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dc.contributor.authorDeDora, Daniel J.en_US
dc.contributor.authorNedic, Sanjaen_US
dc.contributor.authorKatti, Prathaen_US
dc.contributor.authorArnab, Shafiqueen_US
dc.contributor.authorWald, Lawrence L.en_US
dc.contributor.authorTakahashi, Atsushien_US
dc.contributor.authorVan Dijk, Koene R. A.en_US
dc.contributor.authorStrey, Helmut H.en_US
dc.contributor.authorMujica-Parodi, Lilianne R.en_US
dc.date.accessioned2016-06-14T18:52:41Z
dc.date.issued2016en_US
dc.identifier.citationDeDora, Daniel J., Sanja Nedic, Pratha Katti, Shafique Arnab, Lawrence L. Wald, Atsushi Takahashi, Koene R. A. Van Dijk, Helmut H. Strey, and Lilianne R. Mujica-Parodi. 2016. “Signal Fluctuation Sensitivity: An Improved Metric for Optimizing Detection of Resting-State fMRI Networks.” Frontiers in Neuroscience 10 (1): 180. doi:10.3389/fnins.2016.00180. http://dx.doi.org/10.3389/fnins.2016.00180.en
dc.identifier.issn1662-4548en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:27320380
dc.description.abstractTask-free connectivity analyses have emerged as a powerful tool in functional neuroimaging. Because the cross-correlations that underlie connectivity measures are sensitive to distortion of time-series, here we used a novel dynamic phantom to provide a ground truth for dynamic fidelity between blood oxygen level dependent (BOLD)-like inputs and fMRI outputs. We found that the de facto quality-metric for task-free fMRI, temporal signal to noise ratio (tSNR), correlated inversely with dynamic fidelity; thus, studies optimized for tSNR actually produced time-series that showed the greatest distortion of signal dynamics. Instead, the phantom showed that dynamic fidelity is reasonably approximated by a measure that, unlike tSNR, dissociates signal dynamics from scanner artifact. We then tested this measure, signal fluctuation sensitivity (SFS), against human resting-state data. As predicted by the phantom, SFS—and not tSNR—is associated with enhanced sensitivity to both local and long-range connectivity within the brain's default mode network.en
dc.language.isoen_USen
dc.publisherFrontiers Media S.A.en
dc.relation.isversionofdoi:10.3389/fnins.2016.00180en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4854902/pdf/en
dash.licenseLAAen_US
dc.subjectMethodsen
dc.subjectFunctional MRIen
dc.subjectsignal fluctuation sensitivityen
dc.subjectresting state connectivityen
dc.subjecttemporal signal to noise ratioen
dc.subjectdynamic phantomen
dc.subjectfidelityen
dc.titleSignal Fluctuation Sensitivity: An Improved Metric for Optimizing Detection of Resting-State fMRI Networksen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalFrontiers in Neuroscienceen
dash.depositing.authorWald, Lawrence L.en_US
dc.date.available2016-06-14T18:52:41Z
dc.identifier.doi10.3389/fnins.2016.00180*
dash.contributor.affiliatedVan Dijk, Koene R. A.
dash.contributor.affiliatedWald, Lawrence


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