Eugenio Urdapilleta

The paper develops a multiscale model of mouse primary motor cortex to predict cell type-specific, behavior-dependent neural dynamics.

This paper investigates the relationship between spectral harmonicity and cross frequency couplings in nonlinear oscillators and neural models, showing that high harmonic content is not sufficient or necessary for interpreting CFC patterns.

The paper analyzes spectral harmonicity in ictal activity to distinguish between harmonic and non-harmonic phase-amplitude couplings in epilepsy patients, showing its relevance for identifying seizure onset zones.

The paper predicts how grid cell activity patterns change on spherical environments compared to flat ones, finding partial coherence and clustering similar to disordered materials.

The paper shows that rodents raised in hyperbolic environments could develop hyperbolic grid cell patterns, suggesting a flexible neuronal metric beyond Euclidean space.