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Post-traumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) often co-occur in the context of threat to one's life. These conditions also have an overlapping symptomatology and include symptoms of anxiety, poor concentration and memory problems. A major challenge has been articulating the underlying neurobiology of these overlapping conditions. The primary aim of this study was to compare intrinsic functional connectivity between mTBI (without PTSD) and PTSD (without mTBI). The study included functional MRI data from 176 participants: 42 participants with mTBI, 67 with PTSD and a comparison group of 66 age and sex-matched healthy controls. We used network-based statistical analyses for connectome-wide comparisons of intrinsic functional connectivity between mTBI relative to PTSD and controls. Our results showed no connectivity differences between mTBI and PTSD groups. However, we did find that mTBI had significantly reduced connectivity relative to healthy controls within an extensive network of regions including default mode, executive control, visual and auditory networks. The mTBI group also displayed hyperconnectivity between dorsal and ventral attention networks and perceptual regions. The PTSD group also demonstrated abnormal connectivity within these networks relative to controls. Connectivity alterations were not associated with severity of PTSD or post-concussive symptoms in either clinical group. Taken together, the similar profiles of intrinsic connectivity alterations in these two conditions provide neural evidence that can explain, in part, the overlapping symptomatology between mTBI and PTSD., (© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Importance: More than 10% of children experience sexual, physical, or emotional abuse, and abuse experienced during sensitive neurodevelopmental periods is associated with a greater risk of psychiatric disorders., Objective: To investigate the extent to which a history of abuse is associated with alterations in the intrinsic functional connectome of the adult brain independent from the restriction of associated psychiatric conditions., Design, Setting, and Participants: This cohort study assessed data from 768 adult participants from the greater Sydney, Australia, area who were included in the study without diagnostic restrictions and categorized based on a history of childhood sexual, physical, and/or emotional abuse. Data were collected from January 1, 2009, to December 31, 2015; data analysis was performed from October 1, 2020, to March 31, 2022., Main Outcomes and Measures: Outcomes were structured psychiatric interview responses, self-report of the frequency and extent of various types of negative experiences in childhood and adolescence, and intrinsic functional connectivity derived from 5 functional magnetic resonance imaging tasks and estimated among 436 brain regions, comprising intranetwork and internetwork connectivity of 8 large-scale brain networks., Results: Among the 647 individuals with usable data (330 female [51.0%]; mean [SD] age, 33.3 [12.0] years; age range, 18.2-69.2 years), history of abuse was associated with greater likelihood of a current psychiatric illness (odds ratio, 4.55; 95% CI, 3.07-6.72; P < .001) and with greater depressive, anxiety, and stress symptoms (mean difference, 20.4; 95% CI, 16.1-24.7; P < .001). An altered connectome signature of higher connectivity within somatomotor, dorsal, and ventral attention networks and between these networks and executive control and default mode networks was observed in individuals with a history of abuse experienced during childhood (n = 127) vs those without a history of abuse (n = 442; mean difference, 0.07; 95% CI, 0.05-0.08; familywise, Bonferroni-corrected P = .01; Cohen d = 0.82) and compared with those who experienced abuse in adolescence (n = 78; mean difference, 0.06; 95% CI, 0.04-0.08]; familywise, Bonferroni-corrected P < .001; Cohen d = 0.68). Connectome alterations were not observed for those who experienced abuse in adolescence. Connectivity of this signature was transdiagnostic and independent of the nature and frequency of abuse, sex, or current symptomatic state., Conclusions and Relevance: Findings highlight the associations of exposure to abuse before and during adolescence with the whole-brain functional connectome. The experience of child abuse was found to be associated with physiologic changes in intrinsic connectivity, independent of psychopathology, in a way that may affect functioning of systems responsible for perceptual processing and attention.

