This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.
The aim of the present research is to elucidate the neurobiological mechanisms of decision-making. Recent neuroimaging1 and neuropsychological2 data, combined with earlier work in behavioral finance3, demonstrate that the interaction of emotional reactions and cognitive processes is often necessary for adaptive and efficient decisions to be made. Yet, the neural processes enabling this interaction are not understood. According to the Somatic Marker Hypothesis (SMH)4, somatosensory feedback from the body is necessary for the interplay of emotional and cognitive processes in a decision-making situation. Largely due to methodological issues, the results of previous studies testing this claim are inconclusive. This motivated the present research which aims to examine the role of somatosensory feedback in decision-making using a novel approach. Our approach will consist of (a) examining relationships between performance on a decision-making task and a person's sensitivity to feedback signals emanating from the two parts of the nervous system (autonomic and non-autonomic), and (b) investigating the relationship between physiological activity in the autonomic and non-autonomic nervous system (ANS and nANS, respectively) and the adaptive value of subsequent decisions.Hypothesis: Based on the SMH and previous findings (see the Background & Significance section), we hypothesize that performance on the decision-making task will be at least moderately correlated (i.e., the Pearson product-moment correlation coefficient [r] will be equal or greater than 0.40) with sensitivity to ANS feedback signals and with sensitivity to nANS feedback signals. Based on the same rationale, we also predict that the amount of both ANS and nANS physiological activity will vary with the adaptive value of the decision subsequently made.
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