Real-Time fMRI Functional Connectivity Neurofeedback Reducing Repetitive Negative Thinking in Depression: A Double-Blind, Randomized, Sham-Controlled Proof-of-Concept Trial.

INTRODUCTION: Repetitive negative thinking (RNT) is a cognitive process focusing on self-relevant and negative experiences, leading to a poor prognosis of major depressive disorder (MDD). We previously identified that connectivity between the precuneus/posterior cingulate cortex (PCC) and right temporoparietal junction (rTPJ) was positively correlated with levels of RNT. OBJECTIVE: In this double-blind, randomized, sham-controlled, proof-of-concept trial, we employed real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) to delineate the neural processes that may be causally linked to RNT and could potentially become treatment targets for MDD. METHODS: MDD-affected individuals were assigned to either active (n = 20) or sham feedback group (n = 19). RNT was measured by the Ruminative Response Scale-brooding subscale (RRS-B) before and 1 week after the intervention. RESULTS: Individuals in the active but not in the sham group showed a significant reduction in the RRS-B; however, a greater reduction in the PCC-rTPJ connectivity was unrelated to a greater reduction in the RRS-B. Exploratory analyses revealed that a greater reduction in the retrosplenial cortex (RSC)-rTPJ connectivity yielded a more pronounced reduction in the RRS-B in the active but not in the sham group. CONCLUSIONS: RtfMRI-nf was effective in reducing RNT. Considering the underlying mechanism of rtfMIR-nf, the RSC and rTPJ could be part of a network (i.e., default mode network) that might collectively affect the intensity of RNT. Understanding the relationship between the functional organization of targeted neural changes and clinical metrics, such as RNT, has the potential to guide the development of mechanism-based treatment of MDD.

Self-regulation of the posterior cingulate cortex with real-time fMRI neurofeedback augmented mindfulness training in healthy adolescents: A nonrandomized feasibility study.

Mindfulness training (MT) promotes the development of one's ability to observe and attend to internal and external experiences with objectivity and nonjudgment with evidence to improve psychological well-being. Real-time functional MRI neurofeedback (rtfMRI-nf) is a noninvasive method of modulating activity of a brain region or circuit. The posterior cingulate cortex (PCC) has been hypothesized to be an important hub instantiating a mindful state. This nonrandomized, single-arm study examined the feasibility and tolerability of training typically developing adolescents to self-regulate the posterior cingulate cortex (PCC) using rtfMRI-nf during MT. Thirty-four adolescents (mean age: 15 years; 14 females) completed the neurofeedback augmented mindfulness training task, including Focus-on-Breath (MT), Describe (self-referential thinking), and Rest conditions, across three neurofeedback and two non-neurofeedback runs (Observe, Transfer). Self-report assessments demonstrated the feasibility and tolerability of the task. Neurofeedback runs differed significantly from non-neurofeedback runs for the Focus-on-Breath versus Describe contrast, characterized by decreased activity in the PCC during the Focus-on-Breath condition (z = -2.38 to -6.27). MT neurofeedback neural representation further involved the medial prefrontal cortex, anterior cingulate cortex, dorsolateral prefrontal cortex, posterior insula, hippocampus, and amygdala. State awareness of physical sensations increased following rtfMRI-nf and was maintained at 1-week follow-up (Cohens' d = 0.69). Findings demonstrate feasibility and tolerability of rtfMRI-nf in healthy adolescents, replicates the role of PCC in MT, and demonstrate a potential neuromodulatory mechanism to leverage and streamline the learning of mindfulness practice. ( ClinicalTrials.gov identifier #NCT04053582; August 12, 2019).

Behavioral activation therapy for depression is associated with a reduction in the concentration of circulating quinolinic acid.

