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Neural control of dopamine neurotransmission: implications for reinforcement learning


Dr J. R. Wickens, as above.


In the past few decades there has been remarkable convergence of machine learning with neurobiological understanding of reinforcement learning mechanisms, exemplified by temporal difference (TD) learning models. The anatomy of the basal ganglia provides a number of potential substrates for instantiation of the TD mechanism. In contrast to the traditional concept of direct and indirect pathway outputs from the striatum, we emphasize that projection neurons of the striatum are branched and individual striatofugal neurons innervate both globus pallidus externa and globus pallidus interna/substantia nigra (GPi/SNr). This suggests that the GPi/SNr has the necessary inputs to operate as the source of a TD signal. We also discuss the mechanism for the timing processes necessary for learning in the TD framework. The TD framework has been particularly successful in analysing electrophysiogical recordings from dopamine (DA) neurons during learning, in terms of reward prediction error. However, present understanding of the neural control of DA release is limited, and hence the neural mechanisms involved are incompletely understood. Inhibition is very conspicuously present among the inputs to the DA neurons, with inhibitory synapses accounting for the majority of synapses on DA neurons. Furthermore, synchronous firing of the DA neuron population requires disinhibition and excitation to occur together in a coordinated manner. We conclude that the inhibitory circuits impinging directly or indirectly on the DA neurons play a central role in the control of DA neuron activity and further investigation of these circuits may provide important insight into the biological mechanisms of reinforcement learning.