正念與焦慮的作用及其對執行功能的影響

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姓名	迦思瓦(SATISH JAISWAL) 查詢紙本館藏	畢業系所	認知與神經科學研究所
論文名稱	正念與焦慮的作用及其對執行功能的影響 (The interplay between mindfulness and anxiety, and their influence on executive functions)
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摘要(中)	正念和焦慮兩特質呈負向關，不同程度的正念或焦慮特質可能與特定認知表現有所關連。本論文主要目的是同時考慮正念和焦慮這兩項特質對執行功能的影響。第一個橫斷研究，透過兩種量表選取出：高正念-低焦慮組（HMLA）和低正念-高焦慮組（LMHA）兩群不同受試者，比較兩組執行測停止信號作業（SST）的表現，同時觀察短暫的正念練習對反應抑制能力的影響。第二個橫斷研究，如同上述量表分組方式，探討不同特質對執行功能的影響，分別使用注意網絡測驗（ANT）評估注意力能力，以Stroop叫色作業評估衝突控制能力，以變化偵測作業（CDT）評估視覺空間工作記憶容量。我們使用希爾伯特-黃轉換（HHT）與全腦全息希爾伯特頻譜（HHSA）探討靜息狀態與上述認知作業過程之神經機制，並比較不同特質族群的差別。第一個研究行為結果發現：短暫的正念練習並未改變動作控制的表現，該指標為停止信號反應時間（SSRT），能反映抑制控制的能力，正念練習後SSRT有增快的趨勢但未達顯著差異。第二個研究中的Stroop叫色作業與變化偵測作業皆可觀察到：HMLA組比LMHA組有更高的正確率。此外，HMLA組比LMHA組更有能力正確偵測改變，並具有更大的工作記憶容量。但在注意網絡測驗中，兩組受試者在三種注意力面向─警覺、導引與衝突的指標皆無顯著差異。變化偵測作業中，HMLA組的高正確率與後顳葉和枕葉區較低的delta強度有關，可能表示該組較能維持專注狀態。在記憶提取階段，HMLA組的高正確率和工作記憶容量與額葉和頂葉中間區域較大的α強度有關，可能代表該組能更有效率地分配認知資源。透過靜息狀態腦波分析，我們的新發現是：LMHA比HMLA組有更大的振盪強度。我們推測LMHA組在靜息狀態下，可能對當下不確定感或付出更多資源準備未來而產生更多的生理活動。為了進一步研究正念與焦慮特質的個體差異，未來可嘗試透過靜坐冥想訓練，觀察訓練後受試者之認知功能、靜息狀態神經生理狀態以及焦慮程度間的變化和關聯。
摘要(英)	Mindfulness and anxiety are two inversely linked traits that have been independently attributed to a range of cognitive functions. The primary aim of the thesis was to look into the combined effects of mindfulness and anxiety on a series of executive functions. A cross-sectional study with two experimental groups, high mindfulness-low anxiety (HMLA) and low mindfulness-high anxiety (LMHA), was conducted based on findings from a behavioral study investigating the effects of a brief mindfulness induction on motor inhibitory control, measured using a stop signal task (SST). This cross-sectional study investigated a series of executive functions using the attentional network test (ANT) to measure the efficiency of attentional networks, a color Stroop task (CST) to measure the conflict control ability and a change detection task (CDT) to measure the visuospatial working memory capacity. Additionally, neural indices that may reveal the fundamental differences in cognitive functions and spontaneous resting state between the two experimental groups were explored. Advanced EEG analytical approaches, Hilbert-Huang Transform analysis (HHT) and Holo-Hilbert Spectral Analysis (HHSA) were employed to analyze data relating to both cognitive functions and resting state activity. Initial behavioral results showed no significant change in motor control, indexed by altered stop signal reaction time (SSRTs), following interventions including a mindfulness condition, although there was a marginal trend of reduction of SSRT, indicative of better inhibitory control, in the mindfulness condition. In the cross-sectional study, the HMLA group was more accurate than the LMHA group on the Stroop and change detection tasks. Additionally, the HMLA group was more sensitive in detecting changes and had a higher WMC than the LMHA group. However, on the ANT, there were no differences on any of the three attentional networks; with alerting, orienting and conflict scores not significantly differing between the two groups. The higher accuracy rate on the CST in the HMLA group was associated with lower delta EEG activity in posterior temporal and occipital areas, indicating a more attentive state in this group. The higher accuracy rate and WMC in the HMLA group was seen in conjunction with enhanced alpha activity in PFC, fronto-central and centro-parietal regions during the retrieval phase, indicating active allocation of brain resources in this group. In the resting state, the presence of higher oscillation power across the frequency bands in the LMHA group than the HMLA group was a novel finding. This might have been due to higher physiological arousal either as a consequence of uncertainty relating to the resting state or more preparedness for upcoming situations. To investigate individual contributions of mindfulness and anxiety to such differences, future studies could usefully look into how a mindfulness intervention, such as meditation, may alter the dynamics of resting state and cognitive functions as well as their association with levels of anxiety.
