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Abstract #0511

Investigating Brain Connectomic Alterations in PTSD and PCS using the Reproducibility of Independent Components obtained from Resting-State Functional MRI Data

Mohammed Syed1, D Rangaprakash2,3, Michael N Dretsch4,5, Thomas S Denney2,6,7, Jeffrey S Katz2,6,7, and Gopikrishna Deshpande2,6,7

1Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, United States, 2AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, United States, 3Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States, 4Human Dimension Division, HQ TRADOC, Fort Eustis, Fort Eustis, VA, United States, 5U.S. Army Aeromedical Research Laboratory, Fort Rucker, Fort Rucker, AL, United States, 6Department of Psychology, Auburn University, Auburn, AL, United States, 7Alabama Advanced Imaging Consortium, Auburn University and University of Alabama Birmingham, Birmingham, AL, United States

Posttraumatic stress disorder (PTSD) and Post-concussion syndrome (PCS) are heterogeneous neurological disorders where fMRI connectivity metrics derived from them may not be highly reproducible, leading to poor generalizability and consequently lower classification accuracies. We present a method that characterizes the reproducibility of networks using ‘generalized Ranking and Averaging Independent Component Analysis by Reproducibility’ (gRAICAR) algorithm followed by unsupervised clustering to discriminate between the groups based on functional brain networks that are most reproducible within PTSD, PCS, and healthy control groups separately. We identify dorsolateral prefrontal cortex, inferior parietal lobule, caudate and medial prefrontal cortex as regions within the most reproducible independent components.

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