Erik Hermansen

The paper introduces methods to disentangle latent variables driving neural activity by identifying bidirectional local matrices in neural data, applied to reveal movement-driven structures in motor cortex.

This study shows that toroidal manifolds in the MEC emerge early in rat pups, preceding spatial experience and exploration, suggesting innate computational motifs in spatial navigation.

This paper investigates grid cells as a conformal isometric map of space, showing that a module of at least seven grid cells can achieve a distance-preserving representation with regular hexagonal phase patterns.

The paper shows that grid cell population activity forms a 2-D toroidal state space during 1-D behavior, using UMAP and persistent homology to analyze topology.

The paper compares neural correlations and state space approaches using topology to infer neural representations, showing their complementary value in characterizing covariate spaces.

The paper shows that grid cell activity forms a toroidal manifold, supporting continuous attractor network dynamics in the medial entorhinal cortex.