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.