Association of Neural Connectome With Early Experiences of Abuse in Adults

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.

Anosognosia in hoarding disorder is predicted by alterations in cognitive and inhibitory control

Insight impairment contributes significantly to morbidity in psychiatric disorders. The neurologic concept of anosognosia, reflecting deficits in metacognitive awareness of illness, is increasingly understood as relevant to psychopathology, but has been little explored in psychiatric disorders other than schizophrenia. We explored anosognosia as an aspect of insight impairment in n = 71 individuals with DSM-5 hoarding disorder. We used a standardized clutter severity measure to assess whether individuals with hoarding disorder underreport home clutter levels relative to independent examiners. We then explored whether underreporting, as a proxy for anosognosia, is predicted by clinical or neurocognitive behavioral measures. We found that individuals with hoarding disorder underreport their clutter, and that underreporting is predicted by objective severity of clutter. In an n = 53 subset of participants, we found that underreporting is predicted by altered performance on tests of cognitive control and inhibition, specifically Go/No-Go and Stroop tests. The relation of underreporting to objective clutter, the cardinal symptom of hoarding disorder, suggests that anosognosia may reflect core pathophysiology of the disorder. The neurocognitive predictors of clutter underreporting suggest that anosognosia in hoarding disorder shares a neural basis with metacognitive awareness deficits in other neuropsychiatric disorders and that executive anosognosia may be a transdiagnostic manifestation of psychopathology.

TWIN-10: protocol for a 10-year longitudinal twin study of the neuroscience of mental well-being and resilience

INTRODUCTION

Mental well-being is a core component of mental health, and resilience is a key process of positive adaptive recovery following adversity. However, we lack an understanding of the neural mechanisms that contribute to individual variation in the trajectories of well-being and resilience relative to risk. Genetic and/or environmental factors may also modulate these mechanisms. The aim of the TWIN-10 Study is to characterise the trajectories of well-being and resilience over 12 years across four timepoints (baseline, 1 year, 10 years, 12 years) in 1669 Australian adult twins of European ancestry (to account for genetic stratification effects). To this end, we integrate data across genetics, environment, psychological self-report, neurocognitive performance and brain function measures of well-being and resilience.

METHODS AND ANALYSIS

Twins who took part in the baseline TWIN-E Study will be invited back to participate in the TWIN-10 Study, at 10-year and 12-year follow-up timepoints. Participants will complete an online battery of psychological self-reports, computerised behavioural assessments of neurocognitive functions and MRI testing of the brain structure and function during resting and task-evoked scans. These measures will be used as predictors of the risk versus resilience trajectory groups defined by their changing levels of well-being and illness symptoms over time as a function of trauma exposure. Structural equation models will be used to examine the association between the predictors and trajectory groups of resilience and risk over time. Univariate and multivariate twin modelling will be used to determine heritability of the measures, as well as the shared versus unique genetic and environmental contributions.

ETHICS AND DISSEMINATION

This study involves human participants. This study was approved by the University of New South Wales Human Research Ethics Committee (HC180403) and the Scientific Management Panel of Neuroscience Research Australia Imaging (CX2019-05). Results will be disseminated through publications and presentations to the public and the academic community. Participants gave informed consent to participate in the study before taking part.

Cross-trial prediction of depression remission using problem-solving therapy: A machine learning approach

BACKGROUND

Psychotherapy is a standard depression treatment; however, determining a patient's prognosis with therapy relies on clinical judgment that is subject to trial-and-error and provider variability.

PURPOSE

To develop machine learning (ML) algorithms to predict depression remission for patients undergoing 6 months of problem-solving therapy (PST).

METHOD

Using data from the treatment arm of 2 randomized trials, ML models were trained and validated on ENGAGE-2 (ClinicalTrials.gov, #NCT03841682) and tested on RAINBOW (ClinicalTrials.gov, #NCT02246413) for predictions at baseline and at 2-months. Primary outcome was depression remission using the Depression Symptom Checklist (SCL-20) score < 0.5 at 6 months. Predictor variables included baseline characteristics (sociodemographic, behavioral, clinical, psychosocial) and intervention engagement through 2-months.

