以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：154

、訪客IP：3.149.250.1

姓名	邱佳寧(Chia-Ning Chiu)  查詢紙本館藏	畢業系所	認知與神經科學研究所
論文名稱	(The Effects of Challenge, Hindrance Pressure, and Sports Participation on Flanker Task and Executive Task Performance Investigated Using the Drift Diffusion Model)
相關論文	★ Shaping the world through culture: an investigation of the effects of culture on cognition and perception ★ Investigation of the mechanisms of anxiety-related functions in the general population using brain stimulation ★ The effects of visual training on sporting performance in volleyball players ★ 正念與焦慮的作用及其對執行功能的影響
檔案	[Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載] 本電子論文使用權限為同意立即開放。 已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。 請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。
摘要(中)	運動類型可分為開放式技巧運動 (open-skill sport) 與閉鎖式技巧運動 (close-skill sport)，而開放式技巧運動又包含策略型運動 (strategic sports) 與截擊式運動 (interceptive sports)；閉鎖式技巧運動又稱為靜態式運動 (static sports)。過去文獻發現運動訓練對於認知功能具有許多幫助，相較於非運動員，運動員具有較好的認知功能如注意力、記憶力、決策能力等。而運動員努力訓練只為了爭取在運動場上的好成績，但壓力對於運動員扮演著極重要的角色，並對運動表現有著極大的影響。本論文將探討壓力對於不同運動項目認知表現的影響：針對三種不同類型的壓力源──挑戰型壓力 (challenge stress)、阻力型壓力 (hindrance stress) 與作業困難度壓力，對旁側夾擊作業 (flanker task) 與轉換作業 (switching task) 的影響。受試者包含控制組、運動組與排球組：控制組為坐式族群或無運動習慣者；運動組包含從事游泳與跑步族群，並歸類為閉鎖式技巧運動；而排球組則被歸類為開放式技巧運動。分析上採用擴散理論 (drift diffusion model)，包含反應時間分布圖型及決策域值 (decision threshold)，用以更準確地分析決策結果，並避免對於速度與準度不共存 (speed- accurate tradeoff) 的問題產生，進一步剖析決策能力在壓力下的結果。 針對挑戰型壓力的影響，在實驗ㄧ進行時間壓力與側旁夾擊作業，探討時間壓力對於不同運動類型下注意力的影響。對於阻力型壓力的影響，則在實驗二結合視覺觀察 (video observation) 與時間壓力之操弄，探討不同壓力類型對於運動技巧與體能下的影響。從實驗ㄧ與實驗二之結果發現，時間壓力會使決策域值 (threshold separation)、非決策時間 (non-decision time) 與決策速度 (drift rate) 下降，而排球組則對於側旁干擾訊息有較好的處理能力，但從實驗二並無發現視覺觀察的影響；即在挑戰型壓力下，較好的體能有較快的決策速度。而針對作業困難度壓力，實驗三則利用轉換作業測驗，以不同轉換試驗作為不同難度的壓力，以此探討壓力對於認知功能轉換的影響。從實驗三結果發現，較好的體能對於轉換作業中，具有較好的準確度表現。而在不同困難度壓力結果中發現，較簡單的轉換作業會具有較低的決策域值、非決策時間與較快的決策速度；但在難度較高的轉換作業則會具有較高的決策域值、非決策時間以及較低的決策速度。最後從實驗ㄧ到三，本研究發現相較於控制組與運動組，開放式技巧運動—排球組在不同的壓力源下操弄下，對旁側夾擊作業與轉換作業皆具有較好的表現結果。
摘要(英)	Sports can be classified as open-skill sport (strategic and interceptive sports) or closed-skill sports (static sports). Several review papers have provided an overview of the beneficial effects of fitness training on cognitive function and athletes train hard to fight to achieve good performance. However, pressure could be an important issue that would change sports performance. This thesis tried to gain a better understanding of the influence of pressure on cognitive performance and how this can be altered by different sports engagement. Nonsporting controls were compared to an exercise groups, including swimmers and runners (closed-skill, predictable action sports) and a volleyball group (an open-skill, unpredictable action sport) on tasks with three different pressure manipulations: challenge stress; hindrance stress; and task difficulty. These were used to investigate performance on the flanker tasks and an executive task. The drift diffusion model (DDM) which negates problems such as speed-accuracy tradeoffs in cognitive tasks, and provides more specific measurement of aspects of performance, such as the rate at which decisions are made and the decision threshold was specially used to quantify the effects of stress on performance. In Experiment 1, the flanker task in conjunction with a time pressure manipulation was used to investigate how such pressure may influence attention. In Experiment 2, video observation combined with time pressure was used to investigate whether this different stressor influenced decision-making performance and whether this interacted with sporting expertise and fitness. Drift diffusion model analysis of Experiments 1 and 2 showed that time pressure induced reduced threshold separation, non-decision time and decreased drift rate. Higher fitness levels were associate with faster speed to make a decision under time pressure. The volleyball group seem to have a better ability to process