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Abstract #4193

Seed Regions and Independent Component Analysis of Resting State Brain Functional Connectivity in a Rat Model of Parkinson's Disease

Hui-Yu Wang 1 , You-Yin Chen 2 , Sheng-Huang Lin 3,4 , and Jun-Cheng Weng 1,5

1 School of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan, 2 Department of Biomedical Engineering, National Yang-Ming University, Taipei, Taiwan, 3 Department of Neurology, Tzu Chi General Hospital, Tzu Chi University, Hualien, Taiwan, 4 Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan, 5 Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that is characterized by dopamine depletion in the striatum, and it associated with predominantly motor, cognitive and affective symptoms. The clinical diagnosis of PD is extremely difficult, because the symptom is similar to other central nervous disorder, such as Alzheimer’s disease and Hydrocephalus. The most common diagnostic methods are neurologist’s inquiry and positron emission tomogram (PET) studies. One consistent pathophysiological hallmark of PD is the change in spontaneous oscillatory activity in the basal ganglia thalamocortical networks. Therefore, the goal of our study is to evaluate brain functional connectivity changes using frequency-specific resting-state functional MRI (rs-fMRI) in PD rat and baseline controls using three different seed regions analysis, motor cortex (M1), corpus striatum (CPu) and substantia nigra (SNr), and independent component analysis (ICA). Our results showed a PD-associated decrease in cortico-cortical and cortico-striatal functional connectivity and drops in the power content of cortical and striatal signals. Our results demonstrated that PD modulate cortical and striatal resting state BOLD signal oscillations and cortico-cortical as well as cortico-striatal network correlation.

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