Zhaoze Wang

A simple model of the co-emergence of grid and place fields

This paper introduces a unified recurrent network model that co-emerges grid and place cells without supervision or pre-existing spatial-cell representations, reproducing experimental observations.

When and Where: A Model Hippocampal Network Unifies Formation of Time Cells and Place Cells

This paper shows that place and time cells emerge from the same recurrent network model under different input conditions, suggesting a shared origin but task-driven differences.

REMI: Reconstructing Episodic Memory During Internally Driven Path Planning

This paper proposes a system-level theory of MEC-HC wiring to explain how grid and place cell patterns enable cue-triggered goal retrieval and path planning, validated through simulations.

Digital pathology assessment of kidney glomerular filtration barrier ultrastructure in an animal model of podocytopathy

This paper develops a deep learning method to automate measurement of glomerular basement membrane and podocyte foot process widths in TEM images of podocytopathy mouse models, showing comparable accuracy to manual methods.

Time Makes Space: Emergence of Place Fields in Networks Encoding Temporally Continuous Sensory Experiences

The paper shows that place cells emerge in networks trained to reconstruct temporally continuous sensory experiences, reproducing key hippocampal phenomena like remapping and place field orthogonality.

Trading Place for Space: Increasing Location Resolution Reduces Contextual Capacity in Hippocampal Codes

The paper uses a geometric approach to analyze how changes in place cell firing properties affect the contextual capacity of the hippocampus, revealing a trade-off between spatial resolution and context storage.