Publications by authors named "Rodrigo A Gonzalez-Montealegre"

Article Synopsis
  • Structural income inequality, defined as the uneven distribution of income across regions, affects brain dynamics and functions more significantly than individual factors like age or education.
  • This study used EEG signals from 1,394 healthy participants across 10 countries to explore how structural inequality predicts various brain activity metrics, revealing a connection between socioeconomic conditions and neural functioning.
  • Results show that higher structural income inequality is associated with lower brain signal complexity, increased random neural activity, and reduced power in certain brain wave frequencies, suggesting the need for a broader understanding of how social factors influence brain health.
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Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries).

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Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of multimodal diversity (geographical, socioeconomic, sociodemographic, sex, neurodegeneration) on the brain age gap (BAG) is unknown. Here, we analyzed datasets from 5,306 participants across 15 countries (7 Latin American countries -LAC, 8 non-LAC).

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Diversity in brain health is influenced by individual differences in demographics and cognition. However, most studies on brain health and diseases have typically controlled for these factors rather than explored their potential to predict brain signals. Here, we assessed the role of individual differences in demographics (age, sex, and education; n = 1298) and cognition (n = 725) as predictors of different metrics usually used in case-control studies.

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Background: Recent reports suggest that by 2050 there will be an increase of around 310% of cases affected by dementia in Latin American countries. A previous study in a Southern region reported one of the highest prevalences of dementia in Latin America.

Objective: To investigate the prevalence of mild cognitive impairment associated with low education, rurality, and demographic characteristics.

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