Brain-based graph-theoretical predictive modeling to map the trajectory of anhedonia, impulsivity, and hypomania from the human functional connectome

Clinical assessments often fail to discriminate between unipolar and bipolar depression and identify individuals who will develop future (hypo)manic episodes. To address this challenge, we developed a brain-based graph-theoretical predictive model (GPM) to prospectively map symptoms of anhedonia, impulsivity, and (hypo)mania. Individuals seeking treatment for mood disorders (n = 80) underwent an fMRI scan, including (i) resting-state and (ii) a reinforcement-learning (RL) task. Symptoms were assessed at baseline as well as at 3- and 6-month follow-ups. A whole-brain functional connectome was computed for each fMRI task, and the GPM was applied for symptom prediction using cross-validation. Prediction performance was evaluated by comparing the GPM to a corresponding null model. In addition, the GPM was compared to the connectome-based predictive modeling (CPM). Cross-sectionally, the GPM predicted anhedonia from the global efficiency (a graph theory metric that quantifies information transfer across the connectome) during the RL task, and impulsivity from the centrality (a metric that captures the importance of a region) of the left anterior cingulate cortex during resting-state. At 6-month follow-up, the GPM predicted (hypo)manic symptoms from the local efficiency of the left nucleus accumbens during the RL task and anhedonia from the centrality of the left caudate during resting-state. Notably, the GPM outperformed the CPM, and GPM derived from individuals with unipolar disorders predicted anhedonia and impulsivity symptoms for individuals with bipolar disorders. Importantly, the generalizability of cross-sectional models was demonstrated in an external validation sample. Taken together, across DSM mood diagnoses, efficiency and centrality of the reward circuit predicted symptoms of anhedonia, impulsivity, and (hypo)mania, cross-sectionally and prospectively. The GPM is an innovative modeling approach that may ultimately inform clinical prediction at the individual level.

Neurocognitive risk phenotyping to predict mood symptoms in adolescence

Predicting mood disorders in adolescence is a challenge that motivates research to identify neurocognitive predictors of symptom expression and clinical profiles. This study used machine learning to test whether neurocognitive variables predicted future manic or anhedonic symptoms in two adolescent samples risk-enriched for lifetime mood disorders (Sample 1, n = 73, ages = 13-25, M [SD] = 19.22 [2.49] years, 68% lifetime mood disorder) or familial mood disorders (Sample 2, n = 154, ages = 13-21, M [SD] = 16.46 [1.95] years, 62% first-degree family history of mood disorder). Participants completed cognitive testing and functional magnetic resonance imaging at baseline, for behavioral and neural measures of reward processing and executive functioning. Next, participants completed a daily diary procedure for 8-16 weeks. Penalized mixed-effects models identified neurocognitive predictors of future mood symptoms and stress-reactive changes in mood symptoms. Results included the following. In both samples, adolescents showing ventral corticostriatal reward hyposensitivity and lower reward performance reported more severe stress-reactive anhedonia. Poorer executive functioning behavior was associated with heightened anhedonia overall in Sample 1, but lower stress-reactive anhedonia in both samples. In Sample 1, adolescents showing ventral corticostriatal reward hypersensitivity and poorer executive functioning reported more severe stress-reactive manic symptoms. Clustering analyses identified, and replicated, five neurocognitive subgroups. Adolescents characterized by neural or behavioral reward hyposensitivities together with average-to-poor executive functioning reported unipolar symptom profiles. Adolescents showing neural reward hypersensitivity together with poor behavioral executive functioning reported a bipolar symptom profile (Sample 1 only). Together, neurocognitive phenotypes may hold value for predicting symptom expression and profiles of mood pathology. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Reinforcement learning and working memory in mood disorders: A computational analysis in a developmental transdiagnostic sample

BACKGROUND

Mood disorders commonly onset during adolescence and young adulthood and are conceptually and empirically related to reinforcement learning abnormalities. However, the nature of abnormalities associated with acute symptom severity versus lifetime diagnosis remains unclear, and prior research has often failed to disentangle working memory from reward processes.

METHODS

The present sample (N = 220) included adolescents and young adults with a lifetime history of unipolar disorders (n = 127), bipolar disorders (n = 28), or no history of psychopathology (n = 62), and varying severity of mood symptoms. Analyses fitted a reinforcement learning and working memory model to an instrumental learning task that varied working memory load, and tested associations between model parameters and diagnoses or current symptoms.

RESULTS

Current severity of manic or anhedonic symptoms negatively correlated with task performance. Participants reporting higher severity of current anhedonia, or with lifetime unipolar or bipolar disorders, showed lower reward learning rates. Participants reporting higher severity of current manic symptoms showed faster working memory decay and reduced use of working memory.

LIMITATIONS

Computational parameters should be interpreted in the task environment (a deterministic reward learning paradigm), and developmental population. Future work should test replication in other paradigms and populations.

CONCLUSIONS

Results indicate abnormalities in reinforcement learning processes that either scale with current symptom severity, or correspond with lifetime mood diagnoses. Findings may have implications for understanding reward processing anomalies related to state-like (current symptom) or trait-like (lifetime diagnosis) aspects of mood disorders.

