政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/56874
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113318/144297 (79%)
Visitors : 50988110      Online Users : 846
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
    •  Adv. Search
    Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer Goto mobile version


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/56874


    Title: 同理心對於決策中觀察學習的調節作用
    Empathy modulates observational learning in decision making
    Authors: 高常豪
    Contributors: 顏乃欣
    高常豪
    Keywords: 不確定下的決策
    增強學習
    觀察學習
    同理心
    decisions under uncertainty
    reinforcement learning
    observational learning
    empathy
    Date: 2012
    Issue Date: 2013-02-01 16:53:04 (UTC+8)
    Abstract: 生活中許多決策情境是「不確定下的決策（decisions under uncertainty）」，只瞭解選項的結果，不知道結果發生的機率。人們會累積經驗，以學習到適當的決策。許多證據支持，自身會透過增強學習（reinforcement learning）機制學習，根據每次獲得的經驗，調整對於選項的期望，之後選擇期望最大的選項，幫助做出適當的決策。經驗可以透過自身決策或觀察他人決策所獲得，然而，過去較少研究探討觀察學習。因此，本研究欲探討決策中的觀察學習，並釐清同理心對於觀察學習的調節作用。實驗一中，改善過去了研究限制，量測膚電反應、學習速率與行為表現，讓參與者在自身學習、觀察他人與觀察電腦情境進行作業，並透過同理心問卷測量參與者的同理心特質。結果顯示，觀察學習在正向學習與負向學習不同，正向學習為趨向優勢選項，負向學習為避開劣勢選項。正向學習在三種學習情境中無任何差異，負向學習在觀察他人學習時，會受到同理心的調節作用。同理心分數越高，觀察他人的負向行為表現越好，觀察他人負向回饋的膚電反應越大。實驗一只透過問卷測量同理心，無法推論因果關係，因此實驗二直接操弄了不同的同理程度。回饋呈現的同時，呈現他人的情緒或中性臉孔圖片，以引發參與者的同理程度高或低。實驗中，量測回饋相關負波（Feedback-Related Negativity，FRN）、學習速率與行為表現。如同實驗一，只有負向學習受到同理程度不同的影響。同理程度高時，負向學習表現較好。FRN則顯示了同理程度與預期性的交互作用，同理程度低時，與過去研究一致，非預期FRN比預期FRN更加負向；同理程度高時，則無此預期性效果。雖然FRN無預期性差異，但依然能學習到符號機率，行為表現不受影響，推測可能有其他系統參與決策學習。綜上所述，本研究顯示，只有負向學習中，觀察學習會受到同理心的調節，同理心越高，行為表現越好。
    In daily life, we made many decisions under uncertainty. In each decision, we know only the outcome but no probabilities of the outcome. We have to accumulate the experience to learn adaptive decisions. Bunches of studies have shown that people may learn adaptive decisions by reinforcement learning. People modified the expectation for each option according to decision feedbacks, and, in the next time, chose the option with the maximum expectation. People can receive feedback from decisions making by self or others. However, fewer studies examined observational learning in decision making. Therefore, present research would clarify observational learning in decision making, and examine how empathy modulated observational learning. In experiment 1, skin conductance response, learning rate and behavioral performance were recorded and analyzed. Participants would learning decisions in different situations of self learning, observing others and observing computer. The questionnaire of empathy was also measured to examine its modulation in observational learning. The results showed that there were difference in positive learning and negative learning. Positive learning is to approach to the advantageous option, while negative learning is to avoid from the disadvantageous option. In positive learning, there were no difference among the three learning situations, but, in negative learning, empathy would modulate learning by observing others. The higher the empathy score was, the better the behavioral performance of negative learning was. Moreover, the skin conductance response when participants observing others’ negative feedback positively correlated with the empathy score. In experiment 2, the empathy level was manipulated by display pictures of others faces with feedback. Displaying the emotional faces or neutral faces would induce high or low empathy level for others, respectively. The feedback-related negativity (FRN), learning rate and behavioral performance were recorded and analyzed. Similar to experiment 1, only the negative learning was modulated by the empathy level. When participants were induced high empathy level, the behavioral performance was better. The results of FRN showed the interaction between empathy levels and expectancy of feedback. When participant’s empathy level was low, unexpected FRN was more negative than expected FRN. This result was consistent with previous studies. Nevertheless, when participant’s empathy level was high, there was no difference between unexpected FRN and expected FRN. Although FRN didn`t show the effect of expectancy, participants could still learn the probabilities of each signs and made adaptive decisions. This result may result from other systems involved in observational learning. From the results of experiment 1 and 2, present research showed that, only in negative learning, observational learning was modulated by empathy, and the higher the empathy level was, the better the behavioral performance was.