Background: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA)., Methods: Neuroimaging and clinical data were aggregated from 29 research sites in >1300 PTSD cases and >2000 trauma-exposed control subjects (ages 6.2-85.2 years) by the ENIGMA-PGC (Enhancing Neuro Imaging Genetics through Meta Analysis-Psychiatric Genomics Consortium) PTSD working group. Cortical regions in the network were rank ordered by the effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2-148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared with the mean SC of 5000 randomly generated n-region networks., Results: Patients with PTSD, relative to non-PTSD control subjects, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex, and age modulated covariance differences of PTSD-related structural networks., Conclusions: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The SC networks that are perturbed in PTSD comport with converging evidence from resting-state functional connectivity networks and networks affected by inflammatory processes and stress hormones in PTSD., (Copyright © 2022 Society of Biological Psychiatry. All rights reserved.)

Background: Antidepressant efficacy in people with major depressive disorder remains modest, yet identifying treatment-predictive neurobiological markers may improve outcomes. While disruptions in functional connectivity within and between large-scale brain networks predict poorer treatment outcome, it is unclear whether higher trait neuroticism, which has been associated with generally poorer outcomes, contributes to these disruptions and to antidepressant-specific treatment outcomes. Here, we used whole-brain functional connectivity analysis to identify a neural connectomic signature of neuroticism and tested whether this signature predicted antidepressant treatment outcome., Methods: Participants were 226 adults with major depressive disorder and 68 healthy control subjects who underwent functional magnetic resonance imaging and were assessed on clinical features at baseline. Participants with major depressive disorder were then randomized to 1 of 3 commonly prescribed antidepressants and after 8 weeks completed a second functional magnetic resonance imaging and were reassessed for depressive symptom remission/response. Baseline intrinsic functional connectivity between each pair of 436 brain regions was analyzed using network-based statistics to identify connectomic features associated with neuroticism. Features were then assessed on their ability to predict treatment outcome and whether they changed after 8 weeks of treatment., Results: Higher baseline neuroticism was associated with greater connectivity within and between the salience, executive control, and somatomotor brain networks. Greater connectivity across these networks predicted poorer treatment outcome that was not mediated by baseline neuroticism, and connectivity strength decreased after antidepressant treatment., Conclusions: Our findings demonstrate that neuroticism is associated with organization of intrinsic neural networks that predict treatment outcome, elucidating its biological underpinnings and opportunity for better treatment personalization., (Copyright © 2021 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Although trauma-focused cognitive behavior therapy (TF-CBT) is the frontline treatment for post-traumatic stress disorder (PTSD), up to one-half of patients are treatment nonresponders. To understand treatment nonresponse, it is important to understand the neural mechanisms of TF-CBT. Here, we used whole-brain intrinsic functional connectivity analysis to identify neural connectomic signatures of treatment outcome. In total, 36 PTSD patients and 36 healthy individuals underwent functional MRI at pre-treatment baseline. Patients then underwent nine sessions of TF-CBT and completed clinical and follow-up MRIs. We used an established large-scale brain network atlas to parcellate the brain into 343 brain regions. Pairwise intrinsic task-free functional connectivity was calculated and used to identify pre-treatment connectomic features that were correlated with reduction of PTSD severity from pretreatment to post treatment. We formed a composite metric of intrinsic connections associated with therapeutic outcome, and then interrogated this composite metric to determine if it distinguished PTSD treatment responders and nonresponders from healthy control status and changed post treatment. Lower pre-treatment connectivity for the cingulo-opercular, salience, default mode, dorsal attention, and frontoparietal executive control brain networks was associated with treatment improvement. Treatment responders had lower while nonresponders had significantly greater connectivity than controls at pretreatment. With therapy, connectivity significantly increased for responders and decreased for nonresponders, while controls remain unchanged over this time period. We provide evidence that the intrinsic functional architecture of the brain, specifically connectivity within and between brain networks associated with external vigilance, self-awareness, and cognitive control, may characterize a positive response to TF-CBT for PTSD.

