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    Title: 軀體標記假說中的風險因素之探討
    Risk factor in somatic marker hypothesis
    Authors: 仲惠瓘
    Chung, Hui Kuan
    Contributors: 顏乃欣
    Yen, Nai Shing
    仲惠瓘
    Chung, Hui Kuan
    Keywords: 軀體標記假說
    愛荷華賭博作業
    膚電反應
    風險程度
    回饋關聯負波
    N170
    Somatic Marker Hypothesis
    Iowa Gambling Task
    Feedback Related Negativity
    Skin Conductance Response
    Risk Level
    N170
    Date: 2010
    Issue Date: 2013-09-03 13:27:12 (UTC+8)
    Abstract: Damasio(1994)提出軀體標記假說（Somatic Marker Hypothesis）來解釋情緒如何影響行為決策，認為人們在決策前，與過去的情緒經驗關聯的生理反應會再現，幫助人們做出較好的決策判斷。並利用愛荷華賭博作業（Iowa Gambling Task）來模擬日常生活決策情境，並同時紀錄膚電反應(Skin conductance respons)，量測受試者決策前的預期膚電反應（Anticipatory SCR）和結果呈現後的回饋膚電反應(Feedback SCR)，加以佐證其神經生理機制。本研究將從三個方向進一步驗證其假說，分別是風險因素、生理證據和個別差異。在愛荷華賭博作業中，期望值負的牌也是高風險程度的牌，使結果無法清楚解釋是期望值或者風險程度造成的影響。而過去雖然有許多研究也使用膚電反應當做生理指標，但有許多相異的研究結果，並且較少研究利用事件關聯電位瞭解其中樞歷程。再者，過去相關研究發現個別差異的存在，但是缺乏一致的解釋。因此，本研究以修改版愛荷華賭博作業，控制期望值皆為零的狀況下，操弄風險程度，並且利用膚電反應和事件關聯電位當作周邊和和中樞的生理反應指標，探討受試者在單純風險情境，是否也會受到情緒軀體標記影響風險行為偏好，以及各項生理指標和風險行為偏好間的關聯，並瞭解不同風險偏好的受試者生理指標是否有所差異。結果發現，從行為上顯示有風險追逐和風險趨避兩組受試者，不同風險程度的牌損失回饋對受試者的歷程影響也不一樣，額葉的腦部回饋相關負波(Feedback-related Negativity，FRN)結果顯示，風險追逐的受試者對高低風險損失時的FRN沒有差異，風險趨避的受試者看到低風險損失時的FRN大於看到高風險損失時的FRN。此外，看到高風險酬賞比起低風險酬有較大回饋膚電反應的受試者，和看到高風險損失比起低風險損失有較小回饋膚電反應的受試者，接受高風險牌的比率也較高，其它生理變項對風險行為偏好沒有顯著的預測力。並且預期膚電反應並非過去研究認為單純扮演警訊或者誘因，而有更複雜的機制存在，受試者在接受非偏好的牌和拒絕偏好的牌前有較大的預期膚電反應。預期階段N170的結果顯示，受試者看到刺激之後會拒絕的N170會大於之後會接受的N170，顯示接受或拒絕兩種不同情境時受試者對刺激的處理歷程亦相異。
    Somatic Marker Hypothesis was proposed to explain the influence of emotion on decision making. To examine this hypothesis, Damasio and his colleagues designed the Iowa Gambling Task (IGT) and found that the “anticipatory skin conductance responses (SCR)”, i.e. somatic markers, was elevated before selecting from bad decks to serve as alarms and it warned participants not to select “bad deck” which was negative expected value. However, there are three unsolved problem in these IGT researches: the risk factor, inconsistent physiological evidences, and individual differences. In the original IGT, the bad decks are also more risky and that confounds the interpretations of participants’ choice behaviors and related physiological evidences. There are inconsistent evidences of how the anticipatory SCR and feedback SCR related with choice behaviors. Moreover, there are little event-related potential IGT studies. To solve these issues, the primary aim of the present study is to clarify whether decision making is influenced by risk level even when all options have the same expected value. A modified IGT with high risk deck and low risk deck was used and the expected values of two decks were all zero. Moreover, the procedure was different from original IGT. Participants saw a deck with mark first and then decided to accept or reject this deck. Thus, the role of anticipatory SCR could be clarified more clearly. In addition to SCR, ERP was also recorded for further physiological evidences. To elaborately clarify individual differences of choice behavior and physiological evidences, participants would group to risk-seeking (i.e., accepting more high risk deck and rejecting more low risk deck) and risk-aversion (i.e., accepting more low risk deck and rejecting more high risk deck) according their choice behaviors. The result revealed that the participant who accepted more high risk deck, their reward SCR was higher from high risk deck than from low risk decks, and induced lower punishment SCR from high risk deck than from low risk decks. Moreover, the anticipatory SCR was higher both before they decided to reject the liked deck and before they decided to accept the disliked deck. The results of feedback-related negativity (FRN) from ERP data in frontal region showed that the magnitude of FRN was larger under the conflict punishment (the punishment from low risk decks) condition for risk-aversion participants. The results of N170 from ERP data showed that the magnitude of N170 was larger under the reject condition. These results suggest that the SMH could be explained not only with expected value but also with risk preference. In conclusion, the interpretation of anticipatory SCR by previous study was not completed, and it reflected not merely the negative feeling or positive feeling. This strong anticipatory emotion affects people to change the routine behavior about their risk preference, and there exist individual differences of choice behavior and physiological evidences.
