Computer-Based Executive Function Training for Combat Veterans With PTSD: A Pilot Clinical Trial Assessing Feasibility and Predictors of Dropout

Background: While evidence-based PTSD treatments are often efficacious, 20–50% of individuals continue to experience significant symptoms following treatment. Further, these treatments do not directly target associated neuropsychological deficits. Here, we describe the methods and feasibility for computer-based executive function training (EFT), a potential alternative or adjunctive PTSD treatment.Methods: Male combat veterans with full or partial PTSD (n = 20) and combat-exposed controls (used for normative comparison; n = 20) completed clinical, neuropsychological and functional neuroimaging assessments. Those with PTSD were assigned to EFT (n = 13) or placebo training (word games; n = 7) at home for 6 weeks, followed by repeat assessment. Baseline predictors of treatment completion were explored using logistic regressions. Individual feedback and changes in clinical symptoms, neuropsychological function, and neural activation patterns are described.Results: Dropout rates for EFT and placebo training were 38.5 and 57.1%, respectively. Baseline clinical severity and brain activation (i.e., prefrontal-insula-amygdala networks) during an emotional anticipation task were predictive of treatment completion. Decreases in clinical symptoms were observed following treatment in both groups. EFT participants improved on training tasks but not on traditional neuropsychological assessments. All training completers indicated liking EFT, and indicated they would engage in EFT (alone or as adjunctive treatment) if offered.Conclusion: Results provide an initial framework to explore the feasibility of placebo-controlled, computerized, home-based executive function training (EFT) on psychological and neuropsychological function and brain activation in combat veterans with PTSD. Clinical severity and neural reactivity to emotional stimuli may indicate which veterans will complete home-based computerized interventions. While EFT may serve as a potential alternative or adjunctive PTSD treatment, further research is warranted to address compliance and determine whether EFT may benefit functioning above and beyond placebo interventions

Preliminary Evidence for the Impact of Combat Experiences on Gray Matter Volume of the Posterior Insula

Background: Combat-exposed veteran populations are at an increased risk for developing cardiovascular disease. The anterior cingulate cortex (ACC) and insula have been implicated in both autonomic arousal to emotional stressors and homeostatic processes, which may contribute to cardiovascular dysfunction in combat veteran populations. The aim of the present study was to explore the intersecting relationships of combat experiences, rostral ACC and posterior insula volume, and cardiovascular health in a sample of combat veterans. Method: Twenty-four male combat veterans completed clinical assessment of combat experiences and posttraumatic stress symptoms. Subjects completed a magnetic resonance imaging scan and autosegmentation using FreeSurfer was used to estimate regional gray matter volume (controlling for total gray matter volume) of the rostral ACC and posterior insula. Flow-mediated dilation (FMD) was conducted to assess cardiovascular health. Theil-sen robust regressions andWelch’s analysis of variance were used to examine relationships of combat experiences and PTSD symptomology with (1) FMD and (2) regional gray matter volume. Results: Increased combat experiences, deployment duration, and multiple deployments were related to smaller posterior insula volume. Combat experiences were marginally associated with poorer cardiovascular health. However, cardiovascular health was not related to rostral ACC or posterior insula volume. Conclusion: The present study provides initial evidence for the relationships of combat experiences, deployment duration, and multiple deployments with smaller posterior insula volume. Results may suggest that veterans with increased combat experiences may exhibit more dysfunction regulating the autonomic nervous system, a key function of the posterior insula. However, the relationship between combat and cardiovascular health was not mediated by regional brain volume. Future research is warranted to further clarify the cardiovascular or functional impact of smaller posterior insula volume in combat veterans

Always on my mind: Cross-brain associations of mental health symptoms during simultaneous parent-child scanning.

