Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations

Nature Medicine, Год журнала: 2024, Номер 30(12), С. 3646 - 3657

Опубликована: Авг. 26, 2024

Abstract Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding health disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex neurodegeneration) on brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American Caribbean (LAC) 8 non-LAC countries). Based higher-order interactions, we developed a deep learning architecture functional magnetic resonance imaging (2,953) electroencephalography (2,353). The comprised healthy controls individuals with mild cognitive impairment, Alzheimer disease behavioral variant frontotemporal dementia. LAC models evidenced older ages (functional imaging: mean directional error = 5.60, root square (r.m.s.e.) 11.91; electroencephalography: 5.34, r.m.s.e. 9.82) associated frontoposterior networks compared models. Structural socioeconomic inequality, pollution disparities were influential predictors increased gaps, especially in ( R ² 0.37, F 0.59, 6.9). An ascending to impairment was found. In LAC, observed larger gaps females control groups respective males. results not explained by variations signal quality, demographics or acquisition methods. These findings provide quantitative framework capturing accelerated aging.

Язык: Английский

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A synergetic turn in cognitive neuroscience of brain diseases

Trends in Cognitive Sciences, Год журнала: 2024, Номер 28(4), С. 319 - 338

Опубликована: Янв. 21, 2024

Язык: Английский

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Nonlocal Models in Biology and Life Sciences: Sources, Developments, and Applications

Physics of Life Reviews, Год журнала: 2025, Номер 53, С. 24 - 75

Опубликована: Фев. 27, 2025

Язык: Английский

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Temporal Irreversibility of Large-Scale Brain Dynamics in Alzheimer’s Disease

Journal of Neuroscience, Год журнала: 2023, Номер 43(9), С. 1643 - 1656

Опубликована: Фев. 2, 2023

Healthy brain dynamics can be understood as the emergence of a complex system far from thermodynamic equilibrium. Brain are temporally irreversible and thus establish preferred direction in time (i.e., arrow time). However, little is known about how time-reversal symmetry spontaneous activity affected by Alzheimer's disease (AD). We hypothesized that level irreversibility would compromised AD, signaling fundamental shift collective properties toward equilibrium dynamics. investigated resting-state fMRI EEG data male female human patients with AD elderly healthy control subjects (HCs). quantified and, thus, proximity to nonequilibrium comparing forward backward series through time-shifted correlations. was associated breakdown temporal at global, local, network levels, multiple oscillatory frequency bands. At local level, temporoparietal frontal regions were AD. The limbic, frontoparietal, default mode, salience networks most level. reversibility cognitive decline gray matter volume HCs. provided higher accuracy more distinctive information than classical neurocognitive measures when differentiating subjects. Findings validated using an out-of-sample cohort. Present results offer new evidence regarding pathophysiological links between entropy generation rate clinical presentation opening avenues for dementia characterization different levels. SIGNIFICANCE STATEMENT By assessing large-scale across signals, we provide precise signature capable distinguishing Alzheimer’s (AD) levels regimes. Irreversibility default-mode, compared sensory–motor networks. Moreover, time-irreversibility atrophy outperformed complemented markers predictive classification performance. generalized replicated validation procedure. novel multilevel reduced has potential open understating neurodegeneration terms asymmetry

Язык: Английский

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Visual deep learning of unprocessed neuroimaging characterises dementia subtypes and generalises across non-stereotypic samples

