Toward understanding the role of emotion played in cognitive processing, an emotional model has been proposed to quantify the computation involved in assessing the disparity between the expected and the actual outcomes. This study provides the experimental evidence to validate the above emotional model. In this model, emotion serves as an internal feedback to assess the disparity between the internal predicted outcomes and the actual (external) outcomes in reality. It predicts that emotion provides a feedback to reduce the discrepancy between the expected (subjective) reality and actual (objective) reality. The hypothesis for this model is that the intensity of emotional response is proportional to the disparity between the expected outcome and the actual outcome (i.e., gain/loss magnitude). Happiness is an emotional feedback that indicates the congruency between the predicted and actual outcomes. In order to validate this theoretical model of emotion, the classical Ultimatum Game (UG) is used as an experimental paradigm to elicit self-generated (endogenous) emotions in response to a monetary offer, so that the emotional responses with respect to the perceived monetary gain/loss can be assessed by the stimulus-response function. The results showed that the self-reported happiness intensity is directly proportional to the magnitude of the desirable monetary gain. An empirically derived emotion stimulus-response function is shown to quantify the specific emotional biases graphically by the emotional-disparity graph. The results validated the hypothesis that the intensity of self-reported happy emotion is directly proportional to the monetary gain. The analysis also showed that the happy emotional sensitivity is also changed by the perception of fairness (whether the offer is fair or unfair), which can be represented graphically by the emotional-disparity graph
Published in | Psychology and Behavioral Sciences (Volume 3, Issue 2) |
DOI | 10.11648/j.pbs.20140302.15 |
Page(s) | 60-67 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2014. Published by Science Publishing Group |
Emotional Model, Happy, Fairness, Gain, Ultimatum Game, Decision Making, Error Minimization
[1] | D. Tam, "EMOTION-I model: A biologically-based theoretical framework for deriving emotional context of sensation in autonomous control systems," Open Cybern Sys J, vol. 1, pp. 28-46, 2007. |
[2] | D. Tam, "EMOTION-II model: A theoretical framework for happy emotion as a self-assessment measure indicating the degree-of-fit (congruency) between the expectancy in subjective and objective realities in autonomous control systems," Open Cybern Sys J, vol. 1, pp. 47-60, 2007. |
[3] | D. N. Tam, "Computation in emotional processing: quantitative confirmation of proportionality hypothesis for angry unhappy emotional intensity to perceived loss," Cognitive Computation, vol. 3, pp. 394-415, 18 July 2011 2011. |
[4] | D. Tam, "A theoretical model of emotion processing for optimizing the cost function of discrepancy errors between wants and gets," BMC Neuroscience, vol. 10, p. P11, Jul 13 2009. |
[5] | F. Schneider, R. C. Gur, R. E. Gur, and L. R. Muenz, "Standardized mood induction with happy and sad facial expres-sions," Psychiatry Res, vol. 51, pp. 19-31, Jan 1994. |
[6] | R. J. Davidson, D. Mednick, E. Moss, C. Saron, and C. E. Schaffer, "Ratings of emotion in faces are influenced by the visual field to which stimuli are presented," Brain Cogn, vol. 6, pp. 403-11, Oct 1987. |
[7] | B. Derntl, E. M. Seidel, F. Schneider, and U. Habel, "How specific are emotional deficits? A comparison of empathic abilities in schizophrenia, bipolar and depressed patients," Schizophr Res, vol. 142, pp. 58-64, Dec 2012. |
[8] | J. Jaeger, J. C. Borod, and E. Peselow, "Facial expression of positive and negative emotions in patients with unipolar depression," J Affect Disord, vol. 11, pp. 43-50, Jul-Aug 1986. |
[9] | S. Srivastava, H. O. Sharma, and M. K. Mandal, "Mood induction with facial expressions of emotion in patients with generalized anxiety disorder," Depress Anxiety, vol. 18, pp. 144-8, 2003. |
[10] | V. I. Muller, T. S. Kellermann, S. C. Seligman, B. I. Turetsky, and S. B. Eickhoff, "Modulation of affective face processing deficits in schizophrenia by congruent emotional sounds," Soc Cogn Affect Neurosci, Oct 14 2012. |
[11] | B. Lorey, M. Kaletsch, S. Pilgramm, M. Bischoff, S. Kindermann, I. Sauerbier, et al., "Confidence in emotion perception in point-light displays varies with the ability to perceive own emotions," PLoS One, vol. 7, p. e42169, 2012. |
