Advanced search
Start date
Betweenand
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

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

Full text
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]
Total Authors: 6
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
Total Affiliations: 4
Document type: Journal article
Source: Biomedical Signal Processing and Control; v. 66, APR 2021.
Web of Science Citations: 0
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: 15/09510-7 - Computational EEG analysis for early Alzheimer's Disease diagnosis
Grantee:Francisco José Fraga da Silva
Support type: Regular Research Grants
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 type: Regular Research Grants