Structural inequality and temporal brain dynamics across diverse samples

IF 7.9 1区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL Clinical and Translational Medicine Pub Date : 2024-10-03 DOI:10.1002/ctm2.70032
Sandra Baez, Hernan Hernandez, Sebastian Moguilner, Jhosmary Cuadros, Hernando Santamaria-Garcia, Vicente Medel, Joaquín Migeot, Josephine Cruzat, Pedro A. Valdes-Sosa, Francisco Lopera, Alfredis González-Hernández, Jasmin Bonilla-Santos, Rodrigo A. Gonzalez-Montealegre, Tuba Aktürk, Agustina Legaz, Florencia Altschuler, Sol Fittipaldi, Görsev G. Yener, Javier Escudero, Claudio Babiloni, Susanna Lopez, Robert Whelan, Alberto A Fernández Lucas, David Huepe, Marcio Soto-Añari, Carlos Coronel-Oliveros, Eduar Herrera, Daniel Abasolo, Ruaridh A. Clark, Bahar Güntekin, Claudia Duran-Aniotz, Mario A. Parra, Brian Lawlor, Enzo Tagliazucchi, Pavel Prado, Agustin Ibanez
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引用次数: 0

Abstract

Background

Structural 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.

Methods

Here, 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.

Findings

Despite 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.

Conclusion

These 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.

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不同样本的结构不平等和大脑的时间动态变化。
背景:结构性收入不平等--地区或国家间收入分配不均--可能会影响大脑结构和功能,超越个体差异。方法:在此,我们评估了以基尼系数衡量的结构性收入不平等对多种脑电图指标的影响,同时考虑了人口统计(年龄、性别、教育)和认知因素在受试者层面的影响。静息态脑电信号来自不同的样本(国家=10;健康人=1394,分别来自阿根廷、巴西、哥伦比亚、智利、古巴、希腊、爱尔兰、意大利、土耳其和英国)。分析了复杂性(分形维度、置换熵、维纳熵、频谱结构变异性)、功率谱和非周期性成分(1/f 斜率、膝度、偏移)以及图论测量:尽管样本、数据收集方法和脑电图采集参数存在差异,但结构不等式系统地预测了脑电生理动态,证明它是比个体水平因素更重要的脑动态决定因素。复杂性和非周期性活动指标能更好地捕捉结构不平等对大脑功能的影响。在不平等之后,年龄和认知成为最有影响力的预测因素。总体结果为结构性收入不平等的生物嵌入提供了趋同的多模态度量,其特点是复杂信号较少、随机异步神经活动增加、α和β功率降低,尤其是在颞后区域:这些发现可能会对传统的神经科学方法提出挑战,因为传统的神经科学方法往往过分强调个体层面因素的影响,而忽视结构性因素。研究结果为制定以神经科学为依据的公共政策,解决不同人群中的结构性不平等问题铺平了道路。
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来源期刊
CiteScore
15.90
自引率
1.90%
发文量
450
审稿时长
4 weeks
期刊介绍: Clinical and Translational Medicine (CTM) is an international, peer-reviewed, open-access journal dedicated to accelerating the translation of preclinical research into clinical applications and fostering communication between basic and clinical scientists. It highlights the clinical potential and application of various fields including biotechnologies, biomaterials, bioengineering, biomarkers, molecular medicine, omics science, bioinformatics, immunology, molecular imaging, drug discovery, regulation, and health policy. With a focus on the bench-to-bedside approach, CTM prioritizes studies and clinical observations that generate hypotheses relevant to patients and diseases, guiding investigations in cellular and molecular medicine. The journal encourages submissions from clinicians, researchers, policymakers, and industry professionals.
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