Acute ischaemic stroke alters the brain’s preference for distinct dynamic connectivity states

Brain, Journal Year: 2020, Volume and Issue: 143(5), P. 1525 - 1540

Published: March 14, 2020

Abstract Acute ischaemic stroke disturbs healthy brain organization, prompting subsequent plasticity and reorganization to compensate for the loss of specialized neural tissue function. Static resting state functional MRI studies have already furthered our understanding cerebral by estimating stroke-induced changes in network connectivity aggregated over duration several minutes. In this study, we used dynamic analyses increase temporal resolution seconds explore transient configurations motor acute stroke. To end, collected data 31 patients with 17 age-matched control subjects. Stroke presented moderate severe hand deficits. By within a sliding window framework, identified three distinct motor-related networks. Motor networks were organized into regional domains, i.e. cortical, subcortical cerebellar domain. The patterns diverged from those controls depending on severity initial impairment. Moderately affected (n = 18) spent significantly more time weakly connected configuration that was characterized low levels connectivity, both locally as well between distant regions. contrast, severely 13) showed significant preference transitions spatially segregated configuration. This featured particularly high local domains anti-correlated across domains. A third represented an intermediate pattern compared preceding two, predominantly encompassed decreased interhemispheric cortical independent individual deficit severity. Alterations thus closely resembled previously reported ones originating static post-stroke. summary, not only prompted networks, but it also caused characteristic properties large-scale interactions deficit. These findings offer new vistas mechanisms underlying neurological symptoms, treatment effects patients.

Language: Английский

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What have we really learned from functional connectivity in clinical populations?

NeuroImage, Journal Year: 2021, Volume and Issue: 242, P. 118466 - 118466

Published: Aug. 10, 2021

Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to promise approach across conceptual, technical, and practical levels. With an already vast steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, neurological diseases disorders which FC is primary measure, we aim here provide high-level synthesis major concepts that have arisen from findings manner cuts different conditions sheds light overarching principles. We highlight allowed us discover ubiquity intrinsic networks virtually all brains clarify typical patterns neurodevelopment over lifespan. This understanding maturation with age provided important benchmarks against evaluate divergent early life degeneration late life. turn led insight many are associated complex, distributed, network-level changes brain, opposed solely focal abnormalities. further emphasize role studies played supporting dimensional studying transdiagnostic symptoms enhancing multimodal characterization prediction trajectory symptom progression conditions. unprecedented opportunity offered by probe where function could not be easily studied otherwise, such consciousness. Lastly, suggest high priority areas future research acknowledge critical barriers use methods, particularly those related artifact removal, data denoising feasibility contexts.

Language: Английский

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Towards precise resting-state fMRI biomarkers in psychiatry: synthesizing developments in transdiagnostic research, dimensional models of psychopathology, and normative neurodevelopment

Current Opinion in Neurobiology, Journal Year: 2020, Volume and Issue: 65, P. 120 - 128

Published: Nov. 23, 2020

Language: Английский

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Temporal stability of functional brain modules associated with human intelligence

Human Brain Mapping, Journal Year: 2019, Volume and Issue: 41(2), P. 362 - 372

Published: Oct. 6, 2019

Abstract Individual differences in general cognitive ability (i.e., intelligence) have been linked to individual variations the modular organization of functional brain networks. However, these analyses limited static (time‐averaged) connectivity, and not yet addressed whether dynamic changes configuration networks relate intelligence. Here, we used multiband MRI resting‐state data ( N = 281) estimated subject‐specific time‐varying connectivity Modularity optimization was applied determine time‐variant module partitions assess fluctuations modularity across time. We show that higher intelligence, indexed by an established composite measure, Wechsler Abbreviated Scale Intelligence (WASI), is associated with temporal stability (lower variability) network modularity. Post‐hoc reveal subjects intelligence scores engage fewer periods extremely high — which are characterized greater disconnection task‐positive from task‐negative Further, regions dorsal attention contribute most observed effect. In sum, our study suggests investigating dynamics topology contributes understanding neural bases abilities.

Language: Английский

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The relationship between individual variation in macroscale functional gradients and distinct aspects of ongoing thought

NeuroImage, Journal Year: 2020, Volume and Issue: 220, P. 117072 - 117072

Published: June 22, 2020

Contemporary accounts of ongoing thought recognise it as a heterogeneous and multidimensional construct, varying in both form content. An emerging body evidence demonstrates that distinct types experience are associated with unique neurocognitive profiles, can be described at the whole-brain level interactions between multiple large-scale networks. The current study sought to explore possibility functional connectivity patterns rest may meaningfully related occurred over this period. Participants underwent resting-state magnetic resonance imaging (rs-fMRI) followed by questionnaire retrospectively assessing content their thoughts during scan. A non-linear dimension reduction algorithm was applied rs-fMRI data identify components explaining greatest variance patterns. Using these data, we examined whether specific measured end scan were predictive individual variation along first three low-dimensional rest. Multivariate analyses revealed individuals for whom sensorimotor system maximally from visual most likely report finding solutions problems or goals least past. These results add an literature suggests distributed profiles highlight unimodal systems play important role process.

Language: Английский

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