Social and Economic Decision-Making Utility Based on EEG Signals Analysis in Women Good Economic Decision-Making is related to different EEG signals
Archives of Advances in Biosciences,
Vol. 11 No. 3 (2020),
26 September 2020
,
Page 37-42
https://doi.org/10.22037/aab.v11i3.31959
Abstract
Introduction: One of the new fields of study is Neuroeconomics which investigates the effect of human brain on economic decision makings. In the current study, economic decision making was examined, using the Prisoner’s Dilemma Game among females followed by electroencephalogram (EEG) analysis.
Materials and Methods: Female participants were chosen based on their ability of making rational decision examined in Prisoner’s Dilemma Game for each group. Based on the data obtained from the Prisoner’s Dilemma Game, two groups existed: one includes female with good decision making in economic field in Prisoner’s Dilemma Test and group 2 consists of females who did not chose appropriate economic decision during the game. Also EEG analysis was performed at the end of EEG recording, participates were asked if they feel utility about their economic decision making in their entire life or not.
Results: The current results showed that the Economic Decision-Making Utility was more in group with better economic decision in Prisoner’s Dilemma Game. EEG analysis shows that Alpha/Beta ratio is %16.5 and Theta/Beta ratio is %12.5 less in group 2 who stayed silent and did not betray other suspect (***P<0.001).
Conclusion: According to the current data, utility about economic decisions may affect decision-making and EEG or vice versa, as Alpha/Beta and Theta/Beta ratio are less in the group who stayed silent and did not betray other suspect.
- Choice behavior, Neuroeconomics, EEG data, Prisoner’s Dilemma Game
How to Cite
References
Tee Yi Wen SAMA. Electroencephalogram (EEG) stress analysis on alpha/beta ratio
and theta/beta ratio. Indonesian Journal of Electrical Engineering and Computer Science. 2020;17[1]:175-82.
Ash C. o Our Economic Choices Make Us Happy?. In: Zsolnai L. (eds) Ethical Principles and Economic Transformation - A Buddhist Approach. Springer, Dordrecht.33.
Giusti EM, Pietrabissa G, Manzoni GM, Cattivelli R, Molinari E, Trompetter HR, et al. The Economic Utility of Clinical Psychology in the Multidisciplinary Management of Pain. Front Psychol. 2017;8:1860.
Glimcher PW, Rustichini A. Neuroeconomics: the consilience of brain and decision. Science. 2004;306[5695]:447-52.
Robson SE, Repetto L, Gountouna VE, Nicodemus KK. A review of neuroeconomic gameplay in psychiatric disorders. Mol Psychiatry. 2020;25[1]:67-81.
Gallotti R, Grujic J. A quantitative description of the transition between intuitive altruism and rational deliberation in iterated Prisoner's Dilemma experiments. Sci Rep. 2019;9[1]:17046.
Gosling CJ, Caparos S, Moutier S. The interplay between the importance of a decision and emotion in decision-making. Cogn Emot. 2020:1-11.
Si Y, Li F, Duan K, Tao Q, Li C, Cao Z, et al. Predicting individual decision-making responses based on single-trial EEG. NeuroImage. 2020;206:116333.
Thiago Wendt Viola JPON, Bruno Kluwe-Schiavon, Breno Sanvicente-Vieira and Rodrigo Grassi-Oliveira. Cocaine use disorder in females is associated with altered social decisionmaking: a study with the prisoner’s dilemma and the ultimatum game Viola et al BMC Psychiatry 2019;19[211]:2-9.
Lozano P, Antonioni A, Tomassini M, Sanchez A. Cooperation on dynamic networks within an uncertain reputation environment. Sci Rep. 2018;8[1]:9093.
F. M. Al-Shargie TBT, N. Badruddin and M. Kiguchi. Towards Multilevel Mental Stress Assessment Using
Svm with Ecoc: An EEG Approach. Medical & Biological Engineering & Computing. 2018;56[1]:125-36.
Oullier O, Kirman AP, Kelso JA. The coordination dynamics of economic decision making: a multilevel approach to social neuroeconomics. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. 2008;16[6]:557-71.
Sundararajan RR, Palma MA, Pourahmadi M. Reducing Brain Signal Noise in the Prediction of Economic Choices: A Case Study in Neuroeconomics. Frontiers in neuroscience. 2017;11:704.
F. P. George IM, P. S. F. Hossain, M. Z. Parvez and J. Uddin. Recognition of Emotional States UsingEEG Signals Based on Time-Frequency Analysis and SVM Classifier. International Journal of Electrical and Computer Engineering [IJECE]. 2019;9[2]: 1012-20.
- Abstract Viewed: 344 times
- PDF Downloaded: 269 times