the flanker information which may be a consequence of the characteristics of the sport. No effect of observation was found (Experiment 2 In Experiment 3, task switching with stress manipulation caused by different switch levels, was investigated to evaluate a cognitive equivalent of motor switching and flexibility. The results showed that higher fitness levels led to performing more accurately in the task switch condition. The manipulation of task difficulty resulted in a lower threshold separation and non-decision time but a faster drift rate in a relatively simple task, but higher criteria, non-decision time and lower drift rate in the difficult task. Overall, in addition to performing better on cognitive tasks, the open skill sport (volleyball) group had better performance than nonsporting and exercise group when under different pressure manipulations.
關鍵字(中)	★ 開放式運動 ★ 閉鎖式運動 ★ 壓力 ★ 旁側夾擊作業 ★ 轉換作業 ★ 擴散理論	關鍵字(英)	★ open-skill sport ★ close-skill sport ★ pressure ★ flanker task ★ switching task ★ drift diffusion model
論文目次	摘要 i Abstract iii ACKNOWLEDGEMENTS v Table of contents vi List of figures viii List of tables xii Chapter 1 General Introduction 1 1.1 Sport and cognition 1 1.2 Pressure 3 1.2.1 Anxiety 4 1.2.2 Theories 6 1.2.3 Yerkes–Dodson law 7 1.3 Stress 10 1.3.1 Challenge and hindrance stress 10 1.4 Time pressure 14 1.5 Drift Diffusion Model (DDM) 14 1.6 Research aims 19 Chapter 2 Experiment 1：Challenge Stress and Attention 23 2.1 The effect of time pressure on the flanker task 23 2.1.1 Methods 24 2.1.2 Results 34 2.1.2 Discussion 79 Chapter 3 Experiment 2：Hindrances Stress and Attention 83 3.1 The effects of time pressure and observation on flanker task performance 83 3.1.1 Methods 84 3.1.2 Results 89 3.1.3 Discussion 108 Chapter 4 Experiment 3：Task difficulty and attention 114 4.1 The effects of task difficulty in task switching 114 4.1.1 Methods 115 4.1.2 Results 120 4.1.3 Discussion 133 Chapter 5 General discussion 135 5.1 Limitations 139 5.2 Conclusion 140 Reference 141 Appendix 151
參考文獻	Alves, H., Voss, M. W., Boot, W. R., Deslandes, A., Cossich, V., Salles, J. I., & Kramer, A. F. (2013). Perceptual-cognitive expertise in elite volleyball players. Frontiers in psychology, 4. Assink, N., Lubbe, R., Fox, J.-P., Wang, Y., Pierre, B., & Rudas, I. (2015). Does time pressure induce tunnel vision? An examination with the Eriksen Flanker Task by applying the Hierarchical Drift Diffusion Model. Paper presented at the Proceedings of the International Conference on Neural Networks–Fuzzy Systems (NN-FS 2015). Baltazar, M., Hazem, N., Vilarem, E., Beaucousin, V., Picq, J.-L., & Conty, L. (2014). Eye contact elicits bodily self-awareness in human adults. Cognition, 133(1), 120-127. Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological review, 84(2), 191. Bateson, M., Nettle, D., & Roberts, G. (2006). Cues of being watched enhance cooperation in a real-world setting. Biology letters, 2(3), 412-414. Baumeister, R. F. (1984). Choking under pressure: self-consciousness and paradoxical effects of incentives on skillful performance. Journal of personality and social psychology, 46(3), 610. Behmer, L. P., & Fournier, L. R. (2014). Working memory modulates neural efficiency over motor components during a novel action planning task: An EEG study. Behavioural brain research, 260, 1-7. Beilock, S. L., & Carr, T. H. (2001). On the fragility of skilled performance: What governs choking under pressure? Journal of experimental psychology: General, 130(4), 701. Beilock, S. L., Kulp, C. A., Holt, L. E., & Carr, T. H. (2004). More on the fragility of performance: choking under pressure in mathematical problem solving. Journal of experimental psychology: General, 133(4), 584. Bisagno, E., & Morra, S. (2018). How do we learn to “kill” in volleyball?: The role of working memory capacity and expertise in volleyball motor learning. Journal of Experimental Child Psychology, 167, 128-145. Casey, G., & Moran, A. (1989). The