Cognitive and reward signals for choices under ambiguity

Abstract Poor decisions can have severe consequences, and impaired decision-making behavior is a symptom of many neurological and psychiatric disorders. Decision theory recognizes two forms of uncertainty: risk – in which the underlying probability distributions are known, and ambiguity – in which the underlying probability distributions are not known. Risk is the conceptual foundation for the Expected Utility theory. Despite its enduring influence in economics, this theory fails to adequately describe real-world choice behavior. One reason is that pure risk is rare: it is only encountered in casinos, coin-flips, and decision-making experiments. In the real world, incomplete information, sparse data, and cognitive limitations create states of uncertainty that exist on a spectrum between pure risk and blind ignorance. Therefore, ambiguity, rather than risk, describes the conditions under which most decision-making occurs. In ambiguous circumstances, it is impossible to calculate expected utilities. Instead, decision makers (consciously or subconsciously) substitute beliefs for expected utility estimations, and this has consequences for healthy individuals and those with neurological and psychiatric disorders. Healthy decision makers exhibit ambiguity aversion: they avoid ambiguous prospects, even when doing so is costly. Individuals with prefrontal dysfunctions perform poorly during choices under ambiguity, even when choices under risk remain relatively intact. Despite the prevalence of ambiguity and its consequences, it is not known how neurons code for the uncertainty associated with ambiguity, or how these neural estimates are used for decision making. To understand how neural circuits implement economic choices and how this implementation may be altered with prefrontal dysfunction, we will use a non-human primate model to characterize the contributions of cognitive and reward systems to decisions under ambiguity, and to provide a mechanistic understanding of ambiguity aversion. The central hypothesis of this project is that ambiguity aversion results from the metacognitive appraisal of probability judgements. In other words, it is not beliefs, but rather decision makers’ confidence in those beliefs, that causes ambiguity aversion. We will use behavioral analysis, neurophysiology, and genetically coded silencers to probe the functions of dorsolateral prefrontal cortex and dopamine neurons and answer three fundamental questions. (1) How is ambiguity coded and transformed into beliefs? (2) What are the roles of cognitive systems in estimating ambiguity and making good choices? (3) How does confidence in probability judgements affect decisions? We predict that uncertainty coding in dorsolateral prefrontal cortex will be less reliable in ambiguous, when compared to risky, conditions and lead to lower certainty, lower confidence, and, ultimately, ambiguity aversion. Our results will increase understanding of the neural basis of decision-making under ambiguity and provide insights into diagnosis and treatment options for an array of human disease states.