Although major depressive disorder (MDD) is associated with altered functional coupling between disparate neural networks, the degree to which such measures are ameliorated by antidepressant treatment is unclear. It is also unclear whether functional connectivity can be used as a predictive biomarker of treatment response. Here, we used whole-brain functional connectivity analysis to identify neural signatures of remission following antidepressant treatment, and to identify connectomic predictors of treatment response. 163 MDD and 62 healthy individuals underwent functional MRI during pre-treatment baseline and 8-week follow-up sessions. Patients were randomized to escitalopram, sertraline or venlafaxine-XR antidepressants and assessed at follow-up for remission. Baseline measures of intrinsic functional connectivity between each pair of 333 regions were analyzed to identify pre-treatment connectomic features that distinguish remitters from non-remitters. We then interrogated these connectomic differences to determine if they changed post-treatment, distinguished patients from controls, and were modulated by medication type. Irrespective of medication type, remitters were distinguished from non-remitters by greater connectivity within the default mode network (DMN); specifically, between the DMN, fronto-parietal and somatomotor networks, the DMN and visual, limbic, auditory and ventral attention networks, and between the fronto-parietal and somatomotor networks with cingulo-opercular and dorsal attention networks. This baseline hypo-connectivity for non-remitters also distinguished them from controls and increased following treatment. In contrast, connectivity for remitters was higher than controls at baseline and also following remission, suggesting a trait-like connectomic characteristic. Increased functional connectivity within and between large-scale intrinsic brain networks may characterize acute recovery with antidepressants in depression.

Background: Mechanistically based neural markers, such as amygdala reactivity, offer one approach to addressing the challenges of differentiating bipolar and unipolar depressive disorders independently from mood state and acute symptoms. Although emotion-elicited amygdala reactivity has been found to distinguish patients with bipolar depression from patients with unipolar depression, it remains unknown whether this distinction is traitlike and present in the absence of an acutely depressed mood. We addressed this gap by investigating patients with bipolar disorder (BP) and unipolar major depressive disorder (MDD) in remission., Methods: Supraliminal and subliminal processing of faces exhibiting threat, sad, happy, and neutral emotions during functional magnetic resonance imaging was completed by 73 participants (23 BP patients and 25 MDD patients matched for age and gender, number of depressive episodes and severity; 25 age- and gender-matched healthy control subjects). We compared groups for activation and connectivity for the amygdala., Results: BP patients had lower left amygdala activation than MDD patients during supraliminal and subliminal threat, sad, and neutral emotion processing and for subliminal happy faces. BP patients also exhibited lower amygdala connectivity to the insula and hippocampus for threat and to medial orbitofrontal cortex for happy supraliminal and subliminal processing. BP patients also demonstrated greater amygdala-insula connectivity for sad supraliminal and subliminal face processing. Both patient groups were distinct from control subjects across several measures for activation and connectivity., Conclusions: Independent of valence or level of emotional awareness, amygdala activation and connectivity during facial emotion processing can distinguish BP patients and MDD patients. These findings provide evidence that this neural substrate could be a potential trait marker to differentiate these two disorders largely independent of illness state., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Cognitive control is one of the most important skills in day-to-day social and intellectual functioning but we are yet to understand the neural basis of the group of behaviors required to carry this out. Here, we probed changes over time in the brain network associated with cognitive control (the dorsolateral prefrontal cortex, the dorsal posterior parietal cortex, and the dorsal anterior cingulate cortex) using both behavioral assays and functional brain imaging during a selective working memory task in 69 healthy participants within the age range 18-38 years (mean: 25, SD: ±6), assessed twice, 2 years apart. We aimed to explore the relationship of changing network activation and connectivity with behavioral tasks associated with cognitive control in this otherwise neurodevelopmentally stable group. We found that increased connectivity between frontoparietal cognitive control network regions during the working memory task was associated with improved memory and executive functions over the 2-year period and that this association was not impacted by age, gender, or baseline performance. These results provide evidence that changes in the functional organization of the cognitive control brain network occur despite the absence of neurodevelopment, aging or targeted cognitive training effects, and could modulate cognitive performance in early to mid-adulthood. Understanding how and why this change is occurring could provide insights into the mechanisms through which cognitive control ability is cultivated over time. This could aid in the development of interventions in cases where cognitive control is impaired., (© 2018 Wiley Periodicals, Inc.)