computational metaphor and cognitive psychology. The Irish Journal of Psychology, 10(2), 143-161. Cavanaugh, M. A., Boswell, W. R., Roehling, M. V., & Boudreau, J. W. (2000). An empirical examination of self-reported work stress among US managers. Journal of applied psychology, 85(1), 65. Christenson, G. N., & Winkelstein, A. M. (1988). Visual skills of athletes versus nonathletes: development of a sports vision testing battery. Journal of the American Optometric Association. Colcombe, S., & Kramer, A. F. (2003). Fitness effects on the cognitive function of older adults: a meta-analytic study. Psychological Science, 14(2), 125-130. Colcombe, S. J., Kramer, A. F., Erickson, K. I., Scalf, P., McAuley, E., Cohen, N. J., . . . Elavsky, S. (2004). Cardiovascular fitness, cortical plasticity, and aging. Proceedings of the National academy of Sciences of the United States of America, 101(9), 3316-3321. Costa, P. T., & McCrae, R. R. (2008). The revised neo personality inventory (neo-pi-r). The SAGE handbook of personality theory and assessment, 2, 179-198. Craig, C. L., Marshall, A. L., Sjöström, M., Bauman, A. E., Booth, M. L., Ainsworth, B. E., . . . Sallis, J. F. (2003). International physical activity questionnaire: 12-country reliability and validity. Medicine & Science in Sports & Exercise, 35(8), 1381-1395. Davids, K. (2002). Interceptive actions in sport: Information and movement: Psychology Press. Davids, K., Savelsbergh, G., Bennett, S. J., & Van der Kamp, J. (2002). Theoretical perspectives and practical applications. Interceptive actions in sport: Information and movement, 1. de Beurs, E., Tielen, D., & Wollmann, L. (2014). The Dutch Social Interaction Anxiety Scale and the Social Phobia Scale: Reliability, Validity, and Clinical Utility. Psychiatry journal, 2014. de Lange, F. P., Roelofs, K., & Toni, I. (2008). Motor imagery: a window into the mechanisms and alterations of the motor system. cortex, 44(5), 494-506. Di Russo, F., Bultrini, A., Brunelli, S., Delussu, A. S., Polidori, L., Taddei, F., . . . Spinelli, D. (2010). Benefits of sports participation for executive function in disabled athletes. Journal of neurotrauma, 27(12), 2309-2319. Ditterich, J. (2006). Evidence for time‐variant decision making. European Journal of Neuroscience, 24(12), 3628-3641. Doctor, R. M., & Altman, F. (1969). Worry and emotionality as components of test anxiety: Replication and further data. Psychological reports, 24(2), 563-568. Dosseville, F., Laborde, S., & Raab, M. (2011). Contextual and personal motor experience effects in judo referees’ decisions. The Sport Psychologist, 25(1), 67-81. Driskell, J. E., & Salas, E. (2013). Stress and human performance: Psychology Press. Dustman, R. E., Emmerson, R. Y., Ruhling, R., Shearer, D., Steinhaus, L., Johnson, S., . . . Shigeoka, J. (1990). Age and fitness effects on EEG, ERPs, visual sensitivity, and cognition. Neurobiology of aging, 11(3), 193-200. Egner, T. (2007). Congruency sequence effects and cognitive control. Cognitive, Affective, & Behavioral Neuroscience, 7(4), 380-390. Engle, R. W. (2002). Working memory capacity as executive attention. Current directions in psychological science, 11(1), 19-23. Erickson, G. B. (2007). Sports vision: Vision care for the enhancement of sports performance: Elsevier Health Sciences. Ericsson, K. A. (2003). How the expert performance approach differs from traditional approaches to expertise in sport. Expert performance in sports—Advances in research on sport expertise, 371-402. Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon the identification of a target letter in a nonsearch task. Attention, Perception, & Psychophysics, 16(1), 143-149. Eysenck, M. W., & Calvo, M. G. (1992). Anxiety and performance: The processing efficiency theory. Cognition & Emotion, 6(6), 409-434. Feltz, D. L. (1982). Path analysis of the causal elements in Bandura′s theory of self-efficacy and an anxiety-based model of avoidance behavior. Journal of personality and social psychology, 42(4), 764. Feltz, D. L., Landers, D. M., & Raeder, U. (1979). Enhancing self-efficacy in high-avoidance motor tasks: A comparison of modeling techniques. Journal of Sport Psychology, 1(2), 112-122. Folkman, S. (2013). Stress: appraisal and coping Encyclopedia of behavioral medicine (pp. 1913-1915): Springer. Folkman, S., Lazarus, R. S., Dunkel-Schetter, C., DeLongis, A., & Gruen, R. J. (1986). Dynamics of a stressful encounter: Cognitive appraisal, coping, and encounter outcomes. Journal of personality and social psychology, 50(5), 992. Fontani, G., Lodi, L., Felici, A., Migliorini, S., & Corradeschi, F. (2006). Attention in athletes of high and low experience engaged in different open skill sports. Perceptual and Motor Skills, 102(3), 791-805. Fontani, G., Maffei, D., Cameli, S., & Polidori, F. (1999). Reactivity and event-related potentials during attentional tests in athletes. European journal of applied physiology and occupational physiology, 80(4), 308-317. Freedman, J. L., & Edwards, D. R. (1988). Time pressure, task performance, and enjoyment. Freeman, J. B., Dale, R., & Farmer, T. A. (2011). Hand in motion reveals mind in motion. Frontiers in psychology, 2. Furley, P., & Wood, G. (2016). Working memory, attentional control, and expertise in sports: A review of current literature and directions for future research. Journal of Applied Research in Memory and Cognition, 5(4), 415-425. Furley, P. A., & Memmert, D. (2010). The role of working memory in sport. International Review of Sport and Exercise Psychology, 3(2), 171-194. Furley, P. A., & Memmert, D. (2012). Working memory capacity as controlled attention in tactical decision making. Journal of Sport and Exercise Psychology, 34(3), 322-344. Gold, J. I., & Shadlen, M. N. (2007). The neural basis of decision making. Annu. Rev. Neurosci., 30, 535-574. Gow, D., Tuffey, S., Hardy, L., & Lochbaum, M. (1993). Multidimensional state anxiety and middle distance running performance: An exploratory examination of hanin′s (1 980) zones of optimal functioning hypothesis. Journal of Applied Sport Psychology, 5(1), 85-94. Grös, D. F., Antony, M. M., Simms, L. J., & McCabe, R. E. (2007). Psychometric properties of the State-Trait Inventory for Cognitive and Somatic Anxiety (STICSA): comparison to the State-Trait Anxiety Inventory (STAI). Psychological assessment, 19(4), 369. Grant, S., Corbett, K., Amjad, A., Wilson, J., & Aitchison, T. (1995). A comparison of methods of predicting maximum oxygen uptake. British journal of sports medicine, 29(3), 147-152. Haley, K. J., & Fessler, D. M. (2005). Nobody′s watching?: Subtle cues affect generosity in an anonymous economic game. Evolution and Human behavior, 26(3), 245-256. Hardy, L., & Parfitt, G. (1991). A catastrophe model of anxiety and performance. British journal of psychology, 82(2), 163-178. Heekeren, H. R., Marrett, S., & Ungerleider, L. G. (2008). The neural systems that mediate human perceptual decision making. Nature reviews neuroscience, 9(6), 467-479. Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2008). Be smart, exercise your heart: exercise effects on brain and cognition. Nature reviews neuroscience, 9(1), 58-65. Häkkinen, K. (1993). Changes in physical fitness profile in female volleyball players during the competitive season. The Journal of sports medicine and physical fitness, 33(3), 223-232. Jafarzadehpur, E., Aazami, N., & Bolouri, B. (2007). Comparison of saccadic eye movements and facility of ocular accommodation in female volleyball players and non‐players. Scandinavian journal of medicine & science in sports, 17(2), 186-190. Jennings, B. M. (2008). Work stress and burnout among nurses: Role of the work environment and working conditions. Johnson, J. G. (2006). Cognitive modeling of decision making in sports. Psychology of Sport and Exercise, 7(6), 631-652. Künstlinger, U., Ludwig, H., & Stegemann, J. (1987). Metabolic