CORMSIS seminar: The use of neurophysiological devices and neurocognitive test batteries in experimental studies of affective decision making Event

Event details

Abstract: Over the last years, the study of neurocognitive mechanisms of decision making has gained prominence resulting in a boost of inter-disciplinary research borrowing and mixing constructs, theories, experimental methods from a number of disciplines, including cognitive neuroscience, and leading to the emergence of novel disciplines, such as neuroeconomics, decision neuroscience, neuromarketing, neurofinance, and even neuroaccounting and neuro-information systems. Being termed as ‘neuromania’ by some, the phenomenon continues to grow, resulting in a number of well-equipped laboratories appearing in business schools, or as collaborative efforts between business and medical schools. The outcomes of the multidisciplinary research produced in such collaborative settings are getting increasingly accepted by the top journals, such as Management Science, the Journal of Finance, the Accounting Review, and others. In this talk, I am going to discuss the practical lessons learnt from conducting experimental studies in a behavioural lab established in one of the largest business schools in Australia. My focus would be on multimodal experiments that integrate such technologies as eye-tracking, pupillometry, skin conductance, heart rate, and electroencephalography – in other words, the technologies that allow to measure in an integrated fashion the response from the central and peripheral nervous systems of participants while they attend a variety of decision making tasks. I will discuss how these technologies are used for testing theories of human behaviour. Specifically, I will focus on how these technologies may assist in identifying neurophysiological correlates associated with various decision making conditions, including risk, ambiguity, and variable incentive schemes. I will also report some of our findings that address the role of personal neurocognitive profiles on rationality of risk taking. Both technical (big data) and conceptual (data interpretation) issues associated with conducting this type of laboratory experiments will be discussed.