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The Role of the Basal Ganglia in Discovering Novel Actions

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Intrinsically Motivated Learning in Natural and Artificial Systems

Abstract

Our interest is in the neural circuitry which supports the discovery and encoding of novel actions. We discuss the significant existing literature which identifies the basal ganglia, a complex of subcortical nuclei, as important in both the selection of actions and in reinforcement learning. We discuss the complementarity of these problems of action selection and action learning. Two basic mechanisms of biasing action selection are identified: (a) adjusting the relative strengths of competing inputs and (b) adjusting the relative sensitivity of the receiver of reinforced inputs. We discuss the particular importance of the phasic dopamine signal in the basal ganglia and its proposed role in conveying a reward prediction error. Temporal constraints of this signal limit the information it can convey to immediately surprising sensory events, thus—we argue—making it inappropriate to convey information regarding the economic value of actions (as proposed by the reward prediction error hypothesis). Rather, we suggest this signal is ideal to support the identification of novel actions and their encoding via the biasing of future action selection.

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Acknowledgements

Written while the authors were in receipt of research funding from The Wellcome Trust, BBSRC and EPSRC, this research has also received funds from the European Commission 7th Framework Programme (FP7/2007-2013), “Challenge 2—Cognitive Systems, Interaction, Robotics”, Grant Agreement No. ICT-IP-231722 and Project “IM-CLeVeR—Intrinsically Motivated Cumulative Learning Versatile Robots”.

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  1. Adaptive Behaviour Research Group, Department of Psychology, University of Sheffield, Sheffield, UK

    Peter Redgrave, Kevin Gurney, Tom Stafford, Martin Thirkettle & Jen Lewis

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Correspondence to Peter Redgrave .

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Redgrave, P., Gurney, K., Stafford, T., Thirkettle, M., Lewis, J. (2013). The Role of the Basal Ganglia in Discovering Novel Actions. In: Baldassarre, G., Mirolli, M. (eds) Intrinsically Motivated Learning in Natural and Artificial Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32375-1_6

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