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| Functional Network Characterization Analysis of Parkinson’s Mild Cognitive Impairment Based on EEG |
| LI Xin1,2,ZHANG Qing1,2,ZHANG Ying1,2,XIE Ping1,2,3,YIN Liyong4 |
1. School of Electrical Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China
2. Measurement Technology and Instrumentation Key Lab of Hebei Province, Qinhuangdao, Hebei 066004, China
3. Institute of Health and Wellness Industry Technology, Yanshan University, Qinhuangdao, Hebei 066004, China
4. Qinhuangdao First Hospital, Qinhuangdao, Hebei 066004, China |
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Abstract Parkinson’s mild cognitive impairment (PDMCI) is a precursor to dementia in Parkinsons patients, posing challenges for accurate diagnosis using conventional methods such as neurological rating scales and doctors experience. By using the EEG signals of 26 PDMCI patients and 23 normal subjects, the brain function networks of Delta, Theta, Alpha, Beta and Gamma bands were constructed based on the directional transfer function. A novel graph theory feature, efficiency density, is introduced to capture both network density and transmission efficiency. The findings reveal distinctive connectivity patterns, with tighter connections in Delta and Theta bands and sparser connections in Alpha, Beta, and Gamma bands. Significant differences between PD patients and the control group are observed in Theta, Alpha, Beta, and Gamma bands (p<0.05). Therefore, the brain function network can effectively reflect the abnormal brain function status of PD, and the efficiency density characteristic can reflect the characteristic amount of abnormal brain activity in PD.
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Received: 20 July 2023
Published: 22 January 2024
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2024, Vol. 45 
