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Cerebellar – Premotor cortex interactions underlying visuomotor adaptation

Elinor Tzvi*, Fabian Koeth, Anke N. Karabanov, Hartwig R. Siebner, Ulrike M. Krämer

*Corresponding author for this work

Abstract

Visuomotor adaptation (VMA) is a form of motor learning essential for performing day to day routines. Theoretical models and empirical evidence suggest a specific cortico-striato-cerebellar loop that mediates early and late learning in VMA. Here, we investigated dynamic changes in neural activity and connectivity when learning a novel visuomotor rotation using fMRI. We found that motor cortical regions, parietal cortex and cerebellum are recruited in the early phase of VMA, gradually reduce their activity as learning reaches plateau and rebound when the visuomotor rotation is removed. At this phase, dubbed de-adaptation, individual performance correlated with activity in motor and parietal cortex such that stronger activity was associated with better performance. Theory suggests that VMA is governed by the cortico-striato-cerebellar network during the early phase of learning and by the cortico-cerebellar loop at later stages. We tested this hypothesis using dynamic causal modelling and found distinct modulation of a cerebellar to dorsal premotor cortex (dPMC) loop. Specifically, the cerebellar to dPMC connection was modulated during adaptation, suggesting a release of inhibition and net excitatory effect of cerebellum on dPMC. The modulation of cerebellar to dPMC connection during de-adaptation was specifically related to behavioral learning parameter: stronger release of inhibition of the cerebellar to dPMC connection was associated with better de-adaptation. We interpret these findings to reflect dynamic interactions between representation of movement in cerebellum and visuomotor integration in dPMC.

Original languageEnglish
Article number117142
JournalNeuroImage
Volume220
ISSN1053-8119
DOIs
Publication statusPublished - 15.10.2020

Funding

We would like to thank Matthias Liebrand for his help with the study design and Frieder Paulus for technical assistance with the experiment. In addition, we thank four anonymous reviewers for their valuable contribution to the discussion of this work. This study is supported by the DFG grant TZ 85/1-1 to ET . UMK is supported by the DFG .

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

Research Areas and Centers

  • Academic Focus: Center for Brain, Behavior and Metabolism (CBBM)

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