Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/17659
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dc.contributor.authorYoo, Peter E-
dc.contributor.authorJohn, Sam E-
dc.contributor.authorFarquharson, Shawna-
dc.contributor.authorCleary, Jon O-
dc.contributor.authorWong, Yan T-
dc.contributor.authorNg, Amanda-
dc.contributor.authorMulcahy, Claire B-
dc.contributor.authorGrayden, David B-
dc.contributor.authorOrdidge, Roger J-
dc.contributor.authorOpie, Nicholas L-
dc.contributor.authorO'Brien, Terence J-
dc.contributor.authorOxley, Thomas J-
dc.contributor.authorMoffat, Bradford A-
dc.date2017-03-08-
dc.date.accessioned2018-05-02T23:37:07Z-
dc.date.available2018-05-02T23:37:07Z-
dc.date.issued2018-01-01-
dc.identifier.citationNeuroImage 2018; 164: 214-229-
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/17659-
dc.description.abstractRecent developments in accelerated imaging methods allow faster acquisition of high spatial resolution images. This could improve the applications of functional magnetic resonance imaging at 7 Tesla (7T-fMRI), such as neurosurgical planning and Brain Computer Interfaces (BCIs). However, increasing the spatial and temporal resolution will both lead to signal-to-noise ratio (SNR) losses due to decreased net magnetization per voxel and T1-relaxation effect, respectively. This could potentially offset the SNR efficiency gains made with increasing temporal resolution. We investigated the effects of varying spatial and temporal resolution on fMRI sensitivity measures and their implications on fMRI-based BCI simulations. We compared temporal signal-to-noise ratio (tSNR), observed percent signal change (%∆S), volumes of significant activation, Z-scores and decoding performance of linear classifiers commonly used in BCIs across a range of spatial and temporal resolution images acquired during an ankle-tapping task. Our results revealed an average increase of 22% in %∆S (p=0.006) and 9% in decoding performance (p=0.015) with temporal resolution only at the highest spatial resolution of 1.5×1.5×1.5mm3, despite a 29% decrease in tSNR (p<0.001) and plateaued Z-scores. Further, the volume of significant activation was indifferent (p>0.05) across spatial resolution specifically at the highest temporal resolution of 500ms. These results demonstrate that the overall BOLD sensitivity can be increased significantly with temporal resolution, granted an adequately high spatial resolution with minimal physiological noise level. This shows the feasibility of diffuse motor-network imaging at high spatial and temporal resolution with robust BOLD sensitivity with 7T-fMRI. Importantly, we show that this sensitivity improvement could be extended to an fMRI application such as BCIs.-
dc.language.isoeng-
dc.subject7T, fMRI, sensitivity, temporal resolution-
dc.subjectBCI-
dc.subjectClassification-
dc.subjectPhysiological noise-
dc.title7T-fMRI: Faster temporal resolution yields optimal BOLD sensitivity for functional network imaging specifically at high spatial resolution.-
dc.typeJournal Article-
dc.identifier.journaltitleNeuroImage-
dc.identifier.affiliationMelbourne Brain Centre Imaging Unit, Department of Anatomy and Neuroscience, The University of Melbourne, Parkville, Victoria, Australia-
dc.identifier.affiliationVascular Bionics Laboratory, Melbourne Brain Centre, Department of Medicine, The University of Melbourne, Victoria, Australia-
dc.identifier.affiliationDepartment of Electrical & Electronic Engineering, The University of Melbourne, Victoria, Australia-
dc.identifier.affiliationThe Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia-
dc.identifier.affiliationDepartment of Physiology, Monash University, Clayton, Victoria, Australia-
dc.identifier.affiliationBiomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia-
dc.identifier.affiliationImaging Division, Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia-
dc.identifier.affiliationCenter for Neural Engineering, The University of Melbourne, Victoria, Australia-
dc.identifier.affiliationDepartments of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia-
dc.identifier.affiliationNeuroEngineering Laboratory, Department of Electrical &Electronic Engineering, The University of Melbourne, Melbourne, Victoria, Australia-
dc.identifier.doi10.1016/j.neuroimage.2017.03.002-
dc.identifier.pubmedid28286317-
dc.type.austinJournal Article-
local.name.researcherFarquharson, Shawna
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeJournal Article-
item.grantfulltextnone-
crisitem.author.deptThe Florey Institute of Neuroscience and Mental Health-
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