Project Summary
Posttraumatic stress disorder (PTSD) affects millions of people globally. Existing studies link PTSD
symptoms to cortical structural changes including, for example, thinning in prefrontal and other cortical regions.
Correlations of PTSD changes in different regions of interest (ROIs) suggest involvement of multiple networks.
ROI findings use average measures of thickness across large cortical regions, thus making localization of foci
of thickness changes very difficult. Recent vertex-based work, using measures of thickness beneath individual
vertex surface areas of ~1 mm2, has begun to identify delimited clusters of cortical vertices with focal thinning
in PTSD patients, but associations of changes across vertices remain unstudied. Existing studies of ~300,000
vertices per subject with small sample sizes may lack statistical power, reproducibility and the capacity to
resolve cross vertex relationships. Thus large sample, vertex-based work is arguably needed to advance
understanding of PTSD related cortical thickness changes. This will require innovations in analyses and
transformative changes in approach, because current approaches cannot jointly assess cortical thickness and
network associations from data incorporating hundreds of thousands of vertices per subject in studies involving
thousands of subjects.
With the above rationale, the planned work uses novel approaches, first, to compile the largest existing
database (~19,000 subjects) of vertex-based cortical thickness and associated demographic and comorbid
data for comparing PTSD and non-PTSD subjects and, second, to apply data driven, multi-vertex pattern and
network analysis (MVPNA) to jointly identify localized vertices and distributed networks of vertex clusters that
have associated structural abnormalities which predict PTSD. This work will advance current understanding by:
(1) identifying currently unresolved focal cortical sites of thickness change in PTSD patients, (2) providing
seminal insight into vertex-based patterns of PTSD thickness change networks, and (3) developing new
MVPNA approaches for systematic assessment of cortical vertex data from large samples. The proposed work
will have further implications for basic research and clinical investigation of cortical structural changes that
occur with other psychiatric and neurological disorders.
