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  Enhanced go and nogo learning in individuals with obesity

Kube, J., Wiencke, K., Hahn, S., Villringer, A., & Neumann, J. (2020). Enhanced go and nogo learning in individuals with obesity. Frontiers in Behavioral Neuroscience, 14: 15. doi:10.3389/fnbeh.2020.00015.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0005-EA42-9 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-EA43-8
Genre: Journal Article

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 Creators:
Kube, Jana1, 2, 3, Author              
Wiencke, Kathleen1, 2, Author
Hahn, Sandra1, Author
Villringer, Arno1, 2, 4, 5, Author              
Neumann, Jane1, 2, 6, Author              
Affiliations:
1Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
2Integrated Research and Treatment Center Adiposity Diseases, University of Leipzig, Germany, ou_persistent22              
3Faculty of Business, Law and Social Sciences, Brandenburg University of Technology, Senftenberg, Germany, ou_persistent22              
4Clinic for Cognitive Neurology, University of Leipzig, Germany, ou_persistent22              
5Berlin School of Mind and Brain, Humboldt University Berlin, Germany, ou_persistent22              
6Department of Medical Engineering and Biotechnology, University of Applied Sciences, Jena, Germany, ou_persistent22              

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Free keywords: Obesity; Prediction error; Reinforcement learning; Instrumental; Pavlovian
 Abstract: Overeating in individuals with obesity is hypothesized to be partly caused by automatic action tendencies to food cues that have the potential to override goal-directed dietary restriction. Individuals with obesity are often characterized by alterations in the processing of such rewarding food, but also of non-food stimuli, and previous research has suggested a stronger impact on the execution of goal-directed actions in obesity. Here, we investigated whether Pavlovian cues can also corrupt the learning of new approach or withdrawal behavior in individuals with obesity. We employed a probabilistic Pavlovian-instrumental learning paradigm in which participants (29 normal-weight and 29 obese) learned to actively respond (Go learning) or withhold a response (NoGo learning) in order to gain monetary rewards or avoid losses. Participants were better at learning active approach responses (Go) in the light of anticipated rewards and at learning to withhold a response (NoGo) in the light of imminent punishments. Importantly, there was no evidence for a stronger corruption of instrumental learning in individuals with obesity. Instead, they showed better learning across conditions than normal-weight participants. Using a computational reinforcement learning model, we additionally found an increased learning rate in individuals with obesity. Previous studies have mostly reported a lower reinforcement learning performance in individuals with obesity. Our results contradict this and suggest that their performance is not universally impaired: Instead, while previous studies found reduced stimulus-value learning, individuals with obesity may show better action-value learning. Our findings highlight the need for a broader investigation of behavioral adaptation in obesity across different task designs and types of reinforcement learning.

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Language(s): eng - English
 Dates: 2019-04-072020-01-222020-02-14
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.3389/fnbeh.2020.00015
Other: eCollection
PMID: 32116595
PMC: PMC7033453
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Title: Frontiers in Behavioral Neuroscience
  Abbreviation : Front Behav Neurosci
Source Genre: Journal
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Publ. Info: Lausanne, Switzerland : Frontiers Research Foundation
Pages: - Volume / Issue: 14 Sequence Number: 15 Start / End Page: - Identifier: ISSN: 1662-5153
CoNE: https://pure.mpg.de/cone/journals/resource/1662-5153