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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 吳恩賜(Joshua Oon Soo Goh) | |
| dc.contributor.author | Yi-Zhen Wang | en |
| dc.contributor.author | 王苡蓁 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:14:46Z | - |
| dc.date.available | 2022-02-16 | |
| dc.date.available | 2022-11-24T03:14:46Z | - |
| dc.date.copyright | 2022-02-16 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-02-09 | |
| dc.identifier.citation | Barr, D. J., Levy, R., Scheepers, C., Tily, H. J. (2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68(3), 10.1016/j.jml.2012.11.001. PubMed. https://doi.org/10.1016/j.jml.2012.11.001 Bejan, A. (2019). Why the Days Seem Shorter as We Get Older. European Review, 27(2), 187–194. Cambridge Core. https://doi.org/10.1017/S1062798718000741 Block, R. A., Hancock, P. A., Zakay, D. (2010). How cognitive load affects duration judgments: A meta-analytic review. Acta Psychologica, 134(3), 330–343. Bratianu, C. (2019). Exploring knowledge entropy in organizations. Management Dynamics in the Knowledge Economy, 7(3), 353–366. de Tommaso, M., Betti, V., Bocci, T., Bolognini, N., Di Russo, F., Fattapposta, F., Ferri, R., Invitto, S., Koch, G., Miniussi, C., Piccione, F., Ragazzoni, A., Sartucci, F., Rossi, S., Arcara, G., Berchicci, M., Bianco, V., Delussi, M., Gentile, E., … Valeriani, M. (2020). Pearls and pitfalls in brain functional analysis by event-related potentials: A narrative review by the Italian Psychophysiology and Cognitive Neuroscience Society on methodological limits and clinical reliability—Part I. Neurological Sciences, 41(10), 2711–2735. https://doi.org/10.1007/s10072-020-04420-7 Droit-Volet, S., Fayolle, S., Gil, S. (2011). Emotion and Time Perception: Effects of Film-Induced Mood. Frontiers in Integrative Neuroscience, 5, 33. https://doi.org/10.3389/fnint.2011.00033 Hancock, P. A. (1993). Body temperature influence on time perception. The Journal of General Psychology, 120(3), 197–216. Khan, A., Dixit, S. (2006). Effect of Cognitive Load and Paradigm on Time Perception. Journal of the Indian Academy of Applied Psychology, 32, 37–42. Matell, M. S., Meck, W. H. (2000). Neuropsychological mechanisms of interval timing behavior. BioEssays : News and Reviews in Molecular, Cellular and Developmental Biology, 22 1, 94–103. Pariyadath, V., Eagleman, D. (2007). The Effect of Predictability on Subjective Duration. PLOS ONE, 2(11), 1–6. https://doi.org/10.1371/journal.pone.0001264 Polti, I., Martin, B., van Wassenhove, V. (2018). The effect of attention and working memory on the estimation of elapsed time. Scientific Reports, 8(1), 6690. https://doi.org/10.1038/s41598-018-25119-y Reddy, L., Zoefel, B., Possel, J. K., Peters, J., Dijksterhuis, D. E., Poncet, M., van Straaten, E. C. W., Baayen, J. C., Idema, S., Self, M. W. (2021). Human Hippocampal Neurons Track Moments in a Sequence of Events. Journal of Neuroscience, 41(31), 6714–6725. https://doi.org/10.1523/JNEUROSCI.3157-20.2021 Schubotz, R. I., Friederici, A. D., Von Cramon, D. Y. (2000). Time perception and motor timing: A common cortical and subcortical basis revealed by fMRI. Neuroimage, 11(1), 1–12. Schwarz, M. A., Winkler, I., Sedlmeier, P. (2013). The heart beat does not make us tick: The impacts of heart rate and arousal on time perception. Attention, Perception, Psychophysics, 75(1), 182–193. Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(3), 379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x Skagerlund, K., Karlsson, T., Träff, U. (2016). Magnitude Processing in the Brain: An fMRI Study of Time, Space, and Numerosity as a Shared Cortical System. Frontiers in Human Neuroscience, 10, 500. https://doi.org/10.3389/fnhum.2016.00500 Stetson, C., Fiesta, M. P., Eagleman, D. M. (2007). Does time really slow down during a frightening event? PloS One, 2(12), e1295. https://doi.org/10.1371/journal.pone.0001295 Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. Tsao, A., Sugar, J., Lu, L., Wang, C., Knierim, J. J., Moser, M.