Reactivation of motor memory by passive finger movements with robotic hand exoskeleton
Kazuhisa Shibata1 (firstname.lastname@example.org), Hiroki Ohashi1, Hayato Nishioka2, Yuki Ogasawara2; 1RIKEN Center for Brain Science, 2SONY Computer Science Laboratories Inc.
Motor learning evolves beyond the period of training on a skill. Key to this evolution is reactivation, which destabilizes once-consolidated motor memory, thus enabling further refinement of skills through reconsolidation. Here, an important question arises: what triggers this reactivation? While reactivation has traditionally been assumed to occur by re-experiencing the same context as in training, no two experiences are exactly alike in our uncertain world. Consequently, the context involved in reactivation (e.g., motor command, somatosensory feedback, visual input) inevitably differs from that in training. This difference demands the brain to make concessions on the contexts necessary for effective reactivation. However, excessive concessions could admit reactivation under contexts unrelated to the original training, leading to potential overwriting or disruption of the memory. To examine how the brain resolves this plasticity-stability dilemma in reactivation, we conducted finger movement learning experiments that systematically manipulated the context for reactivation. Notably, we introduced a ‘passive condition’ where participants, using a robotic hand exoskeleton, re-experienced the somatosensory feedback and visual inputs in the absence of motor commands. This passive condition resulted in a performance gain comparable to the condition involving all three components. The performance gain was still observed when participants performed a cognitively demanding task while experiencing the somatosensory feedback, suggesting that somatosensory feedback alone can trigger reactivation. In contrast, visual inputs alone did not yield such gain. These results imply that the brain primarily relies on somatosensory feedback related to motor actions during training to resolve the plasticity-stability dilemma in reactivating motor memory.
Topic Area: LONG-TERM MEMORY: Skill Learning
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April 13–16 | 2024