On the nature of time-varying functional connectivity in resting fMRI

Abstract

<p>The brain is a complex dynamical system composed of many interacting sub-regions. Knowledge of how these interactions reconfigure over time is critical to a full understanding of the brain’s functional architecture, the neural basis of flexible cognition and behavior, and how neural systems are disrupted in psychiatric and neurological illness. The idea that we might be able to study neural and cognitive dynamics through analysis of neuroimaging data has catalyzed substantial interest in methods which seek to estimate moment-to-moment fluctuations in functional connectivity (often referred to as “dynamic” or time-varying connectivity; TVC). At the same time, debates have emerged regarding the application of TVC analyses to resting fMRI data, and about the statistical validity, physiological origins, and cognitive relevance of resting TVC. These and other unresolved issues complicate the interpretation of resting TVC findings and limit the insights which can be gained from this otherwise promising research area. This article reviews the current resting TVC literature in light of these issues. We introduce core concepts, define key terms, summarize current controversies and open questions, and present a forward-looking perspective on how resting TVC analyses can be rigorously applied to investigate a wide range of questions in cognitive and systems neuroscience.</p>

Temporal stability of functional brain modules associated with human intelligence

“…The functional brain network correlates of intelligence were so far mostly studied as a static (i.e., time‐invariant) property of the human brain, that is, by averaging time courses of neural activation across the entire duration of a resting‐state fMRI scan (typically 5–10 min). This approach, however, ignores that intrinsic brain networks vary substantially across time (Cohen, ; Lurie et al, ; Zalesky, Fornito, Cocchi, Gollo, & Breakspear, ). Importantly, it has been shown that the dynamic interplay between states of high integration (low modularity) versus high segregation (high modularity) is linked to different levels of attention (Shine, Koyejo, & Poldrack, ) and cognitive performance (Shine et al, ).…”

Time varying connectivity across the brain changes as a function of nicotine abstinence state

“…Recent advances in fMRI time series signal processing allow characterization of "time varying connectivity" (TVC) [29][30][31][32][33] , which characterizes network communication between subnetworks that reconfigure over the course of data collection. Such characterizations of TVC are of particular relevance to the study of SUD, as ongoing, spontaneous (i.e.…”

“…However, considering the variability in clinical NWS symptom presentation, it is notable that these static rsFC studies have almost exclusively employed methods that assume unchanging network structure over time. This assumption limits the temporal resolution of the network communication described to the total data acquisition period and likely underspecifies the nature of the brain-based disruptions associated with the NWS.Recent advances in fMRI time series signal processing allow characterization of "time varying connectivity" (TVC) [29][30][31][32][33] , which characterizes network communication between subnetworks that reconfigure over the course of data collection. Such characterizations of TVC are of particular relevance to the study of SUD, as ongoing, spontaneous (i.e.…”

Static and Dynamic Aspects of Cerebro-Cerebellar Functional Connectivity are Associated with Self-reported Measures of Impulsivity: A Resting-State fMRI Study

“…This has proven to be highly informative in uncovering the neural substrates underlying certain behaviors, cognitive abilities, and personality traits in healthy and clinical populations. However, it is now argued that this "static" approach masks information embedded in the dynamic nature of the brain (Calhoun et al, 2014;Lurie et al, 2018). Accordingly, recent FC studies have begun exploring the temporal dynamics of brain activity and have pointed to the presence of flexible non-random FC configuration (brain states) that transiently appear during task and rest conditions (Allen et al, 2012;Vidaurre et al, 2017).…”