Questions and controversies in the study of time-varying functional connectivity in resting fMRI

Network Neuroscience, Journal Year: 2019, Volume and Issue: 4(1), P. 30 - 69

Published: Dec. 16, 2019

The brain is a complex, multiscale dynamical system composed of many interacting regions. Knowledge the spatiotemporal organization these interactions critical for establishing solid understanding brain's functional architecture and relationship between neural dynamics cognition in health disease. possibility studying through careful analysis neuroimaging data has catalyzed substantial interest methods that estimate time-resolved fluctuations connectivity (often referred to as "dynamic" or time-varying connectivity; TVFC). At same time, debates have emerged regarding application TVFC analyses resting fMRI data, about statistical validity, physiological origins, cognitive behavioral relevance TVFC. These other unresolved issues complicate interpretation findings limit insights can be gained from this promising new research area. This article brings together scientists with variety perspectives on review current literature light issues. We introduce core concepts, define key terms, summarize controversies open questions, present forward-looking perspective how rigorously productively applied investigate wide range questions systems neuroscience.

Language: Английский

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Human cognition involves the dynamic integration of neural activity and neuromodulatory systems

Nature Neuroscience, Journal Year: 2019, Volume and Issue: 22(2), P. 289 - 296

Published: Jan. 12, 2019

Language: Английский

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Cognitive and behavioural flexibility: neural mechanisms and clinical considerations

Nature reviews. Neuroscience, Journal Year: 2021, Volume and Issue: 22(3), P. 167 - 179

Published: Feb. 3, 2021

Cognitive and behavioural flexibility permit the appropriate adjustment of thoughts behaviours in response to changing environmental demands. Brain mechanisms enabling have been examined using non-invasive neuroimaging approaches humans alongside pharmacological lesion studies animals. This work has identified large-scale functional brain networks encompassing lateral orbital frontoparietal, midcingulo-insular frontostriatal regions that support across lifespan. Flexibility can be compromised early-life neurodevelopmental disorders, clinical conditions emerge during adolescence late-life dementias. We critically evaluate evidence for enhancement through cognitive training, physical activity bilingual experience. is critical optimal adaptation actions under circumstances. In this Review, Uddin summarizes research processes neural systems supporting discusses ways improve

Language: Английский

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Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks

Nature Communications, Journal Year: 2018, Volume and Issue: 9(1)

Published: July 24, 2018

Frequency-specific oscillations and phase-coupling of neuronal populations are essential mechanisms for the coordination activity between brain areas during cognitive tasks. Therefore, ongoing ascribed to different functional networks should also be able reorganise coordinate via similar mechanisms. We develop a novel method identifying large-scale phase-coupled network dynamics show that resting in magnetoencephalography well characterised by visits short-lived transient states, with spatially distinct patterns oscillatory power coherence specific frequency bands. Brain states identified sensory, motor higher-order networks. The include posterior alpha (8-12 Hz) an anterior delta/theta range (1-7 network, both exhibiting high correspond subdivisions default mode network. Our results cortical have characteristic signatures very bands, possibly reflecting specialisation at intrinsic timescales.

Language: Английский

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Discovering dynamic brain networks from big data in rest and task

NeuroImage, Journal Year: 2017, Volume and Issue: 180, P. 646 - 656

Published: June 29, 2017

Brain activity is a dynamic combination of the responses to sensory inputs and its own spontaneous processing. Consequently, such brain continuously changing whether or not one focusing on an externally imposed task. Previously, we have introduced analysis method that allows us, using Hidden Markov Models (HMM), model task rest as sequence distinct networks, overcoming many limitations posed by sliding window approaches. Here, present advance enables HMM handle very large amounts data, making possible inference reproducible interpretable networks in range different datasets, including task, rest, MEG fMRI, with potentially thousands subjects. We anticipate generation publicly available datasets from initiatives Human Connectome Project UK Biobank, computational methods can work at this scale, will bring breakthrough our understanding function both health disease.

