Functional Connectivity Analysis of Visually Evoked ERPs for Mild Cognitive Impairment: Pilot Study.

Abstract

Mild cognitive impairment (MCI) is considered the early stage of Alzheimer's disease, characterized as mild memory loss. 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 analyze the effects of MCI. Applying FC method of weighted phase lag index (wPLI) to P300 ERPs provided insight on the link between the pathology of Alzheimer's disease and cognitive loss. wPLI was analyzed per frequency band (θ, α, μ, β) 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 ΔwPLIP300 compared to normal controls in the μ intra-hemispheric short (p = 0.0286), μ intra-hemispheric long (p = 0.0477), μ inter-hemispheric short (p = 0.0018) and the α 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.