7:30-9:00          Breakfast (Blackford)

Session 1:         All-Brain Challenge #1 (Chaired by Alex Koulakov)

8:55                   Opening remarks

9:00                   Jorge Gamez, California Institute of Technology

Cognitive spatial representations in human posterior parietal cortex

9:30                   Takuya Ito, Yale University

Multi-task representations in human cortex transform along a sensory-to-motor hierarchy

10:00                 Christopher Langdon, Cold Spring Harbor Laboratory

Latent circuit inference from heterogeneous neural responses during cognitive tasks

10:30                 Break

Session 2:         All-Brain Challenge #2 (Chaired by Khristina Samoilova)

11:00                 Hsin-Hung Li, New York University

The neural code of working memory in human cortex: uncertainty and temporal dynamics

11:30                 Rich Pang, Princeton University

Inferring neural codes from natural behavior in Drosophila social communication

12:00                 Lunch

Session 3:         Geometry of Neural Population Codes (Chaired by Preston Jiang)

1:30                   Matthew Farrell, Harvard University

How Many Objects can be Linearly Classified Under All Possible Views?

2:00                   Luciano Dyballa, Yale University

Neural manifolds reveal encoding architectures in mouse visual system

2:30                   Valeria Fascianelli, Columbia              University

Representational geometry predicts behavioral differences between two monkeys

3:00                   Teddy Einstein, University of Pittsburgh       

Walks with jumps: a Model for Spike Train Dynamics with Hyperbolic Geometry

3:30                   Break

Session 4:         Theory of Neural Computation  (Chaired by Lindsey S. Brown)

4:00                   Rainer Engelken, Columbia University

 A time-resolved theory of information encoding in recurrent neural networks

4:30                   Naoki Hiratani , Harvard University

Stability and scalability of node perturbation learning

5:00                   Patrick Burauel, California Institute of Technology

Macro-Level Causal Feature Learning from Micro-Level Observations

5:30    Poster Session Reception (Nichols Biondi)*

7:00    Dinner

*Poster Titles

Yanliang Shi, Cold Spring Harbor Laboratory

A framework of large-scale functional dynamics across mouse cortex based on the biological connectome.

Lindsey S. Brown, Princeton University

Models for accumulation of evidence through sequences in a navigation-based, decision-making task

Yunliang Zang, Brandeis University

Neuronal Structure Enhances Robustness to “Noise” Perturbations

Cina Aghamohammadi, Cold Spring Harbor Laboratory

Decision-Making Under Working Memory Limitations

Preston Jiang, University of Washington

Dynamic Predictive Coding: A New Model of Hierarchical Sequence Learning and Prediction in the Cortex

Nathan Buerkle, Yale University

Synaptic mechanisms of temporal pattern separation.

Dongyan Lin, Cold Spring Harbor Laboratory

Time cell encoding is decoupled from time perception in deep reinforcement learning agents

Pavel Tolmachev, Cold Spring Harbor Laboratory

A neural circuit mechanism for context-dependent selection via population dynamics

Khristina Samoilova, Cold Spring Harbor Laboratory

The order code in the olfactory bulb