[12] | P. D. Parker, K. M. Prkachin, and G. C. Prkachin, "Processing of facial expressions of negative emotion in alexithymia: the influence of temporal constraint," J Pers, vol. 73, pp. 1087-107, Aug 2005. |
[13] | I. Laeger, C. Dobel, U. Dannlowski, H. Kugel, D. Grotegerd, J. Kissler, et al., "Amygdala responsiveness to emotional words is modulated by subclinical anxiety and depression," Behav Brain Res, vol. 233, pp. 508-16, Aug 1 2012. |
[14] | M. J. van Tol, L. R. Demenescu, N. J. van der Wee, R. Kortekaas, M. A. N. Marjan, J. A. Boer, et al., "Functional magnetic resonance imaging correlates of emotional word encoding and recognition in depression and anxiety disorders," Biol Psychiatry, vol. 71, pp. 593-602, Apr 1 2012. |
[15] | J. von Neumann, O. Morgenstern, and A. Rubinstein, Theory of games and economic behavior. Princeton, NJ: Princeton University Press, 1953. |
[16] | J. H. Kagel and A. E. Roth, The handbook of experimental economics: PRINCETON University Press, 1995. |
[17] | D. A. Braun, P. A. Ortega, and D. M. Wolpert, "Nash equilibria in multi-agent motor interactions," PLoS Comput Biol, vol. 5, p. e1000468, Aug 2009. |
[18] | K. Sigmund, C. Hauert, and M. A. Nowak, "Reward and punishment," Proc Natl Acad Sci U S A, vol. 98, pp. 10757-10762, Sep 11 2001. |
[19] | A. Bechara, "The role of emotion in decision-making: evidence from neurological patients with orbitofrontal damage," Brain Cogn, vol. 55, pp. 30-40, Jun 2004. |
[20] | C. Civai, C. Corradi-Dell'Acqua, M. Gamer, and R. I. Rumiati, "Are irrational reactions to unfairness truly emotionally-driven? Dissociated behavioural and emotional responses in the Ultimatum Game task," Cognition, vol. 114, pp. 89-95, Jan 2010. |
[21] | J. D. Greene, L. E. Nystrom, A. D. Engell, J. M. Darley, and J. D. Cohen, "The neural bases of cognitive conflict and control in moral judgment," Neuron, vol. 44, pp. 389-400, Oct 14 2004. |
[22] | K. M. Harle and A. G. Sanfey, "Incidental sadness biases social economic decisions in the Ultimatum Game," Emotion, vol. 7, pp. 876-881, Nov 2007. |
[23] | S. M. McClure, D. I. Laibson, G. Loewenstein, and J. D. Cohen, "Separate neural systems value immediate and delayed monetary rewards," Science, vol. 306, pp. 503-7, Oct 15 2004. |
[24] | E. K. Miller and J. D. Cohen, "An integrative theory of prefrontal cortex function," Annu Rev Neurosci, vol. 24, pp. 167-202, 2001. |
[25] | G. J. Quirk and J. S. Beer, "Prefrontal involvement in the regulation of emotion: convergence of rat and human studies," Curr Opin Neurobiol, vol. 16, pp. 723-7, Dec 2006. |
[26] | E. T. Rolls, "Brain mechanisms of emotion and decision-making," Int Congress Series, vol. 1291, pp. 3-13, 2006. |
[27] | A. G. Sanfey, G. Loewenstein, S. M. McClure, and J. D. Cohen, "Neuroeconomics: cross-currents in research on decision-making," Trends Cogn Sci, vol. 10, pp. 108-16, Mar 2006. |
[28] | A. G. Sanfey, J. K. Rilling, J. A. Aronson, L. E. Nystrom, and J. D. Cohen, "The neural basis of economic decision-making in the Ultimatum Game," Science, vol. 300, pp. 1755-1758, Jun 13 2003. |
[29] | J. K. Rilling, A. G. Sanfey, J. A. Aronson, L. E. Nystrom, and J. D. Cohen, "The neural correlates of theory of mind within interpersonal interactions," Neuroimage, vol. 22, pp. 1694-703, Aug 2004. |
[30] | P. Smith and A. Silberberg, "Rational maximizing by humans (Homo sapiens) in an ultimatum game," Anim Cogn, vol. 13, pp. 671-7, Jul 2010. |
[31] | T. Yamagishi, Y. Horita, H. Takagishi, M. Shinada, S. Tanida, and K. S. Cook, "The private rejection of unfair offers and emotional commitment," Proc Natl Acad Sci U S A, vol. 106, pp. 11520-11523, Jul 14 2009. |
[32] | S. S. Komorita, "Attitude content, intensity, and the neutral point on a Likert scale," J Soc Psychol, vol. 61, pp. 327-34, Dec 1963. |
[33] | T. C. Burnham, "High-testosterone men reject low ultimatum game offers," Proc Biol Sci, vol. 274, pp. 2327-30, Sep 22 2007. |
[34] | C. Eisenegger, M. Naef, R. Snozzi, M. Heinrichs, and E. Fehr, "Prejudice and truth about the effect of testosterone on human bargaining behaviour," Nature, vol. 463, pp. 356-9, Jan 21 2010. |
[35] | B. Güroğlu, W. van den Bos, and E. A. Crone, "Fairness considerations: increasing understanding of intentionality during adolescence," J Exp Child Psychol, vol. 104, pp. 398-409, Dec 2009. |
