Signal Fluctuation Sensitivity: An Improved Metric for Optimizing Detection of Resting-State FMRI Networks

Overview

Journal Front Neurosci

Date 2016 May 21

PMID 27199643

Citations 12

Authors

Daniel J DeDora

Sanja Nedic

Pratha Katti

Shafique Arnab

Lawrence L Wald

Atsushi Takahashi

Koene R A Van Dijk

Helmut H Strey

Lilianne R Mujica-Parodi

Affiliations

Soon will be listed here.

Abstract

Task-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.

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