RESULTS

Of the 26 candidate variables, 8 for baseline and 11 for 2-months were predictive of depression remission, and used to train the models. The best-performing model predicted remission with an accuracy significantly greater than chance in internal validation using the ENGAGE-2 cohort, at baseline [72.6% (SD = 3.6%), p < 0.0001] and at 2-months [72.3% (5.1%), p < 0.0001], and in external validation with the RAINBOW cohort at baseline [58.3% (0%), p < 0.0001] and at 2-months [62.3% (0%), p < 0.0001]. Model-agnostic explanations highlighted key predictors of depression remission at the cohort and patient levels, including female sex, lower self-reported sleep disturbance, lower sleep-related impairment, and lower negative problem orientation.

CONCLUSIONS

ML models using clinical and patient-reported data can predict depression remission for patients undergoing PST, affording opportunities for prospective identification of likely responders, and for developing personalized early treatment optimization along the patient care trajectory.

Valence processing alterations in SAPAP3 knockout mice and human OCD

Abnormalities in valence processing - the processing of aversive or appetitive stimuli - may be an underrecognized component of obsessive-compulsive disorder (OCD). Preclinical rodent models have been critical in furthering pathophysiological understanding of OCD, yet there is a dearth of investigations examining whether rodent models of compulsive behavior show alterations in valence systems congruent with those seen in individuals with OCD. In this study, we sought to assess valence processing in a preclinical rodent model of compulsive behavior, the SAPAP3 knockout (KO) mouse model, and compare our preclinical findings to similar behavioral phenomena in OCD patients. In SAPAP3 KO mice, we used auditory fear conditioning and extinction to examine alterations in negative valence processing and reward-based operant conditioning to examine alterations in positive valence processing. We find that SAPAP3 KO mice show evidence of heightened negative valence processing through enhanced fear learning and impaired fear extinction. SAPAP3 KO mice also show deficits in reward acquisition and goal-directed behavior, suggesting impaired positive valence processing. In OCD patients, we used validated behavioral tests to assess explicit and implicit processing of fear-related facial expressions (negative valence) and socially-rewarding happy expressions (positive valence). We find similar trends towards enhanced negative and impaired positive valence processing in OCD patients. Overall, our results reveal valence processing abnormalities in a preclinical rodent model of compulsive behavior similar to those seen in OCD patients, with implications for valence processing alterations as novel therapeutic targets across a translational research spectrum.

Intrinsic Functional Connectivity in the Default Mode Network Differentiates the Combined and Inattentive Attention Deficit Hyperactivity Disorder Types

Neuroimaging studies have revealed neurobiological differences in ADHD, particularly studies examining connectivity disruption and anatomical network organization. However, the underlying pathophysiology of ADHD types remains elusive as it is unclear whether dysfunctional network connections characterize the underlying clinical symptoms distinguishing ADHD types. Here, we investigated intrinsic functional network connectivity to identify neural signatures that differentiate the combined (ADHD-C) and inattentive (ADHD-I) presentation types. Applying network-based statistical (NBS) and graph theoretical analysis to task-derived intrinsic connectivity data from completed fMRI scans, we evaluated default mode network (DMN) and whole-brain functional network topology in a cohort of 34 ADHD participants (aged 8–17 years) defined using DSM-IV criteria as predominantly inattentive (ADHD-I) type (n = 15) or combined (ADHD-C) type (n = 19), and 39 age and gender-matched typically developing controls. ADHD-C were characterized from ADHD-I by reduced network connectivity differences within the DMN. Additionally, reduced connectivity within the DMN was negatively associated with ADHD-RS hyperactivity-impulsivity subscale score. Compared with controls, ADHD-C but not ADHD-I differed by reduced connectivity within the DMN; inter-network connectivity between the DMN and somatomotor networks; the DMN and limbic networks; and between the somatomotor and cingulo-frontoparietal, with ventral attention and dorsal attention networks. However, graph-theoretical measures did not significantly differ between groups. These findings provide insight into the intrinsic networks underlying phenotypic differences between ADHD types. Furthermore, these intrinsic functional connectomic signatures support neurobiological differences underlying clinical variations in ADHD presentations, specifically reduced within and between functional connectivity of the DMN in the ADHD-C type.

