Pratik K. Mutha

This study investigates how sensory prediction errors (SPEs) and task performance errors (TPEs) influence motor learning, finding that SPE-driven learning is unaffected by TPE magnitude.

The paper investigates how interference between motor memories occurs through implicit recalibration, showing that explicit strategies reduce interference and PPC involvement is necessary for implicit learning.

This study shows that explicit reward reduces sensory prediction error-driven motor adaptation by decreasing trial-to-trial updates and variability, even with constant visual errors.

The paper investigates how bimanual coordination adapts to changes in movement direction and extent, showing task-dependent adjustments in arm variability.

The paper shows that humans can selectively adapt to sensorimotor errors based on their task relevance, challenging the idea that all error signals drive adaptation equally.

This study tests whether reactivating a motor memory affects its susceptibility to interference from competing learning, finding that reactivation reduces interference when the competing memory cannot stabilize.

This study investigates how sensorimotor learning is influenced by sensory prediction errors and task performance errors, finding that they drive distinct learning mechanisms.