Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Biological embedding of early trauma: the role of higher prefrontal synaptic strength.

Background: Early trauma predicts poor psychological and physical health. Glutamatergic synaptic processes offer one avenue for understanding this relationship, given glutamate's abundance and involvement in reward and stress sensitivity, emotion, and learning. Trauma-induced glutamatergic excitotoxicity may alter neuroplasticity and approach/avoidance tendencies, increasing risk for psychiatric disorders. Studies examine upstream or downstream effects instead of glutamatergic synaptic processes in vivo, limiting understanding of how trauma affects the brain.Objective: In a pilot study using a previously published data set, we examine associations between early trauma and a proposed measure of synaptic strength in vivo in one of the largest human samples to undergo Carbon-13 (13C MRS) magnetic resonance spectroscopy. Participants were 18 healthy controls and 16 patients with PTSD (male and female).Method: Energy per cycle (EPC), which represents the ratio of neuronal oxidative energy production to glutamate neurotransmitter cycling, was generated as a putative measure of glutamatergic synaptic strength.Results: Results revealed that early trauma was positively correlated with EPC in individuals with PTSD, but not in healthy controls. Increased synaptic strength was associated with reduced behavioural inhibition, and EPC showed stronger associations between reward responsivity and early trauma for those with higher EPC.Conclusion: In the largest known human sample to undergo 13C MRS, we show that early trauma is positively correlated with EPC, a direct measure of synaptic strength. Our study findings have implications for pharmacological treatments thought to impact synaptic plasticity, such as ketamine and psilocybin.

Abnormalities in the strength of synaptic connections have been implicated in trauma and trauma-related disorders but not directly examined.We used magnetic resonance spectroscopy to investigate the association between early trauma and an in vivo measure of synaptic strength.For people with posttraumatic stress disorder, as early trauma severity increased, synaptic strength increased, highlighting the potential for treatments thought to change synaptic connections in trauma-related disorders.

The potential of ketamine for posttraumatic stress disorder: a review of clinical evidence.

Posttraumatic stress disorder (PTSD) is a devastating condition, for which there are few pharmacological agents, often with a delayed onset of action and poor efficacy. Trauma-focused psychotherapies are further limited by few trained providers and low patient engagement. This frequently results in disease chronicity as well as psychiatric and medical comorbidity, with considerable negative impact on quality of life. As such, off-label interventions are commonly used for PTSD, particularly in chronic refractory cases. Ketamine, an N-methyl-D-aspartate (NDMA) receptor antagonist, has recently been indicated for major depression, exhibiting rapid and robust antidepressant effects. It also shows transdiagnostic potential for an array of psychiatric disorders. Here, we synthesize clinical evidence on ketamine in PTSD, spanning case reports, chart reviews, open-label studies, and randomized trials. Overall, there is high heterogeneity in clinical presentation and pharmacological approach, yet encouraging signals of therapeutic safety, efficacy, and durability. Avenues for future research are discussed.

Prefrontal Glutamate Neurotransmission in PTSD: A Novel Approach to Estimate Synaptic Strength in Vivo in Humans.

Background: Trauma and chronic stress are believed to induce and exacerbate psychopathology by disrupting glutamate synaptic strength. However, in vivo in human methods to estimate synaptic strength are limited. In this study, we established a novel putative biomarker of glutamatergic synaptic strength, termed energy-per-cycle (EPC). Then, we used EPC to investigate the role of prefrontal neurotransmission in trauma-related psychopathology. Methods: Healthy controls (n = 18) and patients with posttraumatic stress (PTSD; n = 16) completed 13C-acetate magnetic resonance spectroscopy (MRS) scans to estimate prefrontal EPC, which is the ratio of neuronal energetic needs per glutamate neurotransmission cycle (VTCA/VCycle). Results: Patients with PTSD were found to have 28% reduction in prefrontal EPC (t = 3.0; df = 32, P = .005). There was no effect of sex on EPC, but age was negatively associated with prefrontal EPC across groups (r = -0.46, n = 34, P = .006). Controlling for age did not affect the study results. Conclusion: The feasibility and utility of estimating prefrontal EPC using 13C-acetate MRS were established. Patients with PTSD were found to have reduced prefrontal glutamatergic synaptic strength. These findings suggest that reduced glutamatergic synaptic strength may contribute to the pathophysiology of PTSD and could be targeted by new treatments.

mTORC1 inhibitor effects on rapid ketamine-induced reductions in suicidal ideation in patients with treatment-resistant depression.

