1. Signal Fluctuation Sensitivity: an improved metric for optimizing detection of resting-state fMRI networks
- Author
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Daniel J. DeDora, Sanja eNedic, Pratha eKatti, Shafique eArnab, Lawrence L. Wald, Atsushi eTakahashi, Koene RA Van Dijk, Helmut H. Strey, and Lilianne Rivka Mujica-Parodi
- Subjects
fMRI ,functional MRI ,resting state connectivity ,SFS ,Dynamic phantom ,signal fluctuation sensitivity ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - 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.
- Published
- 2016
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