Dynamic fluctuations coincide with periods of high and low modularity in resting-state functional brain networks

NeuroImage, Journal Year: 2015, Volume and Issue: 127, P. 287 - 297

Published: Dec. 15, 2015

We investigate the relationship of resting-state fMRI functional connectivity estimated over long periods time with time-varying shorter intervals. show that using Pearson's correlation to estimate implies range fluctuations connections short scales is subject statistical constraints imposed by their strength longer scales. present a method for estimating designed mitigate this issue and allows us identify episodes where are unexpectedly strong or weak. apply data recorded from $N=80$ participants, number strong/weak fluctuates time, these variations coincide intermittent high low modularity in connectivity. also find during relative quiescence regions associated default mode network tend join communities attentional, control, primary sensory systems. In contrast, many strong/weak, dissociate form distinct modules. Finally, we go on that, while all can at times manifest stronger (more positively correlated) weaker negatively than expected, small connections, mostly within visual somatomotor networks, do so disproportional times. Our approach detection fluctuate more less expected based long-time averages may be use future studies characterizing spatio-temporal patterns

Language: Английский

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Human Connectomics across the Life Span

Trends in Cognitive Sciences, Journal Year: 2016, Volume and Issue: 21(1), P. 32 - 45

Published: Nov. 16, 2016

Language: Английский

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Towards understanding rTMS mechanism of action: Stimulation of the DLPFC causes network-specific increase in functional connectivity

NeuroImage, Journal Year: 2017, Volume and Issue: 162, P. 289 - 296

Published: Sept. 12, 2017

Language: Английский

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

NeuroImage, Journal Year: 2017, Volume and Issue: 163, P. 160 - 176

Published: Sept. 13, 2017

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

Language: Английский

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Consistency-based thresholding of the human connectome

NeuroImage, Journal Year: 2016, Volume and Issue: 145, P. 118 - 129

Published: Sept. 22, 2016

Language: Английский

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