Comorbid psychiatric disorders, such as anxiety disorders and major depressive disorders (MDD), are very common among military traumatic brain injury (TBI) personnel [Maller 10]. However, the underlying mechanisms are not well understood. The goal of this study is to identify relationships between brain microstructural changes and network connectivity in military TBI patients.Participants and Imaging acquisition Participants included 130 male active military service members diagnosed with mild TBI (mTBI) (age 34.7±7.8 years old) and 53 male non-TBI controls (age 31.9±8.3 years old) who underwent a series of MRI exams including structural MRI, diffusion weighted imaging (DWI) and resting fMRI on a 3T MRI scanner (GE 750), with approval of IRB review and HIPPA compliance. Depression symptoms was rated based on self-report questionnaires, the Beck Depression Inventory (BDI). Subjects with a BDI score greater than 20 are considered to have moderate to severe depression symptoms, and less than 19 is considered mild or minimal. Image analysis Preprocessing of DWI included distortion correction, intra-subject registration of the individual DWIs to the structural T1w image, then to a common template space, the creation of cortical and WM masks from FreeSurfer reconstructions. Global probabilistic tractography was performed using TRACULA [Yendiki 11] to reconstruct major white matter tracts followed by extraction of diffusion tensor imaging (DTI) metrics. For structural network models, Constrained Spherical Deconvolution [Tournier 07], and a probabilisitic streamlines algorithm [Tournier 12], was used to resolve fiber-crossing. Both generalized fractional anisotropy (gFA)-weighted and tract number (TN)-weighted connectivity matrices were constructed using whole brain fiber tracking followed by nodal masking (Automated Anatomical Labeling (AAL) template) and reconstruction of gFA- and TN-weighted adjacency matrices. Preprocessing of rsfMRI included distortion and motion correction, T1w coregistration, high pass filtering and spatial smoothing. Default-mode network (DMN), salience network and fronto-parietal network [Fox 05)] were identified using probabilistic ICA (FSL MELODIC) [Beckmann 05]. Statistical analysis Linear mixed model was applied to assess the role of severity of depression in regional white matter integrity after taking age into account (corrected p < 0.05). Network Based Statistics (NBS) [Zaleske 12], a nonparametric statistical test was used to isolate the components of an N x N undirected gFA and TN-weighted connectivity matrices, e.g. that differ significantly between non-TBI, mild and moderate to severe MDD-TBI populations (corrected p < 0.05). For exploring difference of DMN connectivity among groups, the set of spatial maps from the group-average analysis was used to generate subject-specific versions of the spatial maps, and associated time series, using dual regression [Beckmann 09]. We then tested for group differences between non-TBI, mild and moderate to severe MDD-TBI using permutation test (FSL randomise) (corrected p < 0.05). Among 130 mTBI participants, 75 of them were classified as moderate to severe depression. Fig. 1 illustrates an example of segmented fiber tracts from one TBI participant. When comparing between groups, moderate to severe MDD TBI group had lower FA than mild depression mTBI group over the hippocampal branch of the right cingulum bundle, and both of the temporal and parietal braches of the right superior longitudinal fasciculus. NBS found both mTBI groups had lower TN-weighted nodal connectivity over the parietal-temporal-occipital networks than non-TBI group (not shown), and MDD mTBI group had lower gFA-weighted connectivity than minimal MDD TBI population over the parietal-cerebellar nodal connection (Fig. 2, right precuneus gyrus highlighted as red). In addition, non-parametric permutation testing revealed significantly increased left cingulate involvement in the fronto-parietal network in moderate to severe MDD mTBI population relative to non-TBI controls (Fig. 3). Our results suggest that disrupted neurocircuitry, particularly the cognitive-emotional pathways, such as the cingulum bundle interconnecting frontal cortex, parietal cortex and limbic system, play an important role in the comorbidity of MDD-TBI spectrum disorders.