Dataset Information

Fluctuations between high- and low-modularity topology in time-resolved functional connectivity.

ABSTRACT: Modularity is an important topological attribute for functional brain networks. Recent human fMRI studies have reported that modularity of functional networks varies not only across individuals being related to demographics and cognitive performance, but also within individuals co-occurring with fluctuations in network properties of functional connectivity, estimated over short time intervals. However, characteristics of these time-resolved functional networks during periods of high and low modularity have remained largely unexplored. In this study we investigate basic spatiotemporal properties of time-resolved networks in the high and low modularity periods during rest, with a particular focus on their spatial connectivity patterns, temporal homogeneity and test-retest reliability. We show that spatial connectivity patterns of time-resolved networks in the high and low modularity periods are represented by increased and decreased dissociation of the default mode network module from task-positive network modules, respectively. We also find that the instances of time-resolved functional connectivity sampled from within the high (respectively, low) modularity period are relatively homogeneous (respectively, heterogeneous) over time, indicating that during the low modularity period the default mode network interacts with other networks in a variable manner. We confirmed that the occurrence of the high and low modularity periods varies across individuals with moderate inter-session test-retest reliability and that it is correlated with previously-reported individual differences in the modularity of functional connectivity estimated over longer timescales. Our findings illustrate how time-resolved functional networks are spatiotemporally organized during periods of high and low modularity, allowing one to trace individual differences in long-timescale modularity to the variable occurrence of network configurations at shorter timescales.

SUBMITTER: Fukushima M

PROVIDER: S-EPMC6201264 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Fluctuations between high- and low-modularity topology in time-resolved functional connectivity.

Fukushima Makoto M Betzel Richard F RF He Ye Y de Reus Marcel A MA van den Heuvel Martijn P MP Zuo Xi-Nian XN Sporns Olaf O

NeuroImage 20170817 Pt B

Modularity is an important topological attribute for functional brain networks. Recent human fMRI studies have reported that modularity of functional networks varies not only across individuals being related to demographics and cognitive performance, but also within individuals co-occurring with fluctuations in network properties of functional connectivity, estimated over short time intervals. However, characteristics of these time-resolved functional networks during periods of high and low modu ...[more]

PMID: 28823827

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Project description:Dynamic models of large-scale brain activity have been used for reproducing many empirical findings on human brain functional connectivity. Features that have been shown to be reproducible by comparing modeled to empirical data include functional connectivity measured over several minutes of resting-state functional magnetic resonance imaging, as well as its time-resolved fluctuations on a time scale of tens of seconds. However, comparison of modeled and empirical data has not been conducted yet for fluctuations in global network topology of functional connectivity, such as fluctuations between segregated and integrated topology or between high and low modularity topology. Since these global network-level fluctuations have been shown to be related to human cognition and behavior, there is an emerging need for clarifying their reproducibility with computational models. To address this problem, we directly compared fluctuations in global network topology of functional connectivity between modeled and empirical data, and clarified the degree to which a stationary model of spontaneous brain dynamics can reproduce the empirically observed fluctuations. Modeled fluctuations were simulated using a system of coupled phase oscillators wired according to brain structural connectivity. By performing model parameter search, we found that modeled fluctuations in global metrics quantifying network integration and modularity had more than 80% of magnitudes of those observed in the empirical data. Temporal properties of network states determined based on fluctuations in these metrics were also found to be reproducible, although their spatial patterns in functional connectivity did not perfectly matched. These results suggest that stationary models simulating resting-state activity can reproduce the magnitude of empirical fluctuations in segregation and integration, whereas additional factors, such as active mechanisms controlling non-stationary dynamics and/or greater accuracy of mapping brain structural connectivity, would be necessary for fully reproducing the spatial patterning associated with these fluctuations.

Project description:Anesthesia is often necessary to perform fMRI experiments in the rodent model; however, commonly used anesthetic protocols may manifest changing brain conditions over the duration of the study. This possibility was explored in the current work. Eleven rats were anesthetized with 2% isoflurane anesthesia; four rats were anesthetized for a short period (30?min, simulating induction and fMRI setup) and seven rats were anesthetized for a long period (3?h, simulating surgical preparation). Following the initial anesthetic period, isoflurane was discontinued, and a dexmedetomidine bolus (0.025?mg/kg) and continuous subcutaneous infusion (0.05?mg/kg/h) were administered. Blood-oxygen-level dependent resting state imaging was performed every 30?min from 0.75?h post dexmedetomidine bolus until 5.75?h post-bolus. Evaluation of power spectra obtained from time courses in the primary somatosensory cortex revealed, in general, a monotonic increase in low-frequency power (0.05-0.3?Hz) in both groups over the duration of resting state imaging. Greater low-band spectral power (0.05-0.15?Hz) is present in the short isoflurane group for the first 2.75?h, but the spectra become highly uniform at 3.25?h. The emergence of a ~0.18?Hz peak, beginning at the 3.75?h time point, exists in both groups and evolves similarly, increasing in strength as the duration of dexmedetomidine sedation (and time since isoflurane cessation) extends. In the long isoflurane group only, bilateral functional connectivity strengthens with anesthetic duration, and correlation is linearly linked to low-band spectral power. Convergence of connectivity and spectral metrics between the short and long isoflurane groups occurs at ~3.25?h, suggesting the effects of isoflurane have subsided. Researchers using dexmedetomidine following isoflurane for functional studies should be aware of the duration specific effects of the pre-scan isoflurane durations as well as the continuing influences of long-term imaging under dexmedetomidine.

Dataset Information

Fluctuations between high- and low-modularity topology in time-resolved functional connectivity.

Publications

Fluctuations between high- and low-modularity topology in time-resolved functional connectivity.

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