    Reference: Baker, T. E., & Holroyd, C. B. (2009). Which way do I go? Neural activation in response to feedback and spatial processing in a virtual T-maze. Cerebral Cortex, 19, 1708-1722.
    Bechara, A. (2004). The role of emotion in decision-making: Evidence from neurological patients with orbitofrontal damage. Brain and Cognition, 55, 30-40.
    Bechara, A., & Damasio, A. R. (2005). The somatic marker hypothesis: a neural theory of economic decision. Games and Economic Behavior, 52, 336-372.
    Bechara, A., Damasio, H., Damasio, A. R., & Lee, G. P. (1999). Different contributions of the human amygdala and ventromedial prefrontal cortex to decision-making. The Journal of Neuroscience, 19, 5473-5481.
    Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (1997). Deciding advantageously before knowing the advantageous strategy. Science, 275, 1293-1295.
    Bechara, A., Dolan, S., & Hindes, A. (2002). Decision-making and addiction (part II): myopia for the future or hypersensitivity to reward? Neuropsychologia, 40, 1690-1705.
    Bechara, A., Tranel, D., Damasio, H., & Damasio, A. R. (1996). Failure to respond autonomically to anticipated future outcomes following damage to prefrontal cortex. Cerebral Cortex, 6, 215-225.
    Bianchin, M., & Angrilli A. (2011). Decision preceding negativity in the Iowa gambling task: an ERP study. Brain and Cognition, 75(3), 273-280.
    Bolla, K. I., Eldreth, D. A., Matochik, J.A., & Cadet, J. L. (2005). Neural substrates of faulty decision-making in abstinent marijuana users. NeuroImage, 26, 480-492.
    Bolla, K. I., Eldreth, D. A., London, E. D., Kiehl, K. A., Mouratidis, M., Contoreggi, C., & Ernst, M. (2003). Orbitofrontal cortex dysfunction in abstinent cocaine abusers performing a decision-making task. NeuroImage, 19, 1085-1094.
    Bowman, C. H., & Turnbull, O. H. (2003). Real versus facsimile reinforcers on the Iowa Gambling Task. Brain and Cognition, 53, 207-210.
    Buelow, M. T., & Suhr, J. A. (2009). Construct validity of the Iowa gambling task. Neuropsychology Review, 19, 102.
    Busemeyer, J. R., & Stout, J. C. (2002). A contribution of cognitive decision models to clinical assessment: Decomposing performance on the Bechara gambling task. Psychological Assessment, 14, 253-262.
    Colombetti, G. (2008). The Somatic Marker Hypotheses, and What the Iowa Gambling Task Does and Does not Show. British Journal for the Philosophy of Science, 59, 51-71.
    Crone, E. A., Somsen, R. J. M., Beek, B. V., & Van Der Molena, M. W. (2004). Heart rate and skin conductance analysis of antecendents and consequences of decision making. Psychophysiology, 41, 531-540.
    d`Acremont, M., Lu, Z.-L., Li, X., Van der Linden, M., & Bechara, A. (2009). Neural correlates of risk prediction error during reinforcement learning in humans. NeuroImage, 47, 1929-1939.
    Damasio, A. (1994). Descartes` error: emotion, reason, and the human brain. New York: G. P.: Putnam`s Sons.
    Damasio, A. R., Tranel, D., & Damasio, H. (1991). Somatic markers and the guidance of behavior: Theory and preliminary testing. In H. S. Levin, H. M. Eisenberg, & A. L. Bemton (Eds.), Frontal lobe function and dysfunction (pp.217-229). NY: Oxford University Press.