關鍵字(中)	★ 正念 ★ 焦慮 ★ 執行功能 ★ 希爾伯特-黃轉換 ★ 全腦全息希爾伯特頻譜	關鍵字(英)	★ mindfulness ★ anxiety ★ executive functions ★ Hilbert-Huang transform ★ Holo-Hilbert spectrum analysis
論文目次	Table of Content Chinese Abstract i English Abstract ii Acknowledgements iii Table of Content vi Table of Figures x List of Tables xii List of Abbreviations xiii Chapter 1: General Introduction 1 1.1 Introduction 1 1.2 Evidence suggesting an inverse relationship between mindfulness and anxiety 3 1.2.1 Self-report measures 3 1.2.2 Behavioral measures 3 1.2.3 Electrophysiological measures 4 1.2.4 Hemodynamic neuroimaging 7 1.2.5 Neural dynamics of mindfulness and anxiety pertaining to executive functions 9 1.3 Conception of current research 12 1.4 Issues of research in mindfulness and anxiety contexts 17 1.5 Electroencephalography and neural oscillations 19 1.5.1 Operation of Hilbert Huang Transform (HHT) methodology 22 1.5.2 Definition of frequency bands 23 1.5.3 Operation of Holo-Hilbert Spectrum Analysis methodology 28 1.6 Purpose and Hypothesis 31 Chapter 2: Exploring the impact of a brief mindfulness induction on motor inhibitory control 34 2.1 Background 34 2.2 Method 39 2.2.1 Participants 39 2.2.2 Self-Report measures 39 2.2.3 Stop Signal Task 40 2.2.4 Procedure 41 2.3 Analysis 43 2.4 Results 44 2.4.1 Stop Signal measures 44 2.4.2 Self-report correlational measures 47 2.4.3 Regression analysis on self-report measures and stop signal task measures 47 2.5 Discussion 49 Chapter 3: Better cognitive performance is associated with the combination of high trait mindfulness and low trait anxiety 54 3.1 Background 54 3.2 Method 60 3.2.1 Participants 60 3.2.2 Double selection criteria 60 3.2.3 Task procedure 64 3.2.4 Stimuli and task performance 65 3.3 Analysis 68 3.3.1 Variables analyzed for the Attentional Network Test 68 3.3.2 Variables analyzed for the Color Stroop Task 69 3.3.3 Variables analyzed for the Change Detection Task 69 3.4 Results 71 3.4.1 Attentional Network Test 71 3.4.2 Color Stroop Task 73 3.4.3 Change Detection Task 75 3.4.4 Correlation between primary behavioral measures and trait mindfulness and trait anxiety 79 3.4.5 Supplementary questionnaires 79 3.5 Discussion 81 Chapter 4: Low delta and high alpha power is associated with better conflict control and working memory in high mindfulness, low anxiety individuals 87 4.1 Background 87 4.2 Method 92 4.2.1 Participants 92 4.2.2 Task Procedure 92 4.3 Analysis 93 4.3.1 Behavioral analyses 93 4.3.2 EEG recording parameters 93 4.3.3 Operation of Ensemble Empirical Mode Decomposition (EEMD) and HHT 93 4.3.4 Statistical analysis 94 4.3.5 EEG analysis: Attentional Network Test 94 4.3.6 EEG analysis: Color Stroop Task 95 4.3.7 EEG analysis: Change Detection Task 96 4.4 Results 97 4.4.1 Behavioral Results 97 4.4.2 Time-Frequency HHT Spectrum Results: Attentional Network Test 99 4.4.2 Time-Frequency HHT Spectrum Results: Color Stroop Task 102 4.4.3 Time-Frequency HHT Spectrum Results: Change Detection Task 105 4.5 Discussion 111 4.5.1 Neural dynamics of conflict control 111 4.5.2 Neural dynamics related to working memory capacity 112 Chapter 5: High anxiety and low mindfulness exhibit high physiological arousal elicited by uncertain resting state: a nonlinear and nonstationary perspective 118 5.1 Background 118 5.2 Method 124 5.2.1 Participants 124 5.2.2 Procedure 124 5.2.3 Resting EEG recording 124 5.2.4 EEG Recording Parameters 125 5.3 Analysis 126 5.3.1 Data extraction 126 5.3.2 Operation of EEMD and HHSA analysis 126 5.3.3 Statistical analysis 127 5.4 Results 128 5.4.1 Contrast between EO and EC: Within-group comparison 128 5.4.2 Contrast between the LMHA and HMLA groups: Between-group comparison 130 5.5 Discussion 133 Chapter 6: General discussion 138 6.1 Results summary 138 6.2 Conclusion 140 References 144
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指導教授	阮啟弘馬杰仁(Chi-Hung Juan Neil G. Muggleton)	審核日期	2019-6-20
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