Gut microbiota composition links to variation in functional domains across psychiatric disorders.

OBJECTIVE: Changes in microbial composition are observed in various psychiatric disorders, but their specificity to certain symptoms or processes remains unclear. This study explores the associations between the gut microbiota composition and the Research Domain Criteria (RDoC) domains of functioning, representing symptom domains, specifically focusing on stress-related and neurodevelopmental disorders in patients with and without psychiatric comorbidity. METHODS: The gut microbiota was analyzed in 369 participants, comprising 272 individuals diagnosed with a mood disorder, anxiety disorder, attention deficit/hyperactivity disorder, autism spectrum disorder, and/or substance use disorder, as well as 97 psychiatrically unaffected individuals. The RDoC domains were estimated using principal component analysis (PCA) with oblique rotation on a range of psychiatric, psychological, and personality measures. Associations between the gut microbiota and the functional domains were assessed using multiple linear regression and permanova, adjusted for age, sex, diet, smoking, medication use and comorbidity status. RESULTS: Four functional domains, aligning with RDoC's negative valence, social processes, cognitive systems, and arousal/regulatory systems domains, were identified. Significant associations were found between these domains and eight microbial genera, including associations of negative valence with the abundance of the genera Sellimonas, CHKCI001, Clostridium sensu stricto 1, Oscillibacter, and Flavonifractor; social processes with Sellimonas; cognitive systems with Sporobacter and Hungatella; and arousal/regulatory systems with Ruminococcus torques (all pFDR < 0.05). CONCLUSION: Our findings demonstrate associations between the gut microbiota and the domains of functioning across patients and unaffected individuals, potentially mediated by immune-related processes. These results open avenues for microbiota-focused personalized interventions, considering psychiatric comorbidity. However, further research is warranted to establish causality and elucidate mechanistic pathways.

Towards implementation of cognitive bias modification in mental health care: State of the science, best practices, and ways forward.

Cognitive bias modification (CBM) has evolved from an experimental method testing cognitive mechanisms of psychopathology to a promising tool for accessible digital mental health care. While we are still discovering the conditions under which clinically relevant effects occur, the dire need for accessible, effective, and low-cost mental health tools underscores the need for implementation where such tools are available. Providing our expert opinion as Association for Cognitive Bias Modification members, we first discuss the readiness of different CBM approaches for clinical implementation, then discuss key considerations with regard to implementation. Evidence is robust for approach bias modification as an adjunctive intervention for alcohol use disorders and interpretation bias modification as a stand-alone intervention for anxiety disorders. Theoretical predictions regarding the mechanisms by which bias and symptom change occur await further testing. We propose that CBM interventions with demonstrated efficacy should be provided to the targeted populations. To facilitate this, we set a research agenda based on implementation frameworks, which includes feasibility and acceptability testing, co-creation with end-users, and collaboration with industry partners.

Autistic and non-autistic individuals show the same amygdala activity during emotional face processing.

BACKGROUND: Autistic and non-autistic individuals often differ in how they perceive and show emotions, especially in their ability and inclination to infer other people's feelings from subtle cues like facial expressions. Prominent theories of autism have suggested that these differences stem from alterations in amygdala functioning and that amygdala hypoactivation causes problems with emotion recognition. Thus far, however, empirical investigations of this hypothesis have yielded mixed results and largely relied on relatively small samples. METHODS: In a sample of 72 autistic and 79 non-autistic participants, we conducted a study in which we used the Hariri paradigm to test whether amygdala activation during emotional face processing is altered in autism spectrum disorder, and whether common mental disorders like depression, ADHD or anxiety disorders influence any potential alterations in activation patterns. RESULTS: We found no evidence for differences in amygdala activation, neither when comparing autistic and non-autistic participants, nor when taking into account mental disorders or the overall level of functional impairment. LIMITATIONS: Because we used one basic emotion processing task in a Dutch sample, results might not generalise to other tasks and other populations. CONCLUSIONS: Our results challenge the view that autistic and non-autistic processing of emotional faces in the amygdala is vastly different and call for a more nuanced view of differences between non-autistic and autistic emotion processing.

