Abstract #1566

Abnormal Multilayer Brain Network in Early-Stage Akinetic-Rigid Parkinson’s Disease

Kaiyue Ding¹, Yu Shen², Yao Ge², Xinhui Wang², Yan Bai², Wei Wei², Xianchang Zhang³, Mengzhu Wang³, Kaixin Li³, and Meiyun Wang^1,2,4

¹Henan University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China, ²Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China, ³MR Research Collaboration, Siemens Healthineers Ltd., Beijing, China, ⁴Biomedical Research Institute, Henan Academy of Sciences, Zhengzhou, China

Synopsis

Keywords: fMRI Analysis, Parkinson's Disease

Motivation: This study uses multilayer neural network techniques to explore brain network abnormalities in early-stage Akinetic-Rigid Parkinson’s Disease (AR-PD).

Goal(s): AR-PD patients exhibit rapid clinical progression, necessitating early detection of abnormal brain network activity.

Approach: To investigate the relationship between dynamic brain network properties (modularity and switching rates) and clinical scores in AR-PD.

Results: fMRI data from 38 AR-PD patients and 39 controls were analyzed using a multilayer neural network model.

Impact: AR-PD patients showed abnormal dynamic brain network switching and increased modularity, linked to clinical measures like motor function.

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