Association of COVID-19 impact with outcomes of an integrated obesity and depression intervention: Posthoc analysis of an RCT

OBJECTIVE

To examine the association between COVID-19 impact and clinical outcomes of an integrated collaborative care intervention for adults with obesity and comorbid depression.

METHODS

Latent class analysis identified clusters of self-reported COVID-19 impact. Cluster characteristics were examined using Fishers' least significant difference method and canonical discriminant analysis. Intervention vs. usual care effects on primary (body mass index [BMI], depressive symptoms) and secondary (anxiety symptoms and other psychosocial) outcomes stratified by cluster were examined using linear mixed models.

RESULTS

Three clusters were identified: mental health and sleep impact (cluster 1, n = 37), economic impact (cluster 2, n = 18), and less overall impact (cluster 3, n = 20). Clusters differed in age, income, diet, and baseline coping skills. The intervention led to improvements across several health outcomes compared with usual care, with medium to large effects on functional impairments (standardized mean difference, -0.7 [95% CI: -1.3, -0.1]) in cluster 1, depressive symptoms (-1.1 [95% CI: -2.0, -0.1]) and obesity-related problems (-1.6 [95% CI: -2.8, -0.4]) in cluster 2, and anxiety (-1.1 [95% CI: -1.9, -0.3]) in cluster 3.

CONCLUSIONS

People with obesity and comorbid depression may have varied intervention responses based on COVID-19 impact. Interventions tailored to specific COVID-19 impact clusters may restore post-pandemic health.

Cognitive and Executive Contributions to Trail-Making Task Performance on Adolescents With and Without Attention Deficit Hyperactivity Disorder

OBJECTIVE

The trail making task is used to assess executive functioning in ADHD youth, yet has only been validated in adult populations. We compare the relative contributions of various cognitive measures to performance on a trail making task analog, the Switching of Attention (SoA) task, in typically-developing and ADHD adolescents.

METHOD

Participants were 160 adolescents with ADHD from the International Study to Predict Optimized Treatment-in ADHD, assessed at pretreatment baseline and 6-week medicated follow-up, and 160 matched typically-developing peers. Attention, processing speed, working memory, impulsivity, and motor speed were assessed using a cognitive battery.

RESULTS

Processing speed and working memory significantly contributed to SoA performance in ADHD, regardless of medication status. While medicated, motor speed also underpinned the prediction of most task measures. For typically-developing adolescents, sustained attention and working memory contributed to SoA performance.

CONCLUSION

Typically-developing, unmedicated and treated ADHD adolescents recruit different aspects of cognition during SoA completion.

Spatial attention impairments are characterized by specific electro-encephalographic correlates and partially mediate the association between early life stress and anxiety

Although impaired attention is a diagnostic feature of anxiety disorders, we lack an understanding of which aspects of attention are impaired, the neurobiological basis of these impairments, and the contribution of stressors. To address these gaps in knowledge, we developed and tested behavioral tasks designed to parse the subdomains of attention impairments associated with anxiety symptoms and used electro-encephalographic (EEG) recordings to probe the neural basis of attentional performance. Participants were n = 55 individuals aged 18-35 with mild-to-moderate mood and anxiety symptoms. We also assessed stressful life events that may impact mental health and attention abilities, including stressors that occurred in early life before age 18 years. Severity of anxiety was found to be specifically associated with impairments in spatial attention but not feature-based attention. These impairments in spatial attention also partially mediated the association between early-life stressors and anxiety symptoms. Impairments in spatial selective attention were associated with decreased posterior alpha oscillations in EEG recordings in a subsample of participants, whereas spatial divided attention impairments were associated with decreased frontocentral theta oscillations. Our results provide a thorough characterization of attention impairments associated with anxiety, their EEG correlates, and the impact of stressors both in early life and adulthood.

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

BACKGROUND

Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders.

METHODS

We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.

RESULTS

Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged.

