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Abstracts
  • Stark, R., Zimmermann, M., Kagerer, S., Schienle, A., Walter, B., Weygandt, M., & Vaitl, D. (2007). Hemodynamic brain correlates of disgust and fear ratings. NeuroImage, 37(2), 663–673. https://doi.org/10.1016/j.neuroimage.2007.05.005

    Inconsistent findings from several functional magnetic resonance imaging (fMRI) studies on fear and disgust raise the question which brain regions are relatively specialized and which are general in the processing of these basic emotions. Some of these inconsistencies could partially be due to inter-individual differences in the experience of the applied emotional stimuli. In the present study, we therefore correlated the participants' individual online reports of fear and disgust with their hemodynamic responses towards each of the fear- and disgust-inducing scenes. Sixty six participants (32 females) took part in the fMRI study. In an event-related design, they saw 50 pictures with different emotional impact (10 neutral, 20 disgust-inducing, 20 fear-inducing). Pictures were presented for 4 s and participants rated each picture online - just after the presentation - on the dimensions disgust and fear among others. The results indicate that the processing of disgust- and fear-inducing pictures involves similar as well as distinct brain regions. Both emotional stimulus categories resulted in activations in the extended occipital cortex, in the prefrontal cortex, and in the amygdala. However, insula activations were only significantly correlated with subjective ratings of disgust, pointing to a specific role of this brain structure in the processing of disgust.

  • Hölzel, B. K., Ott, U., Gard, T., Hempel, H., Weygandt, M., Morgen, K., & Vaitl, D. (2008). Investigation of mindfulness meditation practitioners with voxel-based morphometry. Social Cognitive and Affective Neuroscience, 3(1), 55–61. https://doi.org/10.1093/scan/nsm038

    Mindfulness meditators practice the non-judgmental observation of the ongoing stream of internal experiences as they arise. Using voxel-based morphometry, this study investigated MRI brain images of 20 mindfulness (Vipassana) meditators (mean practice 8.6 years; 2 h daily) and compared the regional gray matter concentration to that of non-meditators matched for sex, age, education and handedness. Meditators were predicted to show greater gray matter concentration in regions that are typically activated during meditation. Results confirmed greater gray matter concentration for meditators in the right anterior insula, which is involved in interoceptive awareness. This group difference presumably reflects the training of bodily awareness during mindfulness meditation. Furthermore, meditators had greater gray matter concentration in the left inferior temporal gyrus and right hippocampus. Both regions have previously been found to be involved in meditation. The mean value of gray matter concentration in the left inferior temporal gyrus was predictable by the amount of meditation training, corroborating the assumption of a causal impact of meditation training on gray matter concentration in this region. Results suggest that meditation practice is associated with structural differences in regions that are typically activated during meditation and in regions that are relevant for the task of meditation.

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

    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.

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