Neural Substrates Related to Motor Memory with Multiple Timescales in Sensorimotor Adaptation.

Sungshin Kim,Nicolas Schweighofer,Hiroshi Imamizu,Jinchi Lv,Kenji Ogawa,James Ashe

doi:10.1371/journal.pbio.1002312

Abstract

Recent computational and behavioral studies suggest that motor adaptation results from the update of multiple memories with different timescales. Here, we designed a model-based functional magnetic resonance imaging (fMRI) experiment in which subjects adapted to two opposing visuomotor rotations. A computational model of motor adaptation with multiple memories was fitted to the behavioral data to generate time-varying regressors of brain activity. We identified regional specificity to timescales: in particular, the activity in the inferior parietal region and in the anterior-medial cerebellum was associated with memories for intermediate and long timescales, respectively. A sparse singular value decomposition analysis of variability in specificities to timescales over the brain identified four components, two fast, one middle, and one slow, each associated with different brain networks. Finally, a multivariate decoding analysis showed that activity patterns in the anterior-medial cerebellum progressively represented the two rotations. Our results support the existence of brain regions associated with multiple timescales in adaptation and a role of the cerebellum in storing multiple internal models.

Highlights

Behavioral and computational modeling studies, on the one hand, and neuroimaging studies, on the other hand, have greatly advanced our understanding of motor adaptation
Subjects were instructed to hit a circular target that appeared on the visual display by manipulating a joystick with their left hand, with the goal to decrease the distance between the cursor and the target at the end of the movement
The cursor was rotated 40°, −40°, or 0° from the actual movement direction depending on the task (Task 1: 40°; Task 2: −40°; Control task: 0°), which was cued by the target color (Fig 1)

Summary

Introduction

Behavioral and computational modeling studies, on the one hand, and neuroimaging studies, on the other hand, have greatly advanced our understanding of motor adaptation. The activity of the cerebellum increases in a later stage of visuomotor adaptation [6,15,18] and correlates with the degree of savings at transfer of learning [19]. Such activation is consistent with cerebellum learning from errors [20,21], building internal models [22,23,24], and storing multiple motor skills [25]

Methods

Results

Conclusion