Language: Английский

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Resting brain dynamics at different timescales capture distinct aspects of human behavior

Nature Communications, Journal Year: 2019, Volume and Issue: 10(1)

Published: May 24, 2019

Abstract Linking human behavior to resting-state brain function is a central question in systems neuroscience. In particular, the functional timescales at which different types of behavioral factors are encoded remain largely unexplored. The counterparts static connectivity (FC), resolution several minutes, have been studied but correlates dynamic measures FC few seconds unclear. Here, using fMRI and 58 phenotypic from Human Connectome Project, we find that captures task-based phenotypes (e.g., processing speed or fluid intelligence scores), whereas self-reported loneliness life satisfaction) equally well explained by FC. Furthermore, behaviorally relevant emerges interconnections across all networks, rather than within between pairs networks. Our findings shed new light on cognitive processes involved distinct facets behavior.

Language: Английский

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Shared understanding of narratives is correlated with shared neural responses

NeuroImage, Journal Year: 2018, Volume and Issue: 184, P. 161 - 170

Published: Sept. 12, 2018

Humans have a striking ability to infer meaning from even the sparsest and most abstract forms of narratives. At same time, flexibility in form narrative is matched by inherent ambiguity its interpretation. How does brain represent subtle, idiosyncratic differences interpretation ambiguous narratives? In this fMRI study, subjects were scanned either watching novel 7-min animation depicting complex through movement geometric shapes, or listening narration animation's social story. Using an intersubject representational similarity analysis that compared neural across subjects, we found more similar two people's interpretations shapes were, their responses regions default mode network (DMN) fronto-parietal network. Moreover, these shared modality invariant: movie verbal elicited linguistic areas subset DMN when interpretations. Together, results suggest high-level are not only sensitive subtle individual during naturalistic conditions, but also resilient large narrative.

Language: Английский

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Neuromodulation of Brain State and Behavior

Annual Review of Neuroscience, Journal Year: 2020, Volume and Issue: 43(1), P. 391 - 415

Published: April 6, 2020

Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans animals reveal that these variations not random their nature, but may fact be due large part to rapid shifts neural, cognitive, behavioral states. Here we review recent advances the understanding waking state, how generated, they modulate neural mice humans. We propose brain has an identifiable set states through which it wanders continuously a nonrandom fashion, owing ascending modulatory fast-acting corticocortical subcortical-cortical pathways. These state provide backdrop upon operates, them is critical making progress revealing mechanisms underlying cognition behavior.

Language: Английский

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Capturing the spatiotemporal dynamics of self-generated, task-initiated thoughts with EEG and fMRI

NeuroImage, Journal Year: 2019, Volume and Issue: 194, P. 82 - 92

Published: March 19, 2019

Language: Английский

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Optimising network modelling methods for fMRI

NeuroImage, Journal Year: 2020, Volume and Issue: 211, P. 116604 - 116604

Published: Feb. 13, 2020

A major goal of neuroimaging studies is to develop predictive models analyze the relationship between whole brain functional connectivity patterns and behavioural traits. However, there no single widely-accepted standard pipeline for analyzing connectivity. The common procedure designing based entails three main steps: parcellating brain, estimating interaction defined parcels, lastly, using these integrated associations parcels as features fed a classifier predicting non-imaging variables e.g., traits, demographics, emotional measures, etc. There are also additional considerations when correlation-based measures connectivity, resulting in supplementary utilising Riemannian geometry tangent space parameterization preserve connectivity; penalizing estimates with shrinkage approaches handle challenges related short time-series (and noisy) data; removing confounding from brain-behaviour data. These six steps contingent on each-other, optimise general framework one should ideally examine various methods simultaneously. In this paper, we investigated strengths short-comings, both independently jointly, following measures: parcellation techniques four kinds (categorized further depending upon number parcels), five decision staying ambient matrices or space, choice applying estimators, alternative handling confounds finally novel classifiers/predictors. For performance evaluation, have selected two largest datasets, UK Biobank Human Connectome Project resting state fMRI data, run more than 9000 different variants total ∼14000 individuals determine optimum pipeline. independent validation, some best-performing ABIDE ACPI datasets (∼1000 subjects) evaluate generalisability proposed network modelling methods.

Language: Английский

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