changes during volleyball matches. International Journal of Sports Medicine, 8(05), 315-322. Kahneman, D. (2011). Thinking Fast and Slow London: Penguin. Kamijo, K., & Takeda, Y. (2010). Regular physical activity improves executive function during task switching in young adults. International Journal of Psychophysiology, 75(3), 304-311. Kramer, A. F., & Erickson, K. I. (2007). Capitalizing on cortical plasticity: influence of physical activity on cognition and brain function. Trends in cognitive sciences, 11(8), 342-348. Kubesch, S., Walk, L., Spitzer, M., Kammer, T., Lainburg, A., Heim, R., & Hille, K. (2009). A 30‐Minute Physical Education Program Improves Students′ Executive Attention. Mind, Brain, and Education, 3(4), 235-242. Lachman, R., Lachman, J., & Butterfield, E. (1979). Cognitive psychology and information processing: An introduction.[aAK]. Lazarus, R. S. (1966). Psychological stress and the coping process. Lazarus, R. S., DeLongis, A., Folkman, S., & Gruen, R. (1985). Stress and adaptational outcomes: The problem of confounded measures. Lazarus, R. S., & Folkman, S. (1987). Transactional theory and research on emotions and coping. European Journal of personality, 1(3), 141-169. Le Blanc, A. L., Bruce, L. C., Heimberg, R. G., Hope, D. A., Blanco, C., Schneier, F. R., & Liebowitz, M. R. (2014). Evaluation of the psychometric properties of two short forms of the social interaction anxiety scale and the social phobia scale. Assessment, 21(3), 312-323. Leger, L. A., Mercier, D., Gadoury, C., & Lambert, J. (1988). The multistage 20 metre shuttle run test for aerobic fitness. Journal of Sports Sciences, 6(2), 93-101. LePine, J. A., Podsakoff, N. P., & LePine, M. A. (2005). A meta-analytic test of the challenge stressor–hindrance stressor framework: An explanation for inconsistent relationships among stressors and performance. Academy of Management Journal, 48(5), 764-775. Lewis, B. P., & Linder, D. E. (1997). Thinking about choking? Attentional processes and paradoxical performance. Personality and Social Psychology Bulletin, 23(9), 937-944. Liebert, R. M., & Morris, L. W. (1967). Cognitive and emotional components of test anxiety: A distinction and some initial data. Psychological reports, 20(3), 975-978. Macquet, A. (2009). Recognition within the decision-making process: A case study of expert volleyball players. Journal of Applied Sport Psychology, 21(1), 64-79. Mandal, N., Maity, S., & Sahu, D. (2015). A study of Correlations between dominant handgrip strength with some selected anthropometric and physiological characteristics in inter-college male volleyball players of West Bengal, India. Mann, D. T., Williams, A. M., Ward, P., & Janelle, C. M. (2007). Perceptual-cognitive expertise in sport: A meta-analysis. Journal of Sport and Exercise Psychology, 29(4), 457-478. Martens, R., Vealey, R. S., & Burton, D. (1990). Competitive anxiety in sport: Human kinetics. Mattick, R. P., & Clarke, J. C. (1998). Development and validation of measures of social phobia scrutiny fear and social interaction anxiety. Behaviour research and therapy, 36(4), 455-470. Mattick, R. P., Peters, L., & Clarke, J. C. (1989). Exposure and cognitive restructuring for social phobia: A controlled study. Behavior therapy, 20(1), 3-23. Maule, A. J., Hockey, G. R. J., & Bdzola, L. (2000). Effects of time-pressure on decision-making under uncertainty: changes in affective state and information processing strategy. Acta psychologica, 104(3), 283-301. Maxwell, J., Masters, R., & Poolton, J. (2006). Performance breakdown in sport: the roles of reinvestment and verbal knowledge. Research quarterly for exercise and sport, 77(2), 271-276. McClain, J. J., Welk, G. J., Ihmels, M., & Schaben, J. (2006). Comparison of two versions of the PACER aerobic fitness test. Journal of Physical Activity and Health, 3(s2), S47-S57. McCrae, R. R., & Costa, P. T. (2004). A contemplated revision of