BACKGROUND: An inflammation-induced imbalance in the kynurenine pathway (KP) has been reported in major depressive disorder but the utility of these metabolites as predictive or therapeutic biomarkers of behavioral activation (BA) therapy is unknown. METHODS: Serum samples were provided by 56 depressed individuals before BA therapy and 29 of these individuals also provided samples after 10 weeks of therapy to measure cytokines and KP metabolites. The PROMIS Depression Scale (PROMIS-D) and the Sheehan Disability Scale were administered weekly and the Beck depression inventory was administered pre- and post-therapy. Data were analyzed with linear mixed-effect, general linear, and logistic regression models. The primary outcome for the biomarker analyses was the ratio of kynurenic acid to quinolinic acid (KynA/QA). RESULTS: BA decreased depression and disability scores (p's < 0.001, Cohen's d's > 0.5). KynA/QA significantly increased at post-therapy relative to baseline (p < 0.001, d = 2.2), an effect driven by a decrease in QA post-therapy (p < 0.001, uncorrected, d = 3.39). A trend towards a decrease in the ratio of kynurenine to tryptophan (KYN/TRP) was also observed (p = 0.054, uncorrected, d = 0.78). Neither the change in KynA/QA, nor baseline KynA/QA were associated with response to BA therapy. CONCLUSION: The current findings together with previous research show that electronconvulsive therapy, escitalopram, and ketamine decrease concentrations of the neurotoxin, QA, raise the possibility that a common therapeutic mechanism underlies diverse forms of anti-depressant treatment but future controlled studies are needed to test this hypothesis.

Striatal reactivity during emotion and reward relates to approach-avoidance conflict behaviour and is altered in adults with anxiety or depression.

BACKGROUND: We have previously reported activation in reward, salience and executive control regions during functional MRI (fMRI) using an approach-avoidance conflict (AAC) decision-making task with healthy adults. Further investigations into how anxiety and depressive disorders relate to differences in neural responses during AAC can inform their understanding and treatment. We tested the hypothesis that people with anxiety or depression have altered neural activation during AAC. METHODS: We compared 118 treatment-seeking adults with anxiety or depression and 58 healthy adults using linear mixed-effects models to examine group-level differences in neural activation (fMRI) during AAC decision-making. Correlational analyses examined relationships between behavioural and neural measures. RESULTS: Adults with anxiety or depression had greater striatal engagement when reacting to affective stimuli (p = 0.008, d = 0.31) regardless of valence, and weaker striatal engagement during reward feedback (p = 0.046, d = -0.27) regardless of the presence of monetary reward. They also had blunted amygdala activity during decision-making (p = 0.023, d = -0.32) regardless of the presence of conflict. Across groups, approach behaviour during conflict decision-making was inversely correlated with striatal activation during affective stimuli (p < 0.001, r = -0.28) and positively related to striatal activation during reward feedback (p < 0.001, r = 0.27). LIMITATIONS: Our transdiagnostic approach did not allow for comparisons between specific anxiety disorders, and our cross-sectional approach did not allow for causal inference. CONCLUSION: Anxiety and depression were associated with altered neural responses to AAC. Findings were consistent with the role of the striatum in action selection and reward responsivity, and they point toward striatal reactivity as a future treatment target. Blunting of amygdala activity in anxiety or depression may indicate a compensatory response to inhibit affective salience and maintain approach.

Latent variables for region of interest activation during the monetary incentive delay task.

BACKGROUND: The Monetary Incentive Delay task (MID) has been used extensively to probe anticipatory reward processes. However, individual differences evident during this task may relate to other constructs such as general arousal or valence processing (i.e., anticipation of negative versus positive outcomes). This investigation used a latent variable approach to parse activation patterns during the MID within a transdiagnostic clinical sample. METHODS: Participants were drawn from the first 500 individuals recruited for the Tulsa-1000 (T1000), a naturalistic longitudinal study of 1000 participants aged 18-55 (n = 476 with MID data). We employed a multiview latent analysis method, group factor analysis, to characterize factors within and across variable sets consisting of: (1) region of interest (ROI)-based blood oxygenation level-dependent (BOLD) contrasts during reward and loss anticipation; and (2) self-report measures of positive and negative valence and related constructs. RESULTS: Three factors comprised of ROI indicators emerged to accounted for >43% of variance and loaded on variables representing: (1) general arousal or general activation; (2) valence, with dissociable responses to anticipation of win versus loss; and (3) region-specific activation, with dissociable activation in salience versus perceptual brain networks. Two additional factors were comprised of self-report variables, which appeared to represent arousal and valence. CONCLUSIONS: Results indicate that multiview techniques to identify latent variables offer a novel approach for differentiating brain activation patterns during task engagement. Such approaches may offer insight into neural processing patterns through dimension reduction, be useful for probing individual differences, and aid in the development of optimal explanatory or predictive frameworks.