The dimensional structure of internalizing psychopathology: Relation to diagnostic categories

Recent approaches aim to represent the dimensional structure of psychopathology, but relatively little research has rigorously tested sub-dimensions within internalizing psychopathology. This study tests pre-registered models of the dimensional structure of internalizing psychopathology, and their relations with current and lifetime depressive and anxiety disorders diagnostic data, in adult samples harmonized across three sites (n=427). Across S-1 bifactor and hierarchical models, we found converging evidence for both general and specific internalizing dimensions. Depression, generalized anxiety disorder (GAD), social anxiety disorder (SAD), and panic attacks were all associated with a general internalizing factor that we posit primarily represents motivational anhedonia. GAD was also associated with a specific anxious apprehension factor, and SAD with specific anxious apprehension and low positive affect factors. We suggest that dimensional approaches capturing shared and specific internalizing symptom facets more accurately describe the structure of internalizing psychopathology and provide useful alternatives to categorical diagnoses to advance clinical science.

Amygdala and nucleus accumbens activation during reward anticipation moderates the association between life stressor frequency and depressive symptoms

BACKGROUND

Life stressors confer risk for depressive symptoms, but individuals vary in the extent of their sensitivity to life stressors. One protective factor may be an individual's level of reward sensitivity, e.g., a stronger neurobiological response to environmental rewards may mitigate emotional responses to stressors. However, the nature of neurobiological reward sensitivity that corresponds with stress resilience is unknown. Further, this model is untested in adolescence, when life stressor frequency and depression increase.

METHODS

We tested the hypothesis that stronger reward-related activation in the left and right nucleus accumbens (NAc), amygdala, and medial prefrontal cortex (mPFC) attenuates the strength of the stress-depression relation. We measured BOLD activation throughout Win and Lose blocks of a monetary reward task, as well as during anticipation and outcome phases of the task. Participants (N = 151, ages 13-19) were recruited to be stratified on risk for mood disorders to enhance variance in depressive symptoms.

RESULTS

Activation during anticipation of rewards in the bilateral amygdala and NAc, but not mPFC, buffered the association between life stressors and depressive symptoms. This buffering effect was not found for reward outcome activation or activation across Win blocks.

CONCLUSIONS

Results highlight the importance of reward anticipation activation of subcortical structures in attenuating the stress-depression link, suggesting that reward motivation may be a cognitive mechanism through which this stress buffering occurs.

Longitudinal Relations Between Emotion Regulation and Internalizing Symptoms in Emerging Adults During the Covid-19 Pandemic

Background

Maladaptive and adaptive emotion regulation are putative risk and protective factors for depression and anxiety, but most prior research does not differentiate within-person effects from between-person individual differences. The current study does so during the early part of the Covid-19 pandemic when internalizing symptoms were high.

Methods

A sample of emerging adult undergraduate students (N = 154) completed online questionnaires bi-weekly on depression, anxiety, and emotion regulation across eight weeks during the early days of the Covid-19 pandemic (April 2nd to June 27th, 2020).

Results

Depression demonstrated significantly positive between-person correlations with overall maladaptive emotion regulation, catastrophizing, and self-blame, and negative correlations with overall adaptive emotion regulation and reappraisal. Anxiety demonstrated significantly positive between-person correlations with overall maladaptive emotion regulation, rumination, and catastrophizing, and a negative correlation with reappraisal. After controlling for these between-person associations, however, there were generally no within-person associations between emotion regulation and internalizing symptoms.

Conclusions

Emotion regulation and internalizing symptoms might be temporally stable individual differences that cooccur with one another as opposed to having a more dynamic relation. Alternatively, these dynamic mechanisms might operate over much shorter or longer periods compared to the two-week time lag in the current study.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10608-023-10366-9.

Mood Symptom Dimensions and Developmental Differences in Neurocognition in Adolescence

Adolescence is critical period of neurocognitive development as well as increased prevalence of mood pathology. This cross-sectional study replicated developmental patterns of neurocognition and tested whether mood symptoms moderated developmental effects. Participants were 419 adolescents (n=246 with current mood disorders) who completed reward learning and executive functioning tasks, and reported on age, puberty, and mood symptoms. Structural equation modeling revealed a quadratic relationship between puberty and reward learning performance that was moderated by symptom severity: in early puberty, adolescents reporting higher manic symptoms exhibited heightened reward learning performance (better maximizing of rewards on learning tasks), whereas adolescents reporting elevated anhedonia showed blunted reward learning performance. Models also showed a linear relationship between age and executive functioning that was moderated by manic symptoms: adolescents reporting higher mania showed poorer executive functioning at older ages. Findings suggest neurocognitive development is altered in adolescents with mood pathology and suggest directions for longitudinal studies.

Stress and reward: A multimodal assessment of childhood sexual abuse

Background

Childhood adversity has been found to impact stress and brain reward systems but it is unclear whether interactions between these systems might explain resilient vs. non-resilient trajectories following childhood sexual abuse (CSA). To address this gap, we adopted a multimodal approach in which cortisol reactivity to an acute stressor was assessed in conjunction with behavioral and neural measures of reward responsiveness in females with major depressive disorder (MDD) or no psychiatric disorders (i.e., resilient) who experienced CSA compared to females with and without MDD who did not experience abuse.

Methods

Latent Class Mixed Modelling (LCMM) identified classes of adults (n = 62; MAge = 26.48, SD = 5.68) characterized by distinct cortisol trajectories in response to a combined social evaluative cold pressor task. Classes were examined for their history of CSA and resilience as well as behavioral and neural measures of reward responsiveness using 128-channel electroencephalography (event-related potentials and source localization analysis).

