博碩士論文 103885601 詳細資訊




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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
參考文獻 Aiken, S.G., West, S.G., Reno, R.R. (1991). Multiple regression: Testing and interpreting interactions: Thousand Oaks, CA, US: Sage Publications, Inc.
Al-Fahoum, A. S., & Al-Fraihat, A. A. (2014). Methods of EEG signal features extraction using linear analysis in frequency and time-frequency domains. ISRN Neuroscience, 2014, 730218-730218.
Ando, S., Kida, N., & Oda, S. (2002). Practice effects on reaction time for peripheral and central visual fields. Perceptual and Motor Skills, 95(3), 747-751.
Arch, J. J., & Craske, M. G. (2010). Laboratory stressors in clinically anxious and non-anxious individuals: the moderating role of mindfulness. Behavior Research Therapy, 48(6), 495-505.
Archana, R., & Mukilan, R. (2016). Beneficial effect of preferential music on exercise induced changes in heart rate variability. Journal of Clinical and Diagnostic Research : JCDR, 10(5), CC09-CC11.
Babiloni, F., Cincotti, F., Carducci, F., Rossini, P., & Babiloni, C. (2001). Spatial enhancement of EEG data by surface Laplacian estimation: the use of magnetic resonance imaging-based head models. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 112(5), 724.
Baer, R. A., Smith, G. T., Hopkins, J., Krietemeyer, J., & Toney, L. (2006). Using self-report assessment methods to explore facets of mindfulness. Assessment, 13(1), 27-45.
Baijal, S., & Gupta, R. (2008). Meditation-based training: a possible intervention for attention deficit hyperactivity disorder. Psychiatry (Edgmont), 5(4), 48-55.
Baijal,S., Jha, A. P., Kiyonaga, A., Singh, R., & Srinivasan, N. (2011). The influence of concentrative meditation training on the development of attention networks during early adolescence. Frontiers in Psychology, 2(153).
Band, G. P., van der Molen, M. W., & Logan, G. D. (2003). Horse-race model simulations of the stop-signal procedure. Acta Psychologica (Amst), 112(2), 105-142.
Barry, R. J., Clarke, A. R., Johnstone, S. J., & Brown, C. R. (2009). EEG differences in children between eyes-closed and eyes-open resting conditions. Clinical Neurophysiology, 120(10), 1806-1811.
Barry, R. J., Clarke, A. R., Johnstone, S. J., Magee, C. A., & Rushby, J. A. (2007). EEG differences between eyes-closed and eyes-open resting conditions. Clinical Neurophysiology, 118(12), 2765-2773.
Basar, E., & Guntekin, B. (2012). A short review of alpha activity in cognitive processes and in cognitive impairment. International Journal of Psychophysiology, 86(1), 25-38.
Becker, E. S., Rinck, M., Margraf, J., & Roth, W. T.(2001). The emotional Stroop effect in anxiety disorders: general emotional or disorder specificity? Journal of Anxiety Disorder, 15(3), 147-159.
Berryhill, M. E., & Olson, I. R. (2008). Is the posterior parietal lobe involved in working memory retrieval? Evidence from patients with bilateral parietal lobe damage. Neuropsychologia, 46(7), 1767-1774.
Bieser, A., & Muller-Preuss, P. (1996). Auditory responsive cortex in the squirrel monkey: neural responses to amplitude-modulated sounds. Experimental Brain Research, 108(2), 273-284.
Bishop, S. J. (2009). Trait anxiety and impoverished prefrontal control of attention. Nature Neuroscience, 12(1), 92-98.
Bishop, S. J. Duncan, J. Brett, M. Lawrence, A. D. (2004). Prefrontal cortical function and anxiety: controlling attention to threat-related stimuli. Nature Neuroscience, 7(2), 184-8.
Blair, C., & Razza, R. P. (2007). Relating effortful control, executive function, and false belief understanding to emerging math and literacy ability in kindergarten. Child Develpment, 78(2), 647-663.
Bonnefond, M., & Jensen, O. (2012). Alpha oscillations serve to protect working memory maintenance against anticipated distracters. Current Biology, 22(20), 1969-1974.
Bottiroli, S., Rosi, A., Russo, R., Vecchi, T., & Cavallini, E. (2014). The cognitive effects of listening to background music on older adults: processing speed improves with upbeat music, while memory seems to benefit from both upbeat and downbeat music. Frontiers in Aging Neuroscience, 6, 284.
Botvinick, M. M., Cohen, J. D., & Carter, C. S. (2004). Conflict monitoring and anterior cingulate cortex: an update. Trends in Cognitive Sciences, 8(12), 539-546.
Box, G. E. P., & Cox, D. R. (1964). An analysis of transformations. Journal of the Royal Statistical Society. Series B (Methodological), 211-252.
Brittain, J. S., Watkins, K. E., Joundi, R. A., Ray, N. J., Holland, P., Green, A. L., Aziz, T. Z., & Jenkinson, N. (2012). A role for the subthalamic nucleus in response inhibition during conflict. Journal of Neuroscience, 32(39), 13396-13401.
Brotman, M. A., Rich, B. A., Guyer, A. E., Lunsford, J. R., Horsey, S. E., Reising, M. M., Thomas, L. A., Fromm, S. J., Towbin, K., Pine, D. S., & Leibenluft, E. (2010). Amygdala activation during emotion processing of neutral faces in children with severe mood dysregulation versus ADHD or bipolar disorder. American Journal of Psychiatry, 167(1), 61-69.
Brown, K. W., Goodman, R. J., & Inzlicht, M. (2013). Dispositional mindfulness and the attenuation of neural responses to emotional stimuli. Social Cognitive and Affective Neuroscience, 8(1), 93-99.
Brown, K. W., & Ryan, R. M. (2003). The benefits of being present: mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology, 84(4), 822-848.
Bull, R., & Scerif, G. (2001). Executive functioning as a predictor of children′s mathematics ability: inhibition, switching, and working memory. Developmental Neuropsychology, 19(3), 273-293.
Burle, B., Spieser, L., Roger, C., Casini, L., Hasbroucq, T., & Vidal, F. (2015). Spatial and temporal resolutions of EEG: Is it really black and white? A scalp current density view. International Journal of Psychophysiology, 97(3), 210-220.
Busch, N. A., & Herrmann, C. S. (2003). Object-load and feature-load modulate EEG in a short-term memory task. Neuroreport, 14(13), 1721-1724.
Bush, G., Luu, P., & Posner, M. I. (2000). Cognitive and emotional influences in anterior cingulate cortex. Trends in cognitive sciences, 4(6), 215-222.
Buzsaki, G. (2006). Rhythms of the Brain. NY, US: Oxford University Press.
Buzsaki, G., & Draguhn, A. (2004). Neuronal oscillations in cortical networks. Science, 304(5679), 1926-1929.
Buzsaki, G., & Mizuseki, K. (2014). The log-dynamic brain: how skewed distributions affect network operations. Nature Reviews Neuroscience, 15(4), 264-278.
Callejas, A., Lupianez, J., & Tudela, P. (2004). The three attentional networks: on their independence and interactions. Brain and Cognition, 54(3), 225-227.
Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: the BIS/BAS scales. Journal of Personality Social Psychology, 67(2), 319.
Cavanagh, J. F., Cohen, M. X., & Allen, J. J. (2009). Prelude to and resolution of an error: EEG phase synchrony reveals cognitive control dynamics during action monitoring. Journal of Neuroscience, 29(1), 98-105.
Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in Cognitive Sciences, 18(8), 414-421.
Chabris, C. F. (1999). Prelude or requiem for the ‘Mozart effect’? Nature, 400(6747), 826-827.
Chambers, R., Gullone, E., & Allen, N. B. (2009). Mindful emotion regulation: An integrative review. Clinical Psychology Review, 29(6), 560-572.
Chang, J. H., Huang, C. L, & Lin, Y. C. (2015). Mindfulness, basic psychological needs fulfillment, and well-being. Journal of Happiness Studies, 16(5), 1149-1162.
Chang, C. F., Liang, W. K., Lai, C. L., Hung, D. L., & Juan, C. H. (2016). Theta oscillation reveals the temporal involvement of different attentional networks in contingent reorienting. Frontiers in Human Neuroscience, 10(264).
Chang, Y. P., Li, T. S., Teng, H. Y., Berki, A., & Chen, L. H. (2013). Living with gratitude: Spouse’s gratitude on one’s depression. Journal of Happiness Studies, 14(4), 1431-1442.
Chen, D., Li, D., Xiong, M., Bao, H., & Li, X. (2010). GPGPU-aided ensemble empirical-mode decomposition for EEG analysis during anesthesia. IEEE Transactions on Information Technology in Biomedicine, 14(6), 1417-1427.
Chen, C. Y., Muggleton, N. G., Juan, C. H., Tzeng, O. J., & Hung, D. L. (2008). Time pressure leads to inhibitory control deficits in impulsive violent offenders. Behavior Brain Research, 187(2), 483-488.
Clarke, S. E., Longtin, A., & Maler, L. (2015). Contrast coding in the electrosensory system: parallels with visual computation. Nature Reviews Neuroscience, 16(12), 733-744.
Coffey, K. A., & Hartman, M.(2008). Mechanisms of action in the inverse relationship between mindfulness and psychological distress. Complementary Health Practice Review, 13(2), 79-91.
Cohen, J. (1988), Statistical Power Analysis for the Behavioral Sciences, 2nd Edition. Hillsdale, N.J.: Lawrence Erlbaum.
Cohen, S., Kamarck, T., & Mermelstein, R. (1994). Perceived stress scale. Measuring stress: A Guide for Health and Social Scientists.
Cole, Z., & Maeda, H. (2015). Effects of listening to preferential music on sex differences in endurance running performance. Perceptual and Motor Skills, 121(2), 390-398.
Cole, S. R., & Voytek, B. (2017). Brain oscillations and the importance of waveform shape. Trends in Cognitive Sciences, 21(2), 137-149.
Constantinople, C. M., & Bruno, R. M. (2011). Effects and mechanisms of wakefulness on local cortical networks. Neuron, 69(6), 1061-1068.
Cooney, R. E., Atlas, L. Y., Joormann, J., Eugene, F., & Gotlib, I. H. (2006). Amygdala activation in the processing of neutral faces in social anxiety disorder: is neutral really neutral? Psychiatry Research, 148(1), 55-59.
Cosme, D., & Wiens, S. (2015). Self-reported trait mindfulness and affective reactivity: a motivational approach using multiple psychophysiological measures. Plos One, 10(3), e0119466.
Cowan, N. (2010). The magical mystery four: how is working memory capacity limited, and why? Current Directions in Psychological Science, 19(1), 51-57.
Creswell, J. D. (2017). Mindfulness interventions. Annual Review of Psychology, 68(1), 491-516.
Creswell, J. D., Way, B. M., Eisenberger, N. I., & Lieberman, M. D. (2007). Neural correlates of dispositional mindfulness during affect labeling. Psychosomatic Medicine, 69(6), 560-565.
Darke, S. (1988). Anxiety and working memory capacity. Cognition and Emotion, 2(2), 145-154.
Davidson, R. J. (2002). Anxiety and affective style: role of prefrontal cortex and amygdala. Biological Psychiatry, 51(1), 68-80.
Davidson, R. J., & Kaszniak, A. W. (2015). Conceptual and methodological issues in research on mindfulness and meditation. The American Psychologist, 70(7), 581-592.
Delorme, A., & Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9-21.
Demiralp, T., Bayraktaroglu, Z., Lenz, D., Junge, S., Busch, N., & Herrmann, C. (2006). The interaction of theta and gamma oscillations in human cognition. Paper presented at the International Journal of Psychophysiology.
de Ruiter, C., & Brosschot, J. F. (1994). The emotional Stroop interference effect in anxiety: attentional bias or cognitive avoidance? Behavior Research and Therapy, 32(3), 315-319.
Desrosiers, A., Vine, V., Klemanski, D. H., & Nolen-Hoeksema, S. (2013). Mindfulness and emotion regulation in depression and anxiety: common and distinct mechanisms of action. Depression and Anxiety, 30(7), 654-661.
Di Francesco, S. A., Simione, L., López-Ramón, M. F., Belardinelli, M. O., Lupiáñez, J., & Raffone, A. (2017). Dispositional mindfulness facets predict the efficiency of attentional networks. Mindfulness, 8(1), 101-109.
Diaz, F. M. (2011). Mindfulness, attention, and flow during music listening: An empirical investigation. Psychology of Music, 41(1), 42-58.
Dobson, P. (2000). An investigation into the relationship between neuroticism, extraversion and cognitive test performance in selection. International Journal of Selection and Assessment, 8(3), 99-109.
Dong, S., Reder, L. M., Yao, Y., Liu, Y., & Chen, F. (2015). Individual differences in working memory capacity are reflected in different ERP and EEG patterns to task difficulty. Brain Research, 1616, 146-156.
Dougherty, D. M., Bjork, J. M., Harper, R. A., Marsh, D. M., Moeller, F. G., Mathias, C. W., & Swann, A. C. (2003). Behavioral impulsivity paradigms: a comparison in hospitalized adolescents with disruptive behavior disorders. Journal of Child Psychology and Psychiatry, 44(8), 1145-1157.
Droit-Volet, S., Ramos, d., Bueno, L., & Bigand, E. (2013). Music, emotion, and time perception: the influence of subjective emotional valence and arousal? Frontiers in Psychology, 4(417).
Dugas, M. J., Freeston, M. H., & Ladouceur, R. (1997). Intolerance of uncertainty and problem orientation in worry. Cognitive Therapy and Research, 21(6), 593-606.
Engel, A. K., Fries, P., & Singer, W. (2001). Dynamic predictions: oscillations and synchrony in top-down processing. Nature Reviewa Neuroscience, 2(10), 704-716.
Etkin, A., Klemenhagen, K. C., Dudman, J. T., Rogan, M. T., Hen, R. K., Kandel, E. R., & Hirsch, J. (2004). Individual differences in trait anxiety predict the response of the basolateral amygdala to unconsciously processed fearful faces. Neuron, 44(6), 1043-1055.
