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My scientific interests are in behavioural and experimental economics, with particular focus on the role of emotions in economic decision-making. My MPhil. research was funded and carried in the Centre for Decision Research and Experimental Economics (CeDEx), based in School of Economics at the University of Nottingham. The research investigated the role of emotions in economic decision-making using the approach of experimental economics and by adopting and refining a physiological technique of emotion measurement known as electrodermal activity (EDA) measurement. The tool for measuring emotions in ways that will make them more accessible to researchers wishing to investigate the emotional determinants of decision-making in the groups of interacting subjects was developed. The use of developed equipment was demonstrated in a pilot experiment aimed to investigate the role of emotions in cooperative behaviour.

About my research project

The main feature of this research was the development of a low-cost instrument for electrodermal activity measurement. Being a sensitive measure of emotion-related sympathetic activity caused by presenting a novel unexpected stimulus, EDA measurement is non-invasive and widely used in psychophysiology as an indicator of emotional arousal. The developed instrument is a portable device for continuous measuring of EDA from up to four subjects simultaneously. The data recording is done on PC to which the device is connected using a USB interface. Also research involved the production of custom designed software that facilitates data acquisition and analysis. It allows the synchronisation of recorded EDA data with the timing of events registered by z-Tree, a standard and widely used software for carrying out economics experiments. The project included a stage in which the developed instrument was validated using facilities available in the Medical School, University of Nottingham. The developed device was used in a pilot experiment based on the social dilemma game.

MPhil thesis "Developing and applying skin conductance measurement techniques in the context of economic experiments" can be downloaded here.

Skin Conductance Measuring Device

First generation of SCMDSkin Conductance Measuring Device (SCMD) is an instrument for measuring electrodermal activity which I have developed as a part of my research project. Being portable and low-cost alternative to the advanced biological signal recording equipment available on the market, it is aimed to increase the accessibility of physiological methods for the economics researcher. Due to its simplicity of use it can readily be applied with very little specialist expertise required. The developed equipment can be used in the setting of an experimental economics laboratory for measuring skin conductance from the group of subjects interacting in the economics experiment simultaneously. A validation of the developed instrument was performed to test its suitability and reliability for research purposes.

The system consists of a hardware part and software for data acquisition and analysis. The hardware part is designed for the continuous measuring of skin conductance from up to four subjects simultaneously and for transferring the collected data to a PC where it is captured by "SCMD-Recording" software component for data acquisition and recorded into the ASCII text file. Then, using "SCMD-Analysis" software component designed for elementary analysis, recorded data can be synchronised with the log of events that was generated by z-Tree software for carrying out economics experiments. Advanced event-related analysis of skin conductance data can be performed using suitable third-party software products (e.g. Ledalab).
  • SCMD Driver - required for communicating with SCMD hardware, suitable for both 32 bit and 64 bit architectures (Windows OS).
  • SCMD Software - software for data acquisition and analysis (for use with SCMD device on Windows OS).
EDA data analysis:
  • Ledalab-SCMD - fork of Ledalab software (version 3.4.8) that allows importing SCMD data files, also includes separate SCMD importing and extended exporting functions that can be used with higher versions of Ledalab.
  • Ledalab - Matlab-based free software for the analysis of EDA data by means of decomposition into distinct phasic and tonic components.

SCMD-2

In 2014/2015 the project on development of second generation of SCMD has been carried out. It has addressed number of limitation of existing tool, such as sampling resolution and frequency as well as moving to use manufactured printed circuit boards.

Recommended literature

Below is the list of some useful sources for anyone who wishes to investigate the role of emotions in economic decision-making. They are categorized by the topic of the primary focus.

Emotions
  • Elster, J. (1998). "Emotions and Economic Theory." Journal of Economic Literature 36(1): 47-74.
  • Lerner, J. and G. Loewenstein (2003). The Role of Affect in Decision Making. Handbook of affective science. R. Davidson, H. Goldsmith and K. Scherer. Oxford, England, Oxford University Press: 619-642.
  • Loewenstein, G. (2000). "Emotions in Economic Theory and Economic Behavior." The American Economic Review 90(2): 426-432.
Neuroeconomics
  • Bechara, A. and A. R. Damasio (2005). "The somatic marker hypothesis: A neural theory of economic decision." Games and Economic Behavior
    52(2): 336-372.
  • Camerer, C., G. Loewenstein, et al. (2005). "Neuroeconomics: How Neuroscience Can Inform Economics." Journal of Economic Literature
    XLIII(March): 9-64.
  • Fehr, E. and C. F. Camerer (2007). "Social neuroeconomics: the neural circuitry of social preferences." Trends in Cognitive Sciences 11(10):
    419-427.
  • Sanfey, A. G., G. Loewenstein, et al. (2006). "Neuroeconomics: cross-currents in research on decision-making." Trends in Cognitive Sciences 10(3): 108-116.
  • Zak, P. J. (2004). "Neuroeconomics." Philosophical Transactions of the Royal Society B: Biological Sciences 359(1451): 1737-1748.
Using neuroscientific tools in economics experiments
  • Ben-Shakhar, G., G. Bornstein, et al. (2007). "Reciprocity and emotions in bargaining using physiological and self-report measures." Journal of Economic Psychology 28(3): 314-323.
  • de Quervain, D. J. F., U. Fischbacher, et al. (2004). "The Neural Basis of Altruistic Punishment." Science 305(5688): 1254-1258.
  • Koenigs, M. and D. Tranel (2007). "Irrational Economic Decision-Making after Ventromedial Prefrontal Damage: Evidence from the Ultimatum Game." J. Neurosci. 27(4): 951-956.
  • Lo, A. W. and D. V. Repin (2002). "The Psychophysiology of Real-Time Financial Risk Processing." J. Cogn. Neurosci. 14(3): 323-339.
  • McClure, S. M., D. I. Laibson, et al. (2004). "Separate Neural Systems Value Immediate and Delayed Monetary Rewards." Science 306(5695):
    503-507.
  • Sanfey, A. G., J. K. Rilling, et al. (2003). "The Neural Basis of Economic Decision-Making in the Ultimatum Game." Science 300(5626):
    1755-1758.
  • van 't Wout, M., R. Kahn, et al. (2006). "Affective state and decision-making in the Ultimatum Game." Experimental Brain Research 169(4): 564-568.
  • Zak, P. J., R. Kurzban, et al. (2005). "Oxytocin is associated with human trustworthiness." Hormones and Behavior 48(5): 522-527.
Electrodermal activity
  • Figner, B., & Murphy, R. O. (2011). Using skin conductance in judgment and decision making research. In M. Schulte-Mecklenbeck, A. Kuehberger, & R. Ranyard (Eds.), A handbook of process tracing methods for decision research (pp. 163-184). New York, NY: Psychology Press.
  • Bradley, M. M. (2000). Emotion and Motivation. Handbook of Psychophysiology . J. T. Cacioppo, L. G. Tassinary and G. G. Berntson. Cambridge, MA, Cambridge University Press :602–642.
  • Critchley, H. D. (2002). "Electrodermal Responses: What Happens in the Brain." Neuroscientist 8(2): 132-142.
  • Dawson, M. E., A. M. Schell, et al. (2000). The electrodermal system. Handbook of Psychophysiology . J. T. Cacioppo, L. G. Tassinary and G. G. Berntson. Cambridge, MA, Cambridge University Press :200–223.