Results

LCMM analysis identified two distinct classes of individuals with increased (Responders) or blunted (Non-Responders) cortisol reactivity to an acute stressor. Unlike Responders, Non-Responders did not modulate reward responses throughout the stress manipulation. No differences emerged between Responders and Non-Responders in terms of CSA or resilience. However, exploratory results showed that blunted cortisol response and non-modulation of reward responses emerged for those who experienced CSA at a younger age.

Conclusions

Co-occurring blunted stress and reward reactivity emerged irrespective of adults' experience of CSA or resilience. However, preliminary findings showed that CSA ending during peripubertal development was associated with blunted cortisol and reward responsiveness. Future research needs to replicate findings in larger samples and could investigate if increasing reward responsiveness during critical times of neurodevelopment could normalize stress reactivity to future stressors and thus promote resilience.

Dynamic Resting-State Network Biomarkers of Antidepressant Treatment Response

BACKGROUND

Delivery of effective antidepressant treatment has been hampered by a lack of objective tools for predicting or monitoring treatment response. This study aimed to address this gap by testing novel dynamic resting-state functional network markers of antidepressant response.

METHODS

The Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study randomized adults with major depressive disorder to 8 weeks of either sertraline or placebo, and depression severity was evaluated longitudinally. Participants completed resting-state neuroimaging pretreatment and again after 1 week of treatment (n = 259 eligible for analyses). Coactivation pattern analyses identified recurrent whole-brain states of spatial coactivation, and computed time spent in each state for each participant was the main dynamic measure. Multilevel modeling estimated the associations between pretreatment network dynamics and sertraline response and between early (pretreatment to 1 week) changes in network dynamics and sertraline response.

RESULTS

Dynamic network markers of early sertraline response included increased time in network states consistent with canonical default and salience networks, together with decreased time in network states characterized by coactivation of cingulate and ventral limbic or temporal regions. The effect of sertraline on depression recovery was mediated by these dynamic network changes. In contrast, early changes in dynamic functioning of corticolimbic and frontoinsular-default networks were related to patterns of symptom recovery common across treatment groups.

CONCLUSIONS

Dynamic resting-state markers of early antidepressant response or general recovery may assist development of clinical tools for monitoring and predicting effective intervention.

Resting state brain dynamics: Associations with childhood sexual abuse and major depressive disorder

Early life stress (ELS) and major depressive disorder (MDD) share neural network abnormalities. However, it is unclear how ELS and MDD may separately and/or jointly relate to brain networks, and whether neural differences exist between depressed individuals with vs without ELS. Moreover, prior work evaluated static versus dynamic network properties, a critical gap considering brain networks show changes in coordinated activity over time. Seventy-one unmedicated females with and without childhood sexual abuse (CSA) histories and/or MDD completed a resting state scan and a stress task in which cortisol and affective ratings were collected. Recurring functional network co-activation patterns (CAPs) were examined and time in CAP (number of times each CAP is expressed) and transition frequencies (transitioning between different CAPs) were computed. The effects of MDD and CSA on CAP metrics were examined and CAP metrics were correlated with depression and stress-related variables. Results showed that MDD, but not CSA, related to CAP metrics. Specifically, individuals with MDD (N = 35) relative to HCs (N = 36), spent more time in a posterior default mode (DMN)-frontoparietal network (FPN) CAP and transitioned more frequently between posterior DMN-FPN and prototypical DMN CAPs. Across groups, more time spent in a posterior DMN-FPN CAP and greater DMN-FPN and prototypical DMN CAP transition frequencies were linked to higher rumination. Imbalances between the DMN and the FPN appear central to MDD and might contribute to MDD-related cognitive dysfunction, including rumination. Unexpectedly, CSA did not modulate such dysfunctions, a finding that needs to be replicated by future studies with larger sample sizes.

General and Specific Dimensions of Mood Symptoms Are Associated With Impairments in Common Executive Function in Adolescence and Young Adulthood

Both unipolar and bipolar depression have been linked with impairments in executive functioning (EF). In particular, mood symptom severity is associated with differences in common EF, a latent measure of general EF abilities. The relationship between mood disorders and EF is particularly salient in adolescence and young adulthood when the ongoing development of EF intersects with a higher risk of mood disorder onset. However, it remains unclear if common EF impairments have associations with specific symptom dimensions of mood pathology such as blunted positive affect, mood instability, or physiological arousal, or if differences in common EF more broadly relate to what is shared across various symptom domains, such as general negative affect or distress. To address this question, bifactor models can be applied to simultaneously examine the shared and unique contributions of particular mood symptom dimensions. However, no studies to our knowledge have examined bifactor models of mood symptoms in relation to measures of common EF. This study examined associations between common EF and general vs. specific symptom dimensions (anhedonia, physiological arousal, and mania) using structural equation modeling in adolescents and young adults with varying severity of mood symptoms (n = 495, ages = 13-25 years, 68.69% female). A General Depression factor capturing shared variance across symptoms statistically predicted lower Common EF. Additionally, a factor specific to physiological arousal was associated with lower Common EF. Anhedonia-specific and Mania-specific factors were not significantly related to Common EF. Altogether, these results indicate that deficits in common EF are driven by, or reflect, general features of mood pathology that are shared across symptom dimensions but are also specifically associated with physiological arousal.