How parents manifest symptoms of anxiety or depression may affect how children learn to modulate their own distress, thereby influencing the children's risk for developing an anxiety or mood disorder. Conversely, children's mental health symptoms may impact parents' experiences of negative emotions. Therefore, mental health symptoms can have bidirectional effects in parent-child relationships, particularly during moments of distress or frustration (e.g., when a parent or child makes a costly mistake). The present study used simultaneous functional magnetic resonance imaging (fMRI) of parent-adolescent dyads to examine how brain activity when responding to each other's costly errors (i.e., dyadic error processing) may be associated with symptoms of anxiety and depression. While undergoing simultaneous fMRI scans, healthy dyads completed a task involving feigned errors that indicated their family member made a costly mistake. Inter-brain, random-effects multivariate modeling revealed that parents who exhibited decreased medial prefrontal cortex and posterior cingulate cortex activation when viewing their child's costly error response had children with more symptoms of depression and anxiety. Adolescents with increased anterior insula activation when viewing a costly error made by their parent had more anxious parents. These results reveal cross-brain associations between mental health symptomatology and brain activity during parent-child dyadic error processing

Protocol for a randomized controlled trial examining multilevel prediction of response to behavioral activation and exposure-based therapy for generalized anxiety disorder.

BACKGROUND:Only 40-60% of patients with generalized anxiety disorder experience long-lasting improvement with gold standard psychosocial interventions. Identifying neurobehavioral factors that predict treatment success might provide specific targets for more individualized interventions, fostering more optimal outcomes and bringing us closer to the goal of "personalized medicine." Research suggests that reward and threat processing (approach/avoidance behavior) and cognitive control may be important for understanding anxiety and comorbid depressive disorders and may have relevance to treatment outcomes. This study was designed to determine whether approach-avoidance behaviors and associated neural responses moderate treatment response to exposure-based versus behavioral activation therapy for generalized anxiety disorder. METHODS/DESIGN:We are conducting a randomized controlled trial involving two 10-week group-based interventions: exposure-based therapy or behavioral activation therapy. These interventions focus on specific and unique aspects of threat and reward processing, respectively. Prior to and after treatment, participants are interviewed and undergo behavioral, biomarker, and neuroimaging assessments, with a focus on approach and avoidance processing and decision-making. Primary analyses will use mixed models to examine whether hypothesized approach, avoidance, and conflict arbitration behaviors and associated neural responses at baseline moderate symptom change with treatment, as assessed using the Generalized Anxiety Disorder-7 item scale. Exploratory analyses will examine additional potential treatment moderators and use data reduction and machine learning methods. DISCUSSION:This protocol provides a framework for how studies may be designed to move the field toward neuroscience-informed and personalized psychosocial treatments. The results of this trial will have implications for approach-avoidance processing in generalized anxiety disorder, relationships between levels of analysis (i.e., behavioral, neural), and predictors of behavioral therapy outcome. TRIAL REGISTRATION:The study was retrospectively registered within 21 days of first participant enrollment in accordance with FDAAA 801 with ClinicalTrials.gov, NCT02807480. Registered on June 21, 2016, before results

EEG Microstates Temporal Dynamics Differentiate Individuals with Mood and Anxiety Disorders From Healthy Subjects

Electroencephalography (EEG) measures the brain’s electrophysiological spatio-temporal activities with high temporal resolution. Multichannel and broadband analysis of EEG signals is referred to as EEG microstates (EEG-ms) and can characterize such dynamic neuronal activity. EEG-ms have gained much attention due to the increasing evidence of their association with mental activities and large-scale brain networks identified by functional magnetic resonance imaging (fMRI). Spatially independent EEG-ms are quasi-stationary topographies (e.g., stable, lasting a few dozen milliseconds) typically classified into four canonical classes (microstates A through D). They can be identified by clustering EEG signals around EEG global field power (GFP) maxima points. We examined the EEG-ms properties and the dynamics of cohorts of mood and anxiety (MA) disorders subjects (n = 61) and healthy controls (HCs; n = 52). In both groups, we found four distinct classes of EEG-ms (A through D), which did not differ among cohorts. This suggests a lack of significant structural cortical abnormalities among cohorts, which would otherwise affect the EEG-ms topographies. However, both cohorts’ brain network dynamics significantly varied, as reflected in EEG-ms properties. Compared to HC, the MA cohort features a lower transition probability between EEG-ms B and D and higher transition probability from A to D and from B to C, with a trend towards significance in the average duration of microstate C. Furthermore, we harnessed a recently introduced theoretical approach to analyze the temporal dependencies in EEG-ms. The results revealed that the transition matrices of MA group exhibit higher symmetrical and stationarity properties as compared to HC ones. In addition, we found an elevation in the temporal dependencies among microstates, especially in microstate B for the MA group. The determined alteration in EEG-ms temporal dependencies among the cohorts suggests that brain abnormalities in mood and anxiety disorders reflect aberrant neural dynamics and a temporal dwelling among ceratin brain states (i.e., mood and anxiety disorders subjects have a less dynamicity in switching between different brain states)