Test-retest reliability of approach-avoidance conflict decision-making during functional magnetic resonance imaging in healthy adults.

Neural and behavioral mechanisms during approach-avoidance conflict decision-making are relevant across various psychiatric disorders, particularly anxiety disorders. Studies using approach-avoidance conflict paradigms in healthy adults have identified preliminary neural mechanisms, but findings must be replicated and demonstrated as reliable before further application. This study sought to replicate previous findings and examine test-retest reliability of behavioral (approach behavior, reaction time) and neural (regions of interest [ROIs]) responses during an approach-avoidance conflict task conducted during functional magnetic resonance imaging (fMRI). Thirty healthy adults completed an approach-avoidance conflict task during fMRI on two occasions (mean interval: 17 days; range: 11-32). Effects of task condition during three task phases (decision-making, affective outcome and monetary reward) and intraclass correlation coefficients (ICCs) were calculated across time points. Results replicated that approach behavior was modulated by conflict during decision-making. ROI activations were replicated such that dorsal anterior cingulate cortex (dACC) was modulated by conflict during decision-making, and dACC, striatum, and anterior insula were modulated by valence during affective outcomes (p's <.0083). Approach behavior during conflict demonstrated excellent reliability (ICCs ≥.77). Activation of dACC during conflict decision-making and anterior insula during negative outcomes demonstrated fair reliability (ICCs = .51 and .54), and dACC and striatum activation demonstrated good reliability during negative outcomes (ICCs = .63 and .69). Two additional ROIs (amygdala, left dorsolateral prefrontal cortex) showed good reliability during negative outcomes (ICCs ≥.60). These results characterize several specific behavioral and neuroimaging responses that are replicable and sufficiently reliable during approach-avoidance conflict decision-making to support future utility.

Greater decision uncertainty characterizes a transdiagnostic patient sample during approach-avoidance conflict: a computational modelling approach.

BACKGROUND: Imbalances in approach-avoidance conflict (AAC) decision-making (e.g., sacrificing rewards to avoid negative outcomes) are considered central to multiple psychiatric disorders. We used computational modelling to examine 2 factors that are often not distinguished in descriptive analyses of AAC: decision uncertainty and sensitivity to negative outcomes versus rewards (emotional conflict). METHODS: A previously validated AAC task was completed by 478 participants, including healthy controls (n = 59), people with substance use disorders (n = 159) and people with depression and/or anxiety disorders who did not have substance use disorders (n = 260). Using an active inference model, we estimated individual-level values for a model parameter that reflected decision uncertainty and another that reflected emotional conflict. We also repeated analyses in a subsample (59 healthy controls, 161 people with depression and/or anxiety disorders, 56 people with substance use disorders) that was propensity-matched for age and general intelligence. RESULTS: The model showed high accuracy (72%). As further validation, parameters correlated with reaction times and self-reported task motivations in expected directions. The emotional conflict parameter further correlated with self-reported anxiety during the task (r = 0.32, p < 0.001), and the decision uncertainty parameter correlated with self-reported difficulty making decisions (r = 0.45, p < 0.001). Compared to healthy controls, people with depression and/or anxiety disorders and people with substance use disorders showed higher decision uncertainty in the propensity-matched sample (t = 2.16, p = 0.03, and t = 2.88, p = 0.005, respectively), with analogous results in the full sample; people with substance use disorders also showed lower emotional conflict in the full sample (t = 3.17, p = 0.002). LIMITATIONS: This study was limited by heterogeneity of the clinical sample and an inability to examine learning. CONCLUSION: These results suggest that reduced confidence in how to act, rather than increased emotional conflict, may explain maladaptive approach-avoidance behaviours in people with psychiatric disorders.

Extracurricular Activities, Screen Media Activity, and Sleep May Be Modifiable Factors Related to Children's Cognitive Functioning: Evidence From the ABCD Study®.

This study used a machine learning framework in conjunction with a large battery of measures from 9,718 school-age children (ages 9-11) from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study to identify factors associated with fluid cognitive functioning (FCF), or the capacity to learn, solve problems, and adapt to novel situations. The identified algorithm explained 14.74% of the variance in FCF, replicating previously reported socioeconomic and mental health contributors to FCF, and adding novel and potentially modifiable contributors, including extracurricular involvement, screen media activity, and sleep duration. Pragmatic interventions targeting these contributors may enhance cognitive performance and protect against their negative impact on FCF in children.

