Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-7811
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dc.contributor.authorSchmüser, Lena-
dc.contributor.authorSebastian, Alexandra-
dc.contributor.authorMobascher, Arian-
dc.contributor.authorLieb, Klaus-
dc.contributor.authorTüscher, Oliver-
dc.contributor.authorFeige, Bernd-
dc.date.accessioned2022-10-04T09:39:40Z-
dc.date.available2022-10-04T09:39:40Z-
dc.date.issued2014-
dc.identifier.urihttps://openscience.ub.uni-mainz.de/handle/20.500.12030/7826-
dc.description.abstractDue to its millisecond-scale temporal resolution, EEG allows to assess neural correlates with precisely defined temporal relationship relative to a given event. This knowledge is generally lacking in data from functional magnetic resonance imaging (fMRI) which has a temporal resolution on the scale of seconds so that possibilities to combine the two modalities are sought. Previous applications combining event-related potentials (ERPs) with simultaneous fMRI BOLD generally aimed at measuring known ERP components in single trials and correlate the resulting time series with the fMRI BOLD signal. While it is a valuable first step, this procedure cannot guarantee that variability of the chosen ERP component is specific for the targeted neurophysiological process on the group and single subject level. Here we introduce a newly developed data-driven analysis procedure that automatically selects task-specific electrophysiological independent components (ICs). We used single-trial simultaneous EEG/fMRI analysis of a visual Go/Nogo task to assess inhibition-related EEG components, their trial-to-trial amplitude variability, and the relationship between this variability and the fMRI. Single-trial EEG/fMRI analysis within a subgroup of 22 participants revealed positive correlations of fMRI BOLD signal with EEG-derived regressors in fronto-striatal regions which were more pronounced in an early compared to a late phase of task execution. In sum, selecting Nogo-related ICs in an automated, single subject procedure reveals fMRI-BOLD responses correlated to different phases of task execution. Furthermore, to illustrate utility and generalizability of the method beyond detecting the presence or absence of reliable inhibitory components in the EEG, we show that the IC selection can be extended to other events in the same dataset, e.g., the visual responses.en_GB
dc.description.sponsorshipDFG, Open Access-Publizieren Universität Mainz / Universitätsmedizinde
dc.language.isoengde
dc.rightsCC BY*
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/*
dc.subject.ddc610 Medizinde_DE
dc.subject.ddc610 Medical sciencesen_GB
dc.titleData-driven analysis of simultaneous EEG/fMRI using an ICA approachen_GB
dc.typeZeitschriftenaufsatzde
dc.identifier.doihttp://doi.org/10.25358/openscience-7811-
jgu.type.dinitypearticleen_GB
jgu.type.versionPublished versionde
jgu.type.resourceTextde
jgu.organisation.departmentFB 04 Medizinde
jgu.organisation.number2700-
jgu.organisation.nameJohannes Gutenberg-Universität Mainz-
jgu.rights.accessrightsopenAccess-
jgu.journal.titleFrontiers in neurosciencede
jgu.journal.volume8de
jgu.pages.alternativeArt. 175de
jgu.publisher.year2014-
jgu.publisher.nameFrontiers Research Foundationde
jgu.publisher.placeLausannede
jgu.publisher.urihttp://dx.doi.org/10.3389/fnins.2014.00175de
jgu.publisher.issn1662-453Xde
jgu.publisher.issn1662-4548de
jgu.organisation.placeMainz-
jgu.identifier.pmid25071427-
jgu.subject.ddccode610de
opus.date.modified2018-08-08T09:03:39Z-
opus.subject.dfgcode00-000-
opus.organisation.stringFB 04: Medizin: Psychiatrische Klinik und Poliklinikde_DE
opus.identifier.opusid27369-
opus.importsourcepubmed-
opus.institute.number0432-
opus.metadataonlyfalse-
opus.type.contenttypeKeinede_DE
opus.type.contenttypeNoneen_EN
opus.affiliatedMobascher, Arian-
opus.affiliatedLieb, Klaus-
opus.affiliatedTüscher, Oliver-
jgu.publisher.doi10.3389/fnins.2014.00175de
jgu.organisation.rorhttps://ror.org/023b0x485-
Appears in collections:DFG-OA-Publizieren (2012 - 2017)

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