Reconstruction of Arm Movement Directions from Human Motor Cortex Using fMRI

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dc.contributor.authorNam, Seungkyuko
dc.contributor.authorKim, Dae-Shikko
dc.date.accessioned2017-08-23T06:39:43Z-
dc.date.available2017-08-23T06:39:43Z-
dc.date.created2017-08-21-
dc.date.created2017-08-21-
dc.date.created2017-08-21-
dc.date.issued2017-07-
dc.identifier.citationFRONTIERS IN NEUROSCIENCE, v.11, no.434, pp.1 - 12-
dc.identifier.issn1662-453X-
dc.identifier.urihttp://hdl.handle.net/10203/225483-
dc.description.abstractRecent advances in functional magnetic resonance imaging (fMRI) have been used to reconstruct cognitive states based on brain activity evoked by sensory or cognitive stimuli. To date, such decoding paradigms were mostly used for visual modalities. On the other hand, reconstructing functional brain activity in motor areas was primarily achieved through more invasive electrophysiological techniques. Here, we investigated whether non-invasive fMRI responses from human motor cortex can also be used to predict individual arm movements. To this end, we conducted fMRI studies in which participants moved their arm from a center position to one of eight target directions. Our results suggest that arm movement directions can be distinguished from the multivoxel patterns of fMRI responses in motor cortex. Furthermore, compared to multivoxel pattern analysis, encoding models were able to also reconstruct unknown movement directions from the predicted brain activity. We conclude for our study that non-invasive fMRI signal can be utilized to predict directional motor movements in human motor cortex.-
dc.languageEnglish-
dc.publisherFRONTIERS MEDIA SA-
dc.titleReconstruction of Arm Movement Directions from Human Motor Cortex Using fMRI-
dc.typeArticle-
dc.identifier.wosid000406597000001-
dc.identifier.scopusid2-s2.0-85026669638-
dc.type.rimsART-
dc.citation.volume11-
dc.citation.issue434-
dc.citation.beginningpage1-
dc.citation.endingpage12-
dc.citation.publicationnameFRONTIERS IN NEUROSCIENCE-
dc.identifier.doi10.3389/fnins.2017.00434-
dc.contributor.localauthorKim, Dae-Shik-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
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