The older adult brain is less modular, more integrated, and less efficient at rest: A systematic review of large‐scale resting‐state functional brain networks in aging

Psychophysiology, Journal Year: 2022, Volume and Issue: 60(1)

Published: Sept. 15, 2022

Abstract The literature on large‐scale resting‐state functional brain networks across the adult lifespan was systematically reviewed. Studies published between 1986 and July 2021 were retrieved from PubMed. After reviewing 2938 records, 144 studies included. Results 11 network measures summarized assessed for certainty of evidence using a modified GRADE method. provides high that older adults display reduced within‐network increased between‐network connectivity. Older also show lower segregation, modularity, efficiency hub function, decreased lateralization posterior to anterior shift at rest. Higher‐order reliably showed age differences, whereas primary sensory motor more variable results. inflection point changes is often third or fourth decade life. Age effects found with moderate within‐ altered patterns speed dynamic Research within‐subject bold variability connectivity glucose uptake low differences but warrants further study. Taken together, these age‐related may contribute cognitive decline seen in adults.

Language: Английский

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Why is everyone talking about brain state?

Trends in Neurosciences, Journal Year: 2023, Volume and Issue: 46(7), P. 508 - 524

Published: May 8, 2023

The rapid and coordinated propagation of neural activity across the brain provides foundation for complex behavior cognition. Technical advances neuroscience subfields have advanced understanding these dynamics, but points convergence are often obscured by semantic differences, creating silos subfield-specific findings. In this review we describe how a parsimonious conceptualization state as fundamental building block whole-brain offers common framework to relate findings scales species. We present examples diverse techniques commonly used study states associated with physiology higher-order cognitive processes, discuss integration them will enable more comprehensive mechanistic characterization dynamics that crucial survival disrupted in disease.

Language: Английский

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Controversies and progress on standardization of large-scale brain network nomenclature

Network Neuroscience, Journal Year: 2023, Volume and Issue: 7(3), P. 864 - 905

Published: Jan. 1, 2023

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level macroscale organization brain, beginning to confront challenges associated with developing a taxonomy its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy NETworks (WHATNET) was formed 2020 as an Organization Human Brain Mapping (OHBM)-endorsed best practices committee provide recommendations on points consensus, identify open questions, and highlight areas ongoing debate service moving field toward standardized reporting network neuroscience results. conducted survey catalog current large-scale brain nomenclature. A few well-known names (e.g., default mode network) dominated responses survey, number illuminating disagreement emerged. We summarize results initial considerations from workgroup. This perspective piece includes selective review this enterprise, including (1) scale, resolution, hierarchies; (2) interindividual variability networks; (3) dynamics nonstationarity (4) consideration affiliations subcortical structures; (5) multimodal information. close minimal guidelines cognitive communities adopt.

Language: Английский

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Neuroscience Needs Network Science

Journal of Neuroscience, Journal Year: 2023, Volume and Issue: 43(34), P. 5989 - 5995

Published: Aug. 23, 2023

The brain is a complex system comprising myriad of interacting elements, posing significant challenges in understanding its structure, function, and dynamics. Network science has emerged as powerful tool for studying such intricate systems, offering framework integrating multiscale data complexity. Here, we discuss the application network study brain, addressing topics models metrics, connectome, role dynamics neural networks. We explore opportunities multiple streams transitions from development to healthy function disease, potential collaboration between neuroscience communities. underscore importance fostering interdisciplinary through funding initiatives, workshops, conferences, well supporting students postdoctoral fellows with interests both disciplines. By uniting communities, can develop novel network-based methods tailored circuits, paving way towards deeper functions.

Language: Английский

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Enhancing precision in human neuroscience

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

Published: Aug. 9, 2023

Human neuroscience has always been pushing the boundary of what is measurable. During last decade, concerns about statistical power and replicability – in science general, but also specifically human have fueled an extensive debate. One important insight from this discourse need for larger samples, which naturally increases power. An alternative to increase precision measurements, focus review. This option often overlooked, even though benefits increasing as much sample size. Nonetheless, at heart good scientific practice neuroscience, with researchers relying on lab traditions or rules thumb ensure sufficient their studies. In review, we encourage a more systematic approach precision. We start by introducing measurement its importance well-powered studies neuroscience. Then, determinants range neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, Endocrinology) are elaborated. end discussing how evaluation application respective insights can lead reproducibility

Language: Английский

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The tip of the iceberg: A call to embrace anti-localizationism in human neuroscience research

Imaging Neuroscience, Journal Year: 2024, Volume and Issue: 2, P. 1 - 10

Published: April 1, 2024

Abstract Human neuroscience research remains largely preoccupied with mapping distinct brain areas to complex psychological processes and features of mental health disorders. While this reductionist localizationist perspective has resulted in several substantive contributions the field, it long been viewed as only a piece puzzle. Emerging evidence now empirically demonstrates how historical reliance on techniques may underlie recent challenges reproducibility translation human neuroscience. To advance discovery, we must collectively better incorporate systems machine-learning approaches that capture multidimensional, dynamic, interacting nature brain. Moreover, begin contend best integrate complementary modalities beyond understand processes.

