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

Sungshin Kim; Kenji Ogawa; Jinchi Lv; Nicolas Schweighofer; Hiroshi Imamizu

doi:10.1371/journal.pbio.1002312

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

PLoS Biol. 2015 Dec 8;13(12):e1002312. doi: 10.1371/journal.pbio.1002312. eCollection 2015 Dec.

Authors

Sungshin Kim^{1

2}, Kenji Ogawa^{3

4}, Jinchi Lv⁵, Nicolas Schweighofer^{6

7}, Hiroshi Imamizu^{3

8

9}

Affiliations

¹ Neuroscience Graduate Program, University of Southern California, Los Angeles, California, United States of America.
² Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America.
³ Cognitive Mechanisms Laboratories, Advanced Telecommunications Research Institute International, Keihanna Science City, Kyoto, Japan.
⁴ Department of Psychology, Graduate School of Letters, Hokkaido University, Sapporo, Japan.
⁵ Data Sciences and Operations Department, Marshall School of Business, University of Southern California, Los Angeles, California, United States of America.
⁶ Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, California, United States of America.
⁷ EuroMov, Movement to Health Laboratory (M2H), Université Montpellier-1, Montpellier, France.
⁸ Center for Information and Neural Networks, National Institute of Information and Communications Technology and Osaka University, Suita, Osaka, Japan.
⁹ Department of Psychology, Graduate School of Humanities and Sociology, The University of Tokyo, Tokyo, Japan.

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.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Adaptation, Physiological*
Adult
Brain Mapping
Cerebellar Nuclei
Female
Functional Laterality
Humans
Kinetics
Magnetic Resonance Imaging
Male
Memory, Long-Term*
Memory, Short-Term*
Middle Aged
Models, Neurological*
Multivariate Analysis
Neurons / metabolism*
Parietal Lobe / metabolism
Psychomotor Performance*
Sensorimotor Cortex / metabolism*
Young Adult

Grants and funding

Grant NSF BCS 1031899 to NS supported the behavioral experiment, computational modeling, and model-based fMRI part of this study. http://www.nsf.gov/div/index.jsp?div=bcs. Grant NSF CAREER Award DMS-0955316 to JL supported the SVD analysis of brain data. http://www.nsf.gov/div/index.jsp?div=DMS. Grant JSPS KAKENHI Grant Number 26120002 to HI supported the fMRI experiment and parts of imaging data analysis. http://www.jsps.go.jp/english/index.html. "Development of BMI Technologies for Clinical Application" SRPBS AMED and ImPACT Cabinet Office of Japan to HI supported parts of imaging data analysis. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.