Executive Functions and Impulsivity as Transdiagnostic Correlates of Psychopathology in Childhood: A Behavioral Genetic Analysis

Executive functions (EFs) and impulsivity are dimensions of self-regulation that are both related to psychopathology. However, self-report measures of impulsivity and laboratory EF tasks typically display small correlations, and existing research indicates that impulsivity and EFs may tap separate aspects of self-regulation that independently statistically predict psychopathology in adulthood. However, relationships between EFs, impulsivity, and psychopathology may be different in childhood compared to adulthood. Here, we examine whether these patterns hold in the baseline assessment of the Adolescent Brain and Cognitive Development (ABCD) sample, a national sample of over 11,000 children (including 749 twin pairs) ages 9-10 years. We examine the phenotypic and genetic relationships among latent variables for different components of EFs and multiple facets of impulsivity. Additionally, we assess how EFs and impulsivity relate to composite measures and latent variables of psychopathology derived from parent report. EFs were weakly correlated with impulsivity, and the strength varied by impulsivity facet, emphasizing their separability. We did not identify significant genetic and environmental correlations between EFs and impulsivity. Moreover, controlling for their small relationships with each other, both EFs and some facets of impulsivity statistically predicted an Externalizing factor, attention problems, and social problems, and twin analyses suggested these relationships were genetic in origin. These findings indicate that EFs and impulsivity represent phenotypically and genetically separable aspects of self-regulation that are both transdiagnostic correlates of psychopathology in childhood.

The Emotional Word-Emotional Face Stroop task in the ABCD study: Psychometric validation and associations with measures of cognition and psychopathology

Characterizing the interactions among attention, cognitive control, and emotion during adolescence may provide important insights into why this critical developmental period coincides with a dramatic increase in risk for psychopathology. However, it has proven challenging to develop a single neurobehavioral task that simultaneously engages and differentially measures these diverse domains. In the current study, we describe properties of performance on the Emotional Word-Emotional Face Stroop (EWEFS) task in the Adolescent Brain Cognitive Development (ABCD) Study, a task that allows researchers to concurrently measure processing speed/attentional vigilance (i.e., performance on congruent trials), inhibitory control (i.e., Stroop interference effect), and emotional information processing (i.e., difference in performance on trials with happy as compared to angry distracting faces). We first demonstrate that the task manipulations worked as designed and that Stroop performance is associated with multiple cognitive constructs derived from different measures at a prior time point. We then show that Stroop metrics tapping these three domains are preferentially associated with aspects of externalizing psychopathology and inattention. These results highlight the potential of the EWEFS task to help elucidate the longitudinal dynamics of attention, inhibitory control, and emotion across adolescent development, dynamics which may be altered by level of psychopathology.

Behavioral mediators of stress-related mood symptoms in adolescence & young adulthood

BACKGROUND

Stress is a risk factor for unipolar and bipolar mood disorders, but the mechanisms linking stress to specific symptoms remain elusive. Behavioral responses to stress, such as impulsivity and social withdrawal, may mediate the associations between stress and particular mood symptoms.

METHODS

This study evaluated behavioral mediators of the relationship between self-reported intensity of daily stress and mood symptoms over up to eight weeks of daily diary surveys. The sample included individuals with unipolar or bipolar disorders, or with no psychiatric history (n = 113, ages 15-25).

RESULTS

Results showed that higher daily stress was related to higher severity of mania, and this pathway was mediated by impulsive behaviors. Higher stress also predicted higher severity of anhedonic depression, and social withdrawal mediated this relationship. A k-means clustering analysis revealed six subgroups with divergent profiles of stress-behavior-symptom pathways.

LIMITATIONS

Given the observational study design, analyses cannot determine causal relationships amongst these variables. Further work is needed to determine how relationships between these variables may vary based on stressor type, at different timescales, and within different populations.

CONCLUSIONS

Findings support a theoretical model in which impulsivity and social withdrawal act as behavioral mediators of the relationship between stress and mood symptoms. Additionally, distinct patterns of reactivity distinguished subgroups of people vulnerable to particular types of mood symptoms. These results provide novel information about how stress-reactive behaviors relate to specific mood symptoms, which may have clinical relevance as targets of intervention.

Sex differences in functional network dynamics observed using coactivation pattern analysis

Sex differences in the organization of large-scale resting-state brain networks have been identified using traditional static measures, which average functional connectivity over extended time periods. In contrast, emerging dynamic measures have the potential to define sex differences in network changes over time, providing additional understanding of neurobiological sex differences. To meet this goal, we used a Coactivation Pattern Analysis (CAP) using resting-state functional magnetic resonance imaging data from 181 males and 181 females from the Human Connectome Project. Significant main effects of sex were observed across two independent imaging sessions. Relative to males, females spent more total time in two transient network states (TNSs) spatially overlapping with the dorsal attention network and occipital/sensory-motor network. Greater time spent in these TNSs was related to females making more frequent transitions into these TNSs compared to males. In contrast, males spent more total time in TNSs spatially overlapping with the salience network, which was related to males staying for longer periods once entering these TNSs compared to females. State-to-state transitions also significantly differed between sexes: females transitioned more frequently from default mode network (DMN) states to the dorsal attention network state, whereas males transitioned more frequently from DMN states to salience network states. Results show that males and females spend differing amounts of time at rest in two distinct attention-related networks and show sex-specific transition patterns from DMN states into these attention-related networks. This work lays the groundwork for future investigations into the cognitive and behavioral implications of these sex-specific network dynamics.