Suicide is a public health crisis with limited treatment options. Ketamine has demonstrated rapid and robust improvements in suicidal ideation (SI). The parent study for the secondary pilot analyses presented here was a double-blind, cross-over trial that found pretreatment with the mechanistic target of rapamycin complex 1 (mTORC1) prolonged the antidepressant effects of ketamine. Here we examined the effect of mTORC1 inhibition on ketamine's antisuicidal effects. Twenty patients in a major depressive episode were randomized to pretreatment with oral rapamycin (6 mg) or placebo prior to IV ketamine (0.5 mg/kg). We found ketamine administration resulted in significant improvements across all measures with the largest effect at 24 h with only the Beck Scale for Suicide remaining significant at the two-week follow-up. There were no significant main effects of pretreatment. While these analyses are pilot in nature and overall severity of SI was relatively low, the antisuicidal findings (no effect of rapamycin) being in contrast to the antidepressant effects (prolonged effect with rapamycin), suggest the rapid-acting antisuicidal and antidepressant effects of ketamine may be mechanistically distinct and the trajectories of response, recovery, and relapse may be independent. These findings provide additional evidence of ketamine's antisuicidal effects and highlight the importance of future studies that continue to examine potential differences in mechanisms and trajectory of outcomes.

Transcranial direct current stimulation targeting the medial prefrontal cortex modulates functional connectivity and enhances safety learning in obsessive-compulsive disorder: Results from two pilot studies.

BACKGROUND: Exposed-based psychotherapy is a mainstay of treatment for obsessive-compulsive disorder (OCD) and anxious psychopathology. The medial prefrontal cortex (mPFC) and the default mode network (DMN), which is anchored by the mPFC, promote safety learning. Neuromodulation targeting the mPFC might augment therapeutic safety learning and enhance response to exposure-based therapies. METHODS: To characterize the effects of mPFC neuromodulation on functional connectivity, 17 community volunteers completed resting-state functional magnetic resonance imaging scans before and after 20 min of frontopolar anodal multifocal transcranial direct current stimulation (tDCS). To examine the effects of tDCS on therapeutic safety learning, 24 patients with OCD completed a pilot randomized clinical trial; they were randomly assigned (double-blind, 50:50) to receive active or sham frontopolar tDCS before completing an in vivo exposure and response prevention (ERP) challenge. Changes in subjective emotional distress during the ERP challenge were used to index therapeutic safety learning. RESULTS: In community volunteers, frontal pole functional connectivity with the middle and superior frontal gyri increased, while connectivity with the anterior insula and basal ganglia decreased (ps < .001, corrected) after tDCS; functional connectivity between DMN and salience network also decreased after tDCS (ps < .001, corrected). OCD patients who received active tDCS exhibited more rapid therapeutic safety learning (ps < .05) during the ERP challenge than patients who received sham tDCS. CONCLUSIONS: Frontopolar tDCS may modulate mPFC and DMN functional connectivity and can accelerate therapeutic safety learning. Though limited by small samples, these findings motivate further exploration of the effects of frontopolar tDCS on neural and behavioral targets associated with exposure-based psychotherapies.

Effects of Smoking Status and State on Intrinsic Connectivity.

BACKGROUND: Smoking behavior during the first 24 hours of a quit attempt is a significant predictor of longer-term abstinence, yet little is known about the neurobiology of early tobacco abstinence. Specifically, the effects of acute tobacco deprivation and reinstatement on brain function-particularly at the level of large-scale network dynamics and assessed across the entire brain-remain incompletely understood. To address this gap, this study used a mixed within- and between-subjects design to assess the effects of smoking status (yes/no smoker) and state (deprived vs. satiated) on whole-brain patterns of intrinsic connectivity. METHODS: Participants included 42 tobacco smokers who underwent resting-state functional magnetic resonance imaging following overnight abstinence (deprived state) and following smoking reinstatement (satiated state, randomized order across participants). Sixty healthy control nonsmokers underwent a single resting-state scan using the same acquisition parameters. Functional connectivity data were analyzed using both a canonical network-of-interest approach and a whole-brain, data-driven approach, i.e., intrinsic connectivity distribution. RESULTS: Network-of-interest-based analyses indicated decreased functional connectivity within frontoparietal and salience networks among smokers relative to nonsmokers as well as effects of smoking state on default mode connectivity. In addition, intrinsic connectivity distribution analyses identified novel between-group differences in subcortical-cerebellar and corticocerebellar networks that were largely smoking state dependent. CONCLUSIONS: These data demonstrate the importance of considering smoking state and the utility of using both theory- and data-driven analysis approaches. These data provide much-needed insight into the functional neurobiology of early abstinence, which may be used in the development of novel treatments.