Eysenck, M. W., & Calvo, M. G. (1992). Anxiety and performance: the processing efficiency theory. Cognition and Emotion, 6(6), 409-434.
Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: attentional control theory. Emotion, 7(2), 336-353.
Fan, J., Byrne, J., Worden, M. S., Guise, K. G., McCandliss, B. D., Fossella, J., & Posner, M. I. (2007). The relation of brain oscillations to attentional networks. Journal of Neuroscience, 27(23), 6197-6206.
Fan, J., Flombaum, J. I., McCandliss, B. D., Thomas, K. M., & Posner, M. I. (2003). Cognitive and brain consequences of conflict. Neuroimage, 18(1), 42-57.
Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & Posner, M. I.. (2002). Testing the efficiency and independence of attentional networks. J Cogn Neurosci, 14(3), 340-347.
Fang, R., Ye, S., Huangfu, J., & Calimag, D. P. (2017). Music therapy is a potential intervention for cognition of Alzheimer’s Disease: a mini-review. Translational Neurodegeneration, 6(1), 2.
Faul, F., Erdfelder, E., Lang, A., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191.
Fellinger, R., Klimesch, W., Schnakers, C., Perrin, F., Freunberger, R., Gruber, W., Laureys, S., & Schabus, M. (2011). Cognitive processes in disorders of consciousness as revealed by EEG time-frequency analyses. Clinical Neurophysiology, 122(11), 2177-2184.
Figueira, J. S. B., Oliveira, L., Pereira, M. G., Pacheco, L. B., Lobo, I., Motta-Ribeiro, G. C., & David, I. A. (2017). An unpleasant emotional state reduces working memory capacity: electrophysiological evidence. Social Cognitive and Affective Neuroscience, 12(6), 984-992.
Fitzgerald, P. J., & Watson, B. O. (2018). Gamma oscillations as a biomarker for major depression: an emerging topic. Translational Psychiatry, 8(1), 177-177.
Flandrin, P., Rilling, G., & Goncalves, P. (2004). Empirical mode decomposition as a filter bank. IEEE signal processing letters, 11(2), 112-114.
Florian, G., & Pfurtscheller, G. (1995). Dynamic spectral analysis of event-related EEG data. Electroencephalography and Clinical Neurophysiology, 95(5), 393-396.
Fries, P. (2005). A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends in Cognitive Sciences, 9(10), 474-480.
Fukuda, K., Mance, I., & Vogel, E. K. (2015). α power modulation and event-related slow wave provide dissociable correlates of visual working memory. Journal of Neuroscience, 35(41), 14009-14016.
Gaetano, J. (2018). Holm-Bonferroni sequential correction: An Excel calculator (1.3) [Microsoft Excel workbook]. Available online at:
https://www.researchgate.net/publication/ 322569220_Holm-Bonferroni_sequential_correction_An_Excel_calculator_13
Gallant, S. N. (2016). Mindfulness meditation practice and executive functioning: Breaking down the benefit. Consciousness and Cognition, 40, 116-130.
Garland, E. L. (2011). Trait mindfulness predicts attentional and autonomic regulation of alcohol cue-reactivity. Journal of Psychophysiology, 25(4), 180-189.
Gemignani, A., Santarcangelo, E., Sebastiani, L., Marchese, C., Mammoliti, R., Simoni, A., & Ghelarducci, B. (2000). Changes in autonomic and EEG patterns induced by hypnotic imagination of aversive stimuli in man. Brain Research Bulletin, 53(1), 105-111.
Gevins, A. (1993). High resolution EEG. Brain Topography, 5(4), 321-325.
Gevins, A., Smith, M. E., McEvoy, L., & Yu, D. (1997). High-resolution EEG mapping of cortical activation related to working memory: effects of task difficulty, type of processing, and practice. Cerebral Cortex, 7(4), 374-385.
Glover, G. H. (2011). Overview of functional magnetic resonance imaging. Neurosurgery clinics of North America, 22(2), 133-vii.
Gold, A. L., Morey, R. A., & McCarthy, G. (2015). Amygdala–Prefrontal cortex functional connectivity during threat-induced anxiety and goal distraction. Biological Psychiatry, 77(4), 394-403.
Goldman-Rakic, P. S. (1996). Regional and cellular fractionation of working memory. Proceedings of National Academy of Sciences of the USA, 93(24), 13473-13480.
Gordon, D. L., Russell, J. S., & Rosemary, T. (1997). Impulsivity and Inhibitory Control. Psychological Science, 8(1), 60-64.
Gray, J., & McNaughton, N. (2003). (Ed.), The neuropsychology of anxiety: an enquiry into the function of the septo-hippocampal system. NY, US: Oxford University Press.
Greeson, J., & Brantley, J. (2009). Mindfulness and anxiety disorders: Developing a wise relationship with the inner experience of fear. In Clinical handbook of mindfulness (pp. 171-188): Springer.
Gregoriou, G. G., Gotts, S. J., & Desimone, R. (2012). Cell-type-specific synchronization of neural activity in FEF with V4 during attention. Neuron, 73(3), 581-594.
Gregoriou, G. G., Gotts, S. J., Zhou, H., & Desimone, R. (2009). High-frequency, long-range coupling between prefrontal and visual cortex during attention. Science, 324(5931), 1207-1210.
Groppe, D. M., Urbach, T. P., & Kutas, M. (2011). Mass univariate analysis of event-related brain potentials/fields ii: simulation studies. Psychophysiology, 48(12), 1726-1737.
Grupe, D. W., & Nitschke, J. B. (2013). Uncertainty and anticipation in anxiety: an integrated neurobiological and psychological perspective. Nature Reviews Neuroscience, 14(7), 488-501.
Haegens, S., Cousijn, H., Wallis, G., Harrison, P. J., & Nobre, A. C. (2014). Inter- and intra-individual variability in alpha peak frequency. Neuroimage, 92(100), 46-55.
Hanslmayr, S., Pastotter, B., Bauml, K. H., Gruber, S., Wimber, M., & Klimesch, W. (2008). The electrophysiological dynamics of interference during the Stroop task. Journal of Cognitive Neuroscience, 20(2), 215-225.
Heeren, A., Van Broeck, N., & Philippot, P. (2009). The effects of mindfulness on executive processes and autobiographical memory specificity. Behavior Research Therapy, 47(5), 403-409.
Heitz, R. P., & Schall, J. D. (2012). Neural mechanisms of speed-accuracy tradeoff. Neuron, 76(3), 616-628.
Hofmann, S. G., Sawyer, A. T., Witt, A. A., & Oh, D. (2010). The effect of mindfulness-based therapy on anxiety and depression: A meta-analytic review. J Consult Clin Psychol, 78(2), 169-183.
Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 65-70.
Hölzel, B. K., Carmody, J., Vangel, M., Congleton, C., Yerramsetti, S. M., Gard, T., & Lazar, S. W. (2011). Mindfulness practice leads to increases in regional brain gray matter density. Psychiatry Research, 191(1), 36-43.
Holzel, B. K., Hoge, E. A., Greve, D. N., Gard, T., Creswell, J. D., Brown, K. W., Barrett, L. F., Schwartz, C., Vaitl, D., & Lazar, S. W. (2013). Neural mechanisms of symptom improvements in generalized anxiety disorder following mindfulness training. Neuroimage Clinical, 2, 448-458.
