Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/5569
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dc.contributor.authorBaez, Sandra-
dc.contributor.authorHernandez, Hernan-
dc.contributor.authorMoguilner, Sebastian-
dc.contributor.authorCuadros, Jhosmary-
dc.contributor.authorSantamaria-Garcia, Hernando-
dc.contributor.authorMedel, Vicente-
dc.contributor.authorMigeot, Joaquin-
dc.date.accessioned2024-10-25T15:17:53Z-
dc.date.available2024-10-25T15:17:53Z-
dc.date.issued2024-
dc.identifier.issn2001-1326-
dc.identifier.urihttps://doi.org/10.1002/ctm2.70032-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/5569-
dc.description.abstractBackgroundStructural income inequality - the uneven income distribution across regions or countries - could affect brain structure and function, beyond individual differences. However, the impact of structural income inequality on the brain dynamics and the roles of demographics and cognition in these associations remains unexplored.MethodsHere, we assessed the impact of structural income inequality, as measured by the Gini coefficient on multiple EEG metrics, while considering the subject-level effects of demographic (age, sex, education) and cognitive factors. Resting-state EEG signals were collected from a diverse sample (countries = 10; healthy individuals = 1394 from Argentina, Brazil, Colombia, Chile, Cuba, Greece, Ireland, Italy, Turkey and United Kingdom). Complexity (fractal dimension, permutation entropy, Wiener entropy, spectral structure variability), power spectral and aperiodic components (1/f slope, knee, offset), as well as graph-theoretic measures were analysed.FindingsDespite variability in samples, data collection methods, and EEG acquisition parameters, structural inequality systematically predicted electrophysiological brain dynamics, proving to be a more crucial determinant of brain dynamics than individual-level factors. Complexity and aperiodic activity metrics captured better the effects of structural inequality on brain function. Following inequality, age and cognition emerged as the most influential predictors. The overall results provided convergent multimodal metrics of biologic embedding of structural income inequality characterised by less complex signals, increased random asynchronous neural activity, and reduced alpha and beta power, particularly over temporoposterior regions.ConclusionThese findings might challenge conventional neuroscience approaches that tend to overemphasise the influence of individual-level factors, while neglecting structural factors. Results pave the way for neuroscience-informed public policies aimed at tackling structural inequalities in diverse populations. We analysed EEG data from 1394 participants across 10 countries, using the Gini coefficient and sociodemographic variables to predict EEG metrics.Four categories of EEG metrics were computed: complexity, aperiodic spectral components, power spectrum, and connectivity.ROC curves, feature importance rankings, and topographical brain region information were reported.Structural income inequality consistently predicts EEG metrics, surpassing individual demographic factors. imageen_US
dc.description.sponsorshipFogarty International Center; Fogarty International Center (FIC) [R01 AG057234, R01 AG075775, R01 AG21051, R01 AG083799, CARDS-NIH]; National Institutes of Health, National Institutes of Aging [SG-20-725707]; Alzheimer's Association; Rainwater Charitable Foundation [1210195, 1210176, 1220995, ANID/FONDAP/15150012]; ANID/FONDECYT Regular [ID20I10152]; FONDEF [BL-SRGP2020-02]; Latin American Brain Health Instituteen_US
dc.description.sponsorshipAI is supported by grants from the MULTI-PARTNER CONSORTIUM TO EXPAND DEMENTIA RESEARCH IN LATIN AMERICA [ReDLat, supported by Fogarty International Center (FIC), National Institutes of Health, National Institutes of Aging (R01 AG057234, R01 AG075775, R01 AG21051, R01 AG083799, CARDS-NIH), Alzheimer's Association (SG-20-725707), Rainwater Charitable Foundation - The Bluefield project to cure FTD, and Global Brain Health Institute)], ANID/FONDECYT Regular (1210195 and 1210176 and 1220995); ANID/FONDAP/15150012; ANID/PIA/ANILLOS ACT210096; FONDEF ID20I10152. AI and MP are supported by the Latin American Brain Health Institute (BrainLat) Seed Grant BL-SRGP2020-02.en_US
dc.language.isoenen_US
dc.publisherJohn Wiley & Sons Ltden_US
dc.relation.ispartofClinical and translational medicineen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectbrain dynamicsen_US
dc.subjectcognitionen_US
dc.subjectdemographicsen_US
dc.subjectEEGen_US
dc.subjectindividual differencesen_US
dc.subjectstructural income inequalityen_US
dc.subjectAge-Related-Changesen_US
dc.subjectIncome Inequalityen_US
dc.subjectAlzheimers-Diseaseen_US
dc.subjectElectromagnetic Tomographyen_US
dc.subjectComplexity Analysisen_US
dc.subjectCognitive Declineen_US
dc.subjectSmall-Worldnessen_US
dc.subjectPower Spectraen_US
dc.subjectEegen_US
dc.subjectGenderen_US
dc.titleStructural inequality and temporal brain dynamics across diverse samplesen_US
dc.typeArticleen_US
dc.identifier.doi10.1002/ctm2.70032-
dc.identifier.pmid39360669en_US
dc.departmentİzmir Ekonomi Üniversitesien_US
dc.authoridGonzalez-Montealegre, Rodrigo Alberto/0000-0003-1805-5766-
dc.identifier.volume14en_US
dc.identifier.issue10en_US
dc.identifier.wosWOS:001324725200001en_US
dc.institutionauthor-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
item.grantfulltextnone-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
Appears in Collections:PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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