the NEO Five-Factor Inventory. Personality and Individual Differences, 36(3), 587-596. Mendl, M. (1999). Performing under pressure: stress and cognitive function. Applied Animal Behaviour Science, 65(3), 221-244. Miyazaki, Y. (2013). Increasing visual search accuracy by being watched. PloS one, 8(1), e53500. Miyazaki, Y. (2015). Influence of being videotaped on the prevalence effect during visual search. Frontiers in psychology, 6. Monsell, S. (2003). Task switching. Trends in cognitive sciences, 7(3), 134-140. Moran, A. (2012). Thinking in action: Some insights from cognitive sport psychology. Thinking Skills and Creativity, 7(2), 85-92. Mormann, M. M., Malmaud, J., Huth, A., Koch, C., & Rangel, A. (2010). The drift diffusion model can account for the accuracy and reaction time of value-based choices under high and low time pressure. Morris, L. W., Davis, M. A., & Hutchings, C. H. (1981). Cognitive and emotional components of anxiety: Literature review and a revised worry–emotionality scale. Journal of Educational psychology, 73(4), 541. Munzert, J., Lorey, B., & Zentgraf, K. (2009). Cognitive motor processes: the role of motor imagery in the study of motor representations. Brain research reviews, 60(2), 306-326. Nakata, H., Yoshie, M., Miura, A., & Kudo, K. (2010). Characteristics of the athletes′ brain: evidence from neurophysiology and neuroimaging. Brain research reviews, 62(2), 197-211. Nieuwenhuis, S., Stins, J. F., Posthuma, D., Polderman, T. J., Boomsma, D. I., & de Geus, E. J. (2006). Accounting for sequential trial effects in the flanker task: Conflict adaptation or associative priming? Memory & Cognition, 34(6), 1260-1272. Otten, M. (2009). Choking vs. clutch performance: A study of sport performance under pressure. Journal of Sport and Exercise Psychology, 31(5), 583-601. Pearsall, M. J., Ellis, A. P., & Stein, J. H. (2009). Coping with challenge and hindrance stressors in teams: Behavioral, cognitive, and affective outcomes. Organizational Behavior and Human Decision Processes, 109(1), 18-28. Perner, J., & Lang, B. (1999). Development of theory of mind and executive control. Trends in cognitive sciences, 3(9), 337-344. Philiastides, M. G., Ratcliff, R., & Sajda, P. (2006). Neural representation of task difficulty and decision making during perceptual categorization: a timing diagram. Journal of Neuroscience, 26(35), 8965-8975. Ratcliff, R. (1978). A theory of memory retrieval. Psychological review, 85(2), 59. Ratcliff, R. (2008). The EZ diffusion method: Too EZ? Psychonomic bulletin & review, 15(6), 1218-1228. Ratcliff, R. (2014). Measuring psychometric functions with the diffusion model. Journal of Experimental Psychology: Human Perception and Performance, 40(2), 870. Ratcliff, R., Cherian, A., & Segraves, M. (2003). A comparison of macaque behavior and superior colliculus neuronal activity to predictions from models of two-choice decisions. Journal of neurophysiology, 90(3), 1392-1407. Ratcliff, R., Gomez, P., & McKoon, G. (2004). A diffusion model account of the lexical decision task. Psychological review, 111(1), 159. Ratcliff, R., Hasegawa, Y. T., Hasegawa, R. P., Smith, P. L., & Segraves, M. A. (2007). Dual diffusion model for single-cell recording data from the superior colliculus in a brightness-discrimination task. Journal of neurophysiology, 97(2), 1756-1774. Ratcliff, R., Philiastides, M. G., & Sajda, P. (2009). Quality of evidence for perceptual decision making is indexed by trial-to-trial variability of the EEG. Proceedings of the National Academy of Sciences, 106(16), 6539-6544. Ratcliff, R., & Rouder, J. N. (1998). Modeling response times for two-choice decisions. Psychological Science, 9(5), 347-356. Ratcliff, R., & Rouder, J. N. (2000). A diffusion model account of masking in two-choice letter identification. Journal of Experimental Psychology: Human Perception and Performance, 26(1), 127. Ratcliff, R., & Smith, P. L. (2004). A comparison of sequential