EBioMedicine, Год журнала: 2023, Номер 90, С. 104540 - 104540

Опубликована: Март 25, 2023

Dementia's diagnostic protocols are mostly based on standardised neuroimaging data collected in the Global North from homogeneous samples. In other non-stereotypical samples (participants with diverse admixture, genetics, demographics, MRI signals, or cultural origins), classifications of disease difficult due to demographic and region-specific sample heterogeneities, lower quality scanners, non-harmonised pipelines.We implemented a fully automatic computer-vision classifier using deep learning neural networks. A DenseNet was applied raw (unpreprocessed) 3000 participants (behavioural variant frontotemporal dementia-bvFTD, Alzheimer's disease-AD, healthy controls; both male female as self-reported by participants). We tested our results demographically matched unmatched discard possible biases performed multiple out-of-sample validations.Robust classification across all groups were achieved 3T North, which also generalised Latin America. Moreover, non-standardised, routine 1.5T clinical images These generalisations robust heterogenous recordings not confounded demographics (i.e., samples, when incorporating variables multifeatured model). Model interpretability analysis occlusion sensitivity evidenced core pathophysiological regions for each (mainly hippocampus AD, insula bvFTD) demonstrating biological specificity plausibility.The generalisable approach outlined here could be used future aid clinician decision-making samples.The specific funding this article is provided acknowledgements section.

Язык: Английский

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Model-based whole-brain perturbational landscape of neurodegenerative diseases

eLife, Год журнала: 2023, Номер 12

Опубликована: Март 30, 2023

The treatment of neurodegenerative diseases is hindered by lack interventions capable steering multimodal whole-brain dynamics towards patterns indicative preserved brain health. To address this problem, we combined deep learning with a model reproducing functional connectivity in patients diagnosed Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD). These models included disease-specific atrophy maps as priors to modulate local parameters, revealing increased stability hippocampal insular signatures AD bvFTD, respectively. Using variational autoencoders, visualized different pathologies their severity the evolution trajectories low-dimensional latent space. Finally, perturbed reveal key AD- bvFTD-specific regions induce transitions from pathological healthy states. Overall, obtained novel insights on progression control means external stimulation, while identifying dynamical mechanisms that underlie alterations neurodegeneration.

Язык: Английский

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Brain health in diverse settings: How age, demographics and cognition shape brain function

NeuroImage, Год журнала: 2024, Номер 295, С. 120636 - 120636

Опубликована: Май 21, 2024

Diversity in brain health is influenced by individual differences demographics and cognition. However, most studies on diseases have typically controlled for these factors rather than explored their potential to predict signals. Here, we assessed the role of (age, sex, education; n = 1,298) cognition (n 725) as predictors different metrics usually used case-control studies. These included power spectrum aperiodic (1/f slope, knee, offset) metrics, well complexity (fractal dimension estimation, permutation entropy, Wiener spectral structure variability) connectivity (graph-theoretic mutual information, conditional organizational information) from source space resting-state EEG activity a diverse sample global south north populations. Brain-phenotype models were computed using reflecting local (power components) dynamics interactions (complexity graph-theoretic measures). Electrophysiological modulated despite varied methods data acquisition assessments across multiple centers, indicating that results unlikely be accounted methodological discrepancies. Variations signals mainly age cognition, while education sex exhibited less importance. Power measures sensitive capturing differences. Older age, poorer being male associated with reduced alpha power, whereas older network integration segregation. Findings suggest basic impact core function are standard Considering variability diversity settings would contribute more tailored understanding function.

Язык: Английский

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Safety, tolerability, and efficacy estimate of evoked gamma oscillation in mild to moderate Alzheimer’s disease