-B., Moser, E. I. (2018). Integrating time from experience in the lateral entorhinal cortex. Nature, 561(7721), 57–62. https://doi.org/10.1038/s41586-018-0459-6 Wallisch, P. (2014). Chapter 20—Information Theory. In P. Wallisch, M. E. Lusignan, M. D. Benayoun, T. I. Baker, A. S. Dickey, N. G. Hatsopoulos (Eds.), MATLAB for Neuroscientists (Second Edition) (pp. 317–327). Academic Press. https://doi.org/10.1016/B978-0-12-383836-0.00018-7 Wittmann, M., Paulus, M. (2008). Decision Making, Impulsivity and Time Perception. Trends in Cognitive Sciences, 12, 7–12. https://doi.org/10.1016/j.tics.2007.10.004 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80739 | - |
| dc.description.abstract | 人類經由主觀感受所判斷的時間單位並不準確,且會受特定因素影響而增長。例如,經歷了危及生命的事件或是接受到未預期的新奇刺激,都會導致受試者做出該刺激的持續時間比物理上的時間更長的判斷。這些發現表明刺激強度與主觀持續時間之間存在關聯。本研究旨在探討時間於大腦中的基本表徵,本研究推測大腦對於時長的判斷是基於接收到資訊量轉換而來,並假設時間感知在神經機制與當下所處理資訊量存在相關。為了檢驗資訊量是否代表了主觀時間的基本概念。為了探討資訊量和時間判斷之間的關係,我們設計了一項內隱性時間作業,以行為反應檢驗資訊量對視覺內隱性時間判斷的影響。為了精準量測與計算資訊量,本研究使用Shannon熵來計算與呈現八種程度(0到4.91位元)的資訊熵刺激。實驗結果顯示,在處理較少資訊的情況下,時間單位的長度被低估了;隨著資訊量的增加,時間單位的長度反而被高估了。此結果支持人類主觀判斷時長的基礎是資訊量,意即主觀判斷之時間長度反應了該事件之資訊量。此外,附錄補充了為近一步透過神經活動的效果檢驗資訊量對時間預期的影響,我們使用事件相關電位檢驗其在腦電波中的效果,結果顯示,在事件後200-300毫秒之間的前區的平均振幅與預期時間呈負相關,並且資訊量在其中有顯著主效果,然而對由於樣本數不足,此實驗結果不足以成為支持假設的證據。綜上所述,行為實驗的結果顯示資訊量對內隱性時間判斷有顯著效果。而事件相關電位的研究結果,仍然需要更多樣本數以佐證。目前的研究,符合大腦對於時長的判斷是基於接收到資訊量轉換而來的假設。此研究對人類的時間感知與資訊量之間的關聯提供新的檢驗方法、證據和理解。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:14:46Z (GMT). No. of bitstreams: 1 U0001-0702202216480200.pdf: 5263228 bytes, checksum: 96068778fbeb9774bc12a3f9818e0dea (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | "致謝 i 中文摘要 ii Abstract iii List of Figures 1 List of Tables 2 Chapter1 Introduction 3 Chapter2 Method 10 2.1 Participants 10 2.2 Procedure 10 2.3 Apparatus 11 2.4 Stimuli 11 2.5 The demonstration and calculation of entropy 14 2.6 Analysis 17 2.6.1 Criteria for eliminating subjects and data 17 2.6.2 Analysis range of reaction position 17 2.6.3 Analysis of reaction time: the definition of errorRT 18 2.6.4 Linear mixed model 19 Chapter3 Result 20 3.1 The distribution of the response position across twenty participants 20 3.2 Significant fixed effect of entropy on errorRT 20 3.3 In lower entropy levels, participants underestimate the duration of time, while in higher entropy levels, they overestimate it 21 3.4 Extreme difference between response patterns at high and low levels of entropy 22 Chapter4 Discussion 23 Reference 28 Figures 31 Tables 39 Supplementary 42" | |
| dc.language.iso | en | |
| dc.subject | 時間處理 | zh_TW |
| dc.subject | 時間判斷 | zh_TW |
| dc.subject | 時間感 | zh_TW |
| dc.subject | 資訊量 | zh_TW |
| dc.subject | 熵 | zh_TW |
| dc.subject | 事件相關電位 | zh_TW |
| dc.subject | ERPs | en |
| dc.subject | event-related potentials | en |
| dc.subject | entropy | en |
| dc.subject | temporal judgment | en |
| dc.subject | time perception | en |
| dc.subject | quantities of information | en |
| dc.subject | temporal processing | en |
| dc.title | 視覺資訊量對人類內隱性時間處理之影響 | zh_TW |
| dc.title | The Effect of Visual Information Quantity on Human Implicit Temporal Processing | en |
| dc.date.schoolyear | 110-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 李佳霖(Chia-Lin Lee) | |
| dc.contributor.oralexamcommittee | 黃植懋(Yu-Chiang Frank Wang),葉素玲(Yung-Yu Chuang),(Cheng-Ming Huang),(Mu-Chun Su) | |
| dc.subject.keyword | 時間感,時間判斷,時間處理,資訊量,熵,事件相關電位, | zh_TW |
| dc.subject.keyword | time perception,temporal judgment,temporal processing,quantities of information,entropy,event-related potentials,ERPs, | en |
| dc.relation.page | 66 | |
| dc.identifier.doi | 10.6342/NTU202200335 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2022-02-09 | |
| dc.contributor.author-college | 醫學院 | zh_TW |
| dc.contributor.author-dept | 腦與心智科學研究所 | zh_TW |
| 顯示於系所單位: | 腦與心智科學研究所 | |
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