Nature Neuroscience 8, 1704 - 1711 (2005)
Published online: 6 November 2005; | doi:10.1038/nn1560
Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral controlNathaniel D Daw1, Yael Niv1, 2
& Peter Dayan11
Gatsby Computational Neuroscience Unit, University College London, Alexandra House, 17 Queen Square, London WC1N 3AR, UK. 2
Interdisciplinary Center for Neural Computation, Hebrew University, P.O. Box 1255, Jerusalem 91904, Israel.
Correspondence should be addressed to Nathaniel D Daw daw@gatsby.ucl.ac.uk A broad range of neural and behavioral data suggests that the brain contains multiple systems for behavioral choice, including one associated with prefrontal cortex and another with dorsolateral striatum. However, such a surfeit of control raises an additional choice problem: how to arbitrate between the systems when they disagree. Here, we consider dual-action choice systems from a normative perspective, using the computational theory of reinforcement learning. We identify a key trade-off pitting computational simplicity against the flexible and statistically efficient use of experience. The trade-off is realized in a competition between the dorsolateral striatal and prefrontal systems. We suggest a Bayesian principle of arbitration between them according to uncertainty, so each controller is deployed when it should be most accurate. This provides a unifying account of a wealth of experimental evidence about the factors favoring dominance by either system.
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