Functional Segregation of Human Brain Networks Across the Lifespan: An Exploratory Analysis of Static and Dynamic Resting-State Functional Connectivity

Prior research has shown that during development, there is increased segregation between, and increased integration within, prototypical resting-state functional brain networks. Functional networks are typically defined by static functional connectivity over extended periods of rest. However, little is known about how time-varying properties of functional networks change with age. Likewise, a comparison of standard approaches to functional connectivity may provide a nuanced view of how network integration and segregation are reflected across the lifespan. Therefore, this exploratory study evaluated common approaches to static and dynamic functional network connectivity in a publicly available dataset of subjects ranging from 8 to 75 years of age. Analyses evaluated relationships between age and static resting-state functional connectivity, variability (standard deviation) of connectivity, and mean dwell time of functional network states defined by recurring patterns of whole-brain connectivity. Results showed that older age was associated with decreased static connectivity between nodes of different canonical networks, particularly between the visual system and nodes in other networks. Age was not significantly related to variability of connectivity. Mean dwell time of a network state reflecting high connectivity between visual regions decreased with age, but older age was also associated with increased mean dwell time of a network state reflecting high connectivity within and between canonical sensorimotor and visual networks. Results support a model of increased network segregation over the lifespan and also highlight potential pathways of top-down regulation among networks.

Frontostriatal and Dopamine Markers of Individual Differences in Reinforcement Learning: A Multi-modal Investigation

Prior studies have shown that dopamine (DA) functioning in frontostriatal circuits supports reinforcement learning (RL), as phasic DA activity in ventral striatum signals unexpected reward and may drive coordinated activity of striatal and orbitofrontal regions that support updating of action plans. However, the nature of DA functioning in RL is complex, in particular regarding the role of DA clearance in RL behavior. Here, in a multi-modal neuroimaging study with healthy adults, we took an individual differences approach to the examination of RL behavior and DA clearance mechanisms in frontostriatal learning networks. We predicted that better RL would be associated with decreased striatal DA transporter (DAT) availability and increased intrinsic functional connectivity among DA-rich frontostriatal regions. In support of these predictions, individual differences in RL behavior were related to DAT binding potential in ventral striatum and resting-state functional connectivity between ventral striatum and orbitofrontal cortex. Critically, DAT binding potential had an indirect effect on reinforcement learning behavior through frontostriatal connectivity, suggesting potential causal relationships across levels of neurocognitive functioning. These data suggest that individual differences in DA clearance and frontostriatal coordination may serve as markers for RL, and suggest directions for research on psychopathologies characterized by altered RL.

Machine Learning Identifies Large-Scale Reward-Related Activity Modulated by Dopaminergic Enhancement in Major Depression

BACKGROUND

Theoretical models have emphasized systems-level abnormalities in major depressive disorder (MDD). For unbiased yet rigorous evaluations of pathophysiological mechanisms underlying MDD, it is critically important to develop data-driven approaches that harness whole-brain data to classify MDD and evaluate possible normalizing effects of targeted interventions. Here, using an experimental therapeutics approach coupled with machine learning, we investigated the effect of a pharmacological challenge aiming to enhance dopaminergic signaling on whole-brain response to reward-related stimuli in MDD.

METHODS

Using a double-blind, placebo-controlled design, we analyzed functional magnetic resonance imaging data from 31 unmedicated MDD participants receiving a single dose of 50 mg amisulpride (MDD_Amisulpride), 26 MDD participants receiving placebo (MDD_Placebo), and 28 healthy control subjects receiving placebo (HC_Placebo) recruited through two independent studies. An importance-guided machine learning technique for model selection was used on whole-brain functional magnetic resonance imaging data probing reward anticipation and consumption to identify features linked to MDD (MDD_Placebo vs. HC_Placebo) and dopaminergic enhancement (MDD_Amisulpride vs. MDD_Placebo).

RESULTS

Highly predictive classification models emerged that distinguished MDD_Placebo from HC_Placebo (area under the curve = 0.87) and MDD_Placebo from MDD_Amisulpride (area under the curve = 0.89). Although reward-related striatal activation and connectivity were among the most predictive features, the best truncated models based on whole-brain features were significantly better relative to models trained using striatal features only.

CONCLUSIONS

Results indicate that in MDD, enhanced dopaminergic signaling restores abnormal activation and connectivity in a widespread network of regions. These findings provide new insights into the pathophysiology of MDD and pharmacological mechanism of antidepressants at the system level in addressing reward processing deficits among depressed individuals.

Dynamic functioning of transient resting-state coactivation networks in the Human Connectome Project

Resting‐state analyses evaluating large‐scale brain networks have largely focused on static correlations in brain activity over extended time periods, however emerging approaches capture time‐varying or dynamic patterns of transient functional networks. In light of these new approaches, there is a need to classify common transient network states (TNS) in terms of their spatial and dynamic properties. To fill this gap, two independent resting state scans collected in 462 healthy adults from the Human Connectome Project were evaluated using coactivation pattern analysis to identify (eight) TNS that recurred across participants and over time. These TNS spatially overlapped with prototypical resting state networks, but also diverged in notable ways. In particular, analyses revealed three TNS that shared cortical midline overlap with the default mode network (DMN), but these “complex” DMN states also encompassed distinct regions that fall beyond the prototypical DMN, suggesting that the DMN defined using static methods may represent the average of distinct complex‐DMN states. Of note, dwell time was higher in “complex” DMN states, challenging the idea that the prototypical DMN, as a single unit, is the dominant resting‐state network as typically defined by static resting state methods. In comparing the two resting state scans, we also found high reliability in the spatial organization and dynamic activities of network states involving DMN or sensorimotor regions. Future work will determine whether these TNS defined by coactivation patterns are in other samples, and are linked to fundamental cognitive properties.

