Modeling of reward-regulated learning impairment in alchohol addiction

Abstract

Event Abstract Back to Event Modeling of reward-regulated learning impairment in alchohol addiction Sinem Balta Beylergil1*, Anne Beck2, Florian Schlagenhauf2, Michael Rapp2, Klaus Obermayer1 and Andreas Heinz2 1 Bernstein Center for Computational Neuroscience, Germany 2 Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Germany Alcohol addiction is characterized by compulsive and uncontrolled consumption of alcohol despite its adverse consequences. It is known from previous studies that alcohol-dependent individuals have difficulties in integrating reinforcements to guide future behavior. Main causes of these difficulties might be abnormal computation of reward prediction errors (PEs) and inability to update the value of behavioral options. In this study the aim is modeling the performances of 37 alcohol-dependent patients and 41 healthy controls in a two-alternative forced choice probabilistic reversal task. The subjects first have to learn which of the two choices is more rewarding, and then flexibly switch their choices when reward-contingencies change. We hypothesize that behavioral data of experimental and control groups will have distinct computational models showing discrepancy between their learning patterns. The choice behavior trace of each individual is modeled using Rescorla-Wagner reinforcement theory. The model is optimized with respect to maximum log-likelihood estimate (MLE) such that minimum MLE ensures the best fit of the model to the data. Individual-specific model fitting parameters are derived from the best fitting model in order to show experimental group members might have difficulties in adapting dynamic reward contingencies. Expected values and PEs are generated using these model parameters and convolved with haemodynamic response function (HRF) to generate regressors used in parametrical fMRI analysis. This combined neuroimaging and computational modeling approach lets us demonstrate reward-regulated learning impairment in alcohol-dependent subjects compared to healthy controls. Funding: Deutsche Forschungsgemeinschaft (DFG). Keywords: Alchohol addiction, decision-making Conference: XI International Conference on Cognitive Neuroscience (ICON XI), Palma, Mallorca, Spain, 25 Sep - 29 Sep, 2011. Presentation Type: Poster Presentation Topic: Poster Sessions: Decision Making, Reward Processing & Response Selection Citation: Balta Beylergil S, Beck A, Schlagenhauf F, Rapp M, Obermayer K and Heinz A (2011). Modeling of reward-regulated learning impairment in alchohol addiction. Conference Abstract: XI International Conference on Cognitive Neuroscience (ICON XI). doi: 10.3389/conf.fnhum.2011.207.00367 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 23 Nov 2011; Published Online: 28 Nov 2011. * Correspondence: Dr. Sinem Balta Beylergil, Bernstein Center for Computational Neuroscience, Berlin, Germany, sinembalta@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Sinem Balta Beylergil Anne Beck Florian Schlagenhauf Michael Rapp Klaus Obermayer Andreas Heinz Google Sinem Balta Beylergil Anne Beck Florian Schlagenhauf Michael Rapp Klaus Obermayer Andreas Heinz Google Scholar Sinem Balta Beylergil Anne Beck Florian Schlagenhauf Michael Rapp Klaus Obermayer Andreas Heinz PubMed Sinem Balta Beylergil Anne Beck Florian Schlagenhauf Michael Rapp Klaus Obermayer Andreas Heinz Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.