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  Diagnosing different binge-eating disorders based on reward-related brain activation patterns

Weygandt, M., Schaefer, A., Schienle, A., & Haynes, J.-D. (2012). Diagnosing different binge-eating disorders based on reward-related brain activation patterns. Human Brain Mapping, 33(9), 2135-2146. doi:10.1002/hbm.21345.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000E-B67C-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-FAC3-7
Genre: Journal Article

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Weygandt_2012_Diagnosing.pdf (Publisher version), 701KB
 
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 Creators:
Weygandt, Martin1, Author
Schaefer, Axel2, Author
Schienle, Anne2, Author
Haynes, John-Dylan1, 3, Author              
Affiliations:
1Bernstein Center for Computational Neuroscience, Berlin, Germany, ou_persistent22              
2Department of Clinical Psychology, Institute of Psychology, Karl Franzens University, Graz, Austria, ou_persistent22              
3Max Planck Fellow Research Group Attention and Awareness, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634553              

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Free keywords: Eating disorders; Bulimia nervosa; Cue reactivity; Classification; Functional magnetic resonance imaging
 Abstract: This study addresses how visual food cues are encoded in reward related brain areas and whether this encoding might provide information to differentiate between patients suffering from eating disorders [binge-eating disorder (BED) and bulimia nervosa (BN)], overweight controls (C-OW), and normal-weight controls (C-NW). Participants passively viewed pictures of food stimuli and neutral stimuli in a cue reactivity design. Two classification analyses were conducted. First, we used multivariate pattern recognition techniques to decode the category of a currently viewed picture from local brain activity patterns. In the second analysis, we applied an ensemble classifier to predict the clinical status of subjects (BED, BN, C-OW, and C-NW) based on food-related brain response patterns. The left insular cortex separated between food and neutral contents in all four groups. Patterns in the right insular cortex provided a maximum diagnostic accuracy for the separation of BED patients and C-NW (86% accuracy, P < 10−5, 82% sensitivity, and 90% specificity) as well as BN patients and C-NW (78% accuracy, P = 0.001, 86% sensitivity, and 70% specificity). The right ventral striatum separated maximally between BED patients and C-OW (71% accuracy, P = 0.013, 59% sensitivity, and 82% specificity). The right lateral orbitofrontal cortex separated maximally between BN patients and C-OW (86% accuracy, P < 10−4, 79% sensitivity, and 94% specificity). The best differential diagnostic separation between BED and BN patients was obtained in the left ventral striatum (84% accuracy, P < 10−3, 82% sensitivity, and 86% specificity). Our results indicate that pattern recognition techniques are able to contribute to a reliable differential diagnosis of BN and BED.

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Language(s): eng - English
 Dates: 2011-02-242010-03-162011-04-182011-08-302012-09
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1002/hbm.21345
PMID: 22887826
Other: Epub 2011
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Title: Human Brain Mapping
Source Genre: Journal
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Publ. Info: New York : Wiley-Liss
Pages: - Volume / Issue: 33 (9) Sequence Number: - Start / End Page: 2135 - 2146 Identifier: ISSN: 1065-9471
CoNE: https://pure.mpg.de/cone/journals/resource/954925601686