Language: Английский

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Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: June 4, 2024

Abstract Functional interactions between brain regions can be viewed as a network, enabling neuroscientists to investigate function through network science. Here, we systematically evaluate 768 data-processing pipelines for reconstruction from resting-state functional MRI, evaluating the effect of parcellation, connectivity definition, and global signal regression. Our criteria seek that minimise motion confounds spurious test-retest discrepancies topology, while being sensitive both inter-subject differences experimental effects interest. We reveal vast systematic variability across pipelines’ suitability connectomics. Inappropriate choice pipeline produce results are not only misleading, but so, with majority failing at least one criterion. However, set optimal consistently satisfy all different datasets, spanning minutes, weeks, months. provide full breakdown each pipeline’s performance inform future best practices in

Language: Английский

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Topographic gradients of intrinsic dynamics across neocortex

eLife, Journal Year: 2020, Volume and Issue: 9

Published: Dec. 17, 2020

The intrinsic dynamics of neuronal populations are shaped by both microscale attributes and macroscale connectome architecture. Here we comprehensively characterize the rich temporal patterns neural activity throughout human brain. Applying massive feature extraction to regional haemodynamic activity, systematically estimate over 6000 statistical properties individual brain regions' time-series across neocortex. We identify two robust spatial gradients dynamics, one spanning a ventromedial-dorsolateral axis dominated measures signal autocorrelation, other unimodal-transmodal dynamic range. These reflect gene expression, intracortical myelin cortical thickness, as well structural functional network embedding. Importantly, these correlated with meta-analytic activation, differentiating cognitive versus affective processing sensory higher-order processing. Altogether, findings demonstrate link between architecture, cognition.

Language: Английский

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The community structure of functional brain networks exhibits scale-specific patterns of inter- and intra-subject variability

NeuroImage, Journal Year: 2019, Volume and Issue: 202, P. 115990 - 115990

Published: July 7, 2019

The network organization of the human brain varies across individuals, changes with development and aging, differs in disease. Discovering major dimensions along which this variability is displayed remains a central goal both neuroscience clinical medicine. Such efforts can be usefully framed within context brain's modular organization, assessed quantitatively using computational techniques extended for purposes multi-scale analysis, dimensionality reduction, biomarker generation. Although concept modularity its utility describing clear, principled methods comparing communities individuals time are surprisingly lacking. Here, we present method that uses multi-layer networks to simultaneously discover structure many subjects at once. This builds upon well-known maximization technique, provides viable tool studying differences time. We test on two datasets identify consistent patterns inter-subject community variability, demonstrating - would undetectable past approaches associated measures cognitive performance. In general, multi-layer, multi-subject framework proposed here represents an advance over current by straighforwardly mapping assignments holds promise future investigations variation populations or as result task constraints.

Language: Английский

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Tools of the trade: estimating time-varying connectivity patterns from fMRI data

Social Cognitive and Affective Neuroscience, Journal Year: 2020, Volume and Issue: 16(8), P. 849 - 874

Published: Aug. 5, 2020

Abstract Given the dynamic nature of brain, there has always been a motivation to move beyond ‘static’ functional connectivity, which characterizes interactions over an extended period time. Progress in data acquisition and advances analytical neuroimaging methods now allow us assess whole brain’s connectivity (dFC) its network-based analog, network at macroscale (mm) using fMRI. This resulted rapid growth approaches, some are very complex, requiring technical expertise that could daunt researchers neuroscientists. Meanwhile, making real progress toward understanding association between brain dynamism disorders can only be achieved through research conducted by domain experts, such as neuroscientists psychiatrists. article aims provide gentle introduction application dFC. We first explain what dFC is circumstances under it used. Next, we review two major categories approaches capture discuss caveats considerations analysis. Finally, walk readers openly accessible toolbox properties briefly metrics calculated this toolbox.

Language: Английский

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