sampling models for two-choice reaction time. Psychological review, 111(2), 333. Ratcliff, R., Thapar, A., & McKoon, G. (2001). The effects of aging on reaction time in a signal detection task. Psychology and aging, 16(2), 323. Ratcliff, R., Thapar, A., & Mckoon, G. (2003). A diffusion model analysis of the effects of aging on brightness discrimination. Attention, Perception, & Psychophysics, 65(4), 523-535. Ratcliff, R., Van Zandt, T., & McKoon, G. (1999). Connectionist and diffusion models of reaction time. PSYCHOLOGICAL REVIEW-NEW YORK-, 106, 261-300. Rodell, J. B., & Judge, T. A. (2009). Can “good” stressors spark “bad” behaviors? The mediating role of emotions in links of challenge and hindrance stressors with citizenship and counterproductive behaviors. Journal of applied psychology, 94(6), 1438. Rogers, R. D., & Monsell, S. (1995). Costs of a predictible switch between simple cognitive tasks. Journal of experimental psychology: General, 124(2), 207. Roitman, J. D., & Shadlen, M. N. (2002). Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. Journal of Neuroscience, 22(21), 9475-9489. Rosellini, A. J., & Brown, T. A. (2011). The NEO Five-Factor Inventory: Latent structure and relationships with dimensions of anxiety and depressive disorders in a large clinical sample. Assessment, 18(1), 27-38. Rosenthal, R. (1968). Experimenter expectancy and the reassuring nature of the null hypothesis decision procedure. Safren, S. A., Turk, C. L., & Heimberg, R. G. (1998). Factor structure of the social interaction anxiety scale and the social phobia scale. Behaviour research and therapy, 36(4), 443-453. Salthouse, T. A. (2010). Is flanker-based inhibition related to age? Identifying specific influences of individual differences on neurocognitive variables. Brain and cognition, 73(1), 51-61. Schmitz, F., & Voss, A. (2012). Decomposing task-switching costs with the diffusion model. Journal of Experimental Psychology: Human Perception and Performance, 38(1), 222. Schmitz, F., & Voss, A. (2014). Components of task switching: A closer look at task switching and cue switching. Acta psychologica, 151, 184-196. Scisco, J. L., Leynes, P. A., & Kang, J. (2008). Cardiovascular fitness and executive control during task-switching: an ERP study. International Journal of Psychophysiology, 69(1), 52-60. Selye, H. (1936). A syndrome produced by diverse nocuous agents. Nature, 138(3479), 32. Sibley, B. A., & Etnier, J. L. (2004). Time course of attention and decision making during a volleyball set. Research quarterly for exercise and sport, 75(1), 102-106. Simon, J. (1967). The paradoxical effect of effort. Psychology and Psychotherapy: Theory, Research and Practice, 40(4), 375-380. Singer, R. N. (2000). Performance and human factors: Considerations about cognition and attention for self-paced and externally-paced events. Ergonomics, 43(10), 1661-1680. Smith, D. G., & Mewhort, D. (1998). The distribution of latencies constrains theories of decision time: A test of the random-walk model using numeric comparison. Australian Journal of Psychology, 50(3), 149-156. Stanovich, K. E., & West, R. F. (2000). Individual differences in reasoning: Implications for the rationality debate? Behavioral and brain sciences, 23(5), 645-665. Starkes, J. L., & Ericsson, K. A. (2003). Expert performance in sports: Advances in research on sport expertise: Human Kinetics. Svenson, O., & Benson III, L. (1993). Framing and time pressure in decision making Time pressure and stress in human judgment and decision making (pp. 133-144): Springer. Tomioka, K., Iwamoto, J., Saeki, K., & Okamoto, N. (2011). Reliability and validity of the International Physical Activity Questionnaire (IPAQ) in elderly adults: the Fujiwara-kyo Study. Journal of Epidemiology, 21(6), 459-465. Toner, J., & Moran, A. (2011). The effects of conscious processing on golf putting proficiency and kinematics. Journal of Sports Sciences, 29(7), 673-683. van