研究生: |
楊永毅 Yang, Yung-I |
---|---|
論文名稱: |
利用功能性近紅外線光譜及獨立成分分析演算法來評估更新作業的活化腦區 Using Independent Component Analysis Algorithm to Evaluate Activated Brain Regions in Updating Task by Functional Near-Infrared Spectroscopy |
指導教授: |
劉奕汶
Liu, Yi-Wen 陳新 Chen, Hsin |
口試委員: |
周育如
Chou, Yu-Ju 陳欣進 Chen, Hsin-Chin |
學位類別: |
碩士 Master |
系所名稱: |
電機資訊學院 - 電機工程學系 Department of Electrical Engineering |
論文出版年: | 2018 |
畢業學年度: | 106 |
語文別: | 中文 |
論文頁數: | 122 |
中文關鍵詞: | 功能性近紅外線光譜 、前額葉 、工作記憶 、快速獨立成分分析 |
外文關鍵詞: | functional near-infrared spectroscopy, prefrontal cortex, working memory, fast independent components analysis |
相關次數: | 點閱:1 下載:0 |
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本論文利用功能性近紅外線光譜(functional near-infrared spectroscopy, fNIRS) 獲取大腦前額葉血紅素濃度的變化,來檢驗前額葉區是否對不同的記憶更新材料,呈現不同的活化區域和活化程度。
本研究主題為工作記憶更新作業,採用四種刺激材料與更新作業:(1)字母記憶作業、(2)音調監控作業、(3)空間回數作業及(4)數字回數作業。在作業進行時,受試者必須根據新刺激的不斷出現,持續更新記憶中的答案,並在題目結束後回憶正確答案。
在fNIRS的訊號處理方面,係利用了快速獨立成分分析(fast independent components analysis, fastICA)演算法進行盲訊號分離(blind source separation, BSS),來將血紅素濃度訊號進行特徵提取與資料降維,所得到的獨立成分再利用平均試驗間相關性(Mean inter-trial cross-correlation, MITC)以進行訊號block相關程度的評估,找出最具有block相關性的獨立成分,即為因為神經活化的變化所引發的血紅素濃度改變。
研究結果主要發現有以下三項:(1)不同於文獻中的功能性磁振造影結果,空間回數作業與數字回數作業比較下,發現有dorsal 及ventral prefrontal cortex的分區活化現象、(2)結果觀察到字母、空間及數字素材偏向右腦活化,音調偏向左腦活化、(3)若依據記憶更新答題的表現,比較最高表現組與最低表現組的受試者的fNIRS訊號結果,在字母記憶作業及數字回數作業中可以發現低行為表現組的prefrontal cortex腦區活化值大於高行為表現組,但在音調監控作業及空間回數作業中則呈現高行為表現組的prefrontal cortex腦區活化值大於低行為表現組。總結來說並沒有發現如文獻所說低行為表現組會有較低的腦部活動,高行為表現組則較多腦部活動。
This thesis aims to use functional near-infrared spectroscopy (fNIRS) for obtaining changes in the concentration of hemoglobin in the prefrontal cortex, and tests whether the prefrontal cortex showed different activation areas and activation levels for different memory stimulating materials.
The experimental design is based on working memory updating task, and uses four stimulating materials and updating task: (1) letter memory task, (2) tone monitoring task, (3) spatial N-back task, and (4) digital N-back task. While the task progresses, subjects must continually update the answers in memory based on the constant appearance of new stimuli and recall correct answers after questions end.
In the signal processing, the fast independent components analysis (fastICA) algorithm is used as the practice of blind source separation (BSS). This method can apply in feature extraction and dimensionality reduction of hemoglobin concentration signal. Independent components(ICs) can be extracted after fastICA, and these ICs can be evaluated by mean inter-trial cross-correlation (MITC) for the correlation between signal events. The block-related ICs can be regarded as hemoglobin concentration changes caused by neural activation.
The main findings of the study are as follows: (1) Different from the results of functional magnetic resonance imaging in the literature, the spatial and digital memory updating task trigger the activation of dorsal and ventral prefrontal cortex respectively, (2) The results show that letters, spatial and digital materials are lateralized to the right brain and the tone material to the left brain, (3) Comparing the subjects in the high performance group (HPG) and low performance group (LPG), in letter memory task and digital N-back task, the prefrontal cortex activation of LPG is stronger than of HPG. On the other hand, in tone monitoring task and spatial N-back task, the prefrontal cortex activation value of HPG is stronger than that of LPG. In summary, it is not found that LPG had lower brain activity, while HPG had stronger brain activity as in the literature.
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