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Psychophysiology. 2019 Sep 10:e13472. doi: 10.1111/psyp.13472. [Epub ahead of print]

PTSD and its dissociative subtype through the lens of the insula: Anterior and posterior insula resting-state functional connectivity and its predictive validity using machine learning.

Author information

1
Department of Neuroscience, Western University, London, Ontario, Canada.
2
Department of Psychiatry, Western University, London, Ontario, Canada.
3
Imaging Division, Lawson Health Research Institute, London, Ontario, Canada.
4
Department of Psychological Research and Research Methods, University of Vienna, Vienna, Austria.
5
Mood Disorders Program, St. Joseph's Healthcare, Hamilton, Ontario, Canada.
6
Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.
7
Homewood Research Institute, Guelph, Ontario, Canada.
8
Department of Medical Imaging, Western University, London, Ontario, Canada.
9
Department of Medical Biophysics, Western University, London, Ontario, Canada.
10
Department of Diagnostic Imaging, St. Joseph's Healthcare, London, Ontario, Canada.
11
Department of Psychology, Western University, London, Ontario, Canada.

Abstract

Individuals with post-traumatic stress disorder (PTSD) typically experience states of reliving and hypervigilance; however, the dissociative subtype of PTSD (PTSD+DS) presents with additional symptoms of depersonalization and derealization. Although the insula is critical to emotion processing, its association with these contrasting symptom profiles is yet to be fully delineated. Accordingly, we investigated insula subregion resting-state functional connectivity patterns among individuals with PTSD, PTSD+DS, and healthy controls. Using SPM12 and PRONTO software, we implemented a seed-based resting-state functional connectivity approach, along with multiclass Gaussian process classification machine learning, respectively, in order to evaluate unique patterns and the predictive validity of insula subregion connectivity among individuals with PTSD (n = 84), PTSD+DS (n = 49), and age-matched healthy controls (n = 51). As compared to PTSD and PTSD+DS, healthy controls showed increased right anterior and posterior insula connectivity with frontal lobe structures. By contrast, PTSD showed increased bilateral posterior insula connectivity with subcortical structures, including the periaqueductal gray. Strikingly, as compared to PTSD and controls, PTSD+DS showed increased bilateral anterior and posterior insula connectivity with posterior cortices, including the left lingual gyrus and the left precuneus. Moreover, machine learning analyses were able to classify PTSD, PTSD+DS, and controls using insula subregion connectivity patterns with 80.4% balanced accuracy (p < .01). These findings suggest a neurobiological distinction between PTSD and its dissociative subtype with regard to insula subregion functional connectivity patterns. Furthermore, machine learning algorithms were able to utilize insula resting-state connectivity patterns to discriminate between participant groups with high predictive accuracy.

KEYWORDS:

dissociative subtype; emotion dysregulation; fMRI; insula; machine learning; post-traumatic stress disorder; rsFC

PMID:
31502268
DOI:
10.1111/psyp.13472

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