Maria Papadopouli

The paper develops a PLSR framework to decompose neural activity in mouse V1 into stimulus and population subspaces, finding conserved coding schemes across layers.

The paper decodes motion direction in mouse V1 by analyzing neuronal responses and functional connectivity, finding that high predictive power neurons form dense networks during stimulation but differ in resting state.

The paper predicts neuronal activity in one visual cortical area from another in single trials, with or without visual stimulation, in mice and macaques.

The paper identifies functional neuronal ensembles in mouse V1 and characterizes their connectivity and computational properties across different states.