title: The Feedback-related Negativity Codes Components of Abstract Inference during Reward-based Decision-making.
abstract: Behavioral control is influenced not only by learning from the choices made and the rewards obtained but also by "what might have happened," that is, inference about unchosen options and their fictive outcomes. Substantial progress has been made in understanding the neural signatures of direct learning from choices that are actually made and their associated rewards via reward prediction errors (RPEs). However, electrophysiological correlates of abstract inference in decision-making are less clear. One seminal theory suggests that the so-called feedback-related negativity (FRN), an ERP peaking 200-300 msec after a feedback stimulus at frontocentral sites of the scalp, codes RPEs. Hitherto, the FRN has been predominantly related to a so-called "model-free" RPE: The difference between the observed outcome and what had been expected. Here, by means of computational modeling of choice behavior, we show that individuals employ abstract, "double-update" inference on the task structure by concurrently tracking values of chosen stimuli (associated with observed outcomes) and unchosen stimuli (linked to fictive outcomes). In a parametric analysis, model-free RPEs as well as their modification because of abstract inference were regressed against single-trial FRN amplitudes. We demonstrate that components related to abstract inference uniquely explain variance in the FRN beyond model-free RPEs. These findings advance our understanding of the FRN and its role in behavioral adaptation. This might further the investigation of disturbed abstract inference, as proposed, for example, for psychiatric disorders, and its underlying neural correlates.
authors.affiliation: Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.|University of Leipzig.|Technische Universität Dresden.
authors.forename: Andrea M F
authors.initials: AM
authors.lastname: Reiter
authors.affiliation: Charité-Universitätsmedizin Berlin.
authors.forename: Stefan P
authors.initials: SP
authors.lastname: Koch
authors.affiliation: University of Leipzig.
authors.forename: Erich
authors.initials: E
authors.lastname: Schröger
authors.affiliation: Leibniz Institute for Neurobiology, Magdeburg, Germany.|Otto-von-Guericke University Magdeburg.
authors.forename: Hermann
authors.initials: H
authors.lastname: Hinrichs
authors.affiliation: Leibniz Institute for Neurobiology, Magdeburg, Germany.|Otto-von-Guericke University Magdeburg.
authors.forename: Hans-Jochen
authors.initials: HJ
authors.lastname: Heinze
authors.affiliation: Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.|Charité-Universitätsmedizin Berlin.|Otto-von-Guericke University Magdeburg.
authors.forename: Lorenz
authors.initials: L
authors.lastname: Deserno
authors.affiliation: Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.|Charité-Universitätsmedizin Berlin.
authors.forename: Florian
authors.initials: F
authors.lastname: Schlagenhauf
mesh_terms: D000328:Adult; D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D003657:Decision Making / Q000502:physiology*; D004569:Electroencephalography; D005071:Evoked Potentials; D030141:Feedback, Psychological / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D008960:Models, Psychological; D009483:Neuropsychological Tests; D012201:Reward; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult