This is an historical archive of the activities of the MRC Anatomical Neuropharmacology Unit (MRC ANU) that operated at the University of Oxford from 1985 until March 2015. The MRC ANU established a reputation for world-leading research on the brain, for training new generations of scientists, and for engaging the general public in neuroscience. The successes of the MRC ANU are now built upon at the MRC Brain Network Dynamics Unit at the University of Oxford.

The basal ganglia and cortex implement optimal decision making between alternative actions.

Neural Comput 2007;19(2):442-77. 10.1162/neco.2007.19.2.442

The basal ganglia and cortex implement optimal decision making between alternative actions.

Bogacz R, Gurney K
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Abstract:
Neurophysiological studies have identified a number of brain regions critically involved in solving the problem of action selection or decision making. In the case of highly practiced tasks, these regions include cortical areas hypothesized to integrate evidence supporting alternative actions and the basal ganglia, hypothesized to act as a central switch in gating behavioral requests. However, despite our relatively detailed knowledge of basal ganglia biology and its connectivity with the cortex and numerical simulation studies demonstrating selective function, no formal theoretical framework exists that supplies an algorithmic description of these circuits. This article shows how many aspects of the anatomy and physiology of the circuit involving the cortex and basal ganglia are exactly those required to implement the computation defined by an asymptotically optimal statistical test for decision making: the multihypothesis sequential probability ratio test (MSPRT). The resulting model of basal ganglia provides a new framework for understanding the computation in the basal ganglia during decision making in highly practiced tasks. The predictions of the theory concerning the properties of particular neuronal populations are validated in existing experimental data. Further, we show that this neurobiologically grounded implementation of MSPRT outperforms other candidates for neural decision making, that it is structurally and parametrically robust, and that it can accommodate cortical mechanisms for decision making in a way that complements those in basal ganglia.