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  Impaired flexible reward-based decision-making in binge eating disorder: Evidence from computational modeling and functional neuroimaging

Reiter, A., Heinze, H.-J., Schlagenhauf, F., & Deserno, L. (2017). Impaired flexible reward-based decision-making in binge eating disorder: Evidence from computational modeling and functional neuroimaging. Neuropsychopharmacology, 42(3), 628-637. doi:10.1038/npp.2016.95.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002A-A3A8-5 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-BB29-D
Genre: Journal Article

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https://rdcu.be/YmTM (Publisher version)
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 Creators:
Reiter, Andrea1, 2, Author              
Heinze, Hans-Jochen3, 4, Author
Schlagenhauf, Florian1, 2, 5, Author              
Deserno, Lorenz1, 3, 5, Author              
Affiliations:
1Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
2Lifespan Developmental Neuroscience, Department of Psychology, TU Dresden, Germany, ou_persistent22              
3Department of Neurology, Otto von Guericke University Magdeburg, Germany, ou_persistent22              
4Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany, ou_persistent22              
5Department of Psychiatry and Psychotherapy, Charité University Medicine Berlin, Germany, ou_persistent22              

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Free keywords: Addiction, Cognitive control, Computational models, Decision, Functional magnetic resonance imaging, Psychiatric disorders
 Abstract: Despite its clinical relevance and the recent recognition as a diagnostic category in the DSM-5, Binge Eating Disorder (BED) has rarely been investigated from a cognitive neuroscientific perspective targeting a more precise neurocognitive profiling of the disorder. BED patients suffer from a lack of behavioral control during recurrent binge eating episodes and thus, fail to adapt their behavior in the face of negative consequences, eg, high risk for obesity. To examine impairments in flexible reward-based decision-making, we exposed BED patients (n=22) and matched healthy individuals (n=22) to a reward-guided decision-making task during functional resonance imaging (fMRI). Performing fMRI analysis informed via computational modeling of choice behavior, we were able to identify specific signatures of altered decision-making in BED. On the behavioral level, we observed impaired behavioral adaptation in BED, which was due to enhanced switching behavior, a putative deficit in striking a balance between exploration and exploitation appropriately. This was accompanied by diminished activation related to exploratory decisions in the anterior insula/ventro-lateral prefrontal cortex. Moreover, while so-called model-free reward prediction errors remained intact, representation of ventro-medial prefrontal learning signatures, incorporating inference on unchosen options, was reduced in BED, which was associated with successful decision-making in the task. Based on a computational psychiatry account, the presented findings contribute to defining a neurocognitive phenotype of BED.

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Language(s): eng - English
 Dates: 2016-05-112015-11-292016-05-242016-06-152017-02
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1038/npp.2016.95
PMID: 27301429
PMC: PMC5240187
Other: Epub 2016
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Funding organization : Max Planck Society
Project name : -
Grant ID : SCHL1969/1-1 ; SCHL 1969/2-2
Funding program : -
Funding organization : German Research Foundation (DFG)

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Title: Neuropsychopharmacology
Source Genre: Journal
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Pages: - Volume / Issue: 42 (3) Sequence Number: - Start / End Page: 628 - 637 Identifier: ISSN: 0893-133X
CoNE: /journals/resource/954925558485