Literature DB >> 19853664

Effective connectivity of neural networks in automatic movements in Parkinson's disease.

Tao Wu1, Piu Chan, Mark Hallett.   

Abstract

Patients with Parkinson's disease (PD) have difficulty in performing learned movements automatically. The neural mechanism of this deficiency remains unclear. In the current study, we used functional MRI (fMRI) and psychophysiological interaction (PPI) methods to investigate the changes in effective connectivity of the brain networks when movements become automatic in PD patients and age-matched normal controls. We found that during automaticity, the rostral supplementary motor area, cerebellum, and cingulate motor area had increased effective connectivity with brain networks in PD patients. In controls, in addition to these regions, the putamen also had automaticity-related strengthened interactions with brain networks. The dorsal lateral prefrontal cortex had more connectivity at the novel stage than in the automatic stage in normal subjects, but not in PD patients. The comparison of the PPI results between the groups showed that the rostral supplementary motor area, cerebellum, and cingulate motor area had significantly more increased effective connectivity with several regions in normal subjects than in PD. The changes of effective connectivity in some areas negatively correlated with the Unified Parkinson's Disease Rating Scale (UPDRS). Our findings show that some of the factors related to PD patients having difficulty achieving automaticity are less efficient neural coding of movement and failure to shift execution of automatic movements more subcortically. The changes of effective connectivity become more abnormal as the disorder progresses. In addition, in PD, the connections of the attentional networks are altered. Published by Elsevier Inc.

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Year:  2009        PMID: 19853664      PMCID: PMC2818456          DOI: 10.1016/j.neuroimage.2009.10.051

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  32 in total

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Journal:  J Neurol       Date:  1994-08       Impact factor: 4.849

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  39 in total

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Authors:  Tao Wu; Jun Liu; Hejia Zhang; Mark Hallett; Zheng Zheng; Piu Chan
Journal:  Cereb Cortex       Date:  2014-06-12       Impact factor: 5.357

5.  Movement chunking during sequence learning is a dopamine-dependant process: a study conducted in Parkinson's disease.

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Journal:  Exp Brain Res       Date:  2010-08-03       Impact factor: 1.972

6.  Motor sequence learning-induced neural efficiency in functional brain connectivity.

Authors:  Helmet T Karim; Theodore J Huppert; Kirk I Erickson; Mariegold E Wollam; Patrick J Sparto; Ervin Sejdić; Jessie M VanSwearingen
Journal:  Behav Brain Res       Date:  2016-11-11       Impact factor: 3.332

Review 7.  Motor automaticity in Parkinson's disease.

Authors:  Tao Wu; Mark Hallett; Piu Chan
Journal:  Neurobiol Dis       Date:  2015-06-21       Impact factor: 5.996

Review 8.  Aging, motor skill, and the energy cost of walking: implications for the prevention and treatment of mobility decline in older persons.

Authors:  Jessie M VanSwearingen; Stephanie A Studenski
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2014-09-02       Impact factor: 6.053

Review 9.  The many facets of motor learning and their relevance for Parkinson's disease.

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Journal:  Clin Neurophysiol       Date:  2017-04-09       Impact factor: 3.708

10.  Preclinical and clinical neural network changes in SCA2 parkinsonism.

Authors:  Tao Wu; Chaodong Wang; Jue Wang; Mark Hallett; Yufeng Zang; Piu Chan
Journal:  Parkinsonism Relat Disord       Date:  2012-09-21       Impact factor: 4.891

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