RESUMO
Previous research has documented the utility of synchronous neural interactions (SNI) in classifying women veterans with and without posttraumatic stress disorder (PTSD) and other trauma-related outcomes based on functional connectivity using magnetoencephalography (MEG). Here, we extend that line of research to evaluate trauma-specific PTSD neural signatures with MEG in women veterans. Participants completed diagnostic interviews and underwent a task-free MEG scan from which SNI was computed. Thirty-five women veterans were diagnosed with PTSD due to sexual trauma and sixteen with PTSD due to non-sexual trauma. Strength of SNI was compared in women with and without sexual trauma, and linear discriminant analysis was used to classify the brain patterns of women with PTSD due to sexual trauma and non-sexual trauma. Comparison of SNI strength between the two groups revealed widespread hypercorrelation in women with sexual trauma relative to those without sexual trauma. Furthermore, using SNI, the brains of participants were classified as sexual trauma or non-sexual trauma with 100% accuracy. These findings bolster evidence supporting the utility of task-free SNI and suggest that neural signatures of PTSD are trauma-specific.
Assuntos
Transtornos de Estresse Pós-Traumáticos , Veteranos , Encéfalo , Mapeamento Encefálico , Feminino , Humanos , MagnetoencefalografiaRESUMO
Women veterans represent a unique population whose experiences and neurobiology differ from that of their male counterparts. Thus, while previous research has demonstrated the utility of synchronous neural interactions (SNI) as a biomarker of posttraumatic stress disorder (PTSD) in male veterans, the utility of SNI as a biomarker of PTSD in women veterans is unclear. Here we extend that line of research to evaluate classification of women veterans with and without PTSD and other trauma-related outcomes based on functional connectivity using magnetoencephalography (MEG). A total of 121 U.S. women veterans completed diagnostic interviews and underwent a task-free MEG scan from which SNI was computed. Linear discriminant analysis was used to classify PTSD and control groups according to SNI. That discriminant function was then used to classify each individual in the partial recovery and full recovery diagnostic groups as PTSD or control. All individuals were classified correctly (100% accuracy) according to their SNI in their PTSD and control groups. Seventy-seven percent of the full recovery group and 69% of the partial recovery group were classified as control. Individual staging in PTSD recovery was captured by the Mahalanobis D2 distances from the center of the control and PTSD centroid clusters. These findings provide compelling evidence supporting the utility of task-free SNI as a biomarker of PTSD and related outcomes in women veterans.