Frontiers in Neurology, Год журнала: 2024, Номер 15

Опубликована: Март 6, 2024

Background Alzheimer’s Disease (AD) is a multifactorial, progressive neurodegenerative disease that disrupts synaptic and neuronal activity network oscillations. It characterized by loss, brain atrophy decline in cognitive functional abilities. Cognito’s Evoked Gamma Therapy System provides an innovative approach for AD inducing EEG-verified gamma oscillations through sensory stimulation. Prior research has shown promising disease-modifying effects experimental models. The present study (NCT03556280: OVERTURE) evaluated the feasibly, safety efficacy of evoked oscillation treatment using medical device (CogTx-001) participants with mild to moderate AD. Methods was randomized, double blind, sham-controlled, 6-months clinical trial enrolled 76 participants, aged 50 or older, who met criteria baseline MMSE scores between 14 26. Participants were randomly assigned 2:1 receive self-administered daily, one-hour, therapy, evoking sham treatment. CogTx-001 use at home help care partner, over 6 months. primary outcome measures safety, physical neurological exams monthly assessments adverse events (AEs) MRI, tolerability, measured use. Although not statistically powered evaluate potential outcomes, secondary included several endpoints. Results Total AEs similar groups, there no unexpected serious related AEs, treatment-emergent led discontinuation. MRI did show Amyloid-Related Imaging Abnormalities (ARIA) any participant. High adherence rates (85–90%) observed participants. There statistical separation active arm measure MADCOMS CDR-SB ADAS-Cog14. However, some including ADCS-ADL, MMSE, whole volume demonstrated reduced progression compared treated achieved nominal significance. Conclusion Our results demonstrate 1-h daily safe well-tolerated benefits Clinical Trial Registration: www.ClinicalTrials.gov , identifier: NCT03556280.

Язык: Английский

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Functional and effective EEG connectivity patterns in Alzheimer’s disease and mild cognitive impairment: a systematic review

Frontiers in Aging Neuroscience, Год журнала: 2025, Номер 17

Опубликована: Фев. 12, 2025

Background Alzheimer’s disease (AD) might be best conceptualized as a disconnection syndrome, such that symptoms may largely attributable to disrupted communication between brain regions, rather than deterioration within discrete systems. EEG is uniquely capable of directly and non-invasively measuring neural activity with precise temporal resolution; connectivity quantifies the relationships signals in different regions. research on AD mild cognitive impairment (MCI), often considered prodromal phase AD, has produced mixed results yet synthesized for comprehensive review. Thus, we performed systematic review MCI participants compared cognitively healthy older adult controls. Methods We searched PsycINFO, PubMed, Web Science peer-reviewed studies English EEG, connectivity, MCI/AD relative Of 1,344 initial matches, 124 articles were ultimately included Results The primarily analyzed coherence, phase-locked, graph theory metrics. influence factors demographics, design, approach was integrated discussed. An overarching pattern emerged lower both controls, which most prominent alpha band, consistent AD. In minority reporting greater theta band commonly implicated MCI, followed by alpha. overall prevalence effects indicate its potential provide insight into nuanced changes associated AD-related networks, caveat during resting state where dominant frequency. When reported it task engagement, suggesting compensatory resources employed. common rest, engagement already exhausted. Conclusion highlighted powerful tool advance understanding communication. address need including demographic methodological details, using source space extending this work adults risk toward advancing early detection intervention.

Язык: Английский

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Source space connectomics of neurodegeneration: One-metric approach does not fit all

Neurobiology of Disease, Год журнала: 2023, Номер 179, С. 106047 - 106047

Опубликована: Фев. 23, 2023

Brain functional connectivity in dementia has been assessed with dissimilar EEG metrics and estimation procedures, thereby increasing results' heterogeneity. In this scenario, joint analyses integrating information from different may allow for a more comprehensive characterization of brain interactions subtypes. To test hypothesis, resting-state electroencephalogram (rsEEG) was recorded individuals Alzheimer's Disease (AD), behavioral variant frontotemporal (bvFTD), healthy controls (HCs). Whole-brain estimated the source space using 101 types connectivity, capturing linear nonlinear both time frequency-domains. Multivariate machine learning progressive feature elimination run to discriminate AD HCs, bvFTD based on i) frequency bands, ii) complementary frequency-domain (e.g., instantaneous, lagged, total connectivity), iii) time-domain linearity assumption Pearson correlation coefficient mutual information). <10% all possible connections were responsible differences between patients controls, atypical never captured by >1/4 measures. Joint revealed patterns hypoconnectivity (patientsHCs) groups mainly identified regions. These atypicalities differently frequency- metrics, bandwidth-specific fashion. The multi-metric representation whole-brain evidenced inadequacy single-metric approaches, resulted valid alternative selection problem connectivity. reveal interdependence that are overlooked single contributing reliable interpretable description neurodegeneration.

Язык: Английский

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