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Precision weighting of cortical unsigned prediction errors is mediated by dopamine and benefits learning

J. Haarsma, P.C. Fletcher, H. Ziauddeen, T.J. Spencer, K.M.J. Diederen, G.K. Murray
doi: https://doi.org/10.1101/288936
J. Haarsma
1Department of Psychiatry, University of Cambridge, United Kingdom
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P.C. Fletcher
1Department of Psychiatry, University of Cambridge, United Kingdom
2Wellcome Trust MRC Institute of Metabolic Science, Cambridge Biomedical Campus, United Kingdom
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H. Ziauddeen
1Department of Psychiatry, University of Cambridge, United Kingdom
2Wellcome Trust MRC Institute of Metabolic Science, Cambridge Biomedical Campus, United Kingdom
3Cambridgeshire and Peterborough Foundation Trust, Fulbourn Hospital, United Kingdom
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T.J. Spencer
4Department of Psychosis studies, Institute of Psychiatry, Psychology and Neuroscience King’s College London, De Crespigny Park, United Kingdom
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K.M.J. Diederen
1Department of Psychiatry, University of Cambridge, United Kingdom
4Department of Psychosis studies, Institute of Psychiatry, Psychology and Neuroscience King’s College London, De Crespigny Park, United Kingdom
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  • For correspondence: kelly.diederen@kcl.ac.uk gm285@cam.ac.uk
G.K. Murray
1Department of Psychiatry, University of Cambridge, United Kingdom
3Cambridgeshire and Peterborough Foundation Trust, Fulbourn Hospital, United Kingdom
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  • For correspondence: kelly.diederen@kcl.ac.uk gm285@cam.ac.uk
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Abstract

The predictive coding framework construes the brain as performing a specific form of hierarchical Bayesian inference. In this framework the precision of cortical unsigned prediction error (surprise) signals is proposed to play a key role in learning and decision-making, and to be controlled by dopamine. To test this hypothesis, we re-analysed an existing data-set from healthy individuals who received a dopamine agonist, antagonist or placebo and who performed an associative learning task under different levels of outcome precision. Computational reinforcement-learning modelling of behaviour provided support for precision-weighting of unsigned prediction errors. Functional MRI revealed coding of unsigned prediction errors relative to their precision in bilateral superior frontal gyri and dorsal anterior cingulate. Cortical precision-weighting was (i) perturbed by the dopamine antagonist sulpiride, and (ii) associated with task performance. These findings have important implications for understanding the role of dopamine in reinforcement learning and predictive coding in health and illness.

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Posted March 26, 2018.
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Precision weighting of cortical unsigned prediction errors is mediated by dopamine and benefits learning
J. Haarsma, P.C. Fletcher, H. Ziauddeen, T.J. Spencer, K.M.J. Diederen, G.K. Murray
bioRxiv 288936; doi: https://doi.org/10.1101/288936
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Precision weighting of cortical unsigned prediction errors is mediated by dopamine and benefits learning
J. Haarsma, P.C. Fletcher, H. Ziauddeen, T.J. Spencer, K.M.J. Diederen, G.K. Murray
bioRxiv 288936; doi: https://doi.org/10.1101/288936

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