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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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 Creators:
Weygandt, Martin1, Author
Blecker, Carlo R.2, Author
Schäfer, Axel3, Author
Hackmack, Kerstin1, Author
Haynes, John-Dylan1, 4, Author           
Vaitl, Dieter2, Author
Stark, Rudolf2, 5, Author
Schienle, Anne6, Author
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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Free keywords: Pattern recognition; Obsessive–compulsive disorder; Functional magnetic resonance imaging
 Abstract: 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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Language(s): eng - English
 Dates: 2011-12-122011-07-012012-01-082012-01-172012-04-02
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2012.01.064
PMID: 22281674
Other: Epub 2012
 Degree: -

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 60 (2) Sequence Number: - Start / End Page: 1186 - 1193 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166