AUTHOR=Razzaq Fuleah A. , Calzada-Reyes Ana , Tang Qin , Guo Yanbo , Rabinowitz Arielle G. , Bosch-Bayard Jorge , Galan-Garcia Lidice , Virues-Alba Trinidad , Suarez-Murias Carlos , Miranda Ileana , Riaz Usama , Bernardo Lagomasino Vivian , Bryce Cyralene , Anderson Simon G. , Galler Janina R. , Bringas-Vega Maria L. , Valdes-Sosa Pedro A. 

TITLE=Spectral quantitative and semi-quantitative EEG provide complementary information on the life-long effects of early childhood malnutrition on cognitive decline

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 17 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2023.1149102

DOI=10.3389/fnins.2023.1149102

ISSN=1662-453X

ABSTRACT=Objective: This study compares the complementary information from semi-quantitative EEG (sqEEG) and spectral quantitative EEG (spectral-qEEG) to detect early childhood malnutrition's life-long effects on the brain.Methods: N=202 resting-state EEGs from the Barbados Nutrition Study were used to examine the effects of Protein-Energy Malnutrition (PEM) in childhood and middle adulthood. sqEEG analysis was performed on Grand Total EEG (GTE) protocol, and a single latent variable called semi-quantitative Neurophysiological State (sqNPS) was extracted. A univariate linear mixedeffects (LME) model tested the dependence of sqNPS and nutritional group. sqEEG was compared with the Montreal Cognitive Assessment (MoCA). Stable sparse classifiers (SSC) also measured the predictive power of sqEEG, spectral-qEEG, and a combination of both. Multivariate LME was applied to assess each EEG modality separately and combined under longitudinal settings.The univariate LME showed highly significant differences between groups (p<0.001), age(p=0.01) was also significant, with no interaction between group and age detected. Childhood sqNPS(p=0.02) and adulthood sqNPS (p=0.003) predicted cognitive scores in adulthood. The SSC demonstrated that spectral-qEEG combined with sqEEG had the highest prediction power (mean AUC 0.92±0.005). Finally, multivariate LME showed that the spectral-qEEG+sqEEG combination models had the highest log-likelihood (-479.7).Conclusions: This research has extended our prior work with spectral-qEEG and the long-term impact of early childhood malnutrition on the brain. Our findings showed that sqNPS was significantly linked to accelerated cognitive aging at 45-51 years of age. While sqNPS and spectral-qEEG produced comparable results, our study indicated that sqNPS provided additional information to qEEG. Additionally, combining sqNPS and spectral-qEEG yielded better performance than either method alone, suggesting that a multimodal approach could be advantageous for future investigations.Significance: Based on our findings, a semi-quantitative approach utilizing GTE could be a valuable diagnostic tool for detecting the lasting impacts of childhood malnutrition. Notably, sqEEG has not been previously explored or reported as a biomarker for assessing the longitudinal effects of malnutrition. Furthermore, our observations suggest that sqEEG offers unique features and information not captured by spectral quantitative EEG analysis and could lead to its improvement.