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Cognitive Computation of Jealous Emotion
Psychology and Behavioral Sciences
Volume 3, Issue 6-1, December 2014, Pages: 1-7
Received: Nov. 30, 2014; Accepted: Dec. 3, 2014; Published: Dec. 31, 2014
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Authors
Nicoladie D. Tam, Department of Biological Sciences, University of North Texas, Denton, TX 76203, USA
Krista M. Smith, Department of Sociology & Social Work, Texas Woman’s University, Denton, TX 76204, USA
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Abstract
The computational role of jealous emotion has been proposed in a model of emotion, in which the desirable gain (or loss) is used as a measure for computing the emotional feedback that assesses the discrepancy between what an individual wants and gets. The jealous emotion is elicited when the perception that the other individuals have more than one has, or that the desire of wanting what others have, but cannot get. Such self-identified error measure is used as an internal measure to monitor the incongruence between model prediction and actual outcome, such that the accuracy of predictions by the brain can be assessed. Jealousy can serve as a motivating signal to an individual to self-correct errors that may exist. This error signal signifies the incongruence between the desirable and the actual outcomes. This (unhappy) jealous emotion provides the necessary feedback to self-correct any potential source of errors, which may originate from the errors in (input) perception, (output) execution or (internal) model. An ultimatum game (UG) paradigm is used to elicit self-generated emotion. Results showed that the emotional intensity of jealousy is inversely proportional to perceived gains (and proportional to the perceived losses). Subjective jealousy biases are represented by shifting of the emotional stimulus-response function. This suggested that jealousy can be resolved by correcting (1) the perception of unfairness (perceptual error), (2) wrong decision (execution error) and (3) faulty assumption of entitlement (model prediction error) in this experimental UG paradigm. The results confirmed the hypothesis that self-regulated jealousy is processed cognitively in proportional to the perceived loss, when one wants to gain something that one cannot get. Implications on emotional intelligence are also addressed.
Keywords
Emotion, Jealousy, Fairness, Ultimatum Game, Decision Making, Error Minimization, Emotional Intelligence
To cite this article
Nicoladie D. Tam, Krista M. Smith, Cognitive Computation of Jealous Emotion, Psychology and Behavioral Sciences. Special Issue: Behavioral Neuroscience. Vol. 3, No. 6-1, 2014, pp. 1-7. doi: 10.11648/j.pbs.s.2014030601.11
References
[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]
A. Costa, E. Sophia, C. Sanches, H. Tavares, and M. Zilberman, “Pathological jealousy: Romantic relationship characteristics, emotional and personality aspects, and social adjustment,” J Affect Disord, vol. 174C, pp. 38-44, 2014.
[4]
B. Volling, T. Yu, R. Gonzalez, D. Kennedy, L. Rosenberg, and W. Oh, “Children's responses to mother-infant and father-infant interaction with a baby sibling: jealousy or joy?,” J Fam Psychol, vol. 28, pp. 634-644, 2014.
[5]
B. Batinic, D. Duisin, and J. Barisic, “Obsessive versus delusional jealousy,” Psychiatr Danub, vol. 25, pp. 334-339, 2013.
[6]
D. Marazziti, M. Poletti, L. Dell'Osso, S. Baroni, and U. Bonuccelli, “Prefrontal cortex, dopamine, and jealousy endophenotype,” CNS Spectr, vol. 18, pp. 6-14, 2013.
[7]
J. von Neumann, O. Morgenstern, and A. Rubinstein, Theory of games and economic behavior. Princeton, NJ: Princeton University Press, 1953.
[8]
J. H. Kagel and A. E. Roth, The handbook of experimental economics: PRINCETON University Press, 1995.
[9]
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.
[10]
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.
[11]
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.
[12]
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. 1694-1703, Aug 2004.
[13]
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.
[14]
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.
[15]
P. Smith and A. Silberberg, “Rational maximizing by humans (Homo sapiens) in an ultimatum game,” Anim Cogn, vol. 13, pp. 671-7, Jul 2010.
[16]
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.
[17]
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.
[18]
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.
[19]
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.
[20]
M. M. Pillutla and J. K. Murnighan, “Unfairness, Anger, and Spite: Emotional Rejections of Ultimatum Offers,” Org Behav Human Decis Proc, vol. 68, pp. 208-224, 12// 1996.
[21]
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.
[22]
E. K. Miller and J. D. Cohen, “An integrative theory of prefrontal cortex function,” Annu Rev Neurosci, vol. 24, pp. 167-202, 2001.
[23]
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.
[24]
E. T. Rolls, “Brain mechanisms of emotion and decision-making,” Int Congress Series, vol. 1291, pp. 3-13, 2006.
[25]
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.
[26]
D. Tam, “Variables governing emotion and decision-making: human objectivity underlying its subjective perception,” BMC Neuroscience, vol. 11, p. P96, Jul 20 2010.
[27]
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.
[28]
N. D. Tam, “Quantification of happy emotion: Proportionality relationship to gain/loss,” Psychol Behav Sci, vol. 3, pp. 60-67, April 6, 2014 2014.
[29]
N. D. Tam, “Quantification of happy emotion: Dependence on decisions,” Psychol Behav Sci, vol. 3, pp. 68-74, April 6, 2014 2014.
[30]
M. Koenigs and D. Tranel, “Irrational economic decision-making after ventromedial prefrontal damage: evidence from the Ultimatum Game,” J Neurosci, vol. 27, pp. 951-956, Jan 24 2007.
[31]
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.
[32]
N. D. Tam, “Quantification of fairness bias in relation to decisions using a relativistic fairness-equity model,” Advances in Social Sciences Research Journal, vol. 1, pp. 169-178, 2014.
[33]
N. D. Tam, “Quantification of fairness perception by including other-regarding concerns using a relativistic fairness-equity model,” Advances in Social Sciences Research Journal, vol. 1, pp. 159-168, 2014.
[34]
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.
[35]
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.
[36]
N. D. Tam, “Quantification of fairness perception by including other-regarding concerns using a relativistic fairness-equity model,” Adv in Soc Sci Research J, vol. 1, pp. 159-169, 2014.
[37]
N. D. Tam, “Quantification of fairness bias in relation to decisions using a relativistic fairness-equity model,” Adv in Soc Sci Research J, vol. 1, pp. 169-178, 2014.
[38]
N. D. Tam, “Rational decision-making process choosing fairness over monetary gain as decision criteria,” Psychol Behav Sci, vol. in press, 2104.
[39]
N. D. Tam, “A decision-making phase-space model for fairness assessment,” Psychol Behav Sci, vol. in press, 2014.
[40]
N. D. Tam, “Quantification of happy emotion: Dependence on decisions,” Psychology and Behavioral Sciences, vol. 3, pp. 68-74, April 6, 2014 2014.
[41]
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.
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