Yusi Chen

Balancing Stability and Flow in Hippocampal Networks via Inductive Bias and Learned Symmetry Breaking

This paper shows how recurrent neural networks balance stability and flow in hippocampal networks through symmetry breaking and structured connectivity.

Asymmetric Social Representations in the Prefrontal Cortex for Cooperative Behavior

This study investigates the neural mechanisms of cooperation in mice, showing that the medial prefrontal cortex encodes leadership dynamics and social value maps in an asymmetric, role-specific manner.

Unveiling value functions in social cognition with multi-agentinverse reinforcement learning

This paper introduces MAIRL, a multi-agent inverse reinforcement learning framework that decomposes joint value functions into individual value maps and interaction terms, revealing interpretable social value representations in mice and primates.

Predictive Sequence Learning in the Hippocampal Formation

The paper develops a predictive autoencoder model of the hippocampus to simulate sequence learning, showing CA3's predictive role and CA1's error signaling in mice.

Dynamical differential covariance recovers directional network structure in multiscale neural systems

This paper introduces DDC, a method for detecting directional network interactions in neural systems, validated on simulations and applied to fMRI data.

Functional connectivity of fMRI using differential covariance predicts structural connectivity and behavioral reaction times

This paper introduces differential covariance for functional connectivity analysis in fMRI, showing it better captures structural connectivity and correlates with behavioral reaction times.

Differential covariance: A new method to estimate functional connectivity in fMRI

This paper introduces differential covariance analysis to estimate functional connectivity in fMRI, showing improved performance in complex network simulations.

HiCluster: A Robust Single-Cell Hi-C Clustering Method Based on Convolution and Random Walk

HiCluster improves clustering of low coverage single-cell Hi-C data by imputing using linear convolution and random walk, revealing TAD-like structures consistent with bulk data.