    Reference: 翁開誠. (1986). 同理心-多向度測量與相關研究. 台北: 大洋出版社.
    Abler, B., Walter, H., Erk, S., Kammerer, H., & Spitzer, M. (2006). Prediction error as a linear function of reward probability is coded in human nucleus accumbens. NeuroImage, 31, 790-795.
    Bates, A. T., Patel, T. P., & Liddle, P. F. (2005). External behavior monitoring mirrors internal behavior monitoring error-related negativity for observed errors. Journal of Psychophysiology, 19, 281-288.
    Batson, C. D., Early, S., & Salvarani, G. (1997). Perspective taking: Imagining how another feels versus imaging how you would feel. Personality and Social Psychology Bulletin, 23, 751-758.
    Batson, C. D. (2009). These things called empathy: Eight related but distinct phenomena. In J. Decety & W. Ickes (Eds.), The social neuroscience of empathy (pp. 3-16). Cambridge, MA: MIT Press.
    Bayer, H. M., & Glimcher, P. W. (2005). Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron, 47, 129-141.
    Bellebaum, C., Kobza, S., Thiele, S., & Daum, I. (2010). It was not my fault: Event-related brain potentials in active and observational learning from feedback. Cerebral Cortex, 20, 2874-2883.
    Bellebaum, C., Jokisch, D., Gizewski, E. R., Forsting, M., & Daum, I. (2012). The neural coding of expected and unexpected monetary performance outcomes: Dissociations between active and observational learning. Behavioural Brain Research, 227, 241-251.
    Bernoulli, D. (1954/1738). Exposition of a new theory on the measurement of risk. [Specimen theoriae novae de mensura sortis]. Econometrica, 22, 23-36.
    Biele, G., Rieskamp, J., & Gonzalez, R. (2009). Computational models for the combination of advice and individual learning. Cognitive Science, 33, 206-242.
    Biele, G., Rieskamp, J., Krugel, L. K., & Heekeren, H. R. (2011). The neural basis of following advice. PLoS Biol, 9, e1001089.
    Burke, C. J., Tobler, P. N., Baddeley, M., & Schultz, W. (2010). Neural mechanisms of observational learning. Proceedings of the National Academy of Sciences, 107, 14431-14436.
    Chang, S. W. C., Winecoff, A. A., & Platt, M. L. (2011). Vicarious reinforcement in rhesus macaques (macaca mulatta). Frontiers in Neuroscience, 5, 27.
    Chiao, J. Y., & Mathur, V. A. (2010). Intergroup empathy: How does race affect empathic neural responses? Current Biology, 20, R478-R480.
    Cikara, M., Bruneau, E. G., & Saxe, R. R. (2011). Us and them. Current Directions in Psychological Science, 20, 149-153.
    Cooper, J. C., Dunne, S., Furey, T., & O`Doherty, J. P. (2012). Human dorsal striatum encodes prediction errors during observational learning of instrumental actions. Journal of Cognitive Neuroscience, 24, 106-118.
    Davis, M. (1980). A multidimensional approach to individual differences in empathy. JSAS Catalog of Selected Documents in Psychology, 10, 85.
    Daw, N. D., O`Doherty, J. P., Dayan, P., Seymour, B., & Dolan, R. J. (2006). Cortical substrates for exploratory decisions in humans. Nature, 441, 876-879.
    Dawson, M. E., Schell, A. M., & Filion, D. L. (2007). The electrodermal system. In J. T. Cacioppo, L. G. Tassinary & G. Berntson (Eds.), Handbook of psychophysiology (3 ed., pp. 159-181). New York: Cambridge University Press.
    Dickerson, K. C., Li, J., & Delgado, M. R. (2011). Parallel contributions of distinct human memory systems during probabilistic learning. NeuroImage, 55, 266-276.