    Davidson, R. J., Jackson, D. C., & Kalin, N. H. (2000). Emotion, plasticity, context, and regulation: perspectives from affective neuroscience. Psychological Bulletin, 126, 890-909.
    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). NY: Cambridge University Press.
    de Bruijn, E. R. A., Hulstijn, W., Verkes, R. J., Ruigt, G. S. F., & Sabbe, B. G. C. (2004). Drug-induced stimulation and suppression of action monitoring in healthy volunteers. Psychopharmacology, 177, 151-160.
    Dunn, B. D., Dalgleish, T., & Lawrence, A. D. (2006). The somatic marker hypothesis: A critical evaluation. Neuroscience & Biobehavioral Reviews, 30, 239-271.
    Ekman, P., Levenson, R., & Friesen, W. (1983). Autonomic nervous system activity distinguishes among emotions. Science, 221, 1208-1210.
    Ernst, M., Bolla, K., Mouratidis, M., Contoreggi, C., Matochik, J. A., Kurian, V., London, E. D. (2002). Decision-making in a risk-taking task. Neuropsychopharmacology, 26, 682-691.
    Euser, A., van Meel, C., Snelleman, M., & Franken, I. (2011). Acute effects of alcohol on feedback processing and outcome evaluation during risky decision-making: an ERP study. Psychopharmacology, 1-15.
    Evans, J. S. B. T. (2008). Dual-processing accounts of reasoning, judgment, and social cognition. Annual Review of Psychology, 59, 255-278.
    Fein, G. & Chang, M. (2007). Smaller feedback ERN amplitudes during the BART are associated with a greater family history density of alcohol problems in treatment-naïve alcoholics. Drug and Alcohol Dependence, 92, 141-148.
    Franken, I. H. A., Georgieva, I., & Muris, P. (2006). The rich get richer and the poor get poorer: On risk aversion in behavioral decision-making. Judgment and Decision Making, 1, 153-158.
    Fukui, H., Murai, T., Fukuyama, H., Hayashi, T., & Hanakawa, T. (2005). Functional activity related to risk anticipation during performance of the Iowa gambling task. NeuroImage, 24, 253-259.
    Gehring, W. J., & Willoughby, A. R. (2002). The Medial Frontal Cortex and the Rapid Processing of Monetary Gains and Losses. Science, 295, 2279-2282.
    Gehring, W. J., Goss, B., Coles, M. G. H., Meyer, D. E. & Donchin, E. (1993). A neural system for error detection and compensation. Psychological Science, 4, 385-390.
    Gemba, H., Sasaki, K., & Brooks, V. B. (1986). Error potentials in limbic cortex (anterior cingulate area 24) of monkeys during motor learning. Neuroscience Letters, 70, 223-227.
    Gibson, J., Krigolson, O. E., & Holroyd, C. B. (2006). Sensitivity of the feedback errorrelated negativity to reward probability. Psychophysiology, 43, S41.
    Glicksohn, J., & Zilberman, N. (2010). Gambling on individual differences in decision making. Personality and Individual Differences, 48, 557-562.
    Gu, R., Ge, Yue, Jiang, Y., & Luo, Y. (2010) Anxiety and outcome evaluation: the good, the bad and the ambiguous. Biological Psychology, 85, 200-206.
    Gutnik, L. A., Hakimzada, A. F., Yoskowitz, N. A., & Patel, V. L. (2006). The role of emotion in decision-making: A cognitive neuroeconomic approach towards understanding sexual risk behavior. Journal of Biomedical Informatics, 39, 720-736.
    Hajcak, G., Holroyd, C. B., Moser, J. S., Simons, R. F. (2005). Brain potentials associated with expected and unexpected good and bad outcomes. Psychophysiology, 42, 161-170.
    Hamm, A. O., Schupp, H. T., & Weike, A. I. (2003). Motivational organization of emotions: Autonomic changes, cortical responses, and reflex modulation. In R. J. Davidson, K. R. Scherer, & H. H. Goldsmith (Eds.), Handbook of affective sciences (pp.187-211). NY: Oxford Press.
    Hochman, G., & Yechiam, E. (2011). Loss aversion in the eye and in the heart: The autonomic nervous system`s responses to losses. Journal of Behavioral Decision Making, 24, 140-156.
    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., Larsen, J. T., & Cohen, J. D. (2004). Context dependence of the event-related brain potential associated with reward and punishment. Psychophysiology, 41, 245-253.
    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.
    Hooper, C. J., Luciana, M., Wahlstrom, D., Conklin, H. M., & Yarger, R. S. (2008). Personality correlates of the Iowa Gambling Task performance in healthy adolescents. Personality and Individual Differences, 44, 598-609.
