Changes in functional connectivity and GABA levels with long-term motor learning

Cassandra Sampaio-Baptista,Nicola Filippini,Charlotte J Stagg,Jamie Near,Jan Scholz,Heidi Johansen-Berg

doi:10.1016/j.neuroimage.2014.11.032

Cassandra Sampaio-Baptista, Nicola Filippini + Show 4 more

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https://doi.org/10.1016/j.neuroimage.2014.11.032

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Abstract

Learning novel motor skills alters local inhibitory circuits within primary motor cortex (M1) (Floyer-Lea et al., 2006) and changes long-range functional connectivity (Albert et al., 2009). Whether such effects occur with long-term training is less well established. In addition, the relationship between learning-related changes in functional connectivity and local inhibition, and their modulation by practice, has not previously been tested.Here, we used resting-state functional magnetic resonance imaging (rs-fMRI) to assess functional connectivity and MR spectroscopy to quantify GABA in primary motor cortex (M1) before and after a 6week regime of juggling practice. Participants practiced for either 30min (high intensity group) or 15min (low intensity group) per day. We hypothesized that different training regimes would be reflected in distinct changes in brain connectivity and local inhibition, and that correlations would be found between learning-induced changes in GABA and functional connectivity.Performance improved significantly with practice in both groups and we found no evidence for differences in performance outcomes between the low intensity and high intensity groups. Despite the absence of behavioral differences, we found distinct patterns of brain change in the two groups: the low intensity group showed increases in functional connectivity in the motor network and decreases in GABA, whereas the high intensity group showed decreases in functional connectivity and no significant change in GABA. Changes in functional connectivity correlated with performance outcome. Learning-related changes in functional connectivity correlated with changes in GABA.The results suggest that different training regimes are associated with distinct patterns of brain change, even when performance outcomes are comparable between practice schedules. Our results further indicate that learning-related changes in resting-state network strength in part reflect GABAergic plastic processes.

Highlights

Learning of demanding novel motor skills, acquired over several training sessions, induces structural and functional plasticity in the brain (e.g., Dayan and Cohen, 2011; Doyon et al, 2009; Sampaio-Baptista et al, 2014; Scholz et al, 2009)
Behavioral performance was comparable between two groups that practiced for different amounts of time per day, we found significant differences in brain change between groups: subjects who performed a low intensity practice schedule showed increases in motor network connectivity and decreases in GABA whereas those who underwent a high intensity training regimen showed decreases in connectivity within the motor resting state networks (RSNs) and no significant change in GABA
There were significant relationships between performance outcomes and motor RSN strength change, but the direction of these correlations varied between groups: in the high intensity group better performance was associated with greater decreases whereas in the low intensity group better performance tended to be associated with greater increases in functional connectivity

Summary

Introduction

Learning of demanding novel motor skills, acquired over several training sessions, induces structural and functional plasticity in the brain (e.g., Dayan and Cohen, 2011; Doyon et al, 2009; Sampaio-Baptista et al, 2014; Scholz et al, 2009). The amount of practice undertaken modulates structural changes associated with long-term motor learning (Sampaio-Baptista et al, 2014) and influences the functional networks recruited for task performance (Doyon and Ungerleider, 2002). Resting-state fMRI has been used to show that motor learning changes the resting functional connectivity of the brain. 11 min of motor training increased the strength of the fronto-parietal and the cerebellum resting state networks (RSNs) (Albert et al, 2009).

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