    Dinstein, I., Hasson, U., Rubin, N., & Heeger, D. J. (2007). Brain areas selective for both observed and executed movements. Journal of Neurophysiology, 98, 1415-1427.
    Doll, B. B., Jacobs, W. J., Sanfey, A. G., & Frank, M. J. (2009). Instructional control of reinforcement learning: A behavioral and neurocomputational investigation. Brain Research, 1299, 74-94.
    Evans, J. S. B. T. (2008). Dual-processing accounts of reasoning, judgment, and social cognition. Annual Review of Psychology, 59, 255-278.
    Frank, M. J., Seeberger, L. C., & O`Reilly, R. C. (2004). By carrot or by stick: Cognitive reinforcement learning in parkinsonism. Science, 306, 1940-1943.
    Frank, M. J., Moustafa, A. A., Haughey, H. M., Curran, T., & Hutchison, K. E. (2007). Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning. Proceedings of the National Academy of Sciences, 104, 16311-16316.
    Frith, C. D., & Singer, T. (2008). The role of social cognition in decision making. Philosophical Transactions of the Royal Society B: Biological Sciences, 363, 3875-3886.
    Fukushima, H., & Hiraki, K. (2006). Perceiving an opponent`s loss: Gender-related differences in the medial-frontal negativity. Social Cognitive and Affective Neuroscience, 1, 149-157.
    Fukushima, H., & Hiraki, K. (2009). Whose loss is it? Human electrophysiological correlates of non-self reward processing. Social Neuroscience, 4, 261-275.
    Goldman, A. (2006). Simulating minds: The philosophy, psychology, and neuronscience of mindreading. Oxford, UK: Oxford University Press.
    Haruno, M., Kuroda, T., Doya, K., Toyama, K., Kimura, M., Samejima, K., . . . Kawato, M. (2004). A neural correlate of reward-based behavioral learning in caudate nucleus: A functional magnetic resonance imaging study of a stochastic decision task. The Journal of Neuroscience, 24, 1660-1665.
    Hein, G., & Singer, T. (2008). I feel how you feel but not always: The empathic brain and its modulation. Current Opinion in Neurobiology, 18, 153-158.
    Hein, G., Lamm, C., Brodbeck, C., & Singer, T. (2011). Skin conductance response to the pain of others predicts later costly helping. PLoS ONE, 6, e22759.
    Hertwig, R., Barron, G., Weber, E. U., & Erev, I. (2004). Decisions from experience and the effect of rare events in risky choice. Psychological Science, 15, 534-539.
    Holroyd, C. B., & Coles, M. G. H. (2002). The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109, 679-709.
    Holroyd, C. B., Nieuwenhuis, S., Yeung, N., & Cohen, J. D. (2003). Errors in reward prediction are reflected in the event-related brain potential. NeuroReport, 14, 2481-2484.
    Hurlemann, R., Patin, A., Onur, O. A., Cohen, M. X., Baumgartner, T., Metzler, S., . . . Kendrick, K. M. (2010). Oxytocin enhances amygdala-dependent, socially reinforced learning and emotional empathy in humans. The Journal of Neuroscience, 30, 4999-5007.
    Itagaki, S., & Katayama, J. (2008). Self-relevant criteria determine the evaluation of outcomes induced by others. NeuroReport, 19, 383-387.
    Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263-291.
    Knight, F. H. (1921). Risk, uncertainty, and profit. New York: Sentry Press.
    Kobza, S., Thoma, P., Daum, I., & Bellebaum, C. (2011). The feedback-related negativity is modulated by feedback probability in observational learning. Behavioural Brain Research, 225, 396-404.
    Lamm, C., Porges, E. C., Cacioppo, J. T., & Decety, J. (2008). Perspective taking is associated with specific facial responses during empathy for pain. Brain Research, 1227, 153-161.
    Liljeholm, M., & O Doherty, J. P. (2012). Contributions of the striatum to learning, motivation, and performance: An associative account. Trends in Cognitive Sciences, 16, 467-475.
    Liljeholm, M., Molloy, C. J., & O`Doherty, J. P. (2012). Dissociable brain systems mediate vicarious learning of stimulus–response and action–outcome contingencies. The Journal of Neuroscience, 32, 9878-9886.
    Markman, A. B., & Medin, D. L. (2002). Decision making. In D. L. Medin & H. Pashler (Eds.), Stevens` handbook of experimental psychology: Vol.2. Memory and cognitive process (3 ed., pp. 413-467).