CONCLUSIONS

Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

Prefrontal transcranial magnetic stimulation for depression in US military veterans - A naturalistic cohort study in the veterans health administration

BACKGROUND

Repetitive transcranial magnetic stimulation (TMS) is an evidence-based treatment for pharmacoresistant major depressive disorder (MDD), however, the evidence in veterans has been mixed. To this end, VA implemented a nationwide TMS program that included evaluating clinical outcomes within a naturalistic design. TMS was hypothesized to be safe and provide clinically meaningful reductions in MDD and posttraumatic stress disorder (PTSD) symptoms.

METHODS

Inclusion criteria were MDD diagnosis and standard clinical TMS eligibility. Of the 770 patients enrolled between October 2017 and March 2020, 68.4% (n = 521) met threshold-level PTSD symptom criteria. Treatments generally used standard parameters (e.g., left dorsolateral prefrontal cortex, 120% motor threshold, 10 Hz, 3000 pulses/treatment). Adequate dose was operationally defined as 30 sessions. MDD and PTSD symptoms were measured using the 9-item patient health questionnaire (PHQ-9) and PTSD checklist for DSM-5 (PCL-5), respectively.

RESULTS

Of the 770 who received at least one session, TMS was associated with clinically meaningful (Cohen's d>1.0) and statistically significant (all p<.001) reductions in MDD and PTSD. Of the 340 veterans who received an adequate dose, MDD response and remission rates were 41.4% and 20%, respectively. In veterans with comorbid PTSD, 65.3% demonstrated clinically meaningful reduction and 46.1% no longer met PTSD threshold criteria after TMS. Side effects were consistent with the known safety profile of TMS.

LIMITATIONS

Include those inherent to retrospective observational cohort study in Veterans.

CONCLUSIONS

These multisite, large-scale data supports the effectiveness and safety of TMS for veterans with MDD and PTSD using standard clinical approaches.

Attention enhances category representations across the brain with strengthened residual correlations to ventral temporal cortex

How does attention enhance neural representations of goal-relevant stimuli while suppressing representations of ignored stimuli across regions of the brain? While prior studies have shown that attention enhances visual responses, we lack a cohesive understanding of how selective attention modulates visual representations across the brain. Here, we used functional magnetic resonance imaging (fMRI) while participants performed a selective attention task on superimposed stimuli from multiple categories and used a data-driven approach to test how attention affects both decodability of category information and residual correlations (after regressing out stimulus-driven variance) with category-selective regions of ventral temporal cortex (VTC). Our data reveal three main findings. First, when two objects are simultaneously viewed, the category of the attended object can be decoded more readily than the category of the ignored object, with the greatest attentional enhancements observed in occipital and temporal lobes. Second, after accounting for the response to the stimulus, the correlation in the residual brain activity between a cortical region and a category-selective region of VTC was elevated when that region’s preferred category was attended vs. ignored, and more so in the right occipital, parietal, and frontal cortices. Third, we found that the stronger the residual correlations between a given region of cortex and VTC, the better visual category information could be decoded from that region. These findings suggest that heightened residual correlations by selective attention may reflect the sharing of information between sensory regions and higher-order cortical regions to provide attentional enhancement of goal-relevant information.

Targeting the Salience Network: A Mini-Review on a Novel Neuromodulation Approach for Treating Alcohol Use Disorder

Alcohol use disorder (AUD) continues to be challenging to treat despite the best available interventions, with two-thirds of individuals going on to relapse by 1 year after treatment. Recent advances in the brain-based conceptual framework of addiction have allowed the field to pivot into a neuromodulation approach to intervention for these devastative disorders. Small trials of repetitive transcranial magnetic stimulation (rTMS) have used protocols developed for other psychiatric conditions and applied them to those with addiction with modest efficacy. Recent evidence suggests that a TMS approach focused on modulating the salience network (SN), a circuit at the crossroads of large-scale networks associated with AUD, may be a fruitful therapeutic strategy. The anterior insula or dorsal anterior cingulate cortex may be particularly effective stimulation sites given emerging evidence of their roles in processes associated with relapse.

