從1980年代被提出的擴散磁振造影理論(Diffusion MRI theory)至1994年推導出的擴散張量磁振造影(diffusion tensor imaging)的理論，擴散磁振造影在現今已具有高重現性，擴散磁振造影由一開始的結構影像進階到具有向量資訊的腦神經影像，不難見得在非侵入式的醫學診斷儀器發展得相當蓬勃，此項技術應用於判斷血性腦中風，可以準確評估腦部、肝臟腫瘤的治療效果。擴散張量影像技術，它主要應用在神經疾病的研究。更進一步的使用神經纖維成像技術來檢測神經網路。神經纖維成像技術，在追蹤神經網路的做法可以分為確定型神經徑路追蹤演算法(deterministic tractography methods)，機率型神經徑路追蹤演算法(probabilistic tractography methods)。在過去的研究中，所使用的確定型追蹤法已有一定的發展在於白質區域的神經追蹤，但是比較困難去描述神經在擴散方向不明確的灰質區域。我們所使用的機率型神經徑路追蹤演算法，追蹤腦迴區域間的神經纖維。透過區分不同的大腦皮質區域，並計算各個腦迴區域之間的神經連結。我們的研究運動為棒球，並將其分成三組，Skilled group(S組)：大專盃甲組(公開組)選手，包含擁有棒球專項體育保送生、體育資優生；Intermediate group(I組)：大專盃乙組(一般組)選手，或是擁有類似層級的比賽經驗，如：系際盃、社會棒球聯賽等；Control group(C組)：無棒球運動經驗者(普通體育課除外)。三組各15名受試者，共45人。我們以灰質腦區的連結機率、區域非等向性(Fractional anisotropy)和平均擴散(mean diffusivity)數據來判斷，FA的數值為0~1之間，數值越大越表此部分水分子越以單一方向擴散，臨床上可能代表神經纖維密度(fiber density)或髓鞘化(myelination)的程度。我們在灰質部分發現Paracentral Lobule、Precentral這些腦區在S組與C組受試者有顯著差異，並且也具有較大的連結機率，在白質發現Posterior corona radiata、Superior longitudinal fasciculus中S組與C組同樣有著顯著差異。本研究以棒球運動員為對象，探討長期訓練下對與腦部連結性的改變，初步結果已發現白質組織擴散影像的連結特性會因為訓練而造成群組間的差異，同時以會在灰質間的連結性找到群組間的差異，此部分結果未來可進一步與其他結構資訊(皮質厚度、體積)做比較。

本研究的主要目的在於運用靜息態功能性磁振造影技術來探討高社會焦慮的自我參照處理腦區的功能聯結。根據Clark和Wells(1995)的模型，高社會焦慮者的負向自我心象只透過自我相關的在線索來建構；然而根據Rapee和Heimberg(1997)的模型則假設高社會焦慮者還會納入他人外在訊息，做自我與他人參照訊息的處理。本研究企圖透過神經影像的發現來檢測上述兩個模型。 本研究篩選出四十名大學生分為高社會焦慮組與低社會焦慮組，所有受試者都會進行靜息態功能性磁振造影的掃描，並使用MPFC、PCC、ACC、VMPFC、DMPFC作為種子進行全腦的功能聯結分析並獲得功能聯結圖譜做比較。 研究結果發現高社會焦慮者的MPFC、PCC、ACC都有增加的功能聯結，顯示他們比一般人更容易做自我參照處理，而VMPFC、DMPFC同時有增加的功能聯結，代表高社會焦慮者的自我參照處理除了自我內在的相關訊息外，還會包含他人外在相關訊息的處理，研究結果較支持Rapee和Heimberg(1997)的說法。最後並提出本論文研究限制，與對社會焦慮症的臨床理論與實務上之建議。 / The purpose of the present study was to utilize the resting-state functional magnetic resonance imaging(RS-fMRI) technique to investigate the brain regions in functional connectivity of self-referential processing in socially anxious individuals. According to Clark and Wells’ (1995) view, socially anxious individuals were hypothesized to construct their negative self-image with self-related internal information. However, according to Repee and Heimberg’ s (1997) model, they supposed that socially anxious individuals also brought other-related external information to make other-related external information self-referential and other-referential be processed. The present study was designed to use finding of neuroimaging to examine the two models Forty undergraduate students were assigned to either high or low social-anxiety group. All subjects were asked to be scanned with RS-fMRI. MPFC, PCC, ACC, VMPFC, DMPFC were used as seeds to proceed the whole-brain functional connectivity analysis and acquired functional connectivity maps for comparison. The results revealed that functional connectivity of MPFC, PCC, ACC of high social anxiety group increased, it displayed that they were more easily to do self-referential processing. Besides, functional connectivity of VMPFC and DMPFC also increased simultaneously, which means that the self-referential processing of high social anxiety group not only included self-related internal information but also included other-related external information. The result supported Repee and Heimberg’ s model. The limitations of this study and the suggestions for the theories and clinical treatment of social anxiety disorder were advanced in the end.

在醫學領域中，磁振造影（Magnetic Resonance Imaging, MRI）因為具有良好的空間解析度及對比度，且不會對人體產生任何輻射性或侵入性的傷害，所以在疾病診斷中為經常被醫師們使用的輔助工具。其中利用磁振造影測量患者腦部血流情形所攝得之對比劑濃度與時間關係曲線圖，更是醫學界在對付腦血管病變（Brain Lesion）時的診斷利器。然而截至目前為止，我們尚未有一個較正確且快速的方法可以用來配適其對比劑濃度與時間關係曲線中的參數。所以在本論文中，我們嘗試以統計上的觀點，利用幾種不同的配適方法，找出與原始觀察值最為接近之估計值。 在本研究中使用的配適方法有—「迴歸分析法」、「Whittaker修勻法」、「非線性函數參數修勻法」及「核修勻法（Kernel Graduation）」。 本論文將以往醫學界慣用的「乘方性誤差項」改變為「加成性誤差項」，再以不同的誤差項，利用電腦模擬出各組假資料（Pseudo Data）後，以上述的四種方式對原始觀察值進行參數配適與函數估計。綜合模擬資料與真實資料所配適的比較結果，我們認為在幾種方法中，最穩健（Robust）的配適法是「Whittaker修勻法」。而在本論文中進行配適的真實資料，應該具有較大的誤差項，才導致非線性函數參數修勻法不能得出很好的估計值。 / With greater resolution, higher contrast and no radiative hurt to human body, Magnetic Resonance Imaging (MRI) is widely used by doctors in diagnosing diseases. The concentration of the contrast agent v.s. time curves which generated by MRI for cerebral blood flowing is very useful to doctors when giving treatments to brain lesion. However, we still have no precise and quick solution for fitting the curve of the concentration of the contrast agent vs. time. Therefore, this essay tries to use some different statistical fitting methods to find the closest estimates to the crude observations. We will use four different fitting methods here—"Regression Analysis", "Whittaker Graduation", "Nonlinear Function Parametric Graduation", "Kernel Graduation". This essaywill change the "multiple error term" which was usually used in the medical field to "additive error term". After using different sizes of error terms to generate pseudo data by computer simulation, we fit the parameters and estimate the values of the function to the crude data we've created with the four fitting methods mentioned above. Comparing the fitting result of the simulation data and the real data, we think the most robust fitting method is " Whittaker Graduation". The real data we have fitted in this essay may contain a greater error term, it would make " Nonlinear Function Parametric Graduation" get inadequate fitting values.