Visual cortical regions show sufficient test-retest reliability while salience regions are unreliable during emotional face processing.

Functional magnetic resonance imaging studies frequently use emotional face processing tasks to probe neural circuitry related to psychiatric disorders and treatments with an emphasis on regions within the salience network (e.g., amygdala). Findings across previous test-retest reliability studies of emotional face processing have shown high variability, potentially due to differences in data analytic approaches. The present study comprehensively examined the test-retest reliability of an emotional faces task utilizing multiple approaches to region of interest (ROI) analysis and by examining voxel-wise reliability across the entire brain for both neural activation and functional connectivity. Analyses included 42 healthy adult participants who completed an fMRI scan concurrent with an emotional faces task on two separate days with an average of 25.52 days between scans. Intraclass correlation coefficients (ICCs) were calculated for the 'FACES-SHAPES' and 'FACES' (compared to implicit baseline) contrasts across the following: anatomical ROIs identified from a publicly available brain atlas (i.e., Brainnetome), functional ROIs consisting of 5-mm spheres centered on peak voxels from a publicly available meta-analytic database (i.e., Neurosynth), and whole-brain, voxel-wise analysis. Whole-brain, voxel-wise analyses of functional connectivity were also conducted using both anatomical and functional seed ROIs. While group-averaged neural activation maps were consistent across time, only one anatomical ROI and two functional ROIs showed good or excellent individual-level reliability for neural activation. The anatomical ROI was the right medioventral fusiform gyrus for the FACES contrast (ICC â€‹= â€‹0.60). The functional ROIs were the left and the right fusiform face area (FFA) for both FACES-SHAPES and FACES (Left FFA ICCs â€‹= â€‹0.69 & 0.79; Right FFA ICCs â€‹= â€‹0.68 & 0.66). Poor reliability (ICCs â€‹< â€‹0.4) was identified for almost all other anatomical and functional ROIs, with some exceptions showing fair reliability (ICCs â€‹= â€‹0.4-0.59). Whole-brain voxel-wise analysis of neural activation identified voxels with good (ICCs â€‹= â€‹0.6-0.74) to excellent reliability (ICCs â€‹> â€‹0.75) that were primarily located in visual cortex, with several clusters in bilateral dorsal lateral prefrontal cortex (DLPFC). Whole-brain voxel-wise analyses of functional connectivity for amygdala and fusiform gyrus identified very few voxels with good to excellent reliability using both anatomical and functional seed ROIs. Exceptions included clusters in right cerebellum and right DLPFC that showed reliable connectivity with left amygdala (ICCs â€‹> â€‹0.6). In conclusion, results indicate that visual cortical regions demonstrate good reliability at the individual level for neural activation, but reliability is generally poor for salience regions often focused on within psychiatric research (e.g., amygdala). Given these findings, future clinical neuroimaging studies using emotional faces tasks to examine individual differences might instead focus on visual regions and their role in psychiatric disorders.

A pragmatic clinical trial examining the impact of a resilience program on college student mental health.

BACKGROUND: One in three college students experience significant depression or anxiety interfering with daily functioning. Resilience programs that can be administered to all students offer an opportunity for addressing this public health problem. The current study objective was to assess the benefit of a brief, universal resilience program for first-year college students. METHOD: First-year students at a private, midwestern university participated. This trial used a pragmatic design, delivering the intervention within university-identified orientation courses and was not randomized. The four-session resilience program included goal-building, mindfulness, and resilience skills. The comparison was orientation-as-usual. Primary outcomes included PROMIS® Depression and Anxiety and Connor-Davidson Resilience Scale. Secondary and exploratory outcomes included the Perceived Stress Scale, Emotion Regulation, and Cognitive Behavioral Therapy (CBT) Skills Questionnaires, and Freiburg Mindfulness Inventory. Time by treatment interactions at post-training and semester-end were examined using linear mixed models. RESULTS: Analysis included 252 students, 126 who completed resilience programming and a matched comparison sample. Resilience programming did not relate to improvements in depression at post-training (CI: -2.53 to 1.02; p = .404, d =-0.08), but did at semester-end (95% CI: -4.27 to -0.72; p = .006, d = -0.25) and improvements in perceived stress were observed at post-training (CI: -3.31 to -0.44; p = .011, d = -0.24) and semester-end (CI: -3.30 to -0.41; p = .013, d = -0.24). Emotion regulation, mindfulness, and CBT skills increased, with CBT skills mediating clinical improvements. CONCLUSIONS: Universal implementation of a brief, resilience intervention may be effective for improving college student mental health.