Convergence, preliminary findings and future directions across the four human connectome projects investigating mood and anxiety disorders

In this paper we provide an overview of the rationale, methods, and preliminary results of the four Connectome Studies Related to Human Disease investigating mood and anxiety disorders. The first study, "Dimensional connectomics of anxious misery" (HCP-DAM), characterizes brain-symptom relations of a transdiagnostic sample of anxious misery disorders. The second study, "Human connectome Project for disordered emotional states" (HCP-DES), tests a hypothesis-driven model of brain circuit dysfunction in a sample of untreated young adults with symptoms of depression and anxiety. The third study, "Perturbation of the treatment resistant depression connectome by fast-acting therapies" (HCP-MDD), quantifies alterations of the structural and functional connectome as a result of three fast-acting interventions: electroconvulsive therapy, serial ketamine therapy, and total sleep deprivation. Finally, the fourth study, "Connectomes related to anxiety and depression in adolescents" (HCP-ADA), investigates developmental trajectories of subtypes of anxiety and depression in adolescence. The four projects use comparable and standardized Human Connectome Project magnetic resonance imaging (MRI) protocols, including structural MRI, diffusion-weighted MRI, and both task and resting state functional MRI. All four projects also conducted comprehensive and convergent clinical and neuropsychological assessments, including (but not limited to) demographic information, clinical diagnoses, symptoms of mood and anxiety disorders, negative and positive affect, cognitive function, and exposure to early life stress. The first round of analyses conducted in the four projects offered novel methods to investigate relations between functional connectomes and self-reports in large datasets, identified new functional correlates of symptoms of mood and anxiety disorders, characterized the trajectory of connectome-symptom profiles over time, and quantified the impact of novel treatments on aberrant connectivity. Taken together, the data obtained and reported by the four Connectome Studies Related to Human Disease investigating mood and anxiety disorders describe a rich constellation of convergent biological, clinical, and behavioral phenotypes that span the peak ages for the onset of emotional disorders. These data are being prepared for open sharing with the scientific community following screens for quality by the Connectome Coordinating Facility (CCF). The CCF also plans to release data from all projects that have been pre-processed using identical state-of-the-art pipelines. The resultant dataset will give researchers the opportunity to pool complementary data across the four projects to study circuit dysfunctions that may underlie mood and anxiety disorders, to map cohesive relations among circuits and symptoms, and to probe how these relations change as a function of age and acute interventions. This large and combined dataset may also be ideal for using data-driven analytic approaches to inform neurobiological targets for future clinical trials and interventions focused on clinical or behavioral outcomes.

Greater baseline connectivity of the salience and negative affect circuits are associated with natural improvements in anxiety over time in untreated participants

BACKGROUND

There is limited research examining the natural trajectories of depression and anxiety, how these trajectories relate to baseline neural circuit function, and how symptom trajectory-circuit relationships are impacted by engagement in lifestyle activities including exercise, hobbies, and social interactions. To address these gaps, we assessed these relations over three months in untreated participants.

METHODS

262 adults (59.5% female, mean age 35) with symptoms of anxiety and depression, untreated with pharmacotherapy or behavioral therapy, completed the DASS-42, WHOQOL, and custom surveys at baseline and follow-up to assess symptoms, psychosocial function, and lifestyle activity engagement. At baseline, participants underwent fMRI under task-free and task-evoked conditions. We quantified six circuits implicated in these symptoms: default mode, salience, negative and positive affect, attention, and cognitive control.

RESULTS

From baseline to 3 months, some participants demonstrated a natural improvement in anxiety (24%) and depression (26%) symptoms. Greater baseline salience circuit connectivity (pFDR=0.045), specifically between the left and right insula (pFDR=0.045), and greater negative affect circuit connectivity elicited by sad faces (pFDR=0.030) were associated with anxiety symptom improvement. While engagement in lifestyle activities were not associated with anxiety improvements, engagement in hobbies moderated the association between negative affect circuit connectivity and anxiety symptom improvement (p = 0.048).

LIMITATIONS

The observational design limits causal inference.

