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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On the Importance of Being Flexible: Dynamic Brain Networks and Their Potential Functional Significances

Frontiers in Systems Neuroscience, Journal Year: 2022, Volume and Issue: 15

Published: Jan. 21, 2022

In this theoretical review, we begin by discussing brains and minds from a dynamical systems perspective, then go on to describe methods for characterizing the flexibility of dynamic networks. We discuss how varying degrees kinds may be adaptive (or maladaptive) in different contexts, specifically focusing measures related either more disjoint or cohesive dynamics. While disjointed useful assessing neural entropy, potentially serve as proxy self-organized criticality fundamental property enabling behavior complex systems. Particular attention is given recent studies which have been used investigate neurological cognitive maturation, well breakdown conscious processing under levels anesthesia. further these findings might contextualized within Free Energy Principle with respect fundamentals brain organization biological functioning generally, potential methodological advances paradigm. Finally, relevance computational psychiatry, propose research program obtaining better understanding ways that networks relate forms psychological flexibility, single most important factor ensuring human flourishing.

Language: Английский

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Synchronous high-amplitude co-fluctuations of functional brain networks during movie-watching

Imaging Neuroscience, Journal Year: 2023, Volume and Issue: 1, P. 1 - 21

Published: Oct. 19, 2023

Abstract Recent studies have shown that functional connectivity can be decomposed into its exact frame-wise contributions, revealing short-lived, infrequent, and high-amplitude time points referred to as “events.” Events contribute disproportionately the time-averaged pattern, improve identifiability brain-behavior associations, differences in their expression been linked endogenous hormonal fluctuations autism. Here, we explore characteristics of events while subjects watch movies. Using two independently-acquired imaging datasets which participants passively watched movies, find synchronize across individuals based on level synchronization, categorized three distinct classes: those at boundaries between during do not all. We boundary events, compared other categories, exhibit greater amplitude, co-fluctuation patterns, temporal propagation. show underlying events1 is a specific mode involving activation control salience systems alongside deactivation visual systems. movie, hand, display pattern time-locked movie stimulus. Finally, found subjects’ time-varying brain networks are most similar one another these synchronous events.

Language: Английский

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The diversity and multiplexity of edge communities within and between brain systems

Cell Reports, Journal Year: 2021, Volume and Issue: 37(7), P. 110032 - 110032

Published: Nov. 1, 2021

The human brain is composed of functionally specialized systems that support cognition. Recently, we proposed an edge-centric model for detecting overlapping communities. It remains unclear how these communities and are related. Here, address this question using data from the Midnight Scan Club show all linked via at least two edge We then examine diversity within each system, finding heteromodal more diverse than sensory systems. Next, cluster entire cortex to reveal it according regions' edge-community profiles. find regions in likely form their own clusters. Finally, personalized. Our work reveals pervasive overlap across relationship with provides pathways future research networks.

Language: Английский

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Interpreting null models of resting-state functional MRI dynamics: not throwing the model out with the hypothesis

NeuroImage, Journal Year: 2021, Volume and Issue: 243, P. 118518 - 118518

Published: Aug. 29, 2021

Null models are useful for assessing whether a dataset exhibits non-trivial property of interest. These have recently gained interest in the neuroimaging community as means to explore dynamic properties functional Magnetic Resonance Imaging (fMRI) time series. Interpretation null-model testing this context may not be straightforward because (i) null hypotheses associated different sometimes unclear and (ii) fMRI metrics might 'trivial', i.e. preserved under hypothesis, still applications. In commentary, we review several commonly used series discuss interpretation corresponding tests. We argue that, while allows better characterization statistical metrics, it should considered mandatory validation step assess their relevance representing brain dynamics.

Language: Английский

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Subject identification using edge-centric functional connectivity

NeuroImage, Journal Year: 2021, Volume and Issue: 238, P. 118204 - 118204

Published: June 1, 2021

Group-level studies do not capture individual differences in network organization, an important prerequisite for understanding neural substrates shaping behavior and developing interventions clinical conditions. Recent have employed 'fingerprinting' analyses on functional connectivity to identify subjects' idiosyncratic features. Here, we develop a complementary approach based edge-centric model of connectivity, which focuses the co-fluctuations edges. We first show whole-brain edge (eFC) be robust substrate that improves identifiability over nodal FC (nFC) across different datasets parcellations. Next, characterize at spatial scales, from single nodes level systems clusters using k-means clustering. Across find heteromodal brain regions exhibit consistently greater than unimodal, sensorimotor, limbic regions. Lastly, can further improved by reconstructing eFC specific subsets its principal components. In summary, our results highlight utility capturing meaningful subject-specific features sets stage future investigations into models.

Language: Английский

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Edge-centric analysis of stroke patients: An alternative approach for biomarkers of lesion recovery

NeuroImage Clinical, Journal Year: 2022, Volume and Issue: 35, P. 103055 - 103055

Published: Jan. 1, 2022

Most neuroimaging studies of post-stroke recovery rely on analyses derived from standard node-centric functional connectivity to map the distributed effects in stroke patients. Here, given importance nonlocal and diffuse damage, we use an edge-centric approach order provide alternative description this disorder. These techniques allow for rendering metrics such as normalized entropy, which describes diversity edge communities at each node. Moreover, enables identification high amplitude co-fluctuations fMRI time series. We found that entropy is associated with lesion severity continually increases across patients' recovery. Furthermore, not only relate but are also level The current study first application a clinical population longitudinal dataset demonstrates how different perspective data analysis can further characterize topographic modulations brain dynamics.

Language: Английский

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Frontoparietal network activation is associated with motor recovery in ischemic stroke patients

Communications Biology, Journal Year: 2022, Volume and Issue: 5(1)

Published: Sept. 21, 2022

Abstract Strokes cause lesions that damage brain tissue, disrupt normal activity patterns and can lead to impairments in motor function. Although modulation of cortical is central stimulation-based rehabilitative therapies, aberrant adaptive after stroke have not yet been fully characterized. Here, we apply a dynamics analysis approach study longitudinal individuals with ischemic pontine stroke. We first found 4 commonly occurring states largely characterized by high amplitude activations the visual, frontoparietal, default mode, networks. Stroke subjects spent less time frontoparietal state compared controls. For dominant-hand CST damage, more from 1 week 3-6 months post-stroke was associated better recovery over same period, an association which independent baseline impairment. Furthermore, amount linked empirically functional connectivity. This work suggests when compromised stroke, resting configurations may include increased activation network, facilitate compensatory neural pathways support function traditional circuits dominant-hemisphere are compromised.

Language: Английский

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