Assessment of brain age in posttraumatic stress disorder: Findings from the ENIGMA PTSD and brain age working groups.

BACKGROUND: Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. METHOD: Adult subjects (N = 2229; 56.2% male) aged 18-69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age - chronological age) controlling for chronological age, sex, and scan site. RESULTS: BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. DISCUSSION: Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan.

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium.

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3047 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1426 individuals with PTSD and 1621 controls (2174 males/873 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohen's d = -0.11, p = 0.0055). The tapetum connects the left and right hippocampus, for which structure and function have been consistently implicated in PTSD. Results were consistent even after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.

A robust and reproducible connectome fingerprint of ketamine is highly associated with the connectomic signature of antidepressants.

Over the past decade, various N-methyl-D-aspartate modulators have failed in clinical trials, underscoring the challenges of developing novel rapid-acting antidepressants based solely on the receptor or regional targets of ketamine. Thus, identifying the effect of ketamine on the brain circuitry and networks is becoming increasingly critical. In this longitudinal functional magnetic resonance imaging study of data from 265 participants, we used a validated predictive model approach that allows the full assessment of brain functional connectivity, without the need for seed selection or connectivity summaries. First, we identified a connectome fingerprint (CFP) in healthy participants (Cohort A, n = 25) during intravenous infusion of a subanesthetic dose of ketamine, compared to normal saline. We then demonstrated the robustness and reproducibility of the discovered ketamine CFP in two separate healthy samples (Cohort B, n = 22; Cohort C, n = 18). Finally, we investigated the ketamine CFP connectivity at 1-week post treatment in major depressive disorder patients randomized to 8 weeks of sertraline or placebo (Cohort D, n = 200). We found a significant, robust, and reproducible ketamine CFP, consistent with reduced connectivity within the primary cortices and within the executive network, but increased connectivity between the executive network and the rest of the brain. Compared to placebo, the ketamine CFP connectivity changes at 1 week predicted response to sertraline at 8 weeks. In each of Cohorts A-C, ketamine significantly increased connectivity in a previously identified antidepressant CFP. Investigating the brain connectivity networks, we successfully identified a robust and reproducible ketamine biomarker that is related to the mechanisms of antidepressants.

White matter microstructural alterations in posttraumatic stress disorder: An ROI and whole-brain based meta-analysis.

BACKGROUND: Posttraumatic stress disorder (PTSD) is a debilitating mental illness that is thought to be associated with brain white matter (WM) alterations. Individual diffusion tensor imaging (DTI) studies to date have reported inconsistent alterations in FA across different brain regions in patients with PTSD. Here, we aimed to investigate FA in PTSD using both region-of-interest (ROI)-based and whole-brain-based meta-analytic approaches. OBJECTIVES: Individual ROI-based meta-analysis was carried out in each eligible white matter tract and seed-based D mapping (SDM) meta-analysis was conducted in the whole brain to identify the convergence of FA alterations in PTSD relative to controls. RESULTS: Seventeen studies were included in ROI-based meta-analysis (≥ 3 studies were included for each ROI, NPTSD ≥ 80 and Ncontrol ≥ 103 per ROI). Fourteen studies with a total of 322 PTSD and 335 controls were included in whole-brain based meta-analysis. Both ROI and whole-brain meta-analyses showed that patients with PTSD have significantly higher FA in the inferior fronto-occipital fasciculus and lower FA in the genu of corpus callosum. Whole-brain meta-analyses also identified higher FA in the left inferior temporal gyrus and lower FA in the anterior cingulum and left corticospinal tract. LIMITATIONS: A small number of studies were included in some ROI tracts. Thus the results should be interpreted with caution. CONCLUSIONS: Our results suggest that PTSD patients have increased FA in areas related to visual processing, but decreased FA in anterior brain regions critical to cognition association and fear regulation.