Howard, M. W., Rizzuto, D. S., Caplan, J. B., Madsen, J. R., Lisman, J., Aschenbrenner-Scheibe, R., Scheibe, R., Schulze-Bonhage, A., & Kahana, M. J. (2003). Gamma oscillations correlate with working memory load in humans. Cerebral Cortex, 13(12), 1369-1374.
Hsu, C. H., Lee, C. Y., & Liang, W. K. (2016). An improved method for measuring mismatch negativity using ensemble empirical mode decomposition. Journal of Neuroscience Methods, 264, 78-85.
Hsu, H., Lee, W., Shyu, K., Yeh, T., Chang, C., & Lee, P. (2018). Analyses of eeg oscillatory activities during slow and fast repetitive movements using holo-hilbert spectral analysis. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(9), 1659-1668.
Hsu, T. Y., Tseng, P., Liang, W. K., Cheng, S. K., & Juan, C. H. (2014). Transcranial direct current stimulation over right posterior parietal cortex changes prestimulus alpha oscillation in visual short-term memory task. NeuroImage, 98, 306–313.
Huang, C.-Y., Li, C.-S. R., Fang, S.-C., Wu, C.-S., & Liao, D.-L. (2013). The reliability of the Chinese version of the Barratt Impulsiveness Scale version 11, in abstinent, opioid-dependent participants in Taiwan. Journal of the Chinese Medical Association, 76(5), 289-295.
Huang, N. E., Hu, K., Yang, A. C. C., Chang, H.-C., Jia, D., Liang, W.-K., Yeh, J. R., Kao, C. L., Juan, C. H., Peng, C. K., Meijer, J. H., Wang, Y. H., Long, S. R., & Wu, Z. (2016). On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2065).
Huang, N. E., Shen, Z., Long, S. R., Wu, M. C., Shih, H. H., Zheng, Q., Yen, N. C., Tung, C. C., & Liu, H. H. (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 454(1971), 903-995.
Huang, N. E., & Wu, Z. (2008). A review on Hilbert‐Huang transform: method and its applications to geophysical studies. Reviews of Geophysics, 46(2).
Huang, N. E., Wu, Z., Long, S. R., Arnold, K. C., Chen, X., & Blank, K. (2009). On instantaneous frequency. Advances in Adaptive Data Analysis, 1(02), 177-229.
Hummel, F., Andres, F., Altenmuller, E., Dichgans, J., & Gerloff, C. (2002). Inhibitory control of acquired motor programmes in the human brain. Brain, 125(Pt 2), 404-420.
Jaiswal, S., Tsai, S.-Y., Juan, C.-H., Liang, W.-K., & Muggleton, N. G. (2018). Better cognitive performance is associated with the combination of high trait mindfulness and low trait anxiety. Frontiers in Psychology, 9(627).
Jeong, J., Gore, J. C., & Peterson, B. S. (2002). Detecting determinism in short time series, with an application to the analysis of a stationary EEG recording. Biological Cybernetics, 86(5), 335-342.
Jensen, O., Bonnefond, M., & VanRullen, R. (2012). An oscillatory mechanism for prioritizing salient unattended stimuli. Trends in Cognitive Sciences, 16(4), 200-206.
Jensen, O., Gelfand, J., Kounios, J., & Lisman, J. E. (2002). Oscillations in the alpha band (9-12 Hz) increase with memory load during retention in a shStamort-term memory task. Cerebral Cortex, 12(8), 877-882.
Jensen, O., Spaak, E., & Park, H. (2016). Discriminating valid from spurious indices of phase-amplitude coupling. eNeuro, 3(6), ENEURO.0334-0316.2016.
Jensen, O., & Tesche, C. D. (2002). Frontal theta activity in humans increases with memory load in a working memory task. European Journal of Neuroscience, 15(8), 1395-1399.
Jha, A. P., Stanley, E. A., Kiyonaga, A., Wong, L., & Gelfand, L. (2010). Examining the protective effects of mindfulness training on working memory capacity and affective experience. Emotion, 10(1), 54.
Jo, H. G., Malinowski, P., & Schmidt, S. (2017). Frontal theta dynamics during response conflict in long-term mindfulness meditators. Frontiers in Human Neuroscience, 11(299).
Jo, H. G., Schmidt, S., Inacker, E., Markowiak, M., & Hinterberger, T. (2016). Meditation and attention: A controlled study on long-term meditators in behavioral performance and event-related potentials of attentional control. Int J Psychophysiol, 99, 33-39.
Jokisch, D., & Jensen, O. (2007). Modulation of gamma and alpha activity during a working memory task engaging the dorsal or ventral stream. The Journal of Neuroscience, 27(12), 3244.
Jung, T. P., Makeig, S., Humphries, C., Lee, T. W., McKeown, M. J., Iragui, V., & Sejnowski, T. J. (2000). Removing electroencephalographic artifacts by blind source separation. Psychophysiology, 37(2), 163-178.
Kabat-Zinn, J. (1990). Full catastrophe living: using the wisdom of your body and mind to face stress, Pain, and Illness. New York: Delacorte Press.
Kabat-Zinn, J., Massion, A. O., Kristeller, J., Peterson, L. G., Fletcher, K. E., Pbert, L., Lenderking, W. R., & Santorelli, S. F.(1992). Effectiveness of a meditation-based stress reduction program in the treatment of anxiety disorders. American Journal of Psychiatry, 149(7), 936-943.
Kahana, M. J., Sekuler, R., Caplan, J. B., Kirschen, M., & Madsen, J. R. (1999). Human theta oscillations exhibit task dependence during virtual maze navigation. Nature, 399(6738), 781.
Kane, M. J., & Engle, R. W. (2002). The role of prefrontal cortex in working-memory capacity, executive attention, and general fluid intelligence: An individual-differences perspective. Psychonomic Bulletin & Review, 9(4), 637-671.
Kiken, L. G., Garland, E. L., Bluth, K., Palsson, O. S., & Gaylord, S. A. (2015). From a state to a trait: Trajectories of state mindfulness in meditation during intervention predict changes in trait mindfulness. Personality and Individual Differences, 81, 41-46.
Killgore, W. D., & Yurgelun-Todd, D. A. (2005). Social anxiety predicts amygdala activation in adolescents viewing fearful faces. Neuroreport, 16(15), 1671-1675.
Kizuk, S. A., & Mathewson, K. E. (2017). Power and phase of alpha oscillations reveal an interaction between spatial and temporal visual attention. Journal of Cognitive Neuroscience, 29(3), 480-494.
Klein, K., & Boals, A. (2001). The relationship of life event stress and working memory capacity. Applied Cognitive Psychology: The Official Journal of the Society for Applied Research in Memory and Cognition, 15(5), 565-579.
Klimesch, W. (1996). Memory processes, brain oscillations and EEG synchronization. International Journal of Psychophysiology, 24(1-2), 61-100.
Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Research: Brain Research Reviews, 29(2-3), 169-195.
Knyazev, G. G. (2007). Motivation, emotion, and their inhibitory control mirrored in brain oscillations. Neuroscience & Biobehavioral Reviews, 31(3), 377-395.
