Reason, Emotion and Information Processing in the Brain

Abstract

Building on evidence from neurobiology and neuroscience, we model the physiological limitations faced by individuals in the process of decision-making that starts with sensory perception and ends in action selection. The brain sets a neuronal threshold, observes whether the neuronal cell firing activity reaches the threshold or not, and takes the optimal action conditional on that (limited) information. We show that the optimal threshold is set in a way that existing beliefs are most likely to be confirmed and least likely to be refuted. The conclusion holds in static and dynamic settings, and with linear and quadratic loss functions. We then relate our result to the somatic marker theory, and argue that it provides support for the hypothesis that emotions help decision-making. Last, we discuss the implications for choices in concrete vs. abstract situations, for interactions in cooperative vs. competitive activities, for reactions to expected vs. unexpected events, and for the choice of cognitive vs. affective encoding channels.

Keywords: Bayesian learning, Emotion, Information processing, neurobiology, Neuroeconomics, Reason

JEL Classification: Z0