Conditional Granger Causality Analysis of Effective Connectivity during Motor Imagery and Motor Execution in Stroke Patients
Aims. Motor imagery has emerged as a promising technique for the improvement of motor function following stroke, but the mechanism of functional network reorganization in patients during this process remains unclear. The aim of this study is to evaluate the cortical motor network patterns of effecti...
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| creator | Liu, Hongliang Yan, Rubing Zhang, Ye Zhang, Jing-na Wang, Li Qiu, Ming-guo |
| description | Aims. Motor imagery has emerged as a promising technique for the improvement of motor function following stroke, but the mechanism of functional network reorganization in patients during this process remains unclear. The aim of this study is to evaluate the cortical motor network patterns of effective connectivity in stroke patients. Methods. Ten stroke patients with right hand hemiplegia and ten normal control subjects were recruited. We applied conditional Granger causality analysis (CGCA) to explore and compare the functional connectivity between motor execution and motor imagery. Results. Compared with the normal controls, the patient group showed lower effective connectivity to the primary motor cortex (M1), the premotor cortex (PMC), and the supplementary motor area (SMA) in the damaged hemisphere but stronger effective connectivity to the ipsilesional PMC and M1 in the intact hemisphere during motor execution. There were tighter connections in the cortical motor network in the patients than in the controls during motor imagery, and the patients showed more effective connectivity in the intact hemisphere. Conclusions. The increase in effective connectivity suggests that motor imagery enhances core corticocortical interactions, promotes internal interaction in damaged hemispheres in stroke patients, and may facilitate recovery of motor function. |
| doi_str_mv | 10.1155/2016/3870863 |
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Motor imagery has emerged as a promising technique for the improvement of motor function following stroke, but the mechanism of functional network reorganization in patients during this process remains unclear. The aim of this study is to evaluate the cortical motor network patterns of effective connectivity in stroke patients. Methods. Ten stroke patients with right hand hemiplegia and ten normal control subjects were recruited. We applied conditional Granger causality analysis (CGCA) to explore and compare the functional connectivity between motor execution and motor imagery. Results. Compared with the normal controls, the patient group showed lower effective connectivity to the primary motor cortex (M1), the premotor cortex (PMC), and the supplementary motor area (SMA) in the damaged hemisphere but stronger effective connectivity to the ipsilesional PMC and M1 in the intact hemisphere during motor execution. There were tighter connections in the cortical motor network in the patients than in the controls during motor imagery, and the patients showed more effective connectivity in the intact hemisphere. Conclusions. The increase in effective connectivity suggests that motor imagery enhances core corticocortical interactions, promotes internal interaction in damaged hemispheres in stroke patients, and may facilitate recovery of motor function.</description><identifier>ISSN: 2314-6133</identifier><identifier>EISSN: 2314-6141</identifier><identifier>DOI: 10.1155/2016/3870863</identifier><identifier>PMID: 27200373</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Brain ; Causality ; Comparative analysis ; Connectome - methods ; Data Interpretation, Statistical ; Electroencephalography - methods ; Evoked Potentials, Motor ; Experiments ; Female ; Humans ; Imagination ; Male ; Middle Aged ; Motor ability ; Motor Cortex - physiopathology ; Movement ; Neural Pathways - physiopathology ; Patients ; Physical therapy ; Reproducibility of Results ; Sensitivity and Specificity ; Software ; Stroke ; Stroke - physiopathology ; Stroke patients ; Time series</subject><ispartof>BioMed research international, 2016-01, Vol.2016 (2016), p.1-9</ispartof><rights>Copyright © 2016 Li Wang et al.</rights><rights>COPYRIGHT 2016 John Wiley & Sons, Inc.</rights><rights>Copyright © 2016 Li Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><rights>Copyright © 2016 Li Wang et al. 