    McClure, S. M., Berns, G. S., & Montague, P. R. (2003). Temporal prediction errors in a passive learning task activate human striatum. Neuron, 38, 339-346.
    Miltner, W. H. R., Braun, C. H., & Coles, M. G. H. (1997). Event-related brain potentials following incorrect feedback in a time-estimation task: Evidence for a “generic” neural system for error detection. Journal of Cognitive Neuroscience, 9, 788-798.
    Miltner, W. H. R., Brauer, J., Hecht, H., Trippe, R., & Coles, M. G. H. (2004). Parallel brain activity for self-generated and observed errors. In M. Ullsperger & M. Falkenstein (Eds.), Errors, conflicts, and the brain : Current opinions on performance monitoring (pp. 124-129). Leipzig: Max Planck Institute for Human Cognitive and Brain Sciences.
    Naqvi, N. H., & Bechara, A. (2006). Skin conductance: A psychophysiological approach to the study of decision making. In C. Senior, T. Russell & M. S. Gazzaniga (Eds.), Methods in mind (pp. 103-122). Cambridge, Mass.: MIT Press.
    Newman-Norlund, R. D., Ganesh, S., Schie, H. T. v., De Bruijn, E. R. A., & Bekkering, H. (2009). Self-identification and empathy modulate error-related brain activity during the observation of penalty shots between friend and foe. Social Cognitive and Affective Neuroscience, 4, 10-22.
    Nicolle, A., Symmonds, M., & Dolan, R. J. (2011). Optimistic biases in observational learning of value. Cognition, 119, 394-402.
    O`Doherty, J. P., Dayan, P., Friston, K., Critchley, H., & Dolan, R. J. (2003). Temporal difference models and reward-related learning in the human brain. Neuron, 38, 329-337.
    O`Doherty, J. P., Dayan, P., Schultz, J., Deichmann, R., Friston, K., & Dolan, R. J. (2004). Dissociable roles of ventral and dorsal striatum in instrumental conditioning. Science, 304, 452-454.
    Oliveira, F. T. P., McDonald, J. J., & Goodman, D. (2007). Performance monitoring in the anterior cingulate is not all error related: Expectancy deviation and the representation of action-outcome associations. Journal of Cognitive Neuroscience, 19, 1994-2004.
    Olsson, A., & Phelps, E. A. (2004). Learned fear of "unseen" faces after pavlovian, observational, and instructed fear. Psychological Science, 15, 822-828.
    Olsson, A., Nearing, K. I., & Phelps, E. A. (2007). Learning fears by observing others: The neural systems of social fear transmission. Social Cognitive and Affective Neuroscience, 2, 3-11.
    Poldrack, R., Clark, J., PareÂ-Blagoev, E., Shohamy, D., Moyano, J. C., Myers, C., & Gluck, M. (2001). Interactive memory systems in the human brain. synthesis, 52, 297-314.
    Quartz, S. R. (2009). Reason, emotion and decision-making: Risk and reward computation with feeling. Trends in Cognitive Sciences, 13, 209-215.
    Rizzolatti, G., & Craighero, L. (2004). The mirror-neuron system. Annual Review of Neuroscience, 27, 169-192.
    Rizzolatti, G., & Sinigaglia, C. (2010). The functional role of the parieto-frontal mirror circuit: Interpretations and misinterpretations. Nature Review Neuroscience, 11, 264-274.
    Salzman, C. D., & Fusi, S. (2010). Emotion, cognition, and mental state representation in amygdala and prefrontal cortex. Annual review of neuroscience, 33, 173.
    Sanfey, A. G., & Chang, L. J. (2008). Multiple systems in decision making. Annals of the New York Academy of Sciences, 1128, 53-62.
    Scheffers, M. K., & Coles, M. G. H. (2000). Performance monitoring in a confusing world: Error-related brain activity, judgments of response accuracy, and types of errors. Journal of Experimental Psychology: Human Perception and Performance; Journal of Experimental Psychology: Human Perception and Performance, 26, 141.
    Schultz, W., Dayan, P., & Montague, P. R. (1997). A neural substrate of prediction and reward. Science, 275, 1593-1599.