A Nonlinear Simulation Framework Supports Adjusting for Age When Analyzing BrainAGE

Several imaging modalities, including T1-weighted structural imaging, diffusion tensor imaging, and functional MRI can show chronological age related changes. Employing machine learning algorithms, an individual's imaging data can predict their age with reasonable accuracy. While details vary according to modality, the general strategy is to: (1) extract image-related features, (2) build a model on a training set that uses those features to predict an individual's age, (3) validate the model on a test dataset, producing a predicted age for each individual, (4) define the “Brain Age Gap Estimate” (BrainAGE) as the difference between an individual's predicted age and his/her chronological age, (5) estimate the relationship between BrainAGE and other variables of interest, and (6) make inferences about those variables and accelerated or delayed brain aging. For example, a group of individuals with overall positive BrainAGE may show signs of accelerated aging in other variables as well. There is inevitably an overestimation of the age of younger individuals and an underestimation of the age of older individuals due to “regression to the mean.” The correlation between chronological age and BrainAGE may significantly impact the relationship between BrainAGE and other variables of interest when they are also related to age. In this study, we examine the detectability of variable effects under different assumptions. We use empirical results from two separate datasets [training = 475 healthy volunteers, aged 18–60 years (259 female); testing = 489 participants including people with mood/anxiety, substance use, eating disorders and healthy controls, aged 18–56 years (312 female)] to inform simulation parameter selection. Outcomes in simulated and empirical data strongly support the proposal that models incorporating BrainAGE should include chronological age as a covariate. We propose either including age as a covariate in step 5 of the above framework, or employing a multistep procedure where age is regressed on BrainAGE prior to step 5, producing BrainAGE Residualized (BrainAGER) scores

Preliminary Evidence for the Impact of Combat Experiences on Gray Matter Volume of the Posterior Insula

Background: Combat-exposed veteran populations are at an increased risk for developing cardiovascular disease. The anterior cingulate cortex (ACC) and insula have been implicated in both autonomic arousal to emotional stressors and homeostatic processes, which may contribute to cardiovascular dysfunction in combat veteran populations. The aim of the present study was to explore the intersecting relationships of combat experiences, rostral ACC and posterior insula volume, and cardiovascular health in a sample of combat veterans.Method: Twenty-four male combat veterans completed clinical assessment of combat experiences and posttraumatic stress symptoms. Subjects completed a magnetic resonance imaging scan and autosegmentation using FreeSurfer was used to estimate regional gray matter volume (controlling for total gray matter volume) of the rostral ACC and posterior insula. Flow-mediated dilation (FMD) was conducted to assess cardiovascular health. Theil-sen robust regressions and Welch's analysis of variance were used to examine relationships of combat experiences and PTSD symptomology with (1) FMD and (2) regional gray matter volume.Results: Increased combat experiences, deployment duration, and multiple deployments were related to smaller posterior insula volume. Combat experiences were marginally associated with poorer cardiovascular health. However, cardiovascular health was not related to rostral ACC or posterior insula volume.Conclusion: The present study provides initial evidence for the relationships of combat experiences, deployment duration, and multiple deployments with smaller posterior insula volume. Results may suggest that veterans with increased combat experiences may exhibit more dysfunction regulating the autonomic nervous system, a key function of the posterior insula. However, the relationship between combat and cardiovascular health was not mediated by regional brain volume. Future research is warranted to further clarify the cardiovascular or functional impact of smaller posterior insula volume in combat veterans