Diya Basrai

The paper shows that interactions between motor cortical regions change with behavior, with CFA dominating over RFA during climbing and vice versa during reaching.

The paper shows that neural activity perturbations improve the accuracy of inferring across-region interactions in brain models.

The paper investigates motor cortical hierarchy in mice by analyzing firing patterns during reaching, finding asymmetric influence but shared predictive activity between premotor and primary motor cortices.

This paper introduces AutoLFADS, an automated framework for estimating neural population dynamics from neural data without supervisory information, validated on multiple datasets.