| Summary: | 碩士 === 國立清華大學 === 生醫工程與環境科學系 === 100 === In current study, we adapted independent component analysis as a data-driven based method to establish the possible Resting State Network (RSN) in rat brain. Early work has shown the feasibility of Spontaneously Hypertension Rats in modeling the behavior, gene expression, and pharmacological research of Attention Deficit Hyperactivity Disorder. Therefore, coupling ICA with ALFF analysis and Seed-based Functional Connectivity Analysis, we intended to establish the feasibility of having SHR as a brain function model of ADHD. In this report, we determined the distinguishable connectivity pattern in both groups and SHR exhibits generally intense activation in the cortex areas. Four findings have been revealed from the approaches: 1.) Comparison of ICA maps with different sampling rate. 2.) ALFF/ fALFF analysis. 3.) Cross correlation values in Resting state functional connectivity matrix (RSFC matrix) with different sampling rate. Our study reveals potential feasibility to model the dysfunction network in ADHD, and further, to achieve pioneer investigation in brain network under high field MRI scanner in small animal.
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