Time‐varying nodal measures with temporal community structure: A cautionary note to avoid misinterpretation

Thompson, William Hedley; Kastrati, Gránit; Finc, Karolina; Wright, Jessey; Shine, James M.; Poldrack, Russell A.

doi:10.1002/hbm.24950

Cited by 10 publications

(7 citation statements)

References 33 publications

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“…From simulated rs-fMRI signal, time-resolved functional connectivity was computed using tapered sliding windows 15 . For each instance of time-resolved functional connectivity, three global network measures, mean participation coefficient (mean PC), mean temporal participation coefficient (mean TPC), and modularity, were calculated to track dynamic fluctuations between segregated and integrated patterns of functional connectivity 14 , 23 , 24 , 42 . The time series of mean PC, mean TPC, and modularity served as proxies of dynamic fluctuations between segregation and integration in the brain.…”

Section: Resultsmentioning

confidence: 99%

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Structural determinants of dynamic fluctuations between segregation and integration on the human connectome

Fukushima

Sporns

2020

Commun Biol

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While segregation and integration of neural information in the neocortex are thought to be important for human behavior and cognition, the neural substrates enabling their dynamic fluctuations remain elusive. To tackle this problem, we aim to identify specific network features of the connectome that are responsible for the emergence of dynamic fluctuations between segregated and integrated patterns in human resting-state functional connectivity. Here we examine the contributions of network features to dynamic fluctuations by constructing rewired surrogate connectome in which network features of interest are selectively preserved, and then by assessing the magnitude of fluctuations simulated with these surrogates. Our analysis demonstrates significant contributions from global geometry and topology of the connectome, as well as from localized structural connections involving visual areas. By providing structural accounts of dynamic fluctuations in functional connectivity, this study offers new insights into generative mechanisms driving temporal changes in segregation and integration in the brain.

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Section: Resultsmentioning

confidence: 99%

“…A recent study 42 proposed TPC by extending PC in Eq. ( 2 ) to improve its interpretability with time-varying community partitions.…”

Section: Methodsmentioning

confidence: 99%

Structural determinants of dynamic fluctuations between segregation and integration on the human connectome

Fukushima

Sporns

2020

Commun Biol

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“…Thus, time‐varying network centrality may not be related to the nature of static (or time‐averaged) network centrality. Caution should be exercised in the interpretation of time‐varying centrality, as its polarities are temporally not always equal to those of static network centrality (Thompson et al., 2020 ).…”

Section: Discussionmentioning

confidence: 99%

“…Recent investigations in time‐varying network centralities have revealed several brain network characteristics. Essentially, while the time‐varying EC of the resting‐state appears to reflect individual differences (Wink, 2019 ), time‐varying PC demonstrates the changes in the network structure with increasing integration of various brain regions (Thompson et al., 2020 ). These centralities represent the diverse characteristics of the brain network.…”

Section: Introductionmentioning

confidence: 99%

Time‐varying measures of cerebral network centrality correlate with visual saliency during movie watching

Ogawa

2021

Brain and Behavior

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The extensive development of graph‐theoretic analysis for functional connectivity has revealed the multifaceted characteristics of brain networks. Network centralities identify the principal functional regions, individual differences, and hub structure in brain networks. Neuroimaging studies using movie‐watching have investigated brain function under naturalistic stimuli. Visual saliency is one of the promising measures for revealing cognition and emotions driven by naturalistic stimuli. This study investigated whether the visual saliency in movies was associated with network centrality. The study examined eigenvector centrality (EC), which is a measure of a region's influence in the brain network, and the participation coefficient (PC), which reflects the hub structure in the brain, was used for comparison. Static and time‐varying EC and PC were analyzed by a parcel‐based technique. While EC was correlated with brain activity in parcels in the visual and auditory areas during movie‐watching, it was only correlated with parcels in the visual areas in the retinotopy task. In addition, high PC was consistently observed in parcels in the putative hub both during the tasks and the resting‐state condition. Time‐varying EC in the parietal parcels and time‐varying PC in the primary sensory parcels significantly correlated with visual saliency in the movies. These results suggest that time‐varying centralities in brain networks are distinctively associated with perceptual processing and subsequent higher processing of visual saliency.

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“…Employing the event boundaries identified by independent raters in Ben-Yakov and Henson (2018) with a keypress when they felt that "one event [meaningful unit] ended and Here, a node's native community was the one to which it was assigned in Power et al (2011), the study that validated the functional atlas. It is worth pointing out that because our participation coefficient is based on a static community structure, it is not subject to the drawbacks associated with the participation coefficients derived from temporally varying communities (Thompson et al, 2020).…”

Section: Functional Brain Reorganization: Window-to-window Versus Conmentioning

confidence: 99%

Brain-Environment Alignment during Movie Watching Predicts Cognitive-Affective Function in Adulthood

Petrican

Graham

Lawrence

2020

Preprint

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The brain’s functional architecture changes considerably across multiple timescales. While the role of variations over long timescales (e.g., years) is widely documented, the functional relevance of microtemporal (i.e., second-level) fluctuations is still debated. Using fMRI data collected during movie watching from two independent samples, we demonstrate that the adaptiveness of variability in functional brain architecture fluctuates across the adult lifespan (18-88 years) due to age-related differences in the associated profiles of network communication. Greater coupling between changes in brain architecture and concrete environmental features is stronger at younger ages and linked to poorer cognitive-affective outcomes. Whole-brain communication pathways anchored in regions key to episodic and semantic context creation contribute to greater brain reconfiguration in response to abstract contextual changes and stronger coupling between changes in brain architecture and concrete environmental features. Our results provide new insights into age-related differences in brain-environment alignment and their relevance to cognitive adaptability and psychopathology.

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Time‐varying nodal measures with temporal community structure: A cautionary note to avoid misinterpretation

Cited by 10 publications

References 33 publications

Structural determinants of dynamic fluctuations between segregation and integration on the human connectome

Structural determinants of dynamic fluctuations between segregation and integration on the human connectome

Time‐varying measures of cerebral network centrality correlate with visual saliency during movie watching

Brain-Environment Alignment during Movie Watching Predicts Cognitive-Affective Function in Adulthood

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