Computational modeling of the effects of EEG volume conduction on functional connectivity metrics. Application to Alzheimer's disease continuum. (29th October 2019)

• Record Type: Journal Article
• Authors: Ruiz-Gómez, Saúl J; Hornero, Roberto; Poza, Jesús; Maturana-Candelas, Aarón; Pinto, Nádia; Gómez, Carlos
• Is Part Of: Journal of neural engineering. Volume 16:Number 6(2019:Dec.)
• Publication Date: 2019-10-29
• Subjects: Alzheimer's disease -- mild cognitive impairment -- electroencephalography (EEG) -- synthetic signals -- volume conduction -- neural coupling; Neurosciences -- Periodicals; Biomedical engineering -- Periodicals; 612.8
• DOI: 10.1088/1741-2552/ab4024
• Languages: English
• ISSNs: 1741-2560

Abstract

Abstract: Objective . The aim of this study was to evaluate the effect of electroencephalographic (EEG) volume conduction in different measures of functional connectivity and to characterize the EEG coupling alterations at the different stages of dementia due to Alzheimer's disease (AD). Approach . Magnitude squared coherence ( MSCOH ), imaginary part of coherence ( iCOH ), lagged coherence ( lagCOH ), amplitude envelope correlation ( AEC ), synchronization likelihood ( SL ), phase lag index ( PLI ), phase locking value ( PLV ), and corrected imaginary PLV ( ciPLV ) were applied to: (i) synthetic signals generated with a Kuramoto-based model of several coupled oscillators; and (ii) a resting-state EEG database of real recordings from 51 cognitively healthy controls, 51 mild cognitive impairment (MCI) subjects, 51 mild AD (AD mil ) patients, 50 moderate AD (AD mod ) patients, and 50 severe AD (AD sev ) patients. Main results . Our results using synthetic signals showed that PLI was the least affected parameter by spurious influences in a simulated volume conduction environment. Results using real EEG recordings showed that spontaneous activity of MCI patients is characterized by a significant coupling increase in the band. As dementia progresses, this increase in the band became more pronounced, and a significant widespread decrease in band appeared at the last stage of dementia. Significance . Our results revealed that the estimation of functional EEG connectivity using PLI could reduce the bias introduced by the spurious influence of volume conduction, and it could increase the insight into the underlying brain dynamics at different stages of the AD continuum.