A method for diagnosis support of mild cognitive impairment through EEG rhythms source location during working memory tasks

Author(s)

San-Martin, Rodrigo ^[1] ; Johns, Erin ^[2] ; Mamani, Godofredo Quispe ^{[3, 4]} ; Tavares, Guilherme ^[1] ; Phillips, Natalie A. ^[2] ; Fraga, Francisco J. ^[3]

Affiliation

^[1] Fed Univ ABC, Ctr Math Comp & Cognit, Santo Andre, SP - Brazil

^[2] Concordia Univ, Dept Psychol, Montreal, PQ - Canada

^[3] Fed Univ ABC, Engn Modelling & Appl Social Sci Ctr, Santo Andre, SP - Brazil

^[4] Univ Nacl Altiplano UNAP, Dept Estadist & Informat, Puno - Peru

• Document type: Journal article
• Source: Biomedical Signal Processing and Control; v. 66, APR 2021.
• Web of Science Citations: 2

Abstract

Objective: We investigated group differences in current source density (CSD) patterns from EEG signals before and after a working memory (WM) task performed by mild cognitive impaired (MCI) subjects and healthy elderly (HE). Methods: EEG was recorded during N-back WM tasks in 41 age-, sex- and education-matched participants divided into MCI (N = 19) and HE (N = 22) groups. EEG epochs were divided into pre- and post-stimulus periods, named herein as working memory epochs (WME) and event-related epochs (ERE), respectively. Frequency-domain CSD was extracted for both WME and ERE on delta, theta, alpha, beta, and gamma bands using LORETA. Group comparisons were performed under Statistical non-Parametric Mapping. Moreover, after feature selection, we performed cross-validation with a Support Vector Machine (SVM) classifier. Results: MCI displayed increased spectral CSD on delta and theta (low-frequency) and decreased spectral CSD on (high-frequency) alpha and beta bands when compared to HE. Surprisingly, MCI patients presented an increase in gamma at precuneus and a decrease at occipital cortex. Group prediction through SVM achieved 96% accuracy, 98% specificity and 93% sensitivity when WME and ERE spectral CSD features were combined. Conclusions: Our findings confirmed the overall EEG slowing observed in classical MCI resting-state EEG literature as well as alpha desynchronization changes observed in task-related EEG literature. Furthermore, they also revealed MCI abnormalities in the gamma band. Significance: Our frequency-domain analysis of CSD patterns in task-related EEG, focusing both on pre- and poststimulus periods, may be a clinically relevant tool to support MCI diagnosis. (AU)

• FAPESP's process: 17/15243-7 - Electroencephalography-based brain connectivity analysis for Alzheimer's Disease and Diffuse Axonal Lesion diagnosis
• Grantee: Francisco José Fraga da Silva
• Support Opportunities: Regular Research Grants
• FAPESP's process: 15/09510-7 - Computational EEG analysis for early Alzheimer's Disease diagnosis
• Grantee: Francisco José Fraga da Silva
• Support Opportunities: Regular Research Grants