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c598t-539d725ab34f8ed20c66ae65b6d192c24c27d2869e871034fd2891361fba878c3</citedby><cites>FETCH-LOGICAL-c598t-539d725ab34f8ed20c66ae65b6d192c24c27d2869e871034fd2891361fba878c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4854998/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4854998/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27200373$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Kirino, Eiji</contributor><creatorcontrib>Liu, Hongliang</creatorcontrib><creatorcontrib>Yan, Rubing</creatorcontrib><creatorcontrib>Zhang, Ye</creatorcontrib><creatorcontrib>Zhang, Jing-na</creatorcontrib><creatorcontrib>Wang, Li</creatorcontrib><creatorcontrib>Qiu, Ming-guo</creatorcontrib><title>Conditional Granger Causality Analysis of Effective Connectivity during Motor Imagery and Motor Execution in Stroke Patients</title><title>BioMed research international</title><addtitle>Biomed Res Int</addtitle><description>Aims. Motor imagery has emerged as a promising technique for the improvement of motor function following stroke, but the mechanism of functional network reorganization in patients during this process remains unclear. The aim of this study is to evaluate the cortical motor network patterns of effective connectivity in stroke patients. Methods. Ten stroke patients with right hand hemiplegia and ten normal control subjects were recruited. We applied conditional Granger causality analysis (CGCA) to explore and compare the functional connectivity between motor execution and motor imagery. Results. Compared with the normal controls, the patient group showed lower effective connectivity to the primary motor cortex (M1), the premotor cortex (PMC), and the supplementary motor area (SMA) in the damaged hemisphere but stronger effective connectivity to the ipsilesional PMC and M1 in the intact hemisphere during motor execution. There were tighter connections in the cortical motor network in the patients than in the controls during motor imagery, and the patients showed more effective connectivity in the intact hemisphere. Conclusions. The increase in effective connectivity suggests that motor imagery enhances core corticocortical interactions, promotes internal interaction in damaged hemispheres in stroke patients, and may facilitate recovery of motor function.</description><subject>Brain</subject><subject>Causality</subject><subject>Comparative analysis</subject><subject>Connectome - methods</subject><subject>Data Interpretation, Statistical</subject><subject>Electroencephalography - methods</subject><subject>Evoked Potentials, Motor</subject><subject>Experiments</subject><subject>Female</subject><subject>Humans</subject><subject>Imagination</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Motor ability</subject><subject>Motor Cortex - physiopathology</subject><subject>Movement</subject><subject>Neural Pathways - physiopathology</subject><subject>Patients</subject><subject>Physical therapy</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Software</subject><subject>Stroke</subject><subject>Stroke - physiopathology</subject><subject>Stroke patients</subject><subject>Time series</subject><issn>2314-6133</issn><issn>2314-6141</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNkstrVDEYxS-i2FK7cy0BN4KOzePmtRGGYayFioK6Dpk8pql3kprkVgf84811xrG6ajb58uWXk-Rwuu4pgq8RovQMQ8TOiOBQMPKgO8YE9TOGevTwUBNy1J2Wcg3bEIhByR53R5hjCAknx93PRYo21JCiHsB51nHtMljosegh1C2Yt_a2hAKSB0vvnanh1oF2Jv4uJ8SOOcQ1eJ9qyuBio5vAFuho953lD2fGSR-ECD7VnL468FHX4GItT7pHXg_Fne7nk-7L2-XnxbvZ5Yfzi8X8cmaoFHVGibQcU70ivRfOYmgY047RFbNIYoN7g7nFgkknOIINaguJCEN-pQUXhpx0b3a6N-Nq46xpd2c9qJscNjpvVdJB_bsTw5Vap1vVC9pLKZrAi71ATt9GV6rahGLcMOjo0lgU4rIZyySX90L7hjLY0Of_oddpzM3xiRKUU9RD9Jda68GpEH1qTzSTqJpTDDnqJZ60Xu0ok1Mp2fnD7xBUU1TUFBW1j0rDn9115AD_CUYDXu6AqxCt_h7uKeca47y-Q0veTCS_ADvwz3w</recordid><startdate>20160101</startdate><enddate>20160101</enddate><creator>Liu, Hongliang</creator><creator>Yan, Rubing</creator><creator>Zhang, Ye</creator><creator>Zhang, Jing-na</creator><creator>Wang, Li</creator><creator>Qiu, Ming-guo</creator><general>Hindawi Publishing Corporation</general><general>John Wiley & Sons, Inc</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7QO</scope><scope>7T7</scope><scope>7TK</scope><scope>7U7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20160101</creationdate><title>Conditional