Adarsh Kumar

Contextual Inference Drives Motor Memory Protection and Disruption

The paper investigates how memory reactivation influences motor memory interference, finding that reactivating a memory before interference protects it from disruption.

Contextual Cues and Transition Statistics Drive Expression of Competing Motor Memories

This paper investigates how contextual cues and transition statistics influence the retrieval of competing motor memories, showing that memory expression is biased by learned stability and recency rather than being purely cue-driven.

Interference Between Motor Memories Arises From Implicit Recalibration

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.

Interaction between Model-based and Model-free Mechanisms in Motor Learning

This study shows that initial engagement of model-free or model-based mechanisms in motor learning biases subsequent adaptations, even when task demands change.

Dissociable mechanistic contributions of limb and task related errors during human sensorimotor learning

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