Multi-voxel Patterns in Fear Network Regions Predict Clinical Outcome One-year after Cognitive Behavior Therapy for Social Anxiety Disorder: A Support Vector Machine fMRI Study
2014 (English)In: Biological Psychiatry, Elsevier, 2014, 83S-84S p.Conference paper, Abstract (Refereed)
Background: Cognitive behavioral therapy (CBT) has yielded robust treatment effects for social anxiety disorder (SAD) but still many patients do not respond fully to treatment, and a substantial proportion relapse after treatment has ended. Identification of robust predictors of sustained treatment responses could be of high clinical importance. Methods: We used functional magnetic resonance imaging (fMRI; 3T General Electric) to assess 26 patients (85% women, mean age 32.3 years) with SAD. Blood-oxygen-level dependent (BOLD) responses to self-referential criticism, i.e. reading sentences such as “Nobody likes you” were compared to criticism referring to other individuals. Responses in the fear network, i.e. the amygdala, hippocampus, anterior cingulate cortex (ACC), and insula, were evaluated in a Support Vector Machine (SVM) approach to predict treatment outcome one-year after Internet-delivered CBT. We applied leave-one-out cross-validation to increase the generalizability of the data. Results: At one-year follow-up, three patients had dropped out. Twelve (52%) of the assessed patients met the response criteria, i.e. very much or much improved according to the Clinical Global Impression-Improvement scale (CGI-I). SVM on initial BOLD response, accurately classified patients according to responder status, based on multi-voxel patterns in the ACC (balanced accuracy of 91.7%, p=.001, Figure 1), and the ACC together with the amygdala (83.0%, p=.004) as well as the hippocampus (73.9%, p=.032). Conclusions: We demonstrate that initial multi-voxel BOLD response patterns to self-referential criticism in the ACC, amygdala, and hippocampus are highly predictive of long-term improvement of CBT in patients with SAD.
Place, publisher, year, edition, pages
Elsevier, 2014. 83S-84S p.
Research subject Psychology
IdentifiersURN: urn:nbn:se:umu:diva-94685OAI: oai:DiVA.org:umu-94685DiVA: diva2:755575
69th Annual Scientific Convention and Meeting of the Society-of-Biological-Psychiatry, May 8-10, 2014, New York