McLean Hospital/Harvard Medical School Belmont, MA, United States
Abstract Background: Assessment of trauma-related dissociation has been historically challenging given its subjective nature and the lack of provider education around this topic. Recent work identified a promising neural biomarker of trauma-related dissociation, representing a significant step toward improved assessment and identification of dissociation. However, it is necessary to better understand clinical factors that may be associated with this biomarker. Therefore, across several analyses, we explored patterns of psychopathology linked to this biomarker to better understand this neural signature of dissociation.
Method: Data were drawn from a previously published work that identified a model predicting Multidimensional Inventory of Dissociation severe pathological dissociation score on the basis of neural functional connectivity (i.e., neural signature of dissociation). Participants were 65 women with histories of childhood maltreatment, posttraumatic stress disorder and varying levels of dissociation (e.g., co-occurring dissociative identity disorder). We conducted a k-means cluster analysis to understand patterns in the predictive model and also investigated patterns in the neural signature of dissociation.
Results: The cluster analysis identified four distinct groups, which differed on key clinical variables, including distribution of diagnoses. Both clusters 2 and 3 were largely comprised of participants with dissociative identity disorder (cluster 2 86%, cluster 3 67%), however, the predictive model best predicted those in cluster 3. Follow up analyses revealed that participants with dissociative identity disorder in cluster 3 reported higher levels of self-state intrusions, a type of dissociation specific to dissociative identity disorder, than those in cluster 2. Given that the distribution of diagnoses differed across the identified clusters, we next explored patterns in the neural signature of dissociation based on diagnostic group. We examined each of the 13 links comprising the signature to understand group differences. Preliminary analyses indicate group differences in the functional connectivity of several regions comprising the neural signature of dissociation, particularly within the frontoparietal control network.
Conclusion: Taken together, the present results suggest that the performance of the predictive model is linked with a type of dissociation that is specific to dissociative identity disorder (i.e., self-state intrusions) and the functional connectivity of specific regions may be most contributory. Future work will continue the exploration of the identified neural signature of dissociation in the hopes of ultimately contributing to improved assessment and treatment of dissociation.