Frontoinsular Network Markers of Current and Future Adolescent Mood Health

BACKGROUND

Adolescence is a developmental period in which depression and related mood syndromes often emerge, but few objective markers exist to guide diagnosis or predict symptoms. One potential mood marker is the functioning of frontoinsular networks, which undergo substantial development in adolescence and have been implicated in adult depression. To test this hypothesis, we used task-based neuroimaging to evaluate whether frontoinsular network dysfunction was linked to current and prospective mood health in adolescents.

METHODS

Adolescents (n = 40, 13-19 years of age) reporting varying levels of depressive symptom severity performed an emotional working memory task with neuroimaging. Next, teens completed a 2-week follow-up consisting of a daily diary report of negative affect and final report of depressive symptoms (n = 28 adherent). Analyses tested associations between task-related functional connectivity in frontoinsular networks and baseline or prospective measures of mood health over 2-week follow-up.

RESULTS

Frontoinsular task response was associated with higher current depression severity (p = .049, η_p² = .12), increases in future depression severity (p = .018, η_p² = .23), and more intense and labile negative affect in daily life (ps = .015 to .040, η_p² = .22 to .30). In particular, hypoconnectivity between insula and lateral prefrontal regions of the frontoparietal network was related to both baseline and prospective mood health, and hyperconnectivity between insula and midline or temporal regions of the default network was related to prospective mood health.

CONCLUSIONS

These findings indicate that frontoinsular imbalances are related to both current depression and changes in mood health in the near future and suggest that frontoinsular markers may hold promise as translational tools for risk prediction.

Regional Prefrontal Resting-State Functional Connectivity in Posttraumatic Stress Disorder

BACKGROUND

Prefrontal subregions, including the ventromedial prefrontal cortex (PFC), dorsomedial PFC, and dorsolateral PFC (DLPFC), are differentially implicated in the pathophysiology of posttraumatic stress disorder (PTSD), though few existing studies have examined subregional differences in resting-state functional connectivity (rsFC). We hypothesized that PTSD would involve weaker positive rsFC between ventromedial PFC, dorsomedial PFC, and other default mode network regions and increased negative rsFC between DLPFC and posterior default mode network regions. Additionally, we hypothesized that prefrontal regions exhibiting group differences in rsFC would be characterized by alterations in cortical thickness.

METHODS

Participants included 36 healthy control subjects, 30 trauma-exposed control subjects, and 21 individuals with current DSM-IV PTSD resulting from community-acquired trauma. Participants completed the Clinician Administered PTSD Scale, questionnaires (Childhood Trauma Questionnaire, Adverse Childhood Events, Life Events Checklist, Beck Depression Inventory), structural neuroimaging, and resting-state functional magnetic resonance imaging. rsFC of DLPFC, ventromedial PFC, and dorsomedial PFC seeds was evaluated in SPM12 and CONN. Cortical thickness for regions with significant rsFC findings was assessed using FreeSurfer.

RESULTS

Relative to both healthy control and trauma-exposed control subjects, individuals with PTSD showed increased negative rsFC between the DLPFC and a region of precuneus. This finding was associated with increased overall symptom severity but not with trauma load or childhood trauma exposure. Greater negative DLPFC-precuneus connectivity was associated with greater bilateral precuneus thickness.

CONCLUSIONS

Given participation of precuneus subregions in the central executive network, increased anticorrelation between right DLPFC and precuneus in this sample may reflect increased opposition between anterior and posterior central executive network hubs in PTSD.

Attention Bias in Rumination and Depression: Cognitive Mechanisms and Brain Networks

Depressed individuals exhibit biased attention to negative emotional information. However, much remains unknown about (1) the neurocognitive mechanisms of attention bias (e.g., qualities of negative information that evoke attention bias, or functional brain network dynamics that may reflect a propensity for biased attention) and (2) distinctions in the types of attention bias related to different dimensions of depression (e.g., ruminative depression). Here, in 50 women, clinical depression was associated with facilitated processing of negative information only when such information was self-descriptive and task-relevant. However, among depressed individuals, trait rumination was associated with biases towards negative self-descriptive information regardless of task goals, especially when negative self-descriptive material was paired with self-referential images that should be ignored. Attention biases in ruminative depression were mediated by dynamic variability in frontoinsular resting-state functional connectivity. These findings highlight potential cognitive and functional network mechanisms of attention bias specifically related to the ruminative dimension of depression.

Childhood stress, grown-up brain networks: corticolimbic correlates of threat-related early life stress and adult stress response

BACKGROUND

Exposure to threat-related early life stress (ELS) has been related to vulnerability for stress-related disorders in adulthood, putatively via disrupted corticolimbic circuits involved in stress response and regulation. However, previous research on ELS has not examined both the intrinsic strength and flexibility of corticolimbic circuits, which may be particularly important for adaptive stress responding, or associations between these dimensions of corticolimbic dysfunction and acute stress response in adulthood.