    James, W. (1894). The physical basis of emotion. Psychological Review, 1, 516-529.
    Jenkinson, P. M., Baker, S. R., Edelstyn, N. M. J., & Ellis, S. J. (2008). Does autonomic arousal distinguish good and bad decisions? Healthy individuals??skin conductance reactivity during the Iowa Gambling Task. Journal of Psychophysiology, 22, 141-149.
    Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological Review, 80, 237-251.
    Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263-291.
    Knutson, B., & Greer, S. M. (2008). Anticipatory affect: Neural correlates and consequences for choice. Philosophical Transactions of the Royal Society B: Biological Sciences, 363, 3771-3786.
    Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (1990). Emotion, attention, and the startle reflex. Psychological Review, 97, 377-395.
    Lawrence, N. S., Jollant, F., O`Daly, O., Zelaya, F., & Phillips, M. L. (2008). Distinct roles of prefrontal cortical subregions in the Iowa gambling task. Cerebal Cortex, 19, 1134-1143.
    LeDoux, J. (1996). The Emotional Brain: The Mysterious Underpinnings of Emotional Life. New York: Simon and Schuster.
    Lhermitte, F., Pillon, B., & Serdaru, M. (1986). Human autonomy and the frontal lobes. Part I: Imitation and utilization behavior: A neuropsychological study of 75 patients. Annals of Neurology, 19, 326-334.
    Li, X., Lu, Z. L., D`Argembeau, A., Ng, M., & Bechara, A. (2010). The Iowa gambling task in fMRI images. Human Brain Mapping, 31, 410-423.
    Lin, C.-H., Chiu, Y.-C., Cheng, C.-M., & Hsieh, J.-C. (2008). Brain maps of Iowa gambling task. BMC Neuroscience, 9, 72.
    Locke, J., & Yolton, J. W. (1989). Some Thoughts Concerning Education (3rd ed.). Bristol, England: Oxford University Press.
    Loewenstein, G. F., Weber, E. U., Hsee, C. K., & Welch, N. (2001). Risk as feelings. Psychological Bulletin, 127, 267-286.
    Luck, S. J. (2005). An introduction to the event-related potential and their neural origins. An introduction to the event-related potential technique.(1st, pp. 1-49). MA: MIT Press.
    Maia, T., & McClelland, J. (2004). A reexamination of the evidence for the somatic marker hypothesis: what participants really know in the Iowa gambling task. Proceedings of the National Academy of Sciences USA, 101, 16075 - 16080.
    Martin, L. E., & Potts, G. F. (2009). Impulsivity in decision-making: an event-related potential investigation. Personality and Individual Difference, 46, 303-308.
    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.
    Miu, A. C., R. M. Heilman, Houser, D. (2008). Anxiety impairs decision-making: Psychophysiological evidence from an Iowa Gambling Task. Biological Psychology, 77, 353-358.
    Montalan, B., Caharel, S., Personnaz, B., Le Dantec, C., Germain, R., Bernard, C., Lalonde, R., & Rebaï, M. (2008). Sensitivity of N170 and late positive components to social categorization and emotional valence. Brain Research, 1233, 120-128.
    Morris, J. S., Öhman, A., & Dolan, R. J. (1999). A subcortical pathway to the right amygdala mediating “unseen” fear. Proceedings of the National Academy of Sciences of the United States of America, 96, 1680-1685.
    Münte, T. F., Heldmann, M., Hinrichs, H., Marco-Pallares, J., Krämer, U. M., Sturm, V., et al. (2008). Nucleus accumbens is involved in human action monitoring: evidence from invasive electrophysiological recordings. Frontiers in Human Neuroscience, 1, Article 11.
    Nieuwenhuis, S., Holroyd, C. B., Mol, N., & Coles, M. G. H. (2004). Reinforcement-related brain potentials from medial frontal cortex: origins and functional significance. Neuroscience & Biobehavioral Reviews, 28, 441-448.
    Niki, H., & Watanabe, M. (1979). Prefrontal and cingulate unit activity during timing behavior in the monkey. Brain Research, 171, 213-224.
    Northoff, G., Grimm, S., Boeker, H., Schmidt, C., Bermpohl, F., Heinzel, A., et al. (2006). Affective judgment and beneficial decision making: ventromedial prefrontal activity correlates with performance in the Iowa Gambling Task. Human Brain Mapping, 27, 572-587.