Meta-analytic review of psychological interventions for children survivors of natural and man-made disasters.

Although many post-disaster interventions for children and adolescent survivors of disaster and terrorism have been created, little is known about the effectiveness of such interventions. Therefore, this meta-analysis assessed PTSD outcomes among children and adolescent survivors of natural and man-made disasters receiving psychological interventions. Aggregating results from 24 studies (total N=2630) indicates that children and adolescents receiving psychological intervention fared significantly better than those in control or waitlist groups with respect to PTSD symptoms. Moderator effects were also observed for intervention package, treatment modality (group vs. individual), providers' level of training, intervention setting, parental involvement, participant age, length of treatment, intervention delivery timing, and methodological rigor. Findings are discussed in detail with suggestions for practice and future research.

Sustained increase in depression and anxiety among psychiatrically healthy adolescents during late stage COVID-19 pandemic.

Background: Adolescents have experienced increases in anxiety, depression, and stress during the COVID-19 pandemic and may be at particular risk for suffering from long-term mental health consequences because of their unique developmental stage. This study aimed to determine if initial increases in depression and anxiety in a small sample of healthy adolescents after the onset of the COVID-19 pandemic were sustained at follow-up during a later stage of the pandemic. Methods: Fifteen healthy adolescents completed self-report measures at three timepoints (pre-pandemic [T1], early pandemic [T2], and later pandemic [T3]). The sustained effect of COVID-19 on depression and anxiety was examined using linear mixed-effect analyses. An exploratory analysis was conducted to investigate the relationship between difficulties in emotion regulation during COVID-19 at T2 and increases in depression and anxiety at T3. Results: The severity of depression and anxiety was significantly increased at T2 and sustained at T3 (depression: Hedges' g [T1 to T2] = 1.04, g [T1 to T3] = 0.95; anxiety: g [T1 to T2] = 0.79, g [T1 to T3] = 0.80). This was accompanied by sustained reductions in positive affect, peer trust, and peer communication. Greater levels of difficulties in emotion regulation at T2 were related to greater symptoms of depression and anxiety at T3 (rho = 0.71 to 0.80). Conclusion: Increased symptoms of depression and anxiety were sustained at the later stage of the pandemic in healthy adolescents. Replication of these findings with a larger sample size would be required to draw firm conclusions.

Optimizing outcomes in psilocybin therapy: Considerations in participant evaluation and preparation.

Recent studies have demonstrated the promise of psilocybin therapies in creating positive changes for those with poor mental health across multiple diagnostic categories, including major depressive disorder (MDD), end-of-life anxiety, and obsessive-compulsive disorder (OCD). While there may be a large population that is eligible to participate in psilocybin therapy based on psychiatric diagnosis and medical clearance, little attention has been given to intrapersonal and interpersonal factors that might influence patient's readiness (i.e., eligibility and capacity) for psychedelic interventions. This paper proposes that readiness assessment includes both intrapersonal and interpersonal factors in order to improve safety, patient care, and treatment outcomes. While at the present time a reliable and valid instrument has not been developed, we propose that three specific areas of focus - patient presentation, therapeutic alliance, and patient safety - may be used to establish a patient's readiness for psilocybin therapy, thus increasing therapy optimization and personalization.

A machine learning analysis of risk and protective factors of suicidal thoughts and behaviors in college students.