METHODS

Seventy unmedicated women varying in history of threat-related ELS completed a functional magnetic resonance imaging scan to evaluate voxelwise static (overall) and dynamic (variability over a series of sliding windows) resting-state functional connectivity (RSFC) of bilateral amygdala. In a separate session and subset of participants (n = 42), measures of salivary cortisol and affect were collected during a social-evaluative stress challenge.

RESULTS

Higher severity of threat-related ELS was related to more strongly negative static RSFC between amygdala and left dorsolateral prefrontal cortex (DLPFC), and elevated dynamic RSFC between amygdala and rostral anterior cingulate cortex (rACC). Static amygdala-DLPFC antagonism mediated the relationship between higher severity of threat-related ELS and blunted cortisol response to stress, but increased dynamic amygdala-rACC connectivity weakened this mediated effect and was related to more positive post-stress mood.

CONCLUSIONS

Threat-related ELS was associated with RSFC within lateral corticolimbic circuits, which in turn was related to blunted physiological response to acute stress. Notably, increased flexibility between the amygdala and rACC compensated for this static disruption, suggesting that more dynamic medial corticolimbic circuits might be key to restoring healthy stress response.

General and emotion-specific alterations to cognitive control in women with a history of childhood abuse

BACKGROUND

Although limited, the literature suggests alterations in activation of cognitive control regions in adults and adolescents with a history of childhood abuse. The current study examined whether such alterations are increased in the face of emotionally-distracting as compared to emotionally neutral information, and whether such alterations occur in brain regions that exert cognitive control in a more top-down sustained manner or a more bottom-up transient manner.

METHODS

Participants were young adult women (ages 23-30): one group with a history of childhood physical or sexual abuse (N = 15) and one with no trauma exposure (N = 17), as assessed through the Trauma History Questionnaire and a two-stage interview adapted from the National Crime Victims Survey. Participants underwent fMRI scanning while completing hybrid block/event-related versions of a classic color-word and an emotional Stroop paradigm (threat and positive words). This paradigm allowed us to examine both sustained (activation persisting across blocks) and transient (event-specific activation) aspects of cognitive control.

RESULTS

Women with a history of childhood abuse demonstrated decreased recruitment of frontal-parietal regions involved in cognitive control and enhanced recruitment of a ventral attention surveillance network during blocks of both versions of the Stroop task. Additionally, they had less suppression of brain regions involved in self-referential processes for threat blocks, but greater suppression of these regions for positive blocks. Severity of avoidance symptoms was associated with sustained activation in lateral prefrontal regions, whereas hyperarousal/re-experiencing symptoms were associated with sustained activity in temporal regions. No differential effects were observed for transient control.

CONCLUSIONS

Results suggest exposure to childhood abuse is associated with blunted recruitment of brain regions supporting task-set maintenance but hypervigilance for task-irrelevant information, regardless of whether distractors are emotionally neutral or emotional. Exposure to childhood abuse is also associated with less suppression of default mode brain regions associated with self-referential processing in the face of irrelevant threat information, but heightened ability to suppress similar processing for irrelevant positive information.

Dopaminergic Enhancement of Striatal Response to Reward in Major Depression

OBJECTIVE

Major depressive disorder is characterized by reduced reward-related striatal activation and dysfunctional reward learning, putatively reflecting decreased dopaminergic signaling. The goal of this study was to test whether a pharmacological challenge designed to facilitate dopaminergic transmission can enhance striatal responses to reward and improve reward learning in depressed individuals.

METHOD

In a double-blind placebo-controlled design, 46 unmedicated depressed participants and 43 healthy control participants were randomly assigned to receive either placebo or a single low dose (50 mg) of the D₂/D₃ receptor antagonist amisulpride, which is believed to increase dopamine signaling through presynaptic autoreceptor blockade. To investigate the effects of increased dopaminergic transmission on reward-related striatal function and behavior, a monetary incentive delay task (in conjunction with functional MRI) and a probabilistic reward learning task were administered at absorption peaks of amisulpride.

RESULTS

Depressed participants selected previously rewarded stimuli less frequently than did control participants, indicating reduced reward learning, but this effect was not modulated by amisulpride. Relative to depressed participants receiving placebo (and control participants receiving amisulpride), depressed participants receiving amisulpride exhibited increased striatal activation and potentiated corticostriatal functional connectivity between the nucleus accumbens and the midcingulate cortex in response to monetary rewards. Stronger corticostriatal connectivity in response to rewards predicted better reward learning among depressed individuals receiving amisulpride as well as among control participants receiving placebo.

CONCLUSIONS

Acute enhancement of dopaminergic transmission potentiated reward-related striatal activation and corticostriatal functional connectivity in depressed individuals but had no behavioral effects. Taken together, the results suggest that targeted pharmacological treatments may normalize neural correlates of reward processing in depression; despite such acute effects on neural function, behavioral modification may require more chronic exposure. This is consistent with previous reports that antidepressant effects of amisulpride in depression emerged after sustained administration.

Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity

IMPORTANCE

Major depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive.

OBJECTIVE

To investigate network dysfunction in MDD through a meta-analysis of rsFC studies.

DATA SOURCES

Seed-based voxelwise rsFC studies comparing individuals with MDD with healthy controls (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web of Science, and EMBASE) and authors contacted for additional data.

STUDY SELECTION

Twenty-seven seed-based voxel-wise rsFC data sets from 25 publications (556 individuals with MDD and 518 healthy controls) were included in the meta-analysis.