CONCLUSIONS

Our findings highlight the role of the salience and negative affect circuits as potential circuit markers of natural anxiety symptom improvements over time. Future studies that identify biomarkers associated with symptom improvements are critical for the development of personalized treatment targets.

Coping Strategies, Neural Structure, and Depression and Anxiety During the COVID-19 Pandemic: A Longitudinal Study in a Naturalistic Sample Spanning Clinical Diagnoses and Subclinical Symptoms

BACKGROUND

Although the COVID-19 pandemic has been shown to worsen anxiety and depression symptoms, we do not understand which behavioral and neural factors may mitigate this impact. To address this gap, we assessed whether adaptive and maladaptive coping strategies affect symptom trajectory during the pandemic. We also examined whether pre-pandemic integrity of brain regions implicated in depression and anxiety affect pandemic symptoms.

METHODS

In a naturalistic sample of 169 adults (66.9% female; age 19-74 years) spanning psychiatric diagnoses and subclinical symptoms, we assessed anhedonia, tension, and anxious arousal symptoms using validated components (21-item Depression, Anxiety, and Stress Scale), coping strategies (Brief-Coping Orientation to Problems Experienced), and gray matter volume (amygdala) and cortical thickness (hippocampus, insula, anterior cingulate cortex) from magnetic resonance imaging T1-weighted scans. We conducted general linear mixed-effects models to test preregistered hypotheses that 1) maladaptive coping pre-pandemic and 2) lower structural integrity pre-pandemic would predict more severe pandemic symptoms; and 3) coping would interact with neural structure to predict pandemic symptoms.

RESULTS

Greater use of maladaptive coping strategies was associated with more severe anxious arousal symptoms during the pandemic (p = .011, false discovery rate-corrected p [p FDR] = .035), specifically less self-distraction (p = .014, p FDR = .042) and greater self-blame (p = .002, p FDR = .012). Reduced insula thickness pre-pandemic predicted more severe anxious arousal symptoms (p = .001, p FDR = .027). Self-distraction interacted with amygdala volume to predict anhedonia symptoms (p = .005, p FDR = .020).

CONCLUSIONS

Maladaptive coping strategies and structural variation in brain regions may influence clinical symptoms during a prolonged stressful event (e.g., COVID-19 pandemic). Future studies that identify behavioral and neural factors implicated in responses to global health crises are warranted for fostering resilience.

Emotional face processing correlates with depression/anxiety symptoms but not wellbeing in non-clinical adults: An event-related potential study

Whilst alterations in emotional face processing, as indicated by event-related potentials (ERPs), are associated with depression and anxiety symptoms in clinical and non-clinical samples, it has remained unclear whether they are related to mental wellbeing. The current study aimed to address this question in a non-clinical sample. The analysis included 402 adult twins from the TWIN-E study. The COMPAS-W and the Depression Anxiety Stress Scale (DASS-42) were used to measure mental wellbeing and depression/anxiety symptoms, respectively. Participants viewed facial expressions under Unmasked (conscious) and Masked (subliminal) conditions while ERPs were recorded. The associations of emotion processing with mental wellbeing and depression/anxiety symptoms were assessed using multivariate linear mixed models. There was a strong association between depression/anxiety symptoms and the N170 amplitude difference for the Fear - Happy contrast in the Masked condition after controlling for wellbeing scores (B = 0.34, p < .001). Specifically, higher depression/anxiety symptoms were associated with a lack of differentiation between fearful and happy faces. No associations were found between emotional face processing and mental wellbeing scores. These results indicate that even within a non-clinical sample, alterations in emotional ERPs, namely the N170, reflect differences in depression/anxiety symptoms rather than differences in wellbeing. Furthermore, this effect was limited to automatic processing, rather than conscious processing of emotional stimuli, suggesting the observed differences apply only to the subconscious pathway.

A process for reviewing mental health apps: Using the One Mind PsyberGuide Credibility Rating System

Objective

Given the increasing number of publicly available mental health apps, we need independent advice to guide adoption. This paper discusses the challenges and opportunities of current mental health app rating systems and describes the refinement process of one prominent system, the One Mind PsyberGuide Credibility Rating Scale (PGCRS).

