Neural Economics and Biological Substrates of Valuation

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DESCRIPTION (provided by applicant): Ongoing economic evaluation is a central function for any system that must operate with limited, finite resources, that is, all mobile creatures. The need for neural valuation mechanisms arises from the sheer breadth and variety of information available to a mobile creature's nervous system, and the fact that sensory stimuli and possible behavioral output must be prioritized. This presents a fundamental information-processing problem: vastly different stimuli and behavioral output must be placed on some common valuation scale. Without internal valuation systems in the nervous system, a creature would be unable to assess the relative value of intrinsically different events like drinking water, smelling food, scanning for predators, sitting quietly in the sun, and so forth. To decide on an appropriate behavior, the nervous system must estimate the value of each of these potential actions or stimuli, convert it to a common scale (currency), and use this scale to determine a course of action. This issue has long been appreciated by behavioral psychologists and economists; however, only recently have the underlying neural substrates been addressed experimentally in humans. Midbrain dopamine systems and the target neural structures to which they project have now been identified as participating in the valuation of future rewarding events. In particular, computational work has shown that a subset of these dopamine neurons encode and distribute a prediction error signal representing the ongoing difference between actual reward and predicted reward. This prediction error model of dopaminergic function has now led to behavioral models that predict human behavior on sequential decision-making tasks. These tasks ask the question: "How do humans value ongoing changes in rewarding stimuli?", a question with important implications for drug abuse. However, there has been no biological measure to correlate with these model-based behavioral predictions. The long-term goal of this proposal is to use functional magnetic resonance imaging (fMRI) during the execution of sequential decision tasks to probe the brain responses that correlate with human performance. This work will provide fundamental insights into valuations mechanisms present in human brains.