Default mode network (DMN) dysfunction (particularly within the anterior cingulate cortex (ACC) and medial prefrontal cortex (mPFC)) has been implicated in major depressive disorder (MDD); however, its contribution to treatment outcome has not been clearly established. Here we tested the role of DMN functional connectivity as a general and differential biomarker for predicting treatment outcomes in a large, unmedicated adult sample with MDD. Seventy-five MDD outpatients completed fMRI scans before and 8 weeks after randomization to escitalopram, sertraline, or venlafaxine-XR. A whole-brain voxel-wise t-test identified profiles of pretreatment intrinsic functional connectivity that distinguished patients who were subsequently classified as remitters or non-remitters at follow-up. Connectivity was seeded in the PCC, an important node of the DMN. We further characterized differences between remitters, non-remitters, and 31 healthy controls and characterized changes pretreatment to posttreatment. Remitters were distinguished from non-remitters by relatively intact connectivity between the PCC and ACC/mPFC, not distinguishable from healthy controls, while non-remitters showed relative hypo-connectivity. In validation analyses, we demonstrate that PCC-ACC/mPFC connectivity predicts remission status with >80% cross-validated accuracy. In analyses testing whether intrinsic connectivity differentially relates to outcomes for a specific type of antidepressant, interaction models did not survive the corrected threshold. Our findings demonstrate that the overall capacity to remit on commonly used antidepressants may depend on intact organization of intrinsic functional connectivity between PCC and ACC/mPFC prior to treatment. The findings highlight the potential utility of functional scans for advancing a more precise approach to tailoring antidepressant treatment choices.

Although multiple studies have reported structural deficits in multiple brain regions in attention-deficit hyperactivity disorder (ADHD), we do not yet know if these deficits reflect a more systematic disruption to the anatomical organization of large-scale brain networks. Here we used a graph theoretical approach to quantify anatomical organization in children and adolescents with ADHD. We generated anatomical networks based on covariance of gray matter volumes from 92 regions across the brain in children and adolescents with ADHD (n=34) and age- and sex-matched healthy controls (n=28). Using graph theory, we computed metrics that characterize both the global organization of anatomical networks (interconnectivity (clustering), integration (path length) and balance of global integration and localized segregation (small-worldness)) and their local nodal measures (participation (degree) and interaction (betweenness) within a network). Relative to Controls, ADHD participants exhibited altered global organization reflected in more clustering or network segregation. Locally, nodal degree and betweenness were increased in the subcortical amygdalae in ADHD, but reduced in cortical nodes in the anterior cingulate, posterior cingulate, mid temporal pole and rolandic operculum. In ADHD, anatomical networks were disrupted and reflected an emphasis on subcortical local connections centered around the amygdala, at the expense of cortical organization. Brains of children and adolescents with ADHD may be anatomically configured to respond impulsively to the automatic significance of stimulus input without having the neural organization to regulate and inhibit these responses. These findings provide a novel addition to our current understanding of the ADHD connectome.

Background: Major depressive disorder (MDD) has been shown to be associated with a disrupted topological organization of functional brain networks. However, little is known regarding whether these changes have a structural basis. Diffusion tensor imaging (DTI) enables comprehensive whole-brain mapping of the white matter tracts that link regions distributed throughout the entire brain, the so-called human connectome., Methods: We examined whole-brain structural networks in a cohort of 95 MDD outpatients and 102 matched control subjects. Structural networks were represented by an 84 × 84 connectivity matrix representing probabilistic white matter connections between 84 parcellated cortical and subcortical regions using DTI tractography. Network-based statistics were used to assess differences in the interregional connectivity matrix between the two groups, and graph theory was used to examine overall topological organization., Results: Our network-based statistics analysis demonstrates lowered structural connectivity within two distinct brain networks that are present in depression: the first primarily involves the regions of the default mode network and the second comprises the frontal cortex, thalamus, and caudate regions that are central in emotional and cognitive processing. These two altered networks were observed in the context of an overall preservation of topology as reflected as no significant group differences for the graph-theory measures., Conclusions: This is the first report to use DTI to show the structural connectomic alterations present in MDD. Our findings highlight that altered structural connectivity between nodes of the default mode network and the frontal-thalamo-caudate regions are core neurobiological features associated with MDD., (Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)