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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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Weygandt_2012_Diagnosing.pdf (Verlagsversion), 701KB
 
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 Urheber:
Weygandt, Martin1, Autor
Schaefer, Axel2, Autor
Schienle, Anne2, Autor
Haynes, John-Dylan1, 3, Autor           
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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Schlagwörter: Eating disorders; Bulimia nervosa; Cue reactivity; Classification; Functional magnetic resonance imaging
 Zusammenfassung: 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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Sprache(n): eng - English
 Datum: 2011-02-242010-03-162011-04-182011-08-302012-09
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1002/hbm.21345
PMID: 22887826
Anderer: Epub 2011
 Art des Abschluß: -

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Titel: Human Brain Mapping
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: New York : Wiley-Liss
Seiten: - Band / Heft: 33 (9) Artikelnummer: - Start- / Endseite: 2135 - 2146 Identifikator: ISSN: 1065-9471
CoNE: https://pure.mpg.de/cone/journals/resource/954925601686