Daisuke Kawahara

The Spiking Tolman-Eichenbaum Machine: Emergent Spatial and Temporal Coding through Spiking Network Dynamics

The paper introduces a spiking neural network model that learns grid and place cell patterns through biologically realistic dynamics, reproducing key temporal coding features observed in the hippocampal-entorhinal circuit.

Estimation of animal location from grid cell populationactivity using persistent cohomology

This paper estimates animal position from grid cell activity using persistent cohomology, showing it outperforms traditional methods in high nonlinearity scenarios.