Granger Causality Analysis of Effective Connectivity during Motor Imagery and Motor Execution in Stroke Patients</title><author>Liu, Hongliang ; Yan, Rubing ; Zhang, Ye ; Zhang, Jing-na ; Wang, Li ; Qiu, Ming-guo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c598t-539d725ab34f8ed20c66ae65b6d192c24c27d2869e871034fd2891361fba878c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Brain</topic><topic>Causality</topic><topic>Comparative analysis</topic><topic>Connectome - methods</topic><topic>Data Interpretation, Statistical</topic><topic>Electroencephalography - methods</topic><topic>Evoked Potentials, Motor</topic><topic>Experiments</topic><topic>Female</topic><topic>Humans</topic><topic>Imagination</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Motor ability</topic><topic>Motor Cortex - physiopathology</topic><topic>Movement</topic><topic>Neural Pathways - physiopathology</topic><topic>Patients</topic><topic>Physical therapy</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Software</topic><topic>Stroke</topic><topic>Stroke - physiopathology</topic><topic>Stroke patients</topic><topic>Time series</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Hongliang</creatorcontrib><creatorcontrib>Yan, Rubing</creatorcontrib><creatorcontrib>Zhang, Ye</creatorcontrib><creatorcontrib>Zhang, Jing-na</creatorcontrib><creatorcontrib>Wang, Li</creatorcontrib><creatorcontrib>Qiu, Ming-guo</creatorcontrib><collection>الدوريات العلمية والإحصائية - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BioMed research international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Hongliang</au><au>Yan, Rubing</au><au>Zhang, Ye</au><au>Zhang, Jing-na</au><au>Wang, Li</au><au>Qiu, Ming-guo</au><au>Kirino, Eiji</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Conditional Granger Causality Analysis of Effective Connectivity during Motor Imagery and Motor Execution in Stroke Patients</atitle><jtitle>BioMed research international</jtitle><addtitle>Biomed Res Int</addtitle><date>2016-01-01</date><risdate>2016</risdate><volume>2016</volume><issue>2016</issue><spage>1</spage><epage>9</epage><pages>1-9</pages><issn>2314-6133</issn><eissn>2314-6141</eissn><abstract>Aims. Motor imagery has emerged as a promising technique for the improvement of motor function following stroke, but the mechanism of functional network reorganization in patients during this process remains unclear. The aim of this study is to evaluate the cortical motor network patterns of effective connectivity in stroke patients. Methods. Ten stroke patients with right hand hemiplegia and ten normal control subjects were recruited. We applied conditional Granger causality analysis (CGCA) to explore and compare the functional connectivity between motor execution and motor imagery. Results. Compared with the normal controls, the patient group showed lower effective connectivity to the primary motor cortex (M1), the premotor cortex (PMC), and the supplementary motor area (SMA) in the damaged hemisphere but stronger effective connectivity to the ipsilesional PMC and M1 in the intact hemisphere during motor execution. There were tighter connections in the cortical motor network in the patients than in the controls during motor imagery, and the patients showed more effective connectivity in the intact hemisphere. Conclusions. The increase in effective connectivity suggests that motor imagery enhances core corticocortical interactions, promotes internal interaction in damaged hemispheres in stroke patients, and may facilitate recovery of motor function.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><pmid>27200373</pmid><doi>10.1155/2016/3870863</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Brain Causality Comparative analysis Connectome - methods Data Interpretation, Statistical Electroencephalography - methods Evoked Potentials, Motor Experiments Female Humans Imagination Male Middle Aged Motor ability Motor Cortex - physiopathology Movement Neural Pathways - physiopathology Patients Physical therapy Reproducibility of Results Sensitivity and Specificity Software Stroke Stroke - physiopathology Stroke patients Time series |
| title | Conditional Granger Causality Analysis of Effective Connectivity during Motor Imagery and Motor Execution in Stroke Patients |
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