Multi-polygenic scores in psychiatry: From disorder specific to transdiagnostic perspectives.

The dense co-occurrence of psychiatric disorders questions the categorical classification tradition and motivates efforts to establish dimensional constructs with neurobiological foundations that transcend diagnostic boundaries. In this study, we examined the genetic liability for eight major psychiatric disorder phenotypes under both a disorder-specific and a transdiagnostic framework. The study sample (n = 513) was deeply phenotyped, consisting of 452 patients from tertiary care with mood disorders, anxiety disorders (ANX), attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders, and/or substance use disorders (SUD) and 61 unaffected comparison individuals. We computed subject-specific polygenic risk score (PRS) profiles and assessed their associations with psychiatric diagnoses, comorbidity status, as well as cross-disorder behavioral dimensions derived from a rich battery of psychopathology assessments. High PRSs for depression were unselectively associated with the diagnosis of SUD, ADHD, ANX, and mood disorders (p < 1e-4). In the dimensional approach, four distinct functional domains were uncovered, namely the negative valence, social, cognitive, and regulatory systems, closely matching the major functional domains proposed by the Research Domain Criteria (RDoC) framework. Critically, the genetic predisposition for depression was selectively reflected in the functional aspect of negative valence systems (R2 = 0.041, p = 5e-4) but not others. This study adds evidence to the ongoing discussion about the misalignment between current psychiatric nosology and the underlying psychiatric genetic etiology and underscores the effectiveness of the dimensional approach in both the functional characterization of psychiatric patients and the delineation of the genetic liability for psychiatric disorders.

A transdiagnostic view on MDD and ADHD: shared cognitive characteristics?

BACKGROUND: Major Depressive disorder (MDD) and Attention Deficit Hyperactivity Disorder (ADHD) are prevalent mental disorders that often co-occur. There is overlap in symptomatology between MDD and ADHD that complicates diagnostics and treatment selection. Hence, to aid diagnostics of single and comorbid disorders, we aimed to examine the discriminative power of common symptom measures and cognitive dysfunction to differentiate between participants diagnosed with MDD, ADHD, ADHD and comorbid MDD and without a mental disorder. METHODS: Four diagnosed groups were compared: MDD (n = 103), ADHD (n = 78), comorbid MDD + ADHD (n = 29), healthy controls (HC; n = 123). We examined between-group differences and discriminative functions of clinically validated self-report symptom questionnaires, as well as task-based and self-report measures of cognitive dysfunction. RESULTS: Based on the between group comparisons, all patient groups were characterized by clinically relevant levels of ADHD-symptomatology, executive dysfunction, and diminished cognitive performances in the domain of attention; even the MDD-only group. In addition, based on self-reported symptoms of MDD, ADHD, and executive dysfunction, discriminant function analysis classified all HC correctly (100%) and patients diagnosed with ADHD or MDD relatively well (resp. 85% and 82%). Comorbid MDD + ADHD was poorly differentiated from single MDD or ADHD by the commonly used self-report symptom questionnaires for MDD and ADHD (0% correct predictions), which substantially improved by incorporating the questionnaire on executive functioning (42% correct predictions). CONCLUSIONS: In both MDD and ADHD, clinical levels of attentional and executive dysfunction were found, while these clinical groups differed in cognitive flexibility, initiating, inhibition and meta-cognition. Comorbid MDD + ADHD was poorly distinguishable from non-comorbid MDD and ADHD based on self-reported symptoms of depression and ADHD. Addition of subjective executive function in the discrimination models resulted in increased discriminative power. Our findings indicate that executive functioning measure can improve the diagnostic process of ADHD and MDD.

Brain structure and function link to variation in biobehavioral dimensions across the psychopathological continuum.