DATA EXTRACTION AND SYNTHESIS

Coordinates of seed regions of interest and between-group effects were extracted. Seeds were categorized into seed-networks by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive or reduced negative connectivity) or hypoconnectivity (increased negative or reduced positive connectivity) with each seed-network.

RESULTS

Major depressive disorder was characterized by hypoconnectivity within the frontoparietal network, a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network involved in attending to the external environment. Major depressive disorder was also associated with hyperconnectivity within the default network, a network believed to support internally oriented and self-referential thought, and hyperconnectivity between frontoparietal control systems and regions of the default network. Finally, the MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or salience and midline cortical regions that may mediate top-down regulation of such functions.

CONCLUSIONS AND RELEVANCE

Reduced connectivity within frontoparietal control systems and imbalanced connectivity between control systems and networks involved in internal or external attention may reflect depressive biases toward internal thoughts at the cost of engaging with the external world. Meanwhile, altered connectivity between neural systems involved in cognitive control and those that support salience or emotion processing may relate to deficits regulating mood. These findings provide an empirical foundation for a neurocognitive model in which network dysfunction underlies core cognitive and affective abnormalities in depression.

Distracted and down: neural mechanisms of affective interference in subclinical depression

Previous studies have shown that depressed individuals have difficulty directing attention away from negative distractors, a phenomenon known as affective interference. However, findings are mixed regarding the neural mechanisms and network dynamics of affective interference. The present study addressed these issues by comparing neural activation during emotion-word and color-word Stroop tasks in participants with varying levels of (primarily subclinical) depression. Depressive symptoms predicted increased activation to negative distractors in areas of dorsal anterior cingulate cortex (dACC) and posterior cingulate cortex (PCC), regions implicated in cognitive control and internally directed attention, respectively. Increased dACC activity was also observed in the group-average response to incongruent distractors, suggesting that dACC activity during affective interference is related to overtaxed cognitive control. In contrast, regions of PCC were deactivated across the group in response to incongruent distractors, suggesting that PCC activity during affective interference represents task-independent processing. A psychophysiological interaction emerged in which higher depression predicted more positively correlated activity between dACC and PCC during affective interference, i.e. greater connectivity between cognitive control and internal-attention systems. These findings suggest that, when individuals high in depression are confronted by negative material, increased attention to internal thoughts and difficulty shifting resources to the external world interfere with goal-directed behavior.

Obsessive-compulsive disorder is associated with broad impairments in executive function: A meta-analysis

Obsessive-compulsive disorder (OCD) is a serious and often chronically disabling condition. The current dominant model of OCD focuses on abnormalities in prefrontal-striatal circuits that support executive function (EF). While there is growing evidence for EF impairments associated with OCD, results have been inconsistent, making the nature and magnitude of these impairments controversial. The current meta-analysis uses random-effects models to synthesize 110 previous studies that compared participants with OCD to healthy control participants on at least one neuropsychological measure of EF. The results indicate that individuals with OCD are impaired on tasks measuring most aspects of EF, consistent with broad impairment in EF. EF deficits were not explained by general motor slowness or depression. Effect sizes were largely stable across variation in demographic and clinical characteristics of samples, although medication use, age, and gender moderated some effects.

Opposite effects of anxiety and depressive symptoms on executive function: the case of selecting among competing options

People constantly face the need to choose one option from among many, such as when selecting words to express a thought. Selecting between many options can be difficult for anyone, and can feel overwhelming for individuals with elevated anxiety. The current study demonstrates that anxiety is associated with impaired selection across three different verbal tasks, and tests the specificity of this finding to anxiety. Anxiety and depression frequently co-occur; thus, it might be assumed that they would demonstrate similar associations with selection, although they also have distinct profiles of symptoms, neuroanatomy and neurochemistry. Here, we report for the first time that anxiety and depressive symptoms counter-intuitively have opposite effects on selection among competing options. Specifically, whereas anxiety symptoms are associated with impairments in verbal selection, depressive symptoms are associated with better selection performance. Implications for understanding the mechanisms of anxiety, depression and selection are discussed.

A penny for your thoughts: dimensions of self-generated thought content and relationships with individual differences in emotional wellbeing

A core aspect of human cognition involves overcoming the constraints of the present environment by mentally simulating another time, place, or perspective. Although these self-generated processes confer many benefits, they can come at an important cost, and this cost is greater for some individuals than for others. Here we explore the possibility that the costs and benefits of self-generated thought depend, in part, upon its phenomenological content. To test these hypotheses, we first developed a novel thought sampling paradigm in which a large sample of young adults recalled several recurring thoughts and rated each thought on multiple content variables (i.e., valence, specificity, self-relevance, etc.). Next, we examined multi-level relationships among these content variables and used a hierarchical clustering approach to partition self-generated thought into distinct dimensions. Finally, we investigated whether these content dimensions predicted individual differences in the costs and benefits of the experience, assessed with questionnaires measuring emotional health and wellbeing. Individuals who characterized their thoughts as more negative and more personally significant scored higher on constructs associated with Depression and Trait Negative Affect, whereas those who characterized their thoughts as less specific scored higher on constructs linked to Rumination. In contrast, individuals who characterized their thoughts as more positive, less personally significant, and more specific scored higher on constructs linked to improved wellbeing (Mindfulness). Collectively, these findings suggest that the content of people’s inner thoughts can (1) be productively examined, (2) be distilled into several major dimensions, and (3) account for a large portion of variability in their functional outcomes.