Knyazev, G. G., Savostyanov, A. N., & Levin, E. A. (2005a). Anxiety and synchrony of alpha oscillations. International Journal of Psychophysiology, 57(3), 175-180.
Knyazev, G. G., Savostyanov, A. N., & Levin, E. A. (2005b). Uncertainty, anxiety, and brain oscillations. Neuroscience Letters, 387(3), 121-125.
Knyazev, G. G., Schutter, D. J., & van Honk, J. (2006). Anxious apprehension increases coupling of delta and beta oscillations. International Journal of Psychophysiology, 61(2), 283-287
Knyazev, G. G., & Slobodskaya, H. R. (2003). Personality trait of behavioral inhibition is associated with oscillatory systems reciprocal relationships. International Journal of Psychophysiology, 48(3), 247-261.
Kozasa, E. H., Sato, J. R., Lacerda, S. S., Barreiros, M. A. M., Radvany, J., Russell, T. A., Sanches, L. G., Mello, L. E. A. M., & Amaro, E. (2012). Meditation training increases brain efficiency in an attention task. Neuroimage, 59(1), 745-749.
Krain, A. L., Gotimer, K., Hefton, S., Ernst, M., Castellanos, F. X., Pine, D. S., & Milham, M. P. (2008). A functional magnetic resonance imaging investigation of uncertainty in adolescents with anxiety disorders. Biological Psychiatry, 63(6), 563-568.
Krause, C. M., Lang, A. H., Laine, M., Kuusisto, M., & Porn, B. (1996). Event-related EEG desynchronization and synchronization during an auditory memory task. Electroencephalography and Clinical Neurophysiology, 98(4), 319-326.
Kumari, V., Antonova, E., Wright, B., Hamid, A., Hernandez, E. M., Schmechtig, A., & Ettinger, U. (2017). The mindful eye: smooth pursuit and saccadic eye movements in meditators and non-meditators. Consciousness and Cognition, 48, 66-75.
Kuo, C. Y., & Yeh, Y. Y. (2015). Reset a task set after five minutes of mindfulness practice. Consciousness and Cognition, 35, 98-109.
Lau, M. A., Bishop, S. R., Segal, Z. V., Buis, T., Anderson, N. D., Carlson, L., Shapiro, S., Carmody, J., Abbey, S., & Devins, G. (2006). The Toronto Mindfulness Scale: development and validation. Journal of Clinical Psychology, 62(12), 1445-1467.
Lee, Y. C., & Chao, H. F. (2012). The role of active inhibitory control in psychological well-being and mindfulness. Personality and Individual Differences, 53(5), 618-621.
Lewkowicz, D., Delevoye-Turrell, Y., Bailly, D., Andry, P., & Gaussier, P. (2013). Reading motor intention through mental imagery. Adaptive Behavior, 21(5), 315-327.
Liang, W. K., Lo, M. T., Yang, A. C., Peng, C. K., Cheng, S. K., Tseng, P., & Juan, C. H. (2014). Revealing the brain′s adaptability and the transcranial direct current stimulation facilitating effect in inhibitory control by multiscale entropy. Neuroimage, 90, 218-234.
Li, C. S., Huang, C., Yan, P., Bhagwagar, Z., Milivojevic, V., & Sinha, R. (2008). Neural correlates of impulse control during stop signal inhibition in cocaine-dependent men. Neuropsychopharmacology, 33(8), 1798-1806.
Lim, J., Teng, J., Patanaik, A., Tandi, J., & Massar, S. A. A. (2018). Dynamic functional connectivity markers of objective trait mindfulness. Neuroimage, 176, 193-202.
Lo, Y. H., Liang, W. K., Lee, H. W., Wang, C. H., Tzeng, O. J., Hung, D. L., Cheng, S.K. & Juan, C. H. (2013). The neural development of response inhibition in 5- and 6-year-old preschoolers: an ERP and EEG study. Developmental Neuropsychology, 38(5), 301-316.
Lomas, T., Ivtzan, I., & Fu, C. H. Y. (2015). A systematic review of the neurophysiology of mindfulness on EEG oscillations. Neuroscience & Biobehavioral Reviews, 57, 401-410.
Logan, G. D. (1994). On the ability to inhibit thought and action: A users′ guide to the stop signal paradigm.
Logan, G. D., & Cowan, W. B. (1984). On the ability to inhibit thought and action: A theory of an act of control. Psychological Review, 91(3), 295.
Long, D. L., & Prat, C. S. (2002). Working memory and stroop interference: an individual differences investigation. Memory & Cognition, 30(2), 294-301.
Luck, S. J. (2005). Ten simple rules for designing ERP experiments. Event-related potentials: A methods handbook, 262083337.
Luck, S. J., & Kappenman, E. S. (2012). The Oxford handbook of event-related potential components. New York, NY, US: Oxford University Press.
Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390(6657), 279-281.
Luck, S. J., & Vogel, E. K. (2013). Visual working memory capacity: from psychophysics and neurobiology to individual differences. Trends in Cognitive Sciences, 17(8), 391-400.
Lundqvist, M., Rose, J., Herman, P., Brincat, S. L., Buschman, T. J., & Miller, E. K. (2016). Gamma and beta bursts underlie working memory. Neuron, 90(1), 152-164.
Luu, K., & Hall, P. A. (2017). Examining the Acute Effects of Hatha Yoga and Mindfulness Meditation on Executive Function and Mood. Mindfulness, 8(4), 873-880.
MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002). On the practice of dichotomization of quantitative variables. Psychological Methods, 7(1), 19-40.
MacDonald, A. W., Cohen, J. D., Stenger, V. A., & Carter, C. S. (2000). Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science, 288(5472), 1835-1838.
MacLeod, C., & Donnellan, A. M. (1993). Individual differences in anxiety and the restriction of working memory capacity. Personality and Individual Differences, 15(2), 163-173.
Makeig, S., Bell, A. J., Jung, T.-P., & Sejnowski, T. J. (1996). Independent component analysis of electroencephalographic data. Advances in Neural Information Processing Systems, 145-151.
Malinowski, P. (2013). Neural mechanisms of attentional control in mindfulness meditation. Frontiers in Neuroscience, 7, 8.
Manna, A., Raffone, A., Perrucci, M. G., Nardo, D., Ferretti, A., Tartaro, A., Londei, A., Del Gratta, C., Belardinelli, M. O., & Romani, G. L. (2010). Neural correlates of focused attention and cognitive monitoring in meditation. Brain Research Bulletin, 82(1-2), 46-56.
Mareschal, I., & Baker, C. L., Jr. (1998). Temporal and spatial response to second-order stimuli in cat area 18. J Neurophysiol, 80(6), 2811-2823.
Maris, E., & Oostenveld, R. (2007). Nonparametric statistical testing of EEG- and MEG-data. Journal of Neuroscience Methods, 164(1), 177-190.
Mayers, A. (2013). Introduction to Statistics and SPSS in Psychology: Pearson. ISBN-13: 978-0273731016
McClelland, Lynch, Irwin, Spiller, & Fitzsimons. (2015). Median splits, Type II errors, and false–positive consumer psychology: Don′t fight the power. Journal of Consumer Psychology, 25(4), 679-689.
