1. Monetary feedback modulates performance and electrophysiological indices of belief updating in reward learning
- Author
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Karen Sasmita, Carsten Murawski, Stefan Bode, Ryan T. Maloney, and Daniel Bennett
- Subjects
Male ,Formative Feedback ,Cognitive Neuroscience ,Inference ,Experimental and Cognitive Psychology ,Bayesian inference ,050105 experimental psychology ,Task (project management) ,Error-related negativity ,Formative assessment ,Young Adult ,03 medical and health sciences ,Bayes' theorem ,P3a ,0302 clinical medicine ,Reward ,Developmental Neuroscience ,Humans ,0501 psychology and cognitive sciences ,Evoked Potentials ,Biological Psychiatry ,Endocrine and Autonomic Systems ,General Neuroscience ,05 social sciences ,Uncertainty ,Brain ,Bayes Theorem ,Electroencephalography ,Cognition ,Neuropsychology and Physiological Psychology ,Neurology ,Female ,Psychology ,Psychomotor Performance ,030217 neurology & neurosurgery ,Cognitive psychology - Abstract
Belief updating entails the incorporation of new information about the environment into internal models of the world. Bayesian inference is the statistically optimal strategy for performing belief updating in the presence of uncertainty. An important open question is whether the use of cognitive strategies that implement Bayesian inference is dependent upon motivational state and, if so, how this is reflected in electrophysiological signatures of belief updating in the brain. Here, we recorded the EEG of participants performing a simple reward learning task with both monetary and nonmonetary instructive feedback conditions. Our aim was to distinguish the influence of the rewarding properties of feedback on belief updating from the information content of the feedback itself. A Bayesian updating model allowed us to quantify different aspects of belief updating across trials, including the size of belief updates and the uncertainty of beliefs. Faster learning rates were observed in the monetary feedback condition compared to the instructive feedback condition, while belief updates were generally larger, and belief uncertainty smaller, with monetary compared to instructive feedback. Larger amplitudes in the monetary feedback condition were found for three ERP components: the P3a, the feedback-related negativity, and the late positive potential. These findings suggest that motivational state influences inference strategies in reward learning, and this is reflected in the electrophysiological correlates of belief updating.
- Published
- 2019
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