A Unique Brain Connectome Fingerprint Predates and Predicts Response to Antidepressants.

More than six decades have passed since the discovery of monoaminergic antidepressants. Yet, it remains a mystery why these drugs take weeks to months to achieve therapeutic effects, although their monoaminergic actions are present rapidly after treatment. In an attempt to solve this mystery, rather than studying the acute neurochemical effects of antidepressants, here we propose focusing on the early changes in the brain functional connectome using traditional statistics and machine learning approaches. Capitalizing on three independent datasets (n = 1,261) and recent developments in data and network science, we identified a specific connectome fingerprint that predates and predicts response to monoaminergic antidepressants. The discovered fingerprint appears to generalize to antidepressants with differing mechanism of action. We also established a consensus whole-brain hierarchical connectivity architecture and provided a set of model-based features engineering approaches suitable for identifying connectomic signatures of brain function in health and disease.

Pretreatment Brain Connectome Fingerprint Predicts Treatment Response in Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) treatment is characterized by low remission rate and often involves weeks to months of treatment. Identification of pretreatment biomarkers of response may play a critical role in novel drug development, in enhanced prognostic predictions, and perhaps in providing more personalized medicine. Using a network restricted strength predictive modeling (NRS-PM) approach, the goal of the current study was to identify pretreatment functional connectome fingerprints (CFPs) that (1) predict symptom improvement regardless of treatment modality and (2) predict treatment specific improvement. METHODS: Functional magnetic resonance imaging and behavioral data from unmedicated patients with MDD (n = 200) were investigated. Participants were randomized to daily treatment of sertraline or placebo for 8 weeks. NRS-PM with 1000 iterations of 10 cross-validation were implemented to identify brain connectivity signatures that predict percent improvement in depression severity at week-8. RESULTS: The study identified a pretreatment CFP that significantly predicts symptom improvement independent of treatment modality but failed to identify a treatment specific CFP. Regardless of treatment modality, improved antidepressant response was predicted by high pretreatment connectivity between modules in the default mode network and the rest of the brain, but low external connectivity in the executive network. Moreover, high pretreatment internal nodal connectivity in the bilateral caudate predicted better response. CONCLUSIONS: The identified CFP may contribute to drug development and ultimately to enhanced prognostic predictions. However, the results do not assist with providing personalized medicine, as pretreatment functional connectivity failed to predict treatment specific response.

Salience Network Disruption in U.S. Army Soldiers With Posttraumatic Stress Disorder.

BACKGROUND: Better understanding of the neurobiology of posttraumatic stress disorder (PTSD) may be critical to developing novel, effective therapeutics. Here, we conducted a data-driven investigation using a well-established, graph-based topological measure of nodal strength to determine the extent of functional dysconnectivity in a cohort of active duty US Army soldiers with PTSD compared to controls. METHODS: 102 participants with (n=50) or without PTSD (n=52) completed functional magnetic resonance imaging (fMRI) at rest and during symptom provocation using subject-specific script imagery. Vertex/voxel global brain connectivity with global signal regression (GBCr), a measure of nodal strength, was calculated as the average of its functional connectivity with all other vertices/voxels in the brain gray matter. RESULTS: In contrast to during resting-state, where there were no group differences, we found a significantly higher GBCr during symptom provocation, in PTSD participants compared to controls, in areas within the right hemisphere, including anterior insula, caudal-ventrolateral prefrontal, and rostral-ventrolateral parietal cortices. Overall, these clusters overlapped with the ventral and dorsal salience networks. Post hoc analysis showed increased GBCr in these salience clusters during symptom provocation compared to resting-state. In addition, resting-state GBCr in the salience clusters predicted GBCr during symptom provocation in PTSD participants but not in controls. CONCLUSION: In PTSD, increased connectivity within the salience network has been previously hypothesized, based primarily on seed-based connectivity findings. The current results strongly support this hypothesis using whole-brain network measure in a fully data-driven approach. It remains to be seen in future studies whether these identified salience disturbances would normalize following treatment.

Reduced Salience and Enhanced Central Executive Connectivity Following PTSD Treatment.

