Chicago, IL 60611 United States
Overview
Recent advances in our ability to record simultaneously from large numbers of neurons has shifted the focus in neuroscience from understanding dynamics at a single cell level to the network level. At the same time, the rise of modern machine learning has independently generated interest in how computation arises from the coordinated activity of large networks of simple units. This workshop explores how computation emerges from network dynamics, asking how circuit structure, network architecture, and plasticity/learning shape the neural dynamics underlying cognitive functions.
Participants (Invitation accepted as of July 19, 2026)
Organizers
Hermann Riecke – Northwestern University
Matthew Kaufman – University of Chicago
Marcella Noorman – University of Chicago
Brent Doiron – University of Chicago
Jacob Zavatone-Veth – Harvard University
Ashok Litwin-Kumar – Columbia University
Participants
Hannah Choi – Georgia Institute of Technology
David Clark – Kempner Institute, Harvard University
Bard Ermentrout – University of Pittsburgh
Katie Morrison – University of Northern Colorado
Cengiz Pehlevan – Harvard University
Ulises Pereira Obilinovic – Allen Institute
Jonathan Rubin – University of Pittsburgh
Byron Yu – Carnegie Mellon University