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Neuroimage. 2017 Dec;163:160-176. doi: 10.1016/j.neuroimage.2017.09.020. Epub 2017 Sep 13.

Replicability of time-varying connectivity patterns in large resting state fMRI samples.

Author information

1
The Mind Research Network, Albuquerque, NM, USA; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA. Electronic address: aabrol@unm.edu.
2
The Mind Research Network, Albuquerque, NM, USA; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA.
3
The Mind Research Network, Albuquerque, NM, USA.

Abstract

The past few years have seen an emergence of approaches that leverage temporal changes in whole-brain patterns of functional connectivity (the chronnectome). In this chronnectome study, we investigate the replicability of the human brain's inter-regional coupling dynamics during rest by evaluating two different dynamic functional network connectivity (dFNC) analysis frameworks using 7 500 functional magnetic resonance imaging (fMRI) datasets. To quantify the extent to which the emergent functional connectivity (FC) patterns are reproducible, we characterize the temporal dynamics by deriving several summary measures across multiple large, independent age-matched samples. Reproducibility was demonstrated through the existence of basic connectivity patterns (FC states) amidst an ensemble of inter-regional connections. Furthermore, application of the methods to conservatively configured (statistically stationary, linear and Gaussian) surrogate datasets revealed that some of the studied state summary measures were indeed statistically significant and also suggested that this class of null model did not explain the fMRI data fully. This extensive testing of reproducibility of similarity statistics also suggests that the estimated FC states are robust against variation in data quality, analysis, grouping, and decomposition methods. We conclude that future investigations probing the functional and neurophysiological relevance of time-varying connectivity assume critical importance.

KEYWORDS:

Dynamic functional connectivity; Fuzzy meta-state; Hard clustering; Replicability; Sliding window method; Surrogate testing

PMID:
28916181
PMCID:
PMC5775892
DOI:
10.1016/j.neuroimage.2017.09.020
[Indexed for MEDLINE]
Free PMC Article

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