Literature DB >> 29249372

Neural coupling between contralesional motor and frontoparietal networks correlates with motor ability in individuals with chronic stroke.

Timothy K Lam1, Deirdre R Dawson2, Kie Honjo3, Bernhard Ross4, Malcolm A Binns5, Donald T Stuss6, Sandra E Black7, J Jean Chen4, Brian T Levine8, Takako Fujioka9, Joyce L Chen10.   

Abstract

Movement is traditionally viewed as a process that involves motor brain regions. However, movement also implicates non-motor regions such as prefrontal and parietal cortex, regions whose integrity may thus be important for motor recovery after stroke. Importantly, focal brain damage can affect neural functioning within and between distinct brain networks implicated in the damage. The aim of this study is to investigate how resting state connectivity (rs-connectivity) within and between motor and frontoparietal networks are affected post-stroke in correlation with motor outcome. Twenty-seven participants with chronic stroke with unilateral upper limb deficits underwent motor assessments and magnetic resonance imaging. Participants completed the Chedoke-McMaster Stroke Assessment as a measure of arm (CMSA-Arm) and hand (CMSA-Hand) impairment and the Action Research Arm Test (ARAT) as a measure of motor function. We used a seed-based rs-connectivity approach defining the motor (seed=contralesional primary motor cortex (M1)) and frontoparietal (seed=contralesional dorsolateral prefrontal cortex (DLPFC)) networks. We analyzed the rs-connectivity within each network (intra-network connectivity) and between both networks (inter-network connectivity), and performed correlations between: a) intra-network connectivity and motor assessment scores; b) inter-network connectivity and motor assessment scores. We found: a) Participants with high rs-connectivity within the motor network (between M1 and supplementary motor area) have higher CMSA-Hand stage (z=3.62, p=0.003) and higher ARAT score (z=3.41, p=0.02). Rs-connectivity within the motor network was not significantly correlated with CMSA-Arm stage (z=1.83, p>0.05); b) Participants with high rs-connectivity within the frontoparietal network (between DLPFC and mid-ventrolateral prefrontal cortex) have higher CMSA-Hand stage (z=3.64, p=0.01). Rs-connectivity within the frontoparietal network was not significantly correlated with CMSA-Arm stage (z=0.93, p=0.03) or ARAT score (z=2.53, p=0.05); and c) Participants with high rs-connectivity between motor and frontoparietal networks have higher CMSA-Hand stage (rs=0.54, p=0.01) and higher ARAT score (rs=0.54, p=0.009). Rs-connectivity between the motor and frontoparietal networks was not significantly correlated with CMSA-Arm stage (rs=0.34, p=0.13). Taken together, the connectivity within and between the motor and frontoparietal networks correlate with motor outcome post-stroke. The integrity of these regions may be important for an individual's motor outcome. Motor-frontoparietal connectivity may be a potential biomarker of motor recovery post-stroke.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Chronic stroke; Frontoparietal network; Function; Impairment; Motor network; Resting state fMRI

Mesh:

Year:  2017        PMID: 29249372     DOI: 10.1016/j.jns.2017.11.007

Source DB:  PubMed          Journal:  J Neurol Sci        ISSN: 0022-510X            Impact factor:   3.181


  9 in total

1.  Effects of thalamic infarction on the structural and functional connectivity of the ipsilesional primary somatosensory cortex.

Authors:  Li Chen; Tianyou Luo; Kangcheng Wang; Yong Zhang; Dandan Shi; Fajin Lv; Yang Li; Yongmei Li; Qi Li; Weidong Fang; Zhiwei Zhang; Juan Peng; Hanfeng Yang
Journal:  Eur Radiol       Date:  2019-03-06       Impact factor: 5.315

2.  Brain-Machine Interface Induced Morpho-Functional Remodeling of the Neural Motor System in Severe Chronic Stroke.

Authors:  Andrea Caria; Josué Luiz Dalboni da Rocha; Giuseppe Gallitto; Niels Birbaumer; Ranganatha Sitaram; Ander Ramos Murguialday
Journal:  Neurotherapeutics       Date:  2020-04       Impact factor: 7.620

3.  Dynamics of Top-Down Control and Motor Networks in Parkinson's Disease.

Authors:  Li Chen; Patrick Bedard; Mark Hallett; Silvina G Horovitz
Journal:  Mov Disord       Date:  2021-01-06       Impact factor: 9.698

4.  Deep Brain Stimulation Modulates Multiple Abnormal Resting-State Network Connectivity in Patients With Parkinson's Disease.

Authors:  Yutong Bai; Yu Diao; Lu Gan; Zhizheng Zhuo; Zixiao Yin; Tianqi Hu; Dan Cheng; Hutao Xie; Delong Wu; Houyou Fan; Quan Zhang; Yunyun Duan; Fangang Meng; Yaou Liu; Yin Jiang; Jianguo Zhang
Journal:  Front Aging Neurosci       Date:  2022-03-21       Impact factor: 5.750

5.  Neural substrates in patients with visual-spatial neglect recovering from right-hemispheric stroke.

Authors:  Lei Cao; Linlin Ye; Huanxin Xie; Yichen Zhang; Weiqun Song
Journal:  Front Neurosci       Date:  2022-08-18       Impact factor: 5.152

6.  Aberrant interhemispheric functional reciprocities of the default mode network and motor network in subcortical ischemic stroke patients with motor impairment: A longitudinal study.

Authors:  Yongxin Li; Zeyun Yu; Xuan Zhou; Ping Wu; Jiaxu Chen
Journal:  Front Neurol       Date:  2022-10-04       Impact factor: 4.086

7.  Effective connectivity differences in motor network during passive movement of paretic and non-paretic ankles in subacute stroke patients.

Authors:  Marianna Nagy; Csaba Aranyi; Gábor Opposits; Tamás Papp; Levente Lánczi; Ervin Berényi; Csilla Vér; László Csiba; Péter Katona; Tamás Spisák; Miklós Emri
Journal:  PeerJ       Date:  2020-05-26       Impact factor: 2.984

Review 8.  A New Framework to Interpret Individual Inter-Hemispheric Compensatory Communication after Stroke.

Authors:  Arianna Brancaccio; Davide Tabarelli; Paolo Belardinelli
Journal:  J Pers Med       Date:  2022-01-06

9.  Early motor network connectivity after stroke: An interplay of general reorganization and state-specific compensation.

Authors:  Theresa Paul; Lukas Hensel; Anne K Rehme; Caroline Tscherpel; Simon B Eickhoff; Gereon R Fink; Christian Grefkes; Lukas J Volz
Journal:  Hum Brain Mapp       Date:  2021-08-04       Impact factor: 5.038

  9 in total

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