Dataset Information

Increased Stability and Breakdown of Brain Effective Connectivity During Slow-Wave Sleep: Mechanistic Insights from Whole-Brain Computational Modelling.

ABSTRACT: Recent research has found that the human sleep cycle is characterised by changes in spatiotemporal patterns of brain activity. Yet, we are still missing a mechanistic explanation of the local neuronal dynamics underlying these changes. We used whole-brain computational modelling to study the differences in global brain functional connectivity and synchrony of fMRI activity in healthy humans during wakefulness and slow-wave sleep. We applied a whole-brain model based on the normal form of a supercritical Hopf bifurcation and studied the dynamical changes when adapting the bifurcation parameter for all brain nodes to best match wakefulness and slow-wave sleep. Furthermore, we analysed differences in effective connectivity between the two states. In addition to significant changes in functional connectivity, synchrony and metastability, this analysis revealed a significant shift of the global dynamic working point of brain dynamics, from the edge of the transition between damped to sustained oscillations during wakefulness, to a stable focus during slow-wave sleep. Moreover, we identified a significant global decrease in effective interactions during slow-wave sleep. These results suggest a mechanism for the empirical functional changes observed during slow-wave sleep, namely a global shift of the brain's dynamic working point leading to increased stability and decreased effective connectivity.

SUBMITTER: Jobst BM

PROVIDER: S-EPMC5498661 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Publications

Increased Stability and Breakdown of Brain Effective Connectivity During Slow-Wave Sleep: Mechanistic Insights from Whole-Brain Computational Modelling.

Jobst Beatrice M BM Hindriks Rikkert R Laufs Helmut H Tagliazucchi Enzo E Hahn Gerald G Ponce-Alvarez Adrián A Stevner Angus B A ABA Kringelbach Morten L ML Deco Gustavo G

Scientific reports 20170705 1

Recent research has found that the human sleep cycle is characterised by changes in spatiotemporal patterns of brain activity. Yet, we are still missing a mechanistic explanation of the local neuronal dynamics underlying these changes. We used whole-brain computational modelling to study the differences in global brain functional connectivity and synchrony of fMRI activity in healthy humans during wakefulness and slow-wave sleep. We applied a whole-brain model based on the normal form of a super ...[more]

PMID: 28680119

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Project description:Slow oscillations, a defining characteristic of the nonrapid eye movement sleep electroencephalogram (EEG), proliferate across the scalp in highly reproducible patterns. In adults, the propagation of slow oscillations is a recognized fingerprint of brain connectivity and excitability. In this study, we (1) describe for the first time maturational features of sleep slow oscillation propagation in children (n = 23; 2-13 years) using high-density (hd) EEG and (2) examine associations between sleep slow oscillatory propagation characteristics (ie, distance, traveling speed, cortical involvement) and white matter myelin microstructure as measured with multicomponent Driven Equilibrium Single Pulse Observation of T1 and T2-magnetic resonance imaging (mcDESPOT-MRI). Results showed that with increasing age, slow oscillations propagated across longer distances (average growth of 0.2 cm per year; R(21) = 0.50, p < .05), while traveling speed and cortical involvement (ie, slow oscillation expanse) remained unchanged across childhood. Cortical involvement (R(20) = 0.44) and slow oscillation speed (R(20) = -0.47; both p < .05, corrected for age) were associated with myelin content in the superior longitudinal fascicle, the largest anterior-posterior, intrahemispheric white matter connectivity tract. Furthermore, slow oscillation distance was moderately associated with whole-brain (R(21) = 0.46, p < .05) and interhemispheric myelin content, the latter represented by callosal myelin water fraction (R(21) = 0.54, p < .01, uncorrected). Thus, we demonstrate age-related changes in slow oscillation propagation distance, as well as regional associations between brain activity during sleep and the anatomical connectivity of white matter microstructure. Our findings make an important contribution to knowledge of the brain connectome using a noninvasive and novel analytic approach. These data also have implications for understanding the emergence of neurodevelopmental disorders and the role of sleep in brain maturation trajectories.

Dataset Information

Increased Stability and Breakdown of Brain Effective Connectivity During Slow-Wave Sleep: Mechanistic Insights from Whole-Brain Computational Modelling.

Publications

Increased Stability and Breakdown of Brain Effective Connectivity During Slow-Wave Sleep: Mechanistic Insights from Whole-Brain Computational Modelling.

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