Ben Sorscher

The paper shows that grid cells in the entorhinal cortex form stable maps of novel environments quickly and with minimal distortion, enabling flexible navigation through downstream plasticity.

The paper reassesses claims about grid cell emergence in path-integrator circuits, finding consistency with prior theory.

This paper shows that hexagonal grid cell patterns emerge in neural networks trained for path integration and develops methods to analyze these networks for mechanistic insights.

This study uses task-driven neural networks to show that heterogeneous MEC cells are functionally significant and that reward-modulated models better capture MEC response profiles than traditional models.

The paper proposes a geometric framework for few-shot learning using neural manifolds and a single plastic neuron, demonstrating its effectiveness on visual concepts and linking neurophysiology to behavior.