    Overman, W., Graham, L., Redmond, A., Eubank, R., Boettcher, L., Samplawski, O., & Katherine, W. (2006). Contemplation of moral dilemmas eliminates sex differences on the Iowa gambling task. Behavioral Neuroscience, 120, 817-825.
    Oya, H., Adolphs, R., Kawasaki, H., Bechara, A., Damasio, A., & Howard, M. A., III. (2005). Electrophysiological correlates of reward prediction error recorded in the human prefrontal cortex. 102, 8351-8356.
    Palomba, D., Angrilli, A., & Mini, A. (1997). Visual evoked potentials, heart rate responses, and memory to emotional pictorial stimuli. International Journal of psychophysiology, 27, 55-67.
    Polezzi, D., Sartori, G., Rumiati, R., Vidotto, G., & Daum, I. (2010) Brain correlates of risky decision-making. Neuroimage, 49, 1886-1894.
    Rolls, E. T. (2000). The orbitofrontal cortex and reward. Cerebral Cortex, 10, 284-294.
    Scherer, K. R. (2005). What are emotions? And how can they be measured? Social Science Information, 44, 695-729.
    Schultz, W., Dayan, P., & Montague, P. R. (1997). A neural substrate of prediction and reward. Science, 275, 1593–1599.
    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, 257-261.
    Sevy, S., Burdick, K. E., Visweswaraiah, H., Abdelmessih, S., Lukin, M., Yechiam, E., & Bechara A. (2007). Iowa gambling task in schizophrenia: a review and new data in patients with schizophrenia and co-occurring cannabis use disorders. Schizophrenia Research, 92, 74-84.
    Slovic, P., Finucane, M. L., Peters, E., & MacGregor, D. G. (2007). The affect heuristic. European Journal of Operational Research, 177, 1333-1352.
    Stocco, A., & Fum, D. (2008). Implicit emotional biases in decision making: The case of the Iowa Gambling Task. Brain and Cognition, 66, 253-259.
    Suzuki, A., Hirota, A., Takasawa, N., & Shigemasu, K. (2003). Application of the somatic marker hypothesis to individual differences in decision making. Biological Psychology, 65, 81-88.
    Tanabe, J., Thompson, L., Claus, E., Dalwani, E., Hutchison, K., & Banich, M. T. (2007). Prefrontal cortex activity is reduced in gambling and nongambling substance users during decision-making. Human Brain Mapping, 28, 1276-1286.
    Tomb, I., Hauser, M., Deldin, P., & Caramazza, A. (2002). Do somatic markers mediate decisions on the gambling task? Nature Neuroscience, 5, 1103.
    Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211, 453-458.
    Wagar, B. M., & Thagard, P. (2004). Spiking phineas gage: A neurocomputational theory of cognitive-affective integration in decision making. Psychological Review, 111, 67-79.
    Weber, E. U., Shafir, S., & Blais, A.-R. (2004). Predicting risk sensitivity in humans and lower animals: risk as variance or coefficient of variation. Psychological Review, 111, 430-445.
    Weller, J. A., Levin, I. P., Shiv, B., & Bechara, A. (2007). Neural correlates of adaptive decision making for risky gains and losses. Psychological Science, 18, 958-964.
    Wu, Y., & Zhou, X. (2009). The P300 and reward valence, magnitude, and expectancy in outcome evaluation. Brain Research, 1286, 114–122.
    Yang, J. and Q. Zhang (2011). Electrophysiological correlates of decision-making in high-risk versus low-risk conditions of a gambling game. Psychophysiology.
    Yen, N. S., Kao, C. H., Chou, I. C., & Chung, H. K. (2009). The effects of expected value and risk level on behavioral and electrophysiological data in a modified IGT. Poster presented at the 16th annual meeting of the Cognitive Neuroscience Society, San Francisco, CA, U.S.A.
    Young, L., Bechara, A., Tranel, D., Damasio, H., Hauser, M., & Damasio, A. (2010). Damage to ventromedial prefrontal cortex impairs judgment of harmful intent. Neuron, 65, 845-851.
    Yu, R., & Zhou, X. (2008). To bet or not to bet? The error negativity or error-related negativity associated with risk-taking choices. Journal of Cognitive Neuroscience, 21, 684-696.
    Zani, A., & Proverbio, A. M. (2003). The cognitive electrophysiology of mind and brain. San Diego: Academic Press.
    Zirnheld, P. J., Carroll, C. A., Kieffaber, P. D., O`Donnell, B. F., Shekhar, A., & Hetrick, W. P. (2004). Haloperidol impairs learning and error-related negativity in humans. Journal of Cognitive Neuroscience, 16, 1098-1112.
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