Joana Carmona

The paper uses recurrent network models to show how input alignment with connectivity shapes directional interactions in cortical circuits, explaining shifts in signal flow 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.