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| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 陳中明 | |
| dc.contributor.author | Mu-Fang Lee | en |
| dc.contributor.author | 李睦方 | zh_TW |
| dc.date.accessioned | 2021-06-13T03:14:11Z | - |
| dc.date.available | 2006-08-09 | |
| dc.date.copyright | 2006-08-09 | |
| dc.date.issued | 2006 | |
| dc.date.submitted | 2006-08-04 | |
| dc.identifier.citation | [1] Bollen, K.A. 1989. Structural Equations with Latent Variables. Wiley. New York.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/31521 | - |
| dc.description.abstract | 功能性核磁共振影像讓我們得以看到當大腦在感知人臉情緒時，腦部何處產生活動的改變。過去許多相關文獻指出，amygdala (AMY)、anterior cingulate cortex (ACC)、orbital-frontal cortex (OFC)與人類處理和感知情緒有關。至於這些大腦區域之間是如何相互影響，其中的機轉還不是很明朗。本論文在研究由這四個大腦區域組成的情緒網路，探討兩組受試者之中，健康個體與患者之間，情緒網路的有效聯結架構有何共通性和差異性. 11位健康個體和8位精神分裂症患者參與受試，對特定目標臉部情緒進行辨識的同時，進行功能性核磁共振影像掃描. Dynamic causal modeling (DCM)結合貝氏因子則是用於產生、推論、比較數個可能的情緒網路模型。而這些模型被指定不同的調節性聯結，內在聯結以及感覺輸入起源。 群組分析結果顯示，影像資料較支持以FFG為感覺輸入起源, 缺少從AMY, ACC和OFC到FFC等返回路徑的模型。此外，調節性聯結的作用呈現明顯的個體差異性。我們發現，調節性作用所造成大腦有效性聯結的改變，隨處理情緒物質的不同而有差別，健康受試者與患者之間也有差距。 | zh_TW |
| dc.description.abstract | The present work studied the connectivity architecture in emotional network comprising four brain areas: amygdala (AMY), anterior cingulate cortex (ACC), orbital-frontal cortex (OFC) and fusiform gyrus (FFG). 11 healthy controls and 8 schizophrenic patients underwent block-design fMRI analysis, while making judgment of a particular target facial emotion. Dynamic causal modeling (DCM) in conjunction with Bayes factors was used to compare models with different modulatory connectivity, intrinsic connectivity patterns and input regions in this emotional network. Comparison of group level showed superiority of the model in which the fusiform gyrus (FFG) serving as input region to receive external input. Moreover, models without backward connections from AMY, ACC and OFC to FFG were superior to models with fully connected structure. Furthermore, modulatory connectivity showed significant individual difference among control subjects. Our findings also illustrated differential brain connectivity due to the influence of modulatory effect (e.g. cognitive context, attention and learning), between healthy controls and schizophrenic patients, and between different types of emotional material. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T03:14:11Z (GMT). No. of bitstreams: 1 ntu-95-R91548045-1.pdf: 4531936 bytes, checksum: 0dacb6f276bde0dd6d46745ba53be8b6 (MD5) Previous issue date: 2006 | en |
| dc.description.tableofcontents | Chapter 1 Introduction 10
1.1 Motivation 10 1.2 Thesis Structure 11 Chapter 2 Background 12 2.1 Literature Survey of Brain Connectivity Analysis 12 2.1.1 Multivariate Statistical Modeling 12 2.1.2 Structural Equation Modeling 13 2.1.3 Time-Varying Parameter Regression Modeling 15 2.1.4 Bayesian Network Modeling 16 2.2 Neuronal Model 17 Chapter 3 Materials 18 3.1 Subjects 18 3.2 Study Design 18 3.3 Data Acquisition 20 Chapter 4 Dynamic Causal Modeling 21 4.1 General Model 21 4.2 Estimation 25 4.3 Inference 27 4.3.1 Bayes Factors 27 4.3.2 Group Bayes Factors 28 Chapter 5 Comparison and Determination 30 5.1 Determining Sensory Input Source 30 5.2 Determining Intrinsic Connectivity 31 5.3 Determining Modulatory Connectivity 33 Chapter 6 Results 36 6.1 Determining Sensory Input Source 36 6.2 Determining Intrinsic Connectivity 37 6.3 Determining Modulatory Connectivity 44 6.4 Differences between Controls and Patients 46 Chapter 7 Discussion 53 Chapter 8 Conclusion 55 | |
| dc.language.iso | en | |
| dc.subject | 情緒 | zh_TW |
| dc.subject | 精神分裂症 | zh_TW |
| dc.subject | 有效性聯結 | zh_TW |
| dc.subject | DCM | zh_TW |
| dc.subject | 功能性核磁共振影像 | zh_TW |
| dc.subject | effective connectivity | en |
| dc.subject | DCM | en |
| dc.subject | fMRI | en |
| dc.subject | emotion | en |
| dc.subject | schizophrenia | en |
| dc.title | 臉部情緒感知對於大腦有效性聯結的改變 | zh_TW |
| dc.title | Changes in Effective Connectivity during Perception of Facial Expression: A Dynamic Causal Modeling Study | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 94-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 劉絮愷,歐陽彥正 | |
| dc.subject.keyword | 功能性核磁共振影像,DCM,有效性聯結,情緒,精神分裂症, | zh_TW |
| dc.subject.keyword | fMRI,DCM,effective connectivity,emotion,schizophrenia, | en |
| dc.relation.page | 58 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2006-08-04 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 醫學工程學研究所 | zh_TW |
| Appears in Collections: | 醫學工程學研究所 | |
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| File | Size | Format | |
|---|---|---|---|
| ntu-95-1.pdf Restricted Access | 4.43 MB | Adobe PDF |
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