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Abstract #1190

Neural Network Properties of Combat-Related PTSD

Leslie Yan1

1New York University, NEW YORK, United States

Posttraumatic stress disorder (PTSD) is an anxiety disorder developed after traumatic experience with typical symptoms such as re-experiencing, hyper-arousal and avoidance [1]. Previous neuroimaging studies of PTSD have focused on the abnormal structures and functionality of a few individual brain regions, but have not paid much attention on the connectivity between these structures. Overcoming the limitation of traditional seed-based functional connectivity analysis, the present study used graph theory based analysis approaches to provide an overview of the connectivity in the whole neural network, as well as the properties of the neural network, with resting state fMRI data from trauma-exposed subjects with and without PTSD. The present study used graph theory methods to investigate the network properties of the two groups. Results suggest that the PTSD+ group had decreased amount of connections with weaker connectivity compared to the network of the PTSD- group. Analysis about network properties revealed decreased local cluster coefficients and lower efficiency, with no difference in characteristic path length and small world properties. This approach is very helpful in overcoming the limitation of missing the forest for the trees with traditional approaches and is able to provide an overview about the properties of neural networks.