Dissertation
Dissertation > Medicine, health > Clinical > Diagnostics > Diagnostic Imaging > Magnetic resonance imaging

Functional Connectivity fMRI Study of Hand Motor-Related Brain Areas in Normal Subjects

Author YangMingMing
Tutor ZhangJing
School Tianjin Medical University
Course Medical Imaging and Nuclear Medicine
Keywords functional magnetic resonance functional connectivity connectivity coefficient connectivity degree motor-related brain networ
CLC R445.2
Type Master's thesis
Year 2011
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Objective:Functional connectivity fMRI were performed in normal subjects to investigate the constitution of hand motor-related brain network, to analyze and compare the functional connectivity of motor-related brain network between the resting state and task state, to sieve significant nodes in the network, to reveale the dynamic changes of the network from the resting state to task state and to elucidate the mechanisms of motor functional recovery as normal control.Methods:Sixty-one subjects were recruited in this study. GE 3.0T HDX MR Scanner was used to obtain high resoluation anatomy images and fMRI data in resting and task state. Task state was block-designed fMRI with both hands motion. SPM2 was used to process fMRI data. Pre-processing include slice timing, realign, normalization and smooth. Group analysis was performed with single sample t-test. Finally, activated mapping was overlapped onto standard MNI template. Locations, MNI coordinate and activated intensity of acitived brain areas were recorded. Actived brain areas in task state were selected as seed nodes. Matlab7.0 was used to calculate the connectivity coefficient(Z) and connectivity degree.Results:Bilateral supplementary motor cortex (SMA), primary motor cortex (Ml), dorsal premotor cortex (PMd), ventral premotor cortex (PMv), putamen (Pu), thalamus (Th), cerebellum anterior lobe (CbAL), cerebellum posterior lobe (CbPL) were significantly activated in task state, which consisted of a motor-related brain network, and were selected as seed nodes. Functional connectivity analysis was performed based on these seed nodes. There were 105 couples of functional connectivity in 15 seed nodes. There were 68 couples of significant connectivity coefficient in resting state,105 couples of significant connectivity coefficient in task state(|Z|>0). There were 63 significant couples of significant connectivity coefficient in resting state,105 couples of significant connectivity coefficient in task state(|Z|>0.10). There were just 45 couples of significant connectivity coefficient in resting state,103 couples of significant connectivity coefficient in task state(|Z|>0.15). Bilateral Mls, PMds, right CbAL, and right CbPL demonstrated higher connectivity degree in both resting and task states.Conclusions:1. There is a complexed motor-related brain network in both resting and task states, which is consisted of several motor-relatd brain areas.2. Bilateral Mls, PMds, right CbAL, and right CbPL were the most important and stable nodes of the motor-relatd brain network in both resting and task states.3. The motor-related brain network seems to be loose in resting state and become tighter and more stable in task state, which indicate the dynamic modulated character of the network.

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