臺灣博碩士論文加值系統

近年來，醫學影像相關的研究於大腦和神經活動已逐漸深入探討，例如功能性磁振造影(Functional magnetic resonance imaging, fMRI)。功能性磁振造影比起其他的成像技術不僅能透過大腦血氧的變化觀察腦內活動情況，同時也是種具有高空間解析度的技術。
為了探討在聽覺-運動實驗中腦區域之間的因果關係，我們利用格蘭傑因果關係的分析方法(Granger causality analysis)來辨別其時間上的先後關係。此外，實驗因素的選擇對分析結果會有所差異，例如：濾波器的使用、重複時間(Repetition time, TR)的長短等。本研究透過電腦數值模擬的應用選擇出最適合的實驗因素，進而得出無誤的結果。最後，實驗結果中顯示在重複時間短的實驗且不使用濾波器的情況下最能正確地呈現出大腦認知區域間的因果關係。

Recently, medical imaging studies often search for brain and nerve activity, such as functional magnetic resonance imaging (fMRI). FMRI is not only capable of observing changes in cerebral blood oxygenation but also of higher spatial resolution.
In this study, we would like to explore effect connectivity among brain regions in auditory-motor experiment using conditional Granger causality analysis, which is one statistical test method to analysis temporal causal correlation between fMRI time series. In addition, we discovered that several factors may affect the results of causal analysis, such as the utilization of filter and the selection of repetition time (TR). Thus, the appropriate factors are selected in conditional Granger causality analysis by the conclusion of simulations. The results show the outflows from auditory cortex are highly detectable in auditory-motor experiment. In addition, it is shown that time series acquired with short TR without filtering present higher reproducibility in effective connectivity among brain cognitive regions.

摘要..............................................i
Abstract.........................................ii
Acknowledgement..................................iii
Table of Contents................................iv
List of Tables...................................vii
List of Figures..................................viii
Chapter 1 Introduction...........................1
1.1 Motivation...............................1
1.2 Background and Related Works.............3
1.2.1. Functional Magnetic Resonance Imaging....3
1.2.2. Functional and Effective Connectivity....5
Chapter 2 Materials and Methods..................7
2.1 Flow chart...............................7
2.2 Data Preprocessing.......................9
2.2.1. Slice Timing Correction..................10
2.2.2. Motion Correction........................11
2.2.3. Coregistration, Segmentation and Normalization..12
2.2.4. Spatial Smoothing........................13
2.2.5. General Linear Model.....................14
2.2.6. ROI Selection............................16
2.3 Conditional Granger Causality Analysis...17
2.4 Data Acquisition.........................19
2.5 Possible Confounding Factors in CGC Analysis...21
2.5.1. The effect of IIR band-pass filtering....22
2.5.2. The effect of coefficient and temporal smoothing..23
2.5.3. The effect of repetition time............24
Chapter 3 Result.................................25
3.1 SPM analysis.............................25
3.1.1. Motion Correction........................25
3.1.2. Coregistration, Segmentation and Normalization...28
3.1.3. ROI Selection............................29
3.2 Human Subject Experiment.................32
3.2.1. Causal links from CGC analysis...........32
3.3 Possible Confounding Factors in CGC Analysis.....34
3.3.1. The effect of IIR band-pass filtering....34
3.3.2. The effect of coefficient and temporal smoothing..37
3.3.3. The effect of repetition time............42
Chapter 4 Discussion and Conclusion..............44
4.1. Human Subject Experiment.................44
4.2. The effect of IIR band-pass filtering....44
4.3. The effect of coefficient and temporal smoothing..45
4.4. The effect of repetition time............46
4.5. Future work..............................48
Reference........................................49

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