Links
- ORCID
- Crossref | PDF
- [nrs.harvard.edu] | PDF
- [arxiv.org] | PDF
- [dash.harvard.edu] | PDF
- [dspace.mit.edu] | PDF
- [europepmc.org] | PDF
- [www.researchgate.net] | PDF
- [www.ncbi.nlm.nih.gov] | PDF
- [arxiv.org] | PDF
Tools
Signal Fluctuation Sensitivity: an improved metric for optimizing detection of resting-state fMRI networks
,
Atsushi Takahashi,
Koene R. A. Van Dijk,
Helmut H. Strey,
Lilianne R. Mujica Parodi
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.