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Action prediction error: a value-free dopaminergic teaching signal that drives stable learning

View ORCID ProfileFrancesca Greenstreet, View ORCID ProfileHernando Martinez Vergara, View ORCID ProfileSthitapranjya Pati, Laura Schwarz, Matthew Wisdom, Fred Marbach, View ORCID ProfileYvonne Johansson, Lars Rollik, Theodore Moskovitz, Claudia Clopath, View ORCID ProfileMarcus Stephenson-Jones
doi: https://doi.org/10.1101/2022.09.12.507572
Francesca Greenstreet
1UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London W1T 4JG, United Kingdom
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  • ORCID record for Francesca Greenstreet
Hernando Martinez Vergara
1UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London W1T 4JG, United Kingdom
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  • ORCID record for Hernando Martinez Vergara
Sthitapranjya Pati
1UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London W1T 4JG, United Kingdom
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  • ORCID record for Sthitapranjya Pati
Laura Schwarz
1UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London W1T 4JG, United Kingdom
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Matthew Wisdom
1UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London W1T 4JG, United Kingdom
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Fred Marbach
1UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London W1T 4JG, United Kingdom
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Yvonne Johansson
1UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London W1T 4JG, United Kingdom
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  • ORCID record for Yvonne Johansson
Lars Rollik
1UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London W1T 4JG, United Kingdom
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Theodore Moskovitz
2Gatsby Computational Neuroscience Unit, University College London, London W1T 4JG, United Kingdom
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Claudia Clopath
3Bioengineering Department, Imperial College London, London, UK
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Marcus Stephenson-Jones
1UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London W1T 4JG, United Kingdom
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  • ORCID record for Marcus Stephenson-Jones
  • For correspondence: m.stephenson-jones@ucl.ac.uk
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Abstract

Animals’ choice behavior is characterized by two main tendencies: taking actions that led to rewards and repeating past actions. Theory suggests these strategies may be reinforced by different types of dopaminergic teaching signals: reward prediction error (RPE) to reinforce value-based associations and movement-based action prediction errors to reinforce value-free repetitive associations. Here we use an auditory-discrimination task in mice to show that movement-related dopamine activity in the tail of the striatum encodes the hypothesized action prediction error signal. Causal manipulations reveal that this prediction error serves as a value-free teaching signal that supports learning by reinforcing repeated associations. Computational modeling and experiments demonstrate that action prediction errors cannot support reward-guided learning but when paired with the RPE circuity they serve to consolidate stable sound-action associations in a value-free manner. Together we show that there are two types of dopaminergic prediction errors that work in tandem to support learning.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted September 14, 2022.
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Action prediction error: a value-free dopaminergic teaching signal that drives stable learning
Francesca Greenstreet, Hernando Martinez Vergara, Sthitapranjya Pati, Laura Schwarz, Matthew Wisdom, Fred Marbach, Yvonne Johansson, Lars Rollik, Theodore Moskovitz, Claudia Clopath, Marcus Stephenson-Jones
bioRxiv 2022.09.12.507572; doi: https://doi.org/10.1101/2022.09.12.507572
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Action prediction error: a value-free dopaminergic teaching signal that drives stable learning
Francesca Greenstreet, Hernando Martinez Vergara, Sthitapranjya Pati, Laura Schwarz, Matthew Wisdom, Fred Marbach, Yvonne Johansson, Lars Rollik, Theodore Moskovitz, Claudia Clopath, Marcus Stephenson-Jones
bioRxiv 2022.09.12.507572; doi: https://doi.org/10.1101/2022.09.12.507572

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