Functional Connectivity Analysis of Visually Evoked ERPs for Mild Cognitive Impairment
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Date
2022-04-28
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Authors
Wang, Lana
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Publisher
East Carolina University
Abstract
Mild cognitive impairment (MCI) is considered as the early stage of Alzheimer's disease, characterized as mild memory loss. Using electroencephalogram (EEG) data, a novel method of functional connectivity (FC) analysis can be used to detect MCI before memory is significantly impaired allowing for preventative measures to be taken. FC examines interactions between EEG channels to grant insight on underlying neural networks and can also allow for an examination of the effects of MCI on these neural networks. The FC method of weighted phase lag index (wPLI) provided insight on the link between the pathology of Alzheimer's disease and cognitive loss. wPLI was analyzed per frequency band (theta, alpha, mu, beta) and by channel combination groups (intra-hemispheric short, intra-hemispheric long, inter-hemispheric short, inter-hemispheric long, transverse). MCI was found to have a statistically significant lower [delta]wPLIP300 compared to normal controls in the mu intra-hemispheric short (p = 0.0286), mu intra-hemispheric long (p = 0.0477), mu inter-hemispheric short (p = 0.0018) and the alpha intra-hemispheric short (p = 0.0423). Results indicate a possible deficiency in the dorsal visual processing pathway among MCI subjects as well as an unbalanced coordination between the two hemispheres.