禪定以及休息之腦電波非線性相依性的時間演化

Abstract

禪定時的腦部動態已經被引起關注且受到研究數十年，於本論文中，我們試圖著探索非線性相依性分析於禪定與休息腦電波時α波的振盪現象，基於相空間重建法的非線性相依性(Nonlinear Interdependence)分析，常被應用於分析大腦神經網路之間的動態連結特性，本論文中主要的分析包含了建立並分類相似度矩陣(similarity-index matrix, SIM)，並基於分析結果解釋長時間腦電波時間的演化現象，在於我們先前的研究中，我們對於系統的狀態提出了合適的參數並應用於建立每兩秒三十個通道的完整30×30相似度矩陣，此論文主要專注在多通道腦電波非線性相依性分析的微觀與宏觀現象，並藉由NSAD(normalized sum of absolute difference)分類，此分類結果可以解釋長時間的腦電波演化現象，我們找出最有代表性的非線性腦動態情況出現於數量最多的類別並找到其類別中心，藉由數量最多的類別可知道此類別主導了長時間腦電波的現象，透過最大類別的類別中心與每段兩秒鐘的相似度矩陣進行量化分析，我們發現禪定腦電波出現了平衡行為互相連動神經元之間的振盪，而休息腦電波出現了多變以及偏離了數量最多的主導類別，在ESR (effective source/sink range)方面禪定腦電波主導性較強發生於(Fz, FCz, Cz)通道，且主導範圍較為休息腦電波主導性較強的通道(Pz)範圍更為廣泛，由此可見禪定帶給我們更為全腦性的平衡與開發，並由此論文提供了禪定對我們影響有了新的見解。

Brain dynamics in Chan-Ding state has aroused attention from the researchers for decades. In this thesis, we attempted to explore the difference of nonlinear interdependence under alpha-oscillatory modes between Chan-Ding EEG (electroencephalograph) and resting EEG. Nonlinear-interdependence analysis based on phase space reconstruction may provide a feasible way to access brain dynamical interactions among regional neural networks. In this thesis, the analysis mainly involves the construction of similarity-index matrix (SIM), classification of SIM, and long-term EEG interpretation based on classification results. Our previous study proposed the systematic approach for determining appropriate implementing parameters to evaluate the SI coefficient between two EEG channels and then to construct the complete 30-by-30 SIM for the 2-second, 30-channel EEG epoch. This thesis is mainly focused on the microscopic and macroscopic phenomenon of spatially nonlinear interdependence of multichannel EEG. The SIMs are classified by NSAD (normalized sum of absolute difference) based strategy. The results of classification can be adopted for long-term EEG interpretation. The cluster center of the largest cluster is most representative for characterizing the nonlinear brain dynamics. Accordingly, we interpret the EEG record by encoding the quantitative deviation of each running 2-second SIM from the SIM of the largest cluster center. Chan-Ding EEG exhibits rather stationary behavior with respect to the interconnectivity among regional neural oscillators, whereas resting EEG appears to drift away more often from the center. Moreover, ESR (effective source/sink range) area of Chan-Ding EEG at the predominant channels (Fz, FCz, and Cz) appears to be much larger than which of resting EEG at its predominant channel (Pz).