Meltzer, J. A., Zaveri, H. P., Goncharova, II, Distasio, M. M., Papademetris, X., Spencer, S. S., Spencer, D. D., & Constable, R. T. (2008). Effects of working memory load on oscillatory power in human intracranial EEG. Cerebral Cortex, 18(8), 1843-1855.
Mischel, W., Shoda, Y., & Peake, P. K. (1988). The nature of adolescent competencies predicted by preschool delay of gratification. Journal of Personality and Social Psychology, 54(4), 687-696.
Miskovic, V., Martinovic, J., Wieser, M. M., Petro, N. M., Bradley, M. M., & Keil, A. (2015). Electrocortical amplification for emotionally arousing natural scenes: The contribution of luminance and chromatic visual channels. Biological Psychology, 106, 11-17.
Miyake, A., & Friedman, N. P. (2012). The nature and organization of individual differences in executive functions: four general conclusions. Current Directions in Psychological Science, 21(1), 8-14.
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex "Frontal Lobe" tasks: a latent variable analysis. Cognitive Psychology, 41(1), 49-100.
Mocaiber, I., Pereira, M. G., Erthal, F. S., Figueira, I., Machado-Pinheiro, W., Cagy, M., Volchan, E., & de Oliveira, L. (2009). Regulation of negative emotions in high trait anxious individuals: An ERP study. Psychology & Neuroscience, 2(2), 211.
Moffitt, T. E., Arseneault, L., Belsky, D., Dickson, N., Hancox, R. J., Harrington, H., . . . Caspi, A. (2011). A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of National Academy of Science of the USA, 108(7), 2693-2698.
Moore, A., & Malinowski, P. (2009). Meditation, mindfulness and cognitive flexibility. Consciousnes and Cognition, 18(1), 176-186.
Moran, T.P. (2016). Anxiety and working memory capacity: A meta-analysis and narrative review. Psychol Bull, 142(8), 831-864.
Moreno, A. L., Ávila-Souza, J., Gomes, W. B., & Gauer, G. (2015). Effects of worry on verbal and visual working memory. Psychology & Neuroscience, 8(3), 341.
Moriya, J. (2016). Attentional networks and visuospatial working memory capacity in social anxiety. Cognition and Emotion, 1-9.
Moriya, J., & Sugiura, Y. (2012). High visual working memory capacity in trait social anxiety. PLoS ONE, 7(4), e34244.
Moser, J. S., Becker, M. W., & Moran, T. P. (2012). Enhanced attentional capture in trait anxiety. Emotion, 12(2), 213-216.
Mrazek, M. D., Franklin, M. S., Phillips, D. T., Baird, B., & Schooler J. W. (2013). Mindfulness training improves working memory capacity and gre performance while reducing mind wandering. Psychological Science, 24(5), 776-781.
Munoz, D. P., Armstrong, I. T., Hampton, K. A., & Moore, K. D. (2003). Altered control of visual fixation and saccadic eye movements in attention-deficit hyperactivity disorder. Journal of Neurophysiology, 90(1), 503-514.
Munoz, D. P., & Everling, S. (2004). Look away: the anti-saccade task and the voluntary control of eye movement. Nature Reviews Neuroscience, 5(3), 218-228.
Nakamura, P. M., Pereira, G., Papini, C. B., Nakamura, F. Y., & Kokubun, E. (2010). Effects of preferred and nonpreferred music on continuous cycling exercise performance. Perceptual and Motor Skills, 110(1), 257-264.
Nigbur, R., Ivanova, G., & Sturmer, B. (2011). Theta power as a marker for cognitive interference. Clinical Neurophysiology, 122(11), 2185-2194.
Nunez, P. L. (2000). Toward a quantitative description of large-scale neocortical dynamic function and EEG. Behav Brain Sci, 23(3), 371-398; discussion 399-437.
Nunez, P. L., & Westdorp, A. F. (1994). The surface Laplacian, high resolution EEG and controversies. Brain Topography, 6(3), 221-226.
Oathes, D. J., Bruce, J. M., & Nitschke, J. B. (2008). Worry facilitates corticospinal motor response to transcranial magnetic stimulation. Depression and Anxiety, 25(11), 969-976.
Oya, H., Kawasaki, H., Howard, M. A., 3rd, & Adolphs, R. (2002). Electrophysiological responses in the human amygdala discriminate emotion categories of complex visual stimuli. Journal of Neuroscience, 22(21), 9502-9512.
Pacheco-Unguetti, A. P., Acosta, A, Callejas, A., & Lupiáñez, J. (2010). Attention and Anxiety. Psychological Science, 21(2), 298-304.
Palva, S., & Palva, J. M. (2007). New vistas for alpha-frequency band oscillations. Trends in Neuroscience, 30(4), 150-158.
Pashler, H. (1988). Familiarity and visual change detection. Perception & Psychophysics, 44(4), 369-378.
Pashler, H. (1994). Dual-task interference in simple tasks: data and theory. Psychological Bulletin, 116(2), 220.
Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995). Factor structure of the Barratt impulsiveness scale. Journal of Clinical Psychology, 51(6), 768-774.
Paul, S., Wolfgang, K., Michael, D., Thomas, P., Roman, F., & Simon, H. (2005). EEG alpha synchronization and functional coupling during top‐down processing in a working memory task. Human brain mapping, 26(2), 148-155.
Pesaran, B., Pezaris, J. S., Sahani, M., Mitra, P. P., & Andersen, R. A. (2002). Temporal structure in neuronal activity during working memory in macaque parietal cortex. Nature Neuroscience, 5, 805.
Pessoa, L., Gutierrez, E., Bandettini, P. A., & Ungerleider, L. G. (2002). Neural correlates of visual working memory: fmri amplitude predicts task performance. Neuron, 35(5), 975-987.
Pessoa, L., & Ungerleider, L. G. (2004). Neural correlates of change detection and change blindness in a working memory task. Cerebral Cortex, 14(5), 511-520.
Peters, J. R., Erisman, S. M., Upton, B. T., Baer, R. A., & Roemer, L. (2011). A preliminary investigation of the relationships between dispositional mindfulness and impulsivity. Mindfulness, 2(4), 228-235.
Pfurtscheller, G. (2003). Induced oscillations in the alpha band: functional meaning. Epilepsia, 44 Suppl 12, 2-8.
Pfurtscheller, G., & Lopes da Silva, F. H. (1999). Event-related EEG/MEG synchronization and desynchronization: basic principles. Clinical Neurophysiology, 110(11), 1842-1857.
Poppelaars, E. S., Harrewijn, A., Westenberg, P. M., & van der Molen, M. J. W. (2018). Frontal delta-beta cross-frequency coupling in high and low social anxiety: An index of stress regulation? Cognitive, Affective, & Behavioral Neuroscience, 18(4), 764-777.
Prinzmetal, W., McCool, C., & Park, S. (2005). Attention: reaction time and accuracy reveal different mechanisms. Journal of Experimental Psychology General, 134(1), 73-92.
Putman, P. (2011). Resting state EEG delta-beta coherence in relation to anxiety, behavioral inhibition, and selective attentional processing of threatening stimuli. International Journal of Psychophysiology, 80(1), 63-68.
