Decision-making under uncertainty: neural hardwiring of behavioral algorithms

Abstract

Every day humans make decisions under uncertainty where there are multiple potential outcomes. To do this, multiple pieces of information are integrated: potential outcomes and the likelihoods of those outcomes. In some cases, the likelihoods of each outcome are known, known as risks, and in other cases the likelihoods of each outcome are unknown, known as ambiguity. While most individuals have aversion towards both types of uncertainty, risks and ambiguity, the strength of that aversion changes across individuals. Specifically, adolescents' aversion towards ambiguity decreases while aversion towards risk is the same as adults. In the frontoparietal network (FPN), decreased risk-aversion is associated with increased activity in the right frontal node and increased ambiguity-aversion is associated with increased activity in the left parietal node. Meanwhile, the insula, dorsomedial prefrontal cortex (dmPFC), and the thalamus are consistently activated. This dissertation elucidates upon the decision-making process by looking at the integrated effects of ambiguity and risk on choice behavior (Study 1 and 2), a proposed algorithm for integrating likelihood information (Study 1 and 2), and the neural hardwiring of decisions under varying types of uncertainty (Study 2 and 3). Study 1 looks at this in adults, Study 2 in adolescents, and Study 3 in an older adult population. favorability of the risk information resulted in greater pessimism towards ambiguity particularly in adults and mid-adolescents. Increased perceived favorability of ambiguous likelihoods was associated with increased dmPFC and insula activity. The thalamus, functionally connected to the dmPFC and insula, had increases in dopamine (DA), decreases in norepinephrine (NE) in response to increased uncertainty. The summation of both DA nor NE was most associated with model-derived choice. Decision-making under uncertainty involves integration of information. Behaviorally, the integration of both risk and ambiguity information affects choice. In the neural hardwiring, both DA and NE affected choice. These results elucidate on the mechanics behind decisions under uncertainty and create important hypothesis to be further tested in larger populations.