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  fMRI pattern recognition in obsessive–compulsive disorder

Weygandt, M., Blecker, C. R., Schäfer, A., Hackmack, K., Haynes, J.-D., Vaitl, D., et al. (2012). fMRI pattern recognition in obsessive–compulsive disorder. NeuroImage, 60(2), 1186-1193. doi:10.1016/j.neuroimage.2012.01.064.

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 Urheber:
Weygandt, Martin1, Autor
Blecker, Carlo R.2, Autor
Schäfer, Axel3, Autor
Hackmack, Kerstin1, Autor
Haynes, John-Dylan1, 4, Autor           
Vaitl, Dieter2, Autor
Stark, Rudolf2, 5, Autor
Schienle, Anne6, Autor
Affiliations:
1Bernstein Center for Computational Neuroscience, Berlin, Germany, ou_persistent22              
2Bender Institute of Neuroimaging, Justus Liebig University, Giessen, Germany, ou_persistent22              
3Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Germany, ou_persistent22              
4Max Planck Fellow Research Group Attention and Awareness, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634553              
5Department of Clinical and Physiological Psychology, Justus Liebig University, Giessen, Germany, ou_persistent22              
6Department of Clinical Psychology, Institute of Psychology, Karl Franzens University, Graz, Austria, ou_persistent22              

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Schlagwörter: Pattern recognition; Obsessive–compulsive disorder; Functional magnetic resonance imaging
 Zusammenfassung: Patients suffering from obsessive–compulsive disorder (OCD) are characterized by dysregulated neuronal processing of disorder-specific and also unspecific affective stimuli. In the present study, we investigated whether generic fear-inducing, disgust-inducing, and neutral stimuli can be decoded from brain patterns of single fMRI time samples of individual OCD patients and healthy controls. Furthermore, we tested whether differences in the underlying encoding provide information to classify subjects into groups (OCD patients or healthy controls). Two pattern classification analyses were conducted. In analysis 1, we used a classifier to decode the category of a currently viewed picture from extended fMRI patterns of single time samples (TR = 3 s) in individual subjects for several pairs of categories. In analysis 2, we used a searchlight approach to predict subjects' diagnostic status based on local brain patterns. In analysis 1, we obtained significant accuracies for the separation of fear-eliciting from neutral pictures in OCD patients and healthy controls. Separation of disgust-inducing from neutral pictures was significant in healthy controls. In analysis 2, we identified diagnostic information for the presence of OCD in the orbitofrontal cortex, and in the caudate nucleus. Accuracy obtained in these regions was 100% (p < 10− 6). To summarize our findings, by using multivariate pattern classification techniques we were able to identify neurobiological markers providing reliable diagnostic information about OCD. The classifier-based fMRI paradigms proposed here might be integrated in future diagnostic procedures and treatment concepts.

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Sprache(n): eng - English
 Datum: 2011-12-122011-07-012012-01-082012-01-172012-04-02
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1016/j.neuroimage.2012.01.064
PMID: 22281674
Anderer: Epub 2012
 Art des Abschluß: -

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Titel: NeuroImage
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: Orlando, FL : Academic Press
Seiten: - Band / Heft: 60 (2) Artikelnummer: - Start- / Endseite: 1186 - 1193 Identifikator: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166