface t…
Neuroprobe: Evaluating Intracranial Brain Responses to Naturalistic Stimuli
Andrii Zahorodnii, Christopher Wang, Geeling Chau +7
High-resolution neural datasets enable foundation models for the next generation of brain-computer interfaces and neurological treatments. The community requires rigorous benchmark…
Characterizing control between interacting subsystems with deep Jacobian estimation
Adam J. Eisen, Mitchell Ostrow, Sarthak Chandra +3
Biological function arises through the dynamical interactions of multiple subsystems, including those between brain areas, within gene regulatory networks, and more. A common appro…
Fast dynamical similarity analysis
Arman Behrad, Mitchell Ostrow, Mohammad Taha Fakharian +3
Understanding how nonlinear dynamical systems (e.g., artificial neural networks and neural circuits) process information requires comparing their underlying dynamics at scale, acro…