OBJECTIVE: To identify robust and reproducible factors associated with suicidal thoughts and behaviors (STBs) in college students. METHODS: 356 first-year university students completed a large battery of demographic and clinically-relevant self-report measures during the first semester of college and end-of-year (n = 228). Suicide Behaviors Questionnaire-Revised (SBQ-R) assessed STBs. A machine learning (ML) pipeline using stacking and nested cross-validation examined correlates of SBQ-R scores. RESULTS: 9.6% of students were identified at significant STBs risk by the SBQ-R. The ML algorithm explained 28.3% of variance (95%CI: 28-28.5%) in baseline SBQ-R scores, with depression severity, social isolation, meaning and purpose in life, and positive affect among the most important factors. There was a significant reduction in STBs at end-of-year with only 1.8% of students identified at significant risk. CONCLUSION: Analyses replicated known factors associated with STBs during the first semester of college and identified novel, potentially modifiable factors including positive affect and social connectedness.

Neural processes of inhibitory control in American Indian peoples are associated with reduced mental health problems.

American Indians (AI) experience disproportionately high prevalence of suicide and substance use disorders (SUD). However, accounting for risk burden (e.g. historical trauma and discrimination), the likelihood of mental health disorders or SUD is similar or decreased compared with the broader population. Such findings have spurred psychological research examining the protective factors, but no studies have investigated its potential neural mechanisms. Inhibitory control is one of the potential neurobehavioral construct with demonstrated protective effects, but has not been examined in neuroimaging studies with AI populations specifically. We examined the incidence of suicidal thoughts and behaviors (STB) and SUD among AI (n = 76) and propensity matched (sex, age, income, IQ proxy and trauma exposure) non-Hispanic White (NHW) participants (n = 76). Among the AI sample, functional magnetic resonance imaging (fMRI) data recorded during the stop-signal task (SST) was examined in relation to STB and SUDs. AIs relative to NHW subjects displayed lower incidence of STB. AIs with no reported STBs showed greater activity in executive control regions during the SST compared with AI who endorsed STB. AI without SUD demonstrated lower activity relative to those individual reporting SUD. Results are consistent with a growing body of literature demonstrating the high level of risk burden driving disparate prevalence of mental health concerns in AI. Furthermore, differential activation during inhibitory control processing in AI individuals without STB may represent a neural mechanism of protective effects against mental health problems in AI. Future research is needed to elucidate sociocultural factors contributing protection against mental health outcomes in AIs and further delineate neural mechanisms with respect to specific concerns (e.g. SUD vs STB).

The unique face of anxious depression: Increased sustained threat circuitry response during fear acquisition.

Background: Sensitivity to threat with dysregulation of fear learning is thought to contribute to the development of psychiatric disorders, including anxiety disorders (AD) and major depressive disorder (MDD). However, fewer studies have examined fear learning in MDD than in AD. Nearly half of individuals with MDD have an AD and the comorbid diagnosis has worse outcomes. The current study used propensity matching to examine the hypothesis that AD+MDD shows greater neural correlates of fear learning than MDD, suggesting that the co-occurrence of AD+MDD is exemplified by exaggerated defense related processes. Methods: 195 individuals with MDD (N = 65) or AD+MDD (N=130) were recruited from the community and completed multi-level assessments, including a Pavlovian fear learning task during functional imaging. Results: MDD and AD+MDD showed significantly different patterns of activation for [CSplus-CSminus] in the medial amygdala (ηp2=0.009), anterior insula (ηp2=0.01), dorsolateral prefrontal cortex (ηp2=0.002), dorsal anterior cingulate cortex (ηp2=0.01), mid-cingulate cortex (ηp2=0.01) and posterior cingulate cortex (ηp2=0.02). These differences were driven by greater activation to the CS+ in late conditioning phases in ADD+MDD relative to MDD. Conclusions: AD+MDD showed a pattern of increased sustained activation in regions identified with fear learning. Effects were consistently driven by the threat condition, further suggesting fear signaling as the emergent target process. Differences emerged in regions associated with salience processing, attentional orienting/conflict, and self-relevant processing.These findings help to elucidate the fear signaling mechanisms involved in the pathophysiology of comorbid anxiety and depression, thereby highlighting promising treatment targets for this prevalent treatment group.

A randomized clinical trial of behavioral activation and exposure-based therapy for adults with generalized anxiety disorder.