Methods

PGCRS Version 1 was developed in 2013 and deployed for 7 years, during which time a number of limitations were identified. Version 2 was created through multiple stages, including a review of evaluation guidelines and consumer research, input from scientific experts, testing, and evaluation of face validity. We then re-reviewed 161 mental health apps using the updated rating scale, investigated the reliability and discrepancy of initial scores, and updated ratings on the One Mind PsyberGuide public app guide.

Results

Reliabilities across the scale's 9 items ranged from -0.10 to 1.00, demonstrating that some characteristics of apps are more difficult to rate consistently. The average overall score of the 161 reviewed mental health apps was 2.51/5.00 (range 0.33-5.00). Ratings were not strongly correlated with app store star ratings, suggesting that credibility scores provide different information to what is contained in star ratings.

Conclusion

PGCRS summarizes and weights available information in 4 domains: intervention specificity, consumer ratings, research, and development. Final scores are created through an iterative process of initial rating and consensus review. The process of updating this rating scale and integrating it into a procedure for evaluating apps demonstrates one method for determining app quality.

Reappraisal-related neural predictors of treatment response to cognitive behavior therapy for post-traumatic stress disorder

BACKGROUND

Although trauma-focused cognitive behavior therapy (TF-CBT) is the frontline treatment for post-traumatic stress disorder (PTSD), one-third of patients are treatment non-responders. To identify neural markers of treatment response to TF-CBT when participants are reappraising aversive material.

METHODS

This study assessed PTSD patients (n = 37) prior to TF-CBT during functional magnetic brain resonance imaging (fMRI) when they reappraised or watched traumatic images. Patients then underwent nine sessions of TF-CBT, and were then assessed for symptom severity on the Clinician-Administered PTSD Scale. FMRI responses for cognitive reappraisal and emotional reactivity contrasts of traumatic images were correlated with the reduction of PTSD severity from pretreatment to post-treatment.

RESULTS

Symptom improvement was associated with decreased activation of the left amygdala during reappraisal, but increased activation of bilateral amygdala and hippocampus during emotional reactivity prior to treatment. Lower connectivity of the left amygdala to the subgenual anterior cingulate cortex, pregenual anterior cingulate cortex, and right insula, and that between the left hippocampus and right amygdala were also associated with symptom improvement.

CONCLUSIONS

These findings provide evidence that optimal treatment response to TF-CBT involves the capacity to engage emotional networks during emotional processing, and also to reduce the engagement of these networks when down-regulating emotions.

Problem-solving therapy-induced amygdala engagement mediates lifestyle behavior change in obesity with comorbid depression: a randomized proof-of-mechanism trial

BACKGROUND

Depression hinders obesity treatment; elucidating mechanisms may enable treatment enhancements.

OBJECTIVES

The aim was to investigate whether changes in neural targets in the negative affect circuit following psychotherapy mediate subsequent changes in weight and behaviors.

METHODS

Adults (n = 108) with obesity and depression were randomly assigned to usual care or an intervention that delivered problem-solving therapy (PST) for depression over 2 mo. fMRI for brain imaging was performed at baseline and 2 mo. BMI, physical activity, and diet were measured at baseline and 12 mo. Mediation analysis assessed between-group differences in neural target changes using t test and correlations between neural target changes and outcome changes (simple and interaction effect) using ordinary least-squares regression.

RESULTS

Compared with usual care, PST led to reductions in left amygdala activation (-0.75; 95% CI: -1.49, -0.01) and global scores of the negative affect circuit (-0.43; -0.81, -0.06), engaged by threat stimuli. Increases in amygdala activation and global circuit scores at 2 mo correlated with decreases in physical activity outcomes at 12 mo in the usual-care group; these relations were altered by PST. In relation to change in leisure-time physical activity, standardized β-coefficients were -0.67 in usual care and -0.01 in the intervention (between-group difference: 0.66; 0.02, 1.30) for change in left amygdala activation and -2.02 in usual care and -0.11 in the intervention (difference: 1.92; 0.64, 3.20) for change in global circuit scores. In relation to change in total energy expenditure, standardized β-coefficients were -0.65 in usual care and 0.08 in the intervention (difference: 0.73; 0.29, 1.16) for change in left amygdala activation and -1.65 in usual care and 0.08 in the intervention (difference: 1.74; 0.85, 2.63) for change in global circuit scores. Results were null for BMI and diet.

