Joana Carmona

The paper uses recurrent network models to show how input alignment with connectivity shapes directional interactions in cortical circuits, revealing excitatory inputs' dominant role in controlling directionality.

This paper investigates how the geometry of neural activity in recurrent networks depends on connectivity structure and input dimensionality, revealing how activity subspace dimensions relate to connectivity rank and input configuration.