Objective: Exposure-based therapy (EXP) and behavioral activation (BA) are empirically-supported behavioral intervention techniques that target avoidance and approach behavior to alleviate symptoms. Although EXP is an established treatment for generalized anxiety disorder (GAD), the effectiveness of BA for GAD has not been directly tested or compared with that of EXP. This study examined the efficacy of EXP and BA for adults with GAD. Method: In a randomized clinical trial (clinicaltrials.gov: NCT02807480) with partial blinding in Tulsa, OK, 102 adults with GAD were allocated to manualized, 10-session EXP or BA between April 2016-April 2021. Primary analyses were intention-to-treat and included the 94 (46 EXP, 48 BA) participants who started treatment. The GAD-7 self-report scale was the primary outcome measure. Results: Similar GAD-7 declines were observed at post-treatment for EXP (d=-0.97 [95% CI -1.40 to -0.53]) and BA (d=-1.14 [95% CI -1.57 to -0.70]), and were maintained through 6-month follow-up (EXP: d=-2.13, BA: d=-1.98). Compared to EXP, BA yielded more rapid declines in anxiety and depression scores during therapy (d=0.75-0.77), as well as lower anxiety and depression scores (d=0.13-0.14) and greater participant-rated improvement (d=0.64) at post-treatment. Bayesian analyses indicated 74-99% probability of greater change in BA than EXP at post-treatment. Conclusions: BA and EXP are both effective in treating GAD, and BA may confer greater benefit during treatment. Future research is warranted to inform personalized treatment approaches.

Mindfulness-Based Interventions for the Treatment of Aberrant Interoceptive Processing in Substance Use Disorders.

Altered interoception, or the processing of bodily signals, has been argued to play a role in the development and maintenance of substance use disorders (SUD). Therefore, interoceptive interventions focusing on bodily awareness, such as mindfulness meditation, may improve treatment outcomes for individuals with SUD. Here we review: (1) subjective, behavioral and brain evidence for altered interoceptive processing in SUD, focusing on insular and anterior cingulate cortices (INS, ACC), key regions for interoceptive processing; (2) research highlighting links between mindfulness and brain function; and (3) extant brain research investigating mindfulness-based interventions in SUD. SUD tend to be characterized by heightened INS and ACC responses to drug cues but blunted interoceptive awareness and attenuated INS and ACC responses during tasks involving bodily attention and/or perturbations. In contrast, mindfulness interventions in healthy individuals are linked to enhanced INS and ACC responses and heightened interoceptive awareness. It is crucial for future research to identify: (1) whether mindfulness-based treatments are efficacious across substance classes; (2) what particular approaches and dosages show the largest effect sizes in enhancing INS and ACC function to non-drug stimuli and reducing responsivity to substance cues, thereby improving SUD treatment outcomes (reducing drug craving and relapse).

Neural Processing Dysfunctions During Fear Learning but Not Reward-Related Processing Characterize Depressed Individuals With High Levels of Repetitive Negative Thinking.

BACKGROUND: Repetitive negative thinking (RNT) is a symptom dimension of depression that is associated with a poorer prognosis in terms of higher recurrence, treatment resistance, residual symptoms, and disability. This investigation examined whether RNT is associated with aberrant reward processing and fear learning. METHODS: Very high RNT (VH-RNT) (n = 60) and high RNT (H-RNT) (n = 60) propensity-matched individuals with depression (age, sex, race/ethnicity, income/employment, body mass index, depressive and anxiety symptom severity) participated in this study along with matched healthy comparison volunteers (n = 30). This propensity-matched sample was selected from the larger Tulsa 1000 study. Participants performed two functional magnetic resonance imaging tasks: the monetary incentive delay task probing reward processing and the fear conditioning task probing aversive learning and extinction. RESULTS: Both VH-RNT and H-RNT groups showed lower neural activity than healthy comparison subjects in reward circuitry, including the inferior frontal gyrus (VH-RNT: ß = -1.24, H-RNT: ß = -1.28) and the cerebellum (VH-RNT: ß = -0.93, H-RNT: ß = -1.14). However, individuals with VH-RNT exhibited lower activation than those with H-RNT in central autonomic network components during fear conditioning (ß = -0.84) and continued conditioned responses during early extinction in the postcentral cortex (ß = 0.71). CONCLUSIONS: VH-RNT showed aberrant processing in fear conditioning during both learning and extinction phases compared with H-RNT. These findings demonstrate that dysfunctions of negative valence associated with RNT may be domain specific, which should be taken into account for identifying potential specific targets of intervention.