Please use this identifier to cite or link to this item: http://ahro.austin.org.au/austinjspui/handle/1/17659
Title: 7T-fMRI: Faster temporal resolution yields optimal BOLD sensitivity for functional network imaging specifically at high spatial resolution.
Authors: Yoo, Peter E;John, Sam E;Farquharson, Shawna;Cleary, Jon O;Wong, Yan T;Ng, Amanda;Mulcahy, Claire B;Grayden, David B;Ordidge, Roger J;Opie, Nicholas L;O'Brien, Terence J;Oxley, Thomas J;Moffat, Bradford A
Affiliation: Melbourne Brain Centre Imaging Unit, Department of Anatomy and Neuroscience, The University of Melbourne, Parkville, Victoria, Australia
Vascular Bionics Laboratory, Melbourne Brain Centre, Department of Medicine, The University of Melbourne, Victoria, Australia
Department of Electrical & Electronic Engineering, The University of Melbourne, Victoria, Australia
The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
Department of Physiology, Monash University, Clayton, VIC, Australia
Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
Imaging Division, Florey Institute of Neuroscience and Mental Health, Melbourne Brain Centre, Heidelberg, Melbourne, Victoria, Australia
Center for Neural Engineering, The University of Melbourne, Victoria, Australia
Departments of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
NeuroEngineering Laboratory, Department of Electrical &Electronic Engineering, The University of Melbourne, Melbourne, Victoria, Australia
Issue Date: 1-Jan-2018
EDate: 2017-03-08
Citation: NeuroImage 2018; 164: 214-229
Abstract: Recent 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.
URI: http://ahro.austin.org.au/austinjspui/handle/1/17659
DOI: 10.1016/j.neuroimage.2017.03.002
PubMed URL: 28286317
Type: Journal Article
Subjects: 7T, fMRI, sensitivity, temporal resolution
BCI
Classification
Physiological noise
Appears in Collections:Journal articles

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