Quirk, G. J., Garcia, R., & Gonzalez-Lima, F. (2006). Prefrontal mechanisms in extinction of conditioned fear. Biol Psychiatry, 60(4), 337-343.
Quirk, G. J., & Mueller, D. (2008). Neural mechanisms of extinction learning and retrieval. Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology, 33(1), 56-72.
Rammstedt, B., Danner, D., & Martin, S. (2016). The association between personality and cognitive ability: Going beyond simple effects. Journal of Research in Personality, 62, 39-44.
Ress, D., Backus, B. T., & Heeger, D. J. (2000). Activity in primary visual cortex predicts performance in a visual detection task. Nature neuroscience, 3(9), 940.
Reynolds, J., McClelland, A., & Furnham, A. (2014). An investigation of cognitive test performance across conditions of silence, background noise and music as a function of neuroticism. Anxiety, Stress, and Coping, 27(4), 410-421.
Rickard, N. S. (2004). Intense emotional responses to music: a test of the physiological arousal hypothesis. Psychology of Music, 32(4), 371-388.
Rouder, J. N., Morey, R. D., Morey, C. C. & Cowan, N. (2011). How to measure working memory capacity in the change detection paradigm. Psychonomic Bulletin & Review, 18(2), 324-330.
Roux, F., Wibral, M., Mohr, H. M., Singer, W., & Uhlhaas, P. J. (2012). Gamma-band activity in human prefrontal cortex codes for the number of relevant items maintained in working memory. J Neurosci, 32(36), 12411-12420.
Sacks, O. (2006). The power of music. Brain, 129(10), 2528-2532.
Salenius, S., Kajola, M., Thompson, W. L., Kosslyn, S., & Hari, R. (1995). Reactivity of magnetic parieto-occipital alpha rhythm during visual imagery. Electroencephalography and Clinical Neurophysiology, 95(6), 453-462.
Sauseng, P., Klimesch, W., Doppelmayr, M., Pecherstorfer, T., Freunberger, R., & Hanslmayr, S. (2005). EEG alpha synchronization and functional coupling during top-down processing in a working memory task. Human Brain Mapping, 26(2), 148-155.
Savostyanov, A. N., Tsai, A. C., Liou, M., Levin, E. A., Lee, J. D., Yurganov, A. V., & Knyazev, G. G. (2009). EEG-correlates of trait anxiety in the stop-signal paradigm. Neuroscience Letters, 449(2), 112-116.
Schachar, R., & Logan, G. (1990). Are hyperactive children deficient in attentional capacity? Journal of Abnormal Child Psychology, 18(5), 493-513.
Schachar, R., Tannock, R., Marriott, M., & Logan, G. (1995). Deficient inhibitory control in attention deficit hyperactivity disorder. Journal of Abnormal Child Psychology, 23(4), 411-437.
Scherer, K. R. (2009). Emotions are emergent processes: they require a dynamic computational architecture. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1535), 3459-3474.
Schmader, T., & Johns, M. (2003). Converging evidence that stereotype threat reduces working memory capacity. Journal of Personality and Social Psychology, 85(3), 440-452.
Schupp, H. T., Cuthbert, B. N., Bradley, M. M., Cacioppo, J. T., Ito, T., & Lang, P. J. (2000). Affective picture processing: the late positive potential is modulated by motivational relevance. Psychophysiology, 37(2), 257-261.
Schurmann, M., Demiralp, T., Basar-Eroglu, C., Basar, E., 1999. Selectively distributed gamma-band responses studied in cortex, reticular formation, hippocampus, and cerebellum. In: Basar, E.(Ed.), Brain Function and Oscillations. II. Integrative Brain Function. Neurophysiology and Cognitive Processes. Springer, Berlin, Heidelberg, pp. 61–67. (adapted from Knyazev., 2007)
Schutter, D. J., & van Honk, J. (2005). Salivary cortisol levels and the coupling of midfrontal delta-beta oscillations. International Journal of Psychophysiology, 55(1), 127-129.
Schutter, D. J. L. G., & Knyazev, G. G. (2012). Cross-frequency coupling of brain oscillations in studying motivation and emotion. Motivation and Emotion, 36(1), 46-54.
Schwartz, O., & Simoncelli, E. P. (2001). Natural signal statistics and sensory gain control. Nature Neuroscience, 4(8), 819-825.
Sebastiani, L., Simoni, A., Gemignani, A., Ghelarducci, B., & Santarcangelo, E. L. (2003). Human hypnosis: autonomic and electroencephalographic correlates of a guided multimodal cognitive-emotional imagery. Neuroscience Letters, 338(1), 41-44.
Shek, D. T. (1993). The Chinese version of the State-Trait Anxiety Inventory: its relationship to different measures of psychological well-being. Journal of Clinical Psychology, 49(3), 349-358.
Shih, Y. N., Huang, R. H., & Chiang, H. Y. (2012). Background music: effects on attention performance. Work, 42(4), 573-578.
Shin, L. M., & Liberzon, I. (2010). The neurocircuitry of fear, stress, and anxiety disorders. Neuropsychopharmacology, 35(1), 169-191.
Singer, T., Critchley, H. D., & Preuschoff, K. (2009). A common role of insula in feelings, empathy and uncertainty. Trends in Cognitive Sciences, 13(8), 334-340.
Speer, N. K., Reynolds, J. R., Swallow, K. M., & Zacks, J. M. (2009). Reading stories activates neural representations of visual and motor experiences. Psychological Science, 20(8), 989-999.
Spielberger, C. D., Gorsuch, R. L., & Lushene, R. E. (1970). Manual for the state-trait anxiety inventory.
Srinivasan, R., Nunez, P. L., Tucker, D. M., Silberstein, R. B., & Cadusch, P. J. (1996). Spatial sampling and filtering of EEG with spline laplacians to estimate cortical potentials. Brain Topography, 8(4), 355-366.
Srinivasan, N., & Singh, A. (2017). Concentrative meditation influences visual awareness: a study with color afterimages. Mindfulness, 8(1), 17-26.
Stam, C. J. (2005). Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clinical Neurophysiology, 116(10), 2266-2301.
Steimke, R., Nomi, J. S., Calhoun, V. D., Stelzel, C., Paschke, L. M., Gaschler, R., . . . Uddin, L. Q. (2017). Salience network dynamics underlying successful resistance of temptation. Social Cognitive and Affective Neuroscience, 12(12), 1928-1939.
Steriade, M., McCormick, D. A., & Sejnowski, T. J. (1993). Thalamocortical oscillations in the sleeping and aroused brain. Science, 262(5134), 679-685.
Sternberg, S. (1966). High-speed scanning in human memory. Science, 153(3736), 652-654.
Stroop,J. R. (1935). Studies of interference in serial verbal reactions. Journal of experimental psychology, 18(6), 643.
Swann, N. C., Cai, W., Conner, C. R., Pieters, T. A., Claffey, M. P., George, J. S., . . . Tandon, N. (2012). “Roles for the pre-supplementary motor area and the right inferior frontal gyrus in stopping action: electrophysiological responses and functional and structural connectivity”. Neuroimage, 59(3), 2860-2870.
