Prado Pavel, Mejía Jhony A, Sainz-Ballesteros Agustín, Birba Agustina, Moguilner Sebastian, Herzog Rubén, Otero Mónica, Cuadros Jhosmary, Z-Rivera Lucía, O'Byrne Daniel Franco, Parra Mario, Ibáñez Agustín
Latin American Brain Health Institute (BrainLat) Universidad Adolfo Ibáñez Santiago de Chile Chile.
Escuela de Fonoaudiología Facultad de Odontología y Ciencias de la Rehabilitación Universidad San Sebastián Santiago Chile.
Alzheimers Dement (Amst). 2023 Jul 8;15(3):e12455. doi: 10.1002/dad2.12455. eCollection 2023 Jul-Sep.
Harmonization protocols that address batch effects and cross-site methodological differences in multi-center studies are critical for strengthening electroencephalography (EEG) signatures of functional connectivity (FC) as potential dementia biomarkers.
We implemented an automatic processing pipeline incorporating electrode layout integrations, patient-control normalizations, and multi-metric EEG source space connectomics analyses.
Spline interpolations of EEG signals onto a head mesh model with 6067 virtual electrodes resulted in an effective method for integrating electrode layouts. Z-score transformations of EEG time series resulted in source space connectivity matrices with high bilateral symmetry, reinforced long-range connections, and diminished short-range functional interactions. A composite FC metric allowed for accurate multicentric classifications of Alzheimer's disease and behavioral variant frontotemporal dementia.
Harmonized multi-metric analysis of EEG source space connectivity can address data heterogeneities in multi-centric studies, representing a powerful tool for accurately characterizing dementia.
在多中心研究中，解决批次效应和跨站点方法差异的协调方案对于强化作为潜在痴呆生物标志物的功能连接（FC）的脑电图（EEG）特征至关重要。
我们实施了一个自动处理流程，该流程纳入了电极布局整合、患者-对照标准化以及多指标EEG源空间连接组学分析。
将EEG信号样条插值到具有6067个虚拟电极的头部网格模型上，产生了一种有效的电极布局整合方法。EEG时间序列的Z分数变换产生了具有高双侧对称性、增强的长程连接和减弱的短程功能相互作用的源空间连接矩阵。一个复合FC指标允许对阿尔茨海默病和行为变异型额颞叶痴呆进行准确的多中心分类。
EEG源空间连接的协调多指标分析可以解决多中心研究中的数据异质性问题，是准确表征痴呆的有力工具。
