Journal
JOURNAL OF NEUROSCIENCE
Volume 27, Issue 31, Pages 8170-8173Publisher
SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.1561-07.2007
Keywords
reinforcement learning; reward; cingulate cortex; prefrontal cortex; orbitofrontal cortex; neuroeconomics
Categories
Funding
- Medical Research Council [G0600994] Funding Source: Medline
- NIMH NIH HHS [R01 MH073246, R01 MH073246-05] Funding Source: Medline
- NINDS NIH HHS [P01 NS048328, P01 NS048328-040003] Funding Source: Medline
- MRC [G0600994] Funding Source: UKRI
- Medical Research Council [G0600994] Funding Source: researchfish
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Economic theories of decision making are based on the principle of utility maximization, and reinforcement-learning theory provides computational algorithms that can be used to estimate the overall reward expected from alternative choices. These formal models not only account for a large range of behavioral observations in human and animal decision makers, but also provide useful tools for investigating the neural basis of decision making. Nevertheless, in reality, decision makers must combine different types of information about the costs and benefits associated with each available option, such as the quality and quantity of expected reward and required work. In this article, we put forward the hypothesis that different subdivisions of the primate frontal cortex may be specialized to focus on different aspects of dynamic decision-making processes. In this hypothesis, the lateral prefrontal cortex is primarily involved in maintaining the state representation necessary to identify optimal actions in a given environment. In contrast, the orbitofrontal cortex and the anterior cingulate cortex might be primarily involved in encoding and updating the utilities associated with different sensory stimuli and alternative actions, respectively. These cortical areas are also likely to contribute to decision making in a social context.
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