Ravenzwaaij, D., & Oberauer, K. (2009). How to use the diffusion model: Parameter recovery of three methods: EZ, fast-dm, and DMAT. Journal of Mathematical Psychology, 53(6), 463-473. Vandekerckhove, J., & Tuerlinckx, F. (2007). Fitting the Ratcliff diffusion model to experimental data. Psychonomic bulletin & review, 14(6), 1011-1026. Vickers, J. N., & Williams, A. M. (2007). Performing under pressure: The effects of physiological arousal, cognitive anxiety, and gaze control in biathlon. Journal of Motor Behavior, 39(5), 381-394. Voss, A., Nagler, M., & Lerche, V. (2013). Diffusion models in experimental psychology. Experimental psychology. Voss, A., Rothermund, K., & Voss, J. (2004). Interpreting the parameters of the diffusion model: An empirical validation. Memory & Cognition, 32(7), 1206-1220. Voss, A., & Voss, J. (2007). Fast-dm: A free program for efficient diffusion model analysis. Behavior Research Methods, 39(4), 767-775. Voss, A., & Voss, J. (2008). A fast numerical algorithm for the estimation of diffusion model parameters. Journal of Mathematical Psychology, 52(1), 1-9. Voss, M. W., Kramer, A. F., Basak, C., Prakash, R. S., & Roberts, B. (2010). Are expert athletes ‘expert’in the cognitive laboratory? A meta‐analytic review of cognition and sport expertise. Applied Cognitive Psychology, 24(6), 812-826. Wang, C.-H., Chang, C.-C., Liang, Y.-M., Shih, C.-M., Chiu, W.-S., Tseng, P., . . . Juan, C.-H. (2013). Open vs. closed skill sports and the modulation of inhibitory control. PloS one, 8(2), e55773. Wang, C.-H., Chang, C.-C., Liang, Y.-M., Shih, C.-M., Muggleton, N. G., & Juan, C.-H. (2013). Temporal preparation in athletes: a comparison of tennis players and swimmers with sedentary controls. Journal of Motor Behavior, 45(1), 55-63. Wang, J., Marchant, D., Morris, T., & Gibbs, P. (2004). Self-consciousness and trait anxiety as predictors of choking in sport. Journal of Science and Medicine in Sport, 7(2), 174-185. Webster, J. R., Beehr, T. A., & Christiansen, N. D. (2010). Toward a better understanding of the effects of hindrance and challenge stressors on work behavior. Journal of Vocational Behavior, 76(1), 68-77. White, C. N., Ratcliff, R., & Starns, J. J. (2011). Diffusion models of the flanker task: Discrete versus gradual attentional selection. Cognitive psychology, 63(4), 210-238. Wiecki, T. V., Sofer, I., & Frank, M. J. (2013). HDDM: Hierarchical Bayesian estimation of the drift-diffusion model in Python. Frontiers in neuroinformatics, 7. Williams, A. M., Davids, K., & Williams, J. G. P. (1999). Visual perception and action in sport: Taylor & Francis. Wine, J. (1971). Test anxiety and direction of attention. Psychological bulletin, 76(2), 92. Yerkes, R. M., & Dodson, J. D. (1908). The relation of strength of stimulus to rapidity of habit‐formation. Journal of comparative neurology and psychology, 18(5), 459-482. Yu, J., Tseng, P., Muggleton, N. G., & Juan, C.-H. (2015). Being watched by others eliminates the effect of emotional arousal on inhibitory control. Frontiers in psychology, 6. Zillig, L. M. P., Hemenover, S. H., & Dienstbier, R. A. (2002). What do we assess when we assess a Big 5 trait? A content analysis of the affective, behavioral, and cognitive processes represented in Big 5 personality inventories. Personality and Social Psychology Bulletin, 28(6), 847-858. Zwierko, T., Osinski, W., Lubinski, W., Czepita, D., & Florkiewicz, B. (2010). Speed of visual sensorimotor processes and conductivity of visual pathway in volleyball players. Journal of Human Kinetics, 23, 21-27. 梁記雯. (2005). 高社交焦慮者的自傳式記憶特性--關於記憶清晰度的探討. 國立政治大學心理學研究所碩士論文.[Liang, CW (2005). The Characteristics of Autobiographical Memory in High Social Anxiety: the Exploration of Memory Vividness. Master Thesis of National Chengchi University.] 連結.
指導教授	馬杰仁(Neil G. Muggleton)	審核日期	2018-1-25
推文	facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu
網路書籤	Google bookmarks   del.icio.us   hemidemi   myshare