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, 9 (1), e85489
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Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

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Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

Hang Zhang et al. PLoS One.

Abstract

Background: Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning.

Methodology/principal findings: We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN.

Conclusions/significance: These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Coronal, sagittal, and axial views of the spatial maps and the corresponding spatial patterns of the cognitive and sensory networks in resting state.
a–h represent the RSNs, including VAN, DAN, DMN, SRN, AN, SMN, LVN and MVN, for the experiment group respectively. Red nodes in each spatial pattern represented the regions significantly recruited in the RSN. The red spatial map indicated that the corresponding RSN has exhibited significant alterations of the resting-state functional connectivity after learning. Each map was the result of one-sample t-tests on the individual patterns that were identified using the combined data of pre- and post-rest scans, p<0.005, FDR corrected.
Figure 2
Figure 2. Network strength in the default mode network decreased in the experimental group but not in the control group.
The RSNs were identified across all participants in the experimental and control groups respectively. Network strength was assessed based on the integrative spatial map of each RSN and further compared between the rest scans before and after learning for each group. * p<0.05.
Figure 3
Figure 3. Alterations of connectivity strength only in the experimental group after learning.
(a) Alteration of connectivity strength in the lateral visual network. (b) Alterations of connectivity strength in the sensory-motor network. The RSNs were identified across all participants in the experimental and control groups respectively. The connectivity strength was measured statistically based on each voxel in the spatial map of each RSN and further compared between the rest scans before and after learning for each group. The statistical threshold was set at p<0.05, corrected for multiple comparisons at the cluster level.

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Publication types

Grant support

The National Key Basic Research Program of China (973 Program) (2012CB720704); The Key Program of National Natural Science Foundation of China (60931003 and 61131003). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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