Modular origins of high-amplitude cofluctuations in fine-scale functional connectivity dynamics

Proceedings of the National Academy of Sciences, Journal Year: 2021, Volume and Issue: 118(46)

Published: Nov. 8, 2021

The topology of structural brain networks shapes dynamics, including the correlation structure activity (functional connectivity) as estimated from functional neuroimaging data. Empirical studies have shown that connectivity fluctuates over time, exhibiting patterns vary in spatial arrangement correlations among segregated systems. Recently, an exact decomposition into frame-wise contributions has revealed fine-scale dynamics are punctuated by brief and intermittent episodes (events) high-amplitude cofluctuations involving large sets regions. Their origin is currently unclear. Here, we demonstrate similar readily appear silico using computational simulations whole-brain dynamics. As empirical data, simulated events contribute disproportionately to long-time connectivity, involve recurrence patterned cofluctuations, can be clustered distinct families. Importantly, comparison event-related underlying reveals modular organization present coupling matrix cofluctuations. Our work suggests brief, partly shaped connectivity.

Language: Английский

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A mathematical perspective on edge-centric brain functional connectivity

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: May 16, 2022

Edge time series are increasingly used in brain imaging to study the node functional connectivity (nFC) dynamics at finest temporal resolution while avoiding sliding windows. Here, we lay mathematical foundations for edge-centric analysis of neuroimaging series, explaining why a few high-amplitude cofluctuations drive nFC across datasets. Our exposition also constitutes critique existing studies, showing that their main findings can be derived from under static null hypothesis disregards correlations. Testing analytic predictions on MRI data Human Connectome Project confirms explain most variation edge FC matrix, communities, large cofluctuations, and corresponding spatial patterns. We encourage use dynamic measures future research, which exploit structure cannot replicated by models.

Language: Английский

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Precision dynamical mapping using topological data analysis reveals a hub-like transition state at rest

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: Aug. 15, 2022

Abstract In the absence of external stimuli, neural activity continuously evolves from one configuration to another. Whether these transitions or explorations follow some underlying arrangement lack a predictable ordered plan remains be determined. Here, using fMRI data highly sampled individuals (~5 hours resting-state per individual), we aimed reveal rules that govern in brain at rest. Our Topological Data Analysis based Mapper approach characterized visited transition state acts as switch between different configurations organize spontaneous activity. Further, while was by uniform representation canonical networks (RSNs), periphery landscape dominated subject-specific combination RSNs. Altogether, revealed principles precision dynamics approach.

Language: Английский

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A spatiotemporal complexity architecture of human brain activity

Science Advances, Journal Year: 2023, Volume and Issue: 9(5)

Published: Feb. 1, 2023

The human brain operates in large-scale functional networks. These networks are an expression of temporally correlated activity across regions, but how global network properties relate to the neural dynamics individual regions remains incompletely understood. Here, we show that brain's architecture is tightly linked critical episodes regularity, visible as spontaneous "complexity drops" magnetic resonance imaging signals. closely explain connectivity strength between subserve propagation patterns, and reflect interindividual differences age behavior. Furthermore, complexity drops define states dynamically shape strength, topological configuration, hierarchy comprehensively known structure-function relationships within brain. findings delineate a principled activity-a "complexome" underpins organization.

Language: Английский

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Large-scale neural dynamics in a shared low-dimensional state space reflect cognitive and attentional dynamics

eLife, Journal Year: 2023, Volume and Issue: 12

Published: July 3, 2023

Cognition and attention arise from the adaptive coordination of neural systems in response to external internal demands. The low-dimensional latent subspace that underlies large-scale dynamics relationships these cognitive attentional states, however, are unknown. We conducted functional magnetic resonance imaging as human participants performed tasks, watched comedy sitcom episodes an educational documentary, rested. Whole-brain traversed a common set states spanned canonical gradients brain organization, with global desynchronization among networks modulating state transitions. Neural were synchronized across people during engaging movie watching aligned narrative event structures. reflected fluctuations such different indicated engaged task naturalistic contexts, whereas lapses both contexts. Together, results demonstrate traversals along organization reflect dynamics.

Language: Английский

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