10 citations · 15 across the 5 of their papers we have counts for
6 papers
Bridging Expressivity and Scalability with Adaptive Unitary SSMs
Arjun Karuvally, Franz Nowak, Anderson T. Keller +3
Recent work has revealed that state space models (SSMs), while efficient for long-sequence processing, are fundamentally limited in their ability to represent formal languages-part…
Synaptic spine head morphodynamics from graph grammar rules for actin dynamics
Matthew Hur, Thomas Bartol, Padmini Rangamani +2
There is a morphodynamic component to synaptic learning by which changes in dendritic (postsynaptic) spine head size are associated with the strengthening or weakening of the synap…
A Spatiotemporal Perspective on Dynamical Computation in Neural Information Processing Systems
T. Anderson Keller, Lyle Muller, Terrence J. Sejnowski +1
Spatiotemporal flows of neural activity, such as traveling waves, have been observed throughout the brain since the earliest recordings; yet there is still little consensus on thei…
Hidden Traveling Waves bind Working Memory Variables in Recurrent Neural Networks
Arjun Karuvally, Terrence J. Sejnowski, Hava T. Siegelmann
Traveling waves are a fundamental phenomenon in the brain, playing a crucial role in short-term information storage. In this study, we leverage the concept of traveling wave dynami…
Transformers and Cortical Waves: Encoders for Pulling In Context Across Time
Lyle Muller, Patricia S. Churchland, Terrence J. Sejnowski
The capabilities of transformer networks such as ChatGPT and other Large Language Models (LLMs) have captured the world's attention. The crucial computational mechanism underlying…
Traveling Waves Encode the Recent Past and Enhance Sequence Learning
T. Anderson Keller, Lyle Muller, Terrence Sejnowski +1
Traveling waves of neural activity have been observed throughout the brain at a diversity of regions and scales; however, their precise computational role is still debated. One phy…