Striatal-cerebellar networks mediate consolidation in a motor sequence learning Task: An fMRI study using dynamic causal modelling

Elinor Tzvi*, Anne Stoldt, Karsten Witt, Ulrike M. Krämer

*Corresponding author for this work
13 Citations (Scopus)

Abstract

The fast and slow learning stages of motor sequence learning are suggested to be realized through plasticity in a distributed cortico-striato-cerebellar network. To better understand the causal interactions within this network in the different phases of motor sequence learning, we investigated the effective connectivity within this network during encoding (Day 1) and after consolidation (Day 2) of a serial reaction time task. Using Dynamic Causal Modelling of fMRI data, we found general changes in network connections reflected in altered input nodes and endogenous connections when comparing the early and fast learning session to the late and slow learning session. Whereas encoding of a motor memory early on modulated several connections in a distributed network, slow learning resulted in a pruned network. More specifically, we found a negative modulation of connections from left M1 to right cerebellum, right premotor cortex to left cerebellum, as well as backward connections from putamen to cerebellum bilaterally in the encoding session. While connections during pre-sleep were significantly modulated by learning per se (i.e., specifically modulated by performance on sequence conditions), the connections observed after sleep were rather modulated by general performance (i.e., modulated by performance on both sequence and random conditions). A forward connection from left cerebellum to right putamen was found to be consistent across participants for the sequence condition only during slow learning. Together these findings suggest that whereas encoding in the fast learning phase requires plasticity in several connections implementing both motor and perceptual learning components, slow learning is mediated through connectivity from left cerebellum to right putamen.

Original languageEnglish
JournalNeuroImage
Volume122
Pages (from-to)52-64
Number of pages13
ISSN1053-8119
DOIs
Publication statusPublished - 05.11.2015

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