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dc.contributor.author임창환-
dc.date.accessioned2019-12-04T02:22:45Z-
dc.date.available2019-12-04T02:22:45Z-
dc.date.issued2018-01-
dc.identifier.citationPLOS ONE, v. 13, no. 1, Article no. e190715en_US
dc.identifier.issn1932-6203-
dc.identifier.urihttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0190715-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/117071-
dc.description.abstractBackgroundRecent studies of functional or effective connectivity in the brain have reported that motor-related brain regions were activated during motor execution and motor imagery, but the relationship between motor and cognitive areas has not yet been completely understood. The objectives of our study were to analyze the effective connectivity between motor and cognitive networks in order to define network dynamics during motor execution and motor imagery in healthy individuals. Second, we analyzed the differences in effective connectivity between correct and incorrect responses during motor execution and imagery using dynamic causal modeling (DCM) of electroencephalography (EEG) data.MethodTwenty healthy subjects performed a sequence of finger tapping trials using either motor execution or motor imagery, and the performances were recorded. Changes in effective connectivity between the primary motor cortex (M1), supplementary motor area (SMA), premotor cortex (PMC), and dorsolateral prefrontal cortex (DLPFC) were estimated using dynamic causal modeling. Bayesian model averaging with family-level inference and fixed-effects analysis was applied to determine the most likely connectivity model for these regions.ResultsMotor execution and imagery showed inputs to distinct brain regions, the premotor cortex and the supplementary motor area, respectively. During motor execution, the coupling strength of a feedforward network from the DLPFC to the PMC was greater than that during motor imagery. During motor imagery, the coupling strengths of a feedforward network from the PMC to the SMA and of a feedback network from M1 to the PMC were higher than that during motor execution. In imagined movement, although there were connectivity differences between correct and incorrect task responses, each motor imagery task that included correct and incorrect responses showed similar network connectivity characteristics. Correct motor imagery responses showed connectivity from the PMC to the DLPFC, while the incorrect responses had characteristic connectivity from the SMA to the DLPFC.ConclusionsThese findings provide an understanding of effective connectivity between motor and cognitive areas during motor execution and imagery as well as the basis for future connectivity studies for patients with stroke.en_US
dc.description.sponsorshipThis study was supported by the National Research Foundation of Korea grant funded by the Korean government (NRF-2017R1A2A1A05000730 to YHK). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (NRF-2017R1A2A1A05000730).en_US
dc.language.isoen_USen_US
dc.publisherPUBLIC LIBRARY SCIENCEen_US
dc.subjectPOSITRON-EMISSION-TOMOGRAPHYen_US
dc.subjectFUNCTIONAL-ANATOMYen_US
dc.subjectMOVEMENTSen_US
dc.subjectBRAINen_US
dc.subjectEEGen_US
dc.subjectSUPPLEMENTARYen_US
dc.subjectORGANIZATIONen_US
dc.subjectHUMANSen_US
dc.subjectSYSTEMen_US
dc.subjectCORTEXen_US
dc.titleChanges in network connectivity during motor imagery and executionChanges in network connectivity during motor imagery and executionen_US
dc.typeArticleen_US
dc.relation.noe0190715-
dc.relation.volume13-
dc.identifier.doi10.1371/journal.pone.0190715-
dc.relation.page1-18-
dc.relation.journalPLOS ONE-
dc.contributor.googleauthorKim, Yun Kwan-
dc.contributor.googleauthorPark, Eunhee-
dc.contributor.googleauthorLee, Ahee-
dc.contributor.googleauthorIm, Chang-Hwan-
dc.contributor.googleauthorKim, Yun-Hee-
dc.relation.code2018006288-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDIVISION OF ELECTRICAL AND BIOMEDICAL ENGINEERING-
dc.identifier.pidich-


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