[36] | B. Güroğlu, W. van den Bos, S. A. Rombouts, and E. A. Crone, "Unfair? It depends: neural correlates of fairness in social context," Soc Cogn Affect Neurosci, vol. 5, pp. 414-423, Dec 2010. |
[37] | M. Koenigs and D. Tranel, "Irrational economic decision-making after ventromedial prefrontal damage: evidence from the Ultimatum Game," J Neurosci, vol. 27, pp. 951-6, Jan 24 2007. |
[38] | M. A. Nowak, K. M. Page, and K. Sigmund, "Fairness versus reason in the ultimatum game," Science, vol. 289, pp. 1773-1775, Sep 8 2000. |
[39] | M. M. Pillutla and J. K. Murnighan, "Unfairness, anger, and spite: Emo-tional rejections of ultimatum offers," Organizational Behavior and Human Decision Processes, vol. 68, pp. 208-224, 12// 1996. |
[40] | G. Tabibnia, A. B. Satpute, and M. D. Lieberman, "The sunny side of fairness: preference for fairness activates reward circuitry (and disregarding unfairness activates self-control circuitry)," Psychol Sci, vol. 19, pp. 339-347, Apr 2008. |
[41] | D. N. Tam, "Computation in emotional processing: quantitative confirmation of proportionality hypothesis for angry unhappy emotional intensity to perceived loss," Cogn Comput, vol. 3, pp. 394-415, 2011/06/01 2011. |
[42] | N. D. Tam, "Assessing fairness bias using a relativistic fairness-equity model: theoretical derivation," submitted. |
[43] | M. van’t Wout , R. S. Kahn, A. G. Sanfey, and A. Aleman, "Affective state and decision-making in the Ultimatum Game," Exp Brain Res, vol. 169, pp. 564-8, Mar 2006. |
[44] | P. J. Zak, R. Kurzban, S. Ahmadi, R. S. Swerdloff, J. Park, L. Efremidze, et al., "Testosterone administration decreases generosity in the ultimatum game," PLoS One, vol. 4, p. e8330, 2009. |
[45] | P. J. Zak, A. A. Stanton, and S. Ahmadi, "Oxytocin increases generosity in humans," PLoS One, vol. 2, p. e1128, 2007. |
[46] | D. Tam, "Variables governing emotion and decision-making: human objectivity underlying its subjective perception," BMC Neuroscience, vol. 11, p. P96, Jul 20 2010. |
[47] | E. Xiao and D. Houser, "Emotion expression in human punishment behavior," Proc Natl Acad Sci U S A, vol. 102, pp. 7398-401, May 17 2005. |
[48] | D. N. Tam, "Contributing factors in judgment of fairness by monetary value," in BMC Neuroscience, 2011, p. P329. |
[49] | D. N. Tam, "Quantification of fairness bias by a Fairness-Equity Model," BMC Neuroscience, vol. 12, p. P327, 2011. |
[50] | E. C. Seip, W. W. van Dijk, and M. Rotteveel, "On hotheads and Dirty Harries: the primacy of anger in altruistic punishment," Ann N Y Acad Sci, vol. 1167, pp. 190-196, Jun 2009. |
[51] | E. A. Murray and A. Izquierdo, "Orbitofrontal cortex and amygdala contributions to affect and action in primates," Ann N Y Acad Sci, vol. 1121, pp. 273-96, Dec 2007. |
[52] | S. E. Morrison and C. D. Salzman, "Re-valuing the amygdala," Curr Opin Neurobiol, vol. 20, pp. 221-30, Apr 2010. |
[53] | J. P. O'Doherty, "Lights, camembert, action! The role of human orbitofrontal cortex in encoding stimuli, rewards, and choices," Ann N Y Acad Sci, vol. 1121, pp. 254-72, Dec 2007. |
[54] | E. A. Murray and S. P. Wise, "Interactions between orbital prefrontal cortex and amygdala: advanced cognition, learned responses and instinctive behaviors," Curr Opin Neurobiol, vol. 20, pp. 212-20, Apr 2010. |
[55] | S. M. Tom, C. R. Fox, C. Trepel, and R. A. Poldrack, "The neural basis of loss aversion in decision-making under risk," Science, vol. 315, pp. 515-8, Jan 26 2007. |
[56] | R. L. Solomon and J. D. Corbit, "An opponent-process theory of motivation. I. Temporal dynamics of affect," Psychol review, vol. 81, pp. 119-45, Mar 1974. |
[57] | R. A. Rescorla and R. L. Solomon, "Two-process learning theory: Relationships between Pavlovian conditioning and instrumental learning," Psychol Rev, vol. 74, pp. 151-82, May 1967. |
[58] | Psychology and Behavioral Sciences 2014; 3(2): 68-74. |
APA Style
Nicoladie D. Tam. (2014). Quantification of Happy Emotion: Proportionality Relationship to Gain/Loss. Psychology and Behavioral Sciences, 3(2), 60-67. https://doi.org/10.11648/j.pbs.20140302.15
ACS Style
Nicoladie D. Tam. Quantification of Happy Emotion: Proportionality Relationship to Gain/Loss. Psychol. Behav. Sci. 2014, 3(2), 60-67. doi: 10.11648/j.pbs.20140302.15
AMA Style
Nicoladie D. Tam. Quantification of Happy Emotion: Proportionality Relationship to Gain/Loss. Psychol Behav Sci. 2014;3(2):60-67. doi: 10.11648/j.pbs.20140302.15
