Guillaume S. Masson

The paper shows that sensorimotor learning can correct perceptual biases in motion perception through delayed compensatory eye movements, indicating a dissociation between sensory computations and internal models.

This paper improves gaze decoding in fMRI during eyes-closed states using a deep learning framework, showing it can generalize to eyes-closed conditions with task-specific fine-tuning.

The paper shows mammals achieve similar visual coverage by combining saccade rates, receptive field sizes, and V1 neuronal density across species.

This study shows anticipatory smooth eye movements scale with target speed and acceleration probability, indicating the brain uses internal models of motion kinematics for prediction.

The paper investigates how anticipatory neural responses in monkey V1 arise from horizontal and feedback pathways during motion integration of translating objects.