Dataset Information

Musical training induces functional plasticity in perceptual and motor networks: insights from resting-state FMRI.

ABSTRACT: A number of previous studies have examined music-related plasticity in terms of multi-sensory and motor integration but little is known about the functional and effective connectivity patterns of spontaneous intrinsic activity in these systems during the resting state in musicians. Using functional connectivity and Granger causal analysis, functional and effective connectivity among the motor and multi-sensory (visual, auditory and somatosensory) cortices were evaluated using resting-state functional magnetic resonance imaging (fMRI) in musicians and non-musicians. The results revealed that functional connectivity was significantly increased in the motor and multi-sensory cortices of musicians. Moreover, the Granger causality results demonstrated a significant increase outflow-inflow degree in the auditory cortex with the strongest causal outflow pattern of effective connectivity being found in musicians. These resting state fMRI findings indicate enhanced functional integration among the lower-level perceptual and motor networks in musicians, and may reflect functional consolidation (plasticity) resulting from long-term musical training, involving both multi-sensory and motor functional integration.

SUBMITTER: Luo C

PROVIDER: S-EPMC3346725 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Musical training induces functional plasticity in perceptual and motor networks: insights from resting-state FMRI.

Luo Cheng C Guo Zhi-wei ZW Lai Yong-xiu YX Liao Wei W Liu Qiang Q Kendrick Keith M KM Yao De-zhong DZ Li Hong H

PloS one 20120507 5

A number of previous studies have examined music-related plasticity in terms of multi-sensory and motor integration but little is known about the functional and effective connectivity patterns of spontaneous intrinsic activity in these systems during the resting state in musicians. Using functional connectivity and Granger causal analysis, functional and effective connectivity among the motor and multi-sensory (visual, auditory and somatosensory) cortices were evaluated using resting-state funct ...[more]

PMID: 22586478

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Project description:BackgroundMusician's dystonia critically impacts professional musicians' careers as they may lose musical skills, which have been acquired through long and intensive training. Yet the pathophysiology of musician's dystonia and its link to the neural mechanisms supporting musical skills is poorly understood. We tested if resting-state functional connectivity might reflect an aspect of musical skill linked to the pathophysiology of musician's dystonia. We also tested a second hypothesis that the region with altered resting-state functional connectivity might be correlated with a quantitative measure of musical skills.MethodsWe studied 21 patients with musician's dystonia affecting their hands and 34 healthy musicians, using resting-state functional magnetic resonance imaging and behavioral assessment. We tested between-group differences of resting-state functional connectivity throughout the whole brain using independent component analysis.ResultsWe found abnormal basal ganglia resting-state functional connectivity in the putamina of patients with musician's dystonia compared with those of healthy musicians (P = 0.035 corrected for multiple comparisons). We also found that the temporal precision of keystrokes was correlated with basal ganglia functional connectivity in the putamina of healthy pianists (r = 0.72, P = 0.0005), but not in pianists with musician's dystonia (r = -0.11, P = 0.64).ConclusionsWe show that abnormalities of the putamen exist even at rest in musician's dystonia, whereas putaminal abnormality has previously been reported during a task. Moreover, basal ganglia resting-state functional connectivity in the putamen represented training levels in healthy musicians, and its disruption was associated with musician's dystonia. This novel finding hints at the pathophysiological mechanisms by which musician's dystonia follows extensive musical training. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Project description:PurposeMotor function and recovery after stroke likely rely directly on the residual anatomical connections in the brain and its resting-state functional connectivity. Both structural and functional properties of cortical networks after stroke are revealed using multimodal magnetic resonance imaging (MRI). Specifically, functional connectivity MRI (fcMRI) can extract functional networks of the brain at rest, while structural connectivity can be estimated from white matter fiber orientations measured with high angular-resolution diffusion imaging (HARDI). A model that marries these two techniques may be the key to understanding functional recovery after stroke. In this study, a novel set of voxel-level measures of structurofunctional correlations (SFC) was developed and tested in a group of chronic stroke subjects.MethodsA fully automated method is presented for modeling the structure-function relationship of brain connectivity in individuals with stroke. Brains from ten chronic stroke subjects and nine age-matched controls were imaged with a structural T1-weighted scan, resting-state fMRI, and HARDI. Each subject's T1-weighted image was nonlinearly registered to a T1-weighted 152-brain MNI template using a local histogram-matching technique that alleviates distortions caused by brain lesions. Fractional anisotropy maps and mean BOLD images of each subject were separately registered to the individual's T1-weighted image using affine transformations. White matter fiber orientations within each voxel were estimated with the q-ball model, which approximates the orientation distribution function (ODF) from the diffusion-weighted measurements. Deterministic q-ball tractography was performed in order to obtain a set of fiber trajectories. The new structurofunctional correlation method assigns each voxel a new BOLD time course based on a summation of its structural connections with a common fiber length interval. Then, the voxel's original time-course was correlated with this fiber-distance BOLD signal to derive a novel structurofunctional correlation coefficient. These steps were repeated for eight fiber distance intervals, and the maximum of these correlations was used to define an intrinsic structurofunctional correlation (iSFC) index. A network-based SFC map (nSFC) was also developed in order to enhance resting-state functional networks derived from conventional functional connectivity analyses. iSFC and nSFC maps were individually compared between stroke subjects and controls using a voxel-based two-tailed Student's t-test (alpha = 0.01). A linear regression was also performed between the SFC metrics and the Box and Blocks Score, a clinical measure of arm motor function.ResultsSignificant decreases (p < 0.01) in iSFC were found in stroke subjects within functional hubs of the brain, including the precuneus, prefrontal cortex, posterior parietal cortex, and cingulate gyrus. Many of these differences were significantly correlated with the Box and Blocks Score. The nSFC maps of prefrontal networks in control subjects revealed localized increases within the cerebellum, and these enhancements were diminished in stroke subjects. This finding was further supported by a reduction in functional connectivity between the prefrontal cortex and cerebellum. Default-mode network nSFC maps were higher in the contralesional hemisphere of lower-functioning stroke subjects.ConclusionThe results demonstrate that changes after a stroke in both intrinsic and network-based structurofunctional correlations at rest are correlated with motor function, underscoring the importance of residual structural connectivity in cortical networks.

Dataset Information

Musical training induces functional plasticity in perceptual and motor networks: insights from resting-state FMRI.

Publications

Musical training induces functional plasticity in perceptual and motor networks: insights from resting-state FMRI.

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