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Neuroimage. 2012 Apr 2;60(2):1186-93. doi: 10.1016/j.neuroimage.2012.01.064. Epub 2012 Jan 17.

fMRI pattern recognition in obsessive-compulsive disorder.

Author information

1
Bernstein Center for Computational Neuroscience Berlin, Charité-Universitätsmedizin Berlin, Germany.

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=3s) 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.

[Indexed for MEDLINE]

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