@article{10.11648/j.pbs.20140302.15, author = {Nicoladie D. Tam}, title = {Quantification of Happy Emotion: Proportionality Relationship to Gain/Loss}, journal = {Psychology and Behavioral Sciences}, volume = {3}, number = {2}, pages = {60-67}, doi = {10.11648/j.pbs.20140302.15}, url = {https://doi.org/10.11648/j.pbs.20140302.15}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.pbs.20140302.15}, abstract = {Toward understanding the role of emotion played in cognitive processing, an emotional model has been proposed to quantify the computation involved in assessing the disparity between the expected and the actual outcomes. This study provides the experimental evidence to validate the above emotional model. In this model, emotion serves as an internal feedback to assess the disparity between the internal predicted outcomes and the actual (external) outcomes in reality. It predicts that emotion provides a feedback to reduce the discrepancy between the expected (subjective) reality and actual (objective) reality. The hypothesis for this model is that the intensity of emotional response is proportional to the disparity between the expected outcome and the actual outcome (i.e., gain/loss magnitude). Happiness is an emotional feedback that indicates the congruency between the predicted and actual outcomes. In order to validate this theoretical model of emotion, the classical Ultimatum Game (UG) is used as an experimental paradigm to elicit self-generated (endogenous) emotions in response to a monetary offer, so that the emotional responses with respect to the perceived monetary gain/loss can be assessed by the stimulus-response function. The results showed that the self-reported happiness intensity is directly proportional to the magnitude of the desirable monetary gain. An empirically derived emotion stimulus-response function is shown to quantify the specific emotional biases graphically by the emotional-disparity graph. The results validated the hypothesis that the intensity of self-reported happy emotion is directly proportional to the monetary gain. The analysis also showed that the happy emotional sensitivity is also changed by the perception of fairness (whether the offer is fair or unfair), which can be represented graphically by the emotional-disparity graph}, year = {2014} }
TY - JOUR T1 - Quantification of Happy Emotion: Proportionality Relationship to Gain/Loss AU - Nicoladie D. Tam Y1 - 2014/04/30 PY - 2014 N1 - https://doi.org/10.11648/j.pbs.20140302.15 DO - 10.11648/j.pbs.20140302.15 T2 - Psychology and Behavioral Sciences JF - Psychology and Behavioral Sciences JO - Psychology and Behavioral Sciences SP - 60 EP - 67 PB - Science Publishing Group SN - 2328-7845 UR - https://doi.org/10.11648/j.pbs.20140302.15 AB - Toward understanding the role of emotion played in cognitive processing, an emotional model has been proposed to quantify the computation involved in assessing the disparity between the expected and the actual outcomes. This study provides the experimental evidence to validate the above emotional model. In this model, emotion serves as an internal feedback to assess the disparity between the internal predicted outcomes and the actual (external) outcomes in reality. It predicts that emotion provides a feedback to reduce the discrepancy between the expected (subjective) reality and actual (objective) reality. The hypothesis for this model is that the intensity of emotional response is proportional to the disparity between the expected outcome and the actual outcome (i.e., gain/loss magnitude). Happiness is an emotional feedback that indicates the congruency between the predicted and actual outcomes. In order to validate this theoretical model of emotion, the classical Ultimatum Game (UG) is used as an experimental paradigm to elicit self-generated (endogenous) emotions in response to a monetary offer, so that the emotional responses with respect to the perceived monetary gain/loss can be assessed by the stimulus-response function. The results showed that the self-reported happiness intensity is directly proportional to the magnitude of the desirable monetary gain. An empirically derived emotion stimulus-response function is shown to quantify the specific emotional biases graphically by the emotional-disparity graph. The results validated the hypothesis that the intensity of self-reported happy emotion is directly proportional to the monetary gain. The analysis also showed that the happy emotional sensitivity is also changed by the perception of fairness (whether the offer is fair or unfair), which can be represented graphically by the emotional-disparity graph VL - 3 IS - 2 ER -