Abstract #4148

Altered Dynamic Functional Connectivity State Patterns of Patients with Idiopathic Parkinson’s Disease

Naying He^1,2, Shiyang Chen³, Jason Langley⁴, Yong Zhang⁵, Fuhua Yan¹, and Xiaoping Hu^4,6

¹Radiology, Ruijin Hospital,Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China, ²Center for Advanced Neuroimaging, University of California, Riverside, Riverside, CA, United States, ³Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States, ⁴Center for Advanced Neuroimaging, University of California, Riverside, Riverside, Riverside, CA, United States, ⁵MR Research, GE Healthcare, Shanghai, People's Republic of China, ⁶Department of Bioengineering, University of California, Riverside, Riverside, Riverside, CA, United States

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by nigral-striatal dopamine deficiency and motor symptoms. Neuroimaging studies have shown that functional connectivity within cortical-striatal networks and related connections are disturbed in PD. But these are based on conventional static resting-state analyses which assume functional connectivity being static over time. Recent studies have demonstrated that resting state brain activity is highly dynamic. In this work, we applied Gaussian Hidden Markov Model to investigate dynamic functional connectivity in PD and compared it with that in normal controls. Our results show alterations in sensorimotor, DMN, and visual networks in PD.

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