Home
Scholarly Works
Large-scale functional hyperconnectivity patterns...
Journal article

Large-scale functional hyperconnectivity patterns in trauma-related dissociation: an rs-fMRI study of PTSD and its dissociative subtype

Abstract

The dissociative subtype of post-traumatic stress disorder (PTSD) is a distinct PTSD phenotype characterized by trauma-related dissociation, alongside unique patterns of functional connectivity. However, disparate findings across multiple scales of investigation have highlighted the need for a cohesive understanding of dissociative neurobiology. We took a step towards this goal by conducting one of the broadest region of interest (ROI)-to-ROI analyses performed on a PTSD population to date. In this retrospective study, we investigated resting-state functional MRI data collected from a total of 192 participants, 134 of whom were diagnosed with PTSD. Small functional connectivity differences (maximum effect size 0.27) were found between participants with PTSD and controls in the temporal regions and the right frontoparietal network. Participants with the dissociative subtype showed a markedly different pattern of widespread functional hyperconnectivity compared with controls (maximum effect size 0.46), spanning subcortical regions, sensorimotor and other intrinsic connectivity networks. Furthermore, analysis of latent dimensions underlying both ROI-to-ROI brain results and a range of behavioral and clinical measures identified three clinically relevant latent dimensions—two linked to dissociation and one linked to PTSD symptoms. These results advance our understanding of dissociative neurobiology, characterizing it as a divergence from normative small-world organization. These patterns of hyperconnectivity are thought to serve a compensatory function to preserve global brain functioning in participants experiencing trauma-related dissociation.

Authors

Shaw SB; Terpou BA; Densmore M; Théberge J; Frewen P; McKinnon MC; Lanius RA

Journal

Nature Mental Health, Vol. 1, No. 10, pp. 711–721

Publisher

Springer Nature

Publication Date

October 1, 2023

DOI

10.1038/s44220-023-00115-y

ISSN

2731-6076
View published work (Non-McMaster Users)

Contact the Experts team