Tabachnick, B. G., & Fidell, L. S. (2007). Experimental designs using ANOVA: Thomson / Brooks /Cole.
Tanaka, Sugiura, & Takebayashi. (2013). The relationship between orienting attention and dispositional mindfulness is moderated by alerting attention. The Japanese Journal of Personality, 22(2), 146-155.
Tanay, G., & Bernstein, A. (2013). State Mindfulness Scale (SMS): development and initial validation. Psychological Assessment, 25(4), 1286.
Tang, D., Hu, L., & Chen, A. (2013). The neural oscillations of conflict adaptation in the human frontal region. Biological Psychology, 93(3), 364-372.
Tang, Y. Y., Lu, Fan, Yang, & Posner, M. I. (2012). Mechanisms of white matter changes induced by meditation. Proceedings of the National Academy of Sciences of the USA, 109(26), 10570-10574.
Tang, Y. Y., Lu, Geng, Stein, Yang, & Posner, M. I. (2010). Short-term meditation induces white matter changes in the anterior cingulate. Proceedings of the National Academy of Sciences of the USA, 107(35), 15649-15652.
Tang, Y.-Y., Holzel, B. K., & Posner, M. I. (2015). The neuroscience of mindfulness meditation. Nat Rev Neurosci, 16(4), 213-225.
Tang, Y.-Y., & Posner, M. I. (2013). Tools of the trade: theory and method in mindfulness neuroscience. Social Cognitive and Affective Neuroscience, 8(1), 118-120.
Tang, Y. Y., Ma, Y., Wang, J., Fan, Y., Feng, S., Lu, Q., Yu, Q., Sui, D., Rothbart, M. K., Fan, M., & Posner, M. I. (2007). Short-term meditation training improves attention and self-regulation. Proceedings of the National Academy of Sciences of the United States of America, 104(43), 17152-17156.
Tarrasch, R., Margalit-Shalom, L., & Berger, R. (2017). Enhancing visual perception and motor accuracy among school children through a mindfulness and compassion program. Frontiers in Psychology, 8(281).
Teper, R., & Inzlicht, M. (2013). Meditation, mindfulness and executive control: the importance of emotional acceptance and brain-based performance monitoring. Social Cognitive and Affective Neuroscience, 8(1), 85-92.
Teplan, M. (2002). Fundamentals of EEG measurement. Measurement Science Review, 2(2), 1-11.
Thompson, W. F., Schellenberg, E. G., & Husain, G. (2001). Arousal, mood, and the Mozart effect. Psychological Science, 12(3), 248-251.
Todd, J. J. & Marois, R. (2004). Capacity limit of visual short-term memory in human posterior parietal cortex. Nature, 428(6984), 751-754.
Tsai, Y. C., Lu, H. J., Chang, C. F., Liang, W. K., Muggleton, N. G., & Juan, C. H. (2017). Electrophysiological and behavioral evidence reveals the effects of trait anxiety on contingent attentional capture. Cognitive, Affective and Behavioral Neuroscience.
Tseng, P., Hsu, T. Y., Chang, C. F., Tzeng, O. J., Hung, D. L., Muggleton, N. G., . . . Juan, C. H. (2012). Unleashing potential: transcranial direct current stimulation over the right posterior parietal cortex improves change detection in low-performing individuals. Journal of Neuroscience, 32(31), 10554-10561.
Tuladhar, A. M., Huurne, N. t., Schoffelen, J. M., Maris, E., Oostenveld, R., & Jensen, O. (2007). Parieto‐occipital sources account for the increase in alpha activity with working memory load. Human Brain Mapping, 28(8), 785-792.
Unsworth, N., Heitz, R. P., Schrock, J. C., & Engle, R. W. (2005). An automated version of the operation span task. Behavioral Research Methods, 37(3), 498-505.
von Stein, A., & Sarnthein, J. (2000). Different frequencies for different scales of cortical integration: from local gamma to long range alpha/theta synchronization. International Journal of Psychophysiology, 38(3), 301-313.
Vines, L . M. (2014). Dispositional mindfulness and working memory in the context of acute stress. Electronic Theses and Dissertations. Paper 1493.
Walsh, J. J., Balint, M. G., Smolira, D. R., Fredericksen, L. K., & Madsen, S. (2009). Predicting individual differences in mindfulness: The role of trait anxiety, attachment anxiety and attentional control. Personality and Individual Differences, 46(2), 94-99.
Wang, Z., Chen, J., Boyd, J. E., Zhang, H., Jia, X., Qiu, J., & Xiao, Z. (2011). Psychometric properties of the chinese version of the perceived stress scale in policewomen. PLoS ONE, 6(12), e28610.
Wang, K., Li, Q., Zheng, Y., Wang, H., & Liu, X. (2014). Temporal and spectral profiles of stimulus–stimulus and stimulus–response conflict processing. Neuroimage, 89, 280-288.
Way, B. M., Creswell, J. D., Eisenberger, N. I., & Lieberman, M. D. (2010). Dispositional mindfulness and depressive symptomatology: correlations with limbic and self-referential neural activity during rest. Emotion (Washington, D.C.), 10(1), 12-24.
Welsh, J. A., Nix, R. L., Blair, C., Bierman, K. L., & Nelson, K. E. (2010). The development of cognitive skills and gains in academic school readiness for children from low-income families. Journal of Educational Psychology, 102(1), 43-53.
Williams, N., Nasuto, S. J., & Saddy, J. D. (2011). Evaluation of empirical mode decomposition for event-related potential analysis. EURASIP Journal on Advances in Signal Processing, 2011(1), 965237.
Williams, L. E., Oler, J. A., Fox, A. S., McFarlin, D. R., Rogers, G. M., Jesson, M. A. L., . . . Kalin, N. H. (2015). Fear of the unknown: uncertain anticipation reveals amygdala alterations in childhood anxiety disorders. Neuropsychopharmacology, 40(6), 1428-1435.
Wine, J. (1971). Test anxiety and direction of attention. Psychological bulletin, 76(2), 92.
Womelsdorf, T., Johnston, K., Vinck, M., & Everling, S. (2010). Theta-activity in anterior cingulate cortex predicts task rules and their adjustments following errors. Proceedings of the National Academy of Sciences of the USA, 107(11), 5248.
Wu, Z., & Huang, N. E. (2009). Ensemble empirical mode decomposition: a noise-assisted data analysis method. Advances in Adaptive Data Analysis, 1(01), 1-41.
Zeidan, F., Johnson, S. K., Diamond, B. J., David, Z., & Goolkasian, P. (2010). Mindfulness meditation improves cognition: evidence of brief mental training. Consciousness and Cognition, 19(2), 597-605.
Zhao, J., Liang, W.-K., Juan, C.-H., Wang, L., Wang, S., & Zhu, Z. (2015). Dissociated stimulus and response conflict effect in the Stroop task: Evidence from evoked brain potentials and brain oscillations. Biological Psychology, 104, 130-138.
Zhou, Y. X., & Baker, C. L., Jr. (1993). A processing stream in mammalian visual cortex neurons for non-Fourier responses. Science, 261(5117), 98-101.
1https://www.fil.ion.ucl.ac.uk/spm/software/spm12/
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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