    Shamay-Tsoory, S. G., Aharon-Peretz, J., & Perry, D. (2009). Two systems for empathy: A double dissociation between emotional and cognitive empathy in inferior frontal gyrus versus ventromedial prefrontal lesions. Brain, 132, 617-627.
    Shane, M. S., Stevens, M., Harenski, C. L., & Kiehl, K. A. (2008). Neural correlates of the processing of another`s mistakes: A possible underpinning for social and observational learning. NeuroImage, 42, 450-459.
    Shohamy, D., Myers, C. E., Grossman, S., Sage, J., Gluck, M. A., & Poldrack, R. A. (2004). Cortico‐striatal contributions to feedback‐based learning: Converging data from neuroimaging and neuropsychology. Brain, 127, 851-859.
    Singer, T., Seymour, B., O`Doherty, J., Kaube, H., Dolan, R. J., & Frith, C. D. (2004). Empathy for pain involves the affective but not sensory components of pain. Science, 303, 1157-1162.
    Sutton, R. S., & Barto, A. G. (1998). Reinforcement learning. Cambridge, MA: MIT Press.
    Suzuki, S., Harasawa, N., Ueno, K., Gardner, Justin L., Ichinohe, N., Haruno, M., . . . Nakahara, H. (2012). Learning to simulate others` decisions. Neuron, 74, 1125-1137.
    Torriero, S., Oliveri, M., Koch, G., Caltagirone, C., & Petrosini, L. (2007). The what and how of observational learning. Journal of Cognitive Neuroscience, 19, 1656-1663.
    Tricomi, E. M., Delgado, M. R., & Fiez, J. A. (2004). Modulation of caudate activity by action contingency. Neuron, 41, 281-292.
    Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5, 297-323.
    van Schie, H. T., Mars, R. B., Coles, M. G. H., & Bekkering, H. (2004). Modulation of activity in medial frontal and motor cortices during error observation. Nature Neuroscience, 7, 549-554.
    Von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton, NJ: Princeton University Press.
    Walsh, M. M., & Anderson, J. R. (2011). Modulation of the feedback-related negativity by instruction and experience. Proceedings of the National Academy of Sciences, 108, 19048-19053.
    Walsh, M. M., & Anderson, J. R. (2012). Learning from experience: Event-related potential correlates of reward processing, neural adaptation, and behavioral choice. Neuroscience & Biobehavioral Reviews, 36, 1870-1884.
    Walter, H. (2012). Social cognitive neuroscience of empathy: Concepts, circuits, and genes. Emotion Review, 4, 9-17.
    Weber, E. U., & Johnson, E. J. (2009a). Decisions under uncertainty: Psychological, economic, and neuroeconomic explanations of risk preference. In P. W. Glimcher, C. F. Camerer, E. Fehr & R. A. Poldrack (Eds.), Neuroeconomics: Decision making and the brain (pp. 127-144): Academic Press.
    Weber, E. U., & Johnson, E. J. (2009b). Mindful judgment and decision making. Annual Review of Psychology, 60, 53-85.
    Wicker, B., Keysers, C., Plailly, J., Royet, J.-P., Gallese, V., & Rizzolatti, G. (2003). Both of us disgusted in my insula: The common neural basis of seeing and feeling disgust. Neuron, 40, 655-664.
    Yacubian, J., Gläscher, J., Schroeder, K., Sommer, T., Braus, D. F., & Büchel, C. (2006). Dissociable systems for gain- and loss-related value predictions and errors of prediction in the human brain. The Journal of Neuroscience, 26, 9530-9537.
    Yechiam, E., Busemeyer, J. R., Stout, J. C., & Bechara, A. (2005). Using cognitive models to map relations between neuropsychological disorders and human decision-making deficits. Psychological Science, 16, 973-978.
    Yeung, N., & Sanfey, A. G. (2004). Independent coding of reward magnitude and valence in the human brain. The Journal of Neuroscience, 24, 6258-6264.
    Yu, R., & Zhou, X. (2006). Brain responses to outcomes of one`s own and other`s performance in a gambling task. NeuroReport, 17, 1747-1751.
    Description: 碩士
    國立政治大學
    心理學研究所
    99752001
    101
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0099752001
    Data Type: thesis
    Appears in Collections:[Department of Psychology] Theses

    Files in This Item:

    File SizeFormat
    200101.pdf974KbAdobe PDF21918View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback