Analysis of EEG Complexity in Patients with Mild Cognitive Impairment

Abstract

Objective: Mild cognitive impairment patients and normal elderly people were selected in this research. EEG complexity (Lempel-Ziv Complexity, LZC) and P300 value of the two groups were compared in two statuses (quiet eyes closed, cognitive load), The brain functional characteristics of different cognitive states were explored, it was expected to construct a simple and objective cognitive function evaluation approach to provide criteria for early diagnosis of cognitive dysfunction and disease evaluation. Methods: The clinical data was from 50 MCI patients in Neurology department of the 8th People’s Hospital. 45 normal elderly people with corresponding sex, age and education level was chosen as control group. 5 minutes EEG signals were recorded and measured with P300 for both groups with quiet eyes closed and cognitive load states. Due to smooth baseline and inconspicuous artifacts, 2048-point EEG (about 8s) were selected to perform LZC analysis and complexity calculation in Mat tab. Results: 1. Normal elderly people showed higher LZC than MCI patients. Moreover, LZC was higher in those complex brain function areas such as temporal and frontal areas. 2. With the reduction of cognitive function, the value of EEG complexity was reduced accordingly. 3. The cognitive related brain areas showed more obvious degradation than other brain areas. 4. Under the cognitive load status, the complexity value in cognitive related brain areas of MCI patients decreased significantly. 5. The prolongation of P300 latency and LZC decrease of the MCI patients indicated that LZC could reflect the decrease of cognitive function. Discussion: In this study, P300 latencies of MCI group was delayed, we could deduce that because of the decline in brain function and brain areas of fibers connecting, the reduction in information processing performance could indicate that the delay of P300 latent period. These were identical with another study where the complexity of EEG is testified that. Based on these, we could infer, from the perspective of nonlinearity, EEG complexity reveals the changes of brain function in patients with cognitive impairment. Conclusion: The brain electrical LZC value in normal elderly people group was higher than that in cognitive impairment group, those brain areas with more complex functions like frontal area and temporal area had highest LZC, which illustrated the degree distribution differences in complex brain regions. The prolonged latency of P300, these results of cognitive impairment in patients could also predict the degree of cognitive decline.