Marine Schimel

This study shows that reciprocal excitatory connections between cortical areas create line attractor dynamics that promote consensus on stimulus features across areas.

This study investigates why motor preparation occurs in RNN models of motor control and finds that optimal input-driven control leads to multiple phases of preparation during reach sequences.

The paper introduces iLQR-VAE, a control-based variational inference method for learning dynamics and inputs from neural data, showing effectiveness on synthetic and primate reaching task data.