BACKGROUND: In soldiers with posttraumatic stress disorder (PTSD), symptom provocation was found to induce increased connectivity within the salience network, as measured by functional magnetic resonance imaging (fMRI) and global brain connectivity with global signal regression (GBCr). However, it is unknown whether these GBCr disturbances would normalize following effective PTSD treatment. METHODS: 69 US Army soldiers with (n = 42) and without PTSD (n = 27) completed fMRI at rest and during symptom provocation using subject-specific script imagery. Then, participants with PTSD received 6 weeks (12 sessions) of group cognitive processing therapy (CPT) or present-centered therapy (PCT). At week 8, all participants repeated the fMRI scans. The primary analysis used a region-of-interest approach to determine the effect of treatment on salience GBCr. A secondary analysis was conducted to explore the pattern of GBCr alterations posttreatment in PTSD participants compared to controls. RESULTS: Over the treatment period, PCT significantly reduced salience GBCr (p = .02). Compared to controls, salience GBCr was high pretreatment (PCT, p = .01; CPT, p = .03) and normalized post-PCT (p = .53), but not post-CPT (p = .006). Whole-brain secondary analysis found high GBCr within the central executive network in PTSD participants compared to controls. Post hoc exploratory analyses showed significant increases in executive GBCr following CPT treatment (p = .01). CONCLUSION: The results support previous models relating CPT to central executive network and enhanced cognitive control while unraveling a previously unknown neurobiological mechanism of PCT treatment, demonstrating treatment-specific reduction in salience connectivity during trauma recollection.

The Neurobiology and Pharmacotherapy of Posttraumatic Stress Disorder.

New approaches to the neurobiology of posttraumatic stress disorder (PTSD) are needed to address the reported crisis in PTSD drug development. These new approaches may require the field to move beyond a narrow fear-based perspective, as fear-based medications have not yet demonstrated compelling efficacy. Antidepressants, particularly recent rapid-acting antidepressants, exert complex effects on brain function and structure that build on novel aspects of the biology of PTSD, including a role for stress-related synaptic dysconnectivity in the neurobiology and treatment of PTSD. Here, we integrate this perspective within a broader framework-in other words, a dual pathology model of ( a) stress-related synaptic loss arising from amino acid-based pathology and ( b) stress-related synaptic gain related to monoamine-based pathology. Then, we summarize the standard and experimental (e.g., ketamine) pharmacotherapeutic options for PTSD and discuss their putative mechanism of action and clinical efficacy.

Altered White Matter Diffusivity of the Cingulum Angular Bundle in Posttraumatic Stress Disorder.

PURPOSE OF THE STUDY: Prior studies showed posttraumatic stress disorder (PTSD)-related alterations in white matter integrity, but most of these studies have used region-based approaches. We address this limitation by investigating the relationship between PTSD severity and fractional anisotropy (FA) using a tract-based approach. PROCEDURES: Structural and diffusion magnetic resonance imaging were acquired from 67 combat-exposed US Veterans and processed using FSL/FreeSurfer TRActs Constrained by UnderLying Anatomy. Partial correlations were conducted between PTSD severity and FA of the cingulum and uncinate fasciculi covarying for age, sex, and head motion. RESULTS: Only FA of the left cingulum angular bundle (CAB) was positively correlated with PTSD symptom severity (r = 0.433, p = 0.001, df = 57) and remained significant after Bonferroni correction. CONCLUSIONS: This finding may imply greater organization of the CAB with increasing PTSD severity. The CAB connects directly to the cingulate cortex and the hippocampal subiculum, critical nodes of the default mode network, as well as being implicated in neurodegeneration pathology, decision-making, and executive functions, which may help explain previously shown alterations in this network in PTSD. MESSAGE OF THE PAPER: Further study of white matter tract integrity in PTSD is warranted, particularly to investigate whether the CAB connections with both higher-order cognitive functioning and emotion processing regions contribute to the pathophysiology and comorbidity of PTSD.

Topology of brain functional connectivity networks in posttraumatic stress disorder.

Here we present functional neuroimaging-based network data (focused on the default mode network) collected from a cohort of US Veterans with history of combat exposure, combined with clinical assessments for PTSD and other psychiatric comorbidities. The data has been processed and analyzed using several network construction methods (signed, thresholded, normalized to phase-randomized and rewired surrogates, functional and multimodal parcellation). An interpretation and discussion of the data can be found in the main NeuroImage article by Akiki et al. [51].