A cholinergic feedback circuitto regulate striatal population uncertainty and optimize reinforcement learning

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Abstract

Convergent evidence suggeststhat the basal ganglia support reinforcement learning by adjusting action values according to reward prediction errors. However, adaptive behavior in stochasticenvironments requires the consideration of uncertainty to dynamically adjust the learning rate. We consider how cholinergic tonically active interneurons (TANs) may endow the striatum with such a mechanismin computational models spanning three Marr's levels of analysis. In the neural model, TANs modulate the excitability of spiny neurons, theirpopulation response to reinforcement, and hence the effective learning rate. Long TAN pauses facilitated robustness to spuriousoutcomes by increasing divergence in synaptic weights between neurons coding for alternative action values,whereas short TAN pauses facilitated stochastic behavior but increased responsiveness to change-points in outcome contingencies.A feedback control system allowed TAN pauses to be dynamically modulated by uncertainty across the spiny neuron population,allowing the system to self-tune and optimizeperformance across stochastic environments.

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Nicholas T Franklin

Department of Cognitive, Linguistic and Psychological Sciences, Brown Institute for Brain Science, Brown University, Providence, United States

Competing interests
No competing interests declared.
Michael J Frank

Department of Cognitive, Linguistic and Psychological Sciences, Brown Institute for Brain Science, Brown University, Providence, United States

For correspondence
Michael_Frank@brown.edu

Competing interests
Michael J Frank, Reviewing editor, eLife.

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