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The role of dopamine in positive and negative prediction error utilization during incidental learning: Insights from Positron Emission Tomography, Parkinson’s disease and Huntington’s disease

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Mathar,  David
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Integrated Research and Treatment Center Adiposity Diseases, University of Leipzig, Germany;

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Neumann,  Jane
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Integrated Research and Treatment Center Adiposity Diseases, University of Leipzig, Germany;

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Deserno,  Lorenz
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Department of Psychiatry and Psychotherapy, Charité University Medicine Berlin, Germany;
Department of Neurology, Otto von Guericke University Magdeburg, Germany;

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Villringer,  Arno
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Integrated Research and Treatment Center Adiposity Diseases, University of Leipzig, Germany;
Clinic for Cognitive Neurology, University of Leipzig, Germany;
Berlin School of Mind and Brain, Humboldt University Berlin, Germany;

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Horstmann,  Annette
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Integrated Research and Treatment Center Adiposity Diseases, University of Leipzig, Germany;

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Citation

Mathar, D., Wilkinson, L., Holl, A., Neumann, J., Deserno, L., Villringer, A., et al. (2017). The role of dopamine in positive and negative prediction error utilization during incidental learning: Insights from Positron Emission Tomography, Parkinson’s disease and Huntington’s disease. Cortex, 90, 149-162. doi:10.1016/j.cortex.2016.09.004.


Cite as: http://hdl.handle.net/11858/00-001M-0000-002B-7DD2-3
Abstract
Incidental learning of appropriate stimulus-response associations is crucial for optimal functioning within our complex environment. Positive and negative prediction errors (PEs) serve as neural teaching signals within distinct (‘direct’/‘indirect’) dopaminergic pathways to update associations and optimize subsequent behavior. Using a computational reinforcement-learning model, we assessed learning from positive and negative PEs on a probabilistic task (Weather Prediction Task, [WPT]) in three populations that allow different inferences on the role of dopamine (DA) signals: (1) Healthy volunteers that repeatedly underwent [11C]raclopride Positron Emission Tomography, allowing for assessment of striatal DA release during learning, (2) Parkinson’s disease (PD) patients tested both on and off L-DOPA medication, (3) early Huntington’s disease (HD) patients, a disease that is associated with hyper-activation of the ‘direct’ pathway. Our results show that learning from positive and negative feedback on the WPT is intimately linked to different aspects of dopaminergic transmission. In healthy individuals, the difference in [11C]raclopride binding potential (BP) as a measure for striatal DA release was linearly associated with the positive learning rate. Further, asymmetry between baseline DA tone in the left and right ventral striatum was negatively associated with learning from positive PEs. Female patients with early HD exhibited exaggerated learning rates from positive feedback. In contrast, dopaminergic tone predicted learning from negative feedback, as indicated by an inverted-u-shaped association observed with baseline [11C]raclopride BP in healthy controls and the difference between PD patients’ learning rate on and off dopaminergic medication. Thus, the ability to learn from positive and negative feedback is a sensitive marker for the integrity of dopaminergic signal transmission in the ‘direct’ and ‘indirect’ dopaminergic pathways. The present data are interesting beyond clinical context in that imbalances of dopaminergic signaling have not only been observed for neurological and psychiatric conditions but also been proposed for obesity and adolescence.