title: Quantifying temporal correlations: a test-retest evaluation of functional connectivity in resting-state fMRI.
abstract: There have been many interpretations of functional connectivity and proposed measures of temporal correlations between BOLD signals across different brain areas. These interpretations yield from many studies on functional connectivity using resting-state fMRI data that have emerged in recent years. However, not all of these studies used the same metrics for quantifying the temporal correlations between brain regions. In this paper, we use a public-domain test-retest resting-state fMRI data set to perform a systematic investigation of the stability of the metrics that are often used in resting-state functional connectivity (FC) studies. The fMRI data set was collected across three different sessions. The second session took place approximately eleven months after the first session, and the third session was an hour after the second session. The FC metrics composed of cross-correlation, partial cross-correlation, cross-coherence, and parameters based on an autoregressive model. We discussed the strengths and weaknesses of each metric. We performed ROI-level and full-brain seed-based voxelwise test-retest analyses using each FC metric to assess its stability. For both ROI-level and voxel-level analyses, we found that cross-correlation yielded more stable measurements than the other metrics. We discussed the consequences of this result on the utility of the FC metrics. We observed that for negatively correlated ROIs, their partial cross-correlation is shrunk towards zero, thus affecting the stability of their FC. For the present data set, we found greater stability in FC between the second and third sessions (one hour between sessions) compared to the first and second sessions (approximately 11months between sessions). Finally, we report that some of the metrics showed a positive association between strength and stability. In summary, the results presented in this paper suggest important implications when choosing metrics for quantifying and assessing various types of functional connectivity for resting-state fMRI studies.
authors.affiliation: Department of Psychiatry, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92037, USA. mfiecas@ucsd.edu
authors.forename: Mark
authors.initials: M
authors.lastname: Fiecas
authors.forename: Hernando
authors.initials: H
authors.lastname: Ombao
authors.forename: Dan
authors.initials: D
authors.lastname: van Lunen
authors.forename: Richard
authors.initials: R
authors.lastname: Baumgartner
authors.forename: Alexandre
authors.initials: A
authors.lastname: Coimbra
authors.forename: Dai
authors.initials: D
authors.lastname: Feng
mesh_terms: D000328:Adult; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009434:Neural Pathways / Q000502:physiology*; D015203:Reproducibility of Results; D012146:Rest / Q000502:physiology