CONCLUSIONS

Short-term changes in the negative affect circuit engaged by threat stimuli following PST for depression mediated longer-term changes in physical activity. This trial was registered at www.clinicaltrials.gov as NCT02246413 (https://clinicaltrials.gov/ct2/show/NCT02246413).

Relating whole-brain functional connectivity to self-reported negative emotion in a large sample of young adults using group regularized canonical correlation analysis

The goal of our study was to use functional connectivity to map brain function to self-reports of negative emotion. In a large dataset of healthy individuals derived from the Human Connectome Project (N = 652), first we quantified functional connectivity during a negative face-matching task to isolate patterns induced by emotional stimuli. Then, we did the same in a complementary task-free resting state condition. To identify the relationship between functional connectivity in these two conditions and self-reports of negative emotion, we introduce group regularized canonical correlation analysis (GRCCA), a novel algorithm extending canonical correlations analysis to model the shared common properties of functional connectivity within established brain networks. To minimize overfitting, we optimized the regularization parameters of GRCCA using cross-validation and tested the significance of our results in a held-out portion of the data set using permutations. GRCCA consistently outperformed plain regularized canonical correlation analysis. The only canonical correlation that generalized to the held-out test set was based on resting state data (r = 0.175, permutation test p = 0.021). This canonical correlation loaded primarily on Anger-aggression. It showed high loadings in the cingulate, orbitofrontal, superior parietal, auditory and visual cortices, as well as in the insula. Subcortically, we observed high loadings in the globus pallidus. Regarding brain networks, it loaded primarily on the primary visual, orbito-affective and ventral multimodal networks. Here, we present the first neuroimaging application of GRCCA, a novel algorithm for regularized canonical correlation analyses that takes into account grouping of the variables during the regularization scheme. Using GRCCA, we demonstrate that functional connections involving the visual, orbito-affective and multimodal networks are promising targets for investigating functional correlates of subjective anger and aggression. Crucially, our approach and findings also highlight the need of cross-validation, regularization and testing on held out data for correlational neuroimaging studies to avoid inflated effects.

No support for white matter connectivity differences in the combined and inattentive ADHD presentations

Evidence from functional neuroimaging studies support neural differences between the Attention Deficit Hyperactivity Disorder (ADHD) presentation types. It remains unclear if these neural deficits also manifest at the structural level. We have previously shown that the ADHD combined, and ADHD inattentive types demonstrate differences in graph properties of structural covariance suggesting an underlying difference in neuroanatomical organization. The goal of this study was to examine and validate white matter brain organization between the two subtypes using both scalar and connectivity measures of brain white matter. We used both tract-based spatial statistical (TBSS) and tractography analyses with network-based Statistics (NBS) and graph-theoretical analyses in a cohort of 35 ADHD participants (aged 8–17 years) defined using DSM-IV criteria as combined (ADHD-C) type (n = 19) or as predominantly inattentive (ADHD-I) type (n = 16), and 28 matched neurotypical controls. We performed TBSS analyses on scalar measures of fractional anisotropy (FA), mean (MD), radial (RD), and axial (AD) diffusivity to assess differences in WM between ADHD types and controls. NBS and graph theoretical analysis of whole brain inter-regional tractography examined connectomic differences and brain network organization, respectively. None of the scalar measures significantly differed between ADHD types or relative to controls. Similarly, there were no tractography connectivity differences between the two subtypes and relative to controls using NBS. Global and regional graph measures were also similar between the groups. A single significant finding was observed for nodal degree between the ADHD-C and controls, in the right insula (corrected p = .029). Our result of no white matter differences between the subtypes is consistent with most previous findings. These findings together might suggest that the white matter structural architecture is largely similar between the DSM-based ADHD presentations is similar to the extent of being undetectable with the current cohort size.