The brain is a complex, multiscale dynamical system composed of many interacting regions. Knowledge of the spatiotemporal organization of these interactions is critical for establishing a solid understanding of the brain’s functional architecture and the relationship between neural dynamics and cognition in health and disease. The possibility of studying these dynamics through careful analysis of neuroimaging data has catalyzed substantial interest in methods that estimate time-resolved fluctuations in functional connectivity (often referred to as “dynamic” or time-varying functional connectivity; TVFC). At the same time, debates have emerged regarding the application of TVFC analyses to resting fMRI data, and about the statistical validity, physiological origins, and cognitive and behavioral relevance of resting TVFC. These and other unresolved issues complicate interpretation of resting TVFC findings and limit the insights that can be gained from this promising new research area. This article brings together scientists with a variety of perspectives on resting TVFC to review the current literature in light of these issues. We introduce core concepts, define key terms, summarize controversies and open questions, and present a forward-looking perspective on how resting TVFC analyses can be rigorously and productively applied to investigate a wide range of questions in cognitive and systems neuroscience.

Functional connectivity (FC) has been widely used to study the functional organization of temporally correlated and spatially distributed brain regions. Recent studies of FC dynamics, quantified by windowed correlations, provide new insights to analyze dynamic, context-dependent reconfiguration of brain networks. A set of reoccurring whole-brain connectivity patterns at rest, referred to as FC states, have been identified, hypothetically reflecting underlying cognitive processes or mental states. We posit that the mean FC information for a given subject represents a significant contribution to the group-level FC dynamics. We show that the subject-specific FC profile, termed as FC individuality, can be removed to increase sensitivity to cognitively relevant FC states. To assess the impact of the FC individuality and task-specific FC modulation on the group-level FC dynamics analysis, we generate and analyze group studies of four subjects engaging in four cognitive conditions (rest, simple math, two-back memory, and visual attention task). We also propose a model to quantitatively evaluate the effect of two factors, namely, subject-specific and task-specific modulation on FC dynamics. We show that FC individuality is a predominant factor in group-level FC variability, and the embedded cognitively relevant FC states are clearly visible after removing the individual's connectivity profile. Our results challenge the current understanding of FC states and emphasize the importance of individual heterogeneity in connectivity dynamics analysis.

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Early studies have shown that Tai Chi Chuan (TCC) contributes to the rehabilitation of cognitive disorders and increases blood oxygen concentration levels in the parietal and occipital brain areas; however, the mechanism of TCC training on brain function remains poorly understood. This study hypothesize that TCC has altered brain function and aims to explore the effects of TCC on functional connection and effective connection of the prefrontal cortex (PFC), motor cortex (MC), and occipital cortex (OC). The participants were 23 experienced Chen–style TCC practitioners (TCC group), and 32 demographically matched TCC–naive healthy controls (control group). Functional and effective connections were calculated using wavelet–based coherence analysis and dynamic Bayesian inference method, respectively. Results showed that beyond the intensity of activity in a particular cortical region induced by TCC, significant differences in brain activity and dynamic configuration of connectivity were observed between the TCC and control groups during resting and movement states. These findings suggested that TCC training improved the connection of PFC, MC and OC in myogenic activity, sympathetic nervous system, and endothelial cell metabolic activities; enhanced brain functional connections and relayed the ability of TCC to improve cognition and the anti–memory decline potential.

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Given the dynamic nature of the human brain, there has been an increasing interest in investigating short-term temporal changes in functional connectivity, also known as dynamic functional connectivity (dFC), i.e., the time-varying interregional statistical dependence of blood oxygenation level-dependent (BOLD) signal within the constraints of a single scan. Numerous methodologies have been proposed to characterize dFC during rest and task, but few studies have compared them in terms of their efficacy to capture behavioral and clinically relevant dynamics. This is mostly due to lack of a well-defined ground truth, especially for rest scans. In this study, with a multitask dataset (rest, memory, video, and math) serving as ground truth, we investigated the efficacy of several dFC estimation techniques at capturing cognitively relevant dFC modulation induced by external tasks. We evaluated two framewise methods (dFC estimates for a single time point): dynamic conditional correlation (DCC) and jackknife correlation (JC); and five windowbased methods: sliding window correlation (SWC), sliding window correlation with L1regularization (SWC_L1), a combination of DCC and SWC called moving average DCC (DCC_MA), multiplication of temporal derivatives (MTD), and a variant of jackknife correlation called deleted jackknife correlation (dJC). The efficacy is defined as each dFC metric's ability to successfully subdivide multitask scans into cognitively homogenous segments (even if those Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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