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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