In line with the Research Domain Criteria (RDoC) , we set out to investigate the brain basis of psychopathology within a transdiagnostic, dimensional framework. We performed an integrative structural-functional linked independent component analysis to study the relationship between brain measures and a broad set of biobehavioral measures in a sample (n = 295) with both mentally healthy participants and patients with diverse non-psychotic psychiatric disorders (i.e. mood, anxiety, addiction, and neurodevelopmental disorders). To get a more complete understanding of the underlying brain mechanisms, we used gray and white matter measures for brain structure and both resting-state and stress scans for brain function. The results emphasize the importance of the executive control network (ECN) during the functional scans for the understanding of transdiagnostic symptom dimensions. The connectivity between the ECN and the frontoparietal network in the aftermath of stress was correlated with symptom dimensions across both the cognitive and negative valence domains, and also with various other health-related biological and behavioral measures. Finally, we identified a multimodal component that was specifically associated with the diagnosis of autism spectrum disorder (ASD). The involvement of the default mode network, precentral gyrus, and thalamus across the different modalities of this component may reflect the broad functional domains that may be affected in ASD, like theory of mind, motor problems, and sensitivity to sensory stimuli, respectively. Taken together, the findings from our extensive, exploratory analyses emphasize the importance of a dimensional and more integrative approach for getting a better understanding of the brain basis of psychopathology.

Follow-up outcomes of Mindfulness-Based Cognitive Therapy (MBCT) for patients with chronic, treatment-resistant depression.

BACKGROUND: Mindfulness-based cognitive therapy (MBCT) is an evidence-based treatment for depression. The current study focused on the long-term outcomes of MBCT for chronically, treatment-resistant depressed patients during a 6-months follow-up period. Additionally, predictors of treatment outcomes were explored. METHOD: The outcomes of MBCT on depressive symptoms, remission rates, quality of life, rumination, mindfulness skills and self-compassion were investigated in a cohort of chronically, treatment-resistant depressed outpatients (N = 106), who had taken part in an RCT comparing MBCT with treatment-as-usual (TAU). Measures were assessed pre-MBCT, post-MBCT, at 3-months follow-up, and at 6-months follow-up. RESULTS: Results of linear mixed effect models and Bayesian repeated measures ANOVA's reveal that depressive symptoms, quality of life, rumination, mindfulness skills and self-compassion consolidated during follow-up. Remission rates even further increased over the course of follow-up. When controlling for symptoms at baseline, higher baseline levels of rumination predicted lower depressive symptoms and quality of life at 6-month follow-up. No other predictors (i.e. duration of current depressive episode, level of treatment-resistance, childhood trauma, mindfulness skills, self-compassion) were found. LIMITATIONS: All participants received MBCT, therefore time or other non-specific effects might have influenced the results and replication studies including a control conditions are needed. CONCLUSIONS: Results indicate that the clinical benefits of MBCT for chronically, treatment-resistant depressed patients persist up to 6 months after completing MBCT. Duration of the current episode, level of treatment-resistance, childhood trauma and baseline levels of mindfulness skills and self-compassion did not predict treatment outcome. When controlling for baseline depressive symptoms participants with high levels of rumination seem to benefit more; however more research is needed. TRIAL REGISTRY: Dutch Trial Registry, number NTR4843.

Unpacking the functional heterogeneity of the Emotional Face Matching Task: a normative modelling approach.

Functional neuroimaging has contributed substantially to understanding brain function but is dominated by group analyses that index only a fraction of the variation in these data. It is increasingly clear that parsing the underlying heterogeneity is crucial to understand individual differences and the impact of different task manipulations. We estimate large-scale (N=7728) normative models of task-evoked activation during the Emotional Face Matching Task, which enables us to bind heterogeneous datasets to a common reference and dissect heterogeneity underlying group-level analyses. We apply this model to a heterogenous patient cohort, to map individual differences between patients with one or more mental health diagnoses relative to the reference cohort and determine multivariate associations with transdiagnostic symptom domains. For the face>shapes contrast, patients have a higher frequency of extreme deviations which are spatially heterogeneous. In contrast, normative models for faces>baseline have greater predictive value for individuals' transdiagnostic functioning.

Working it out: can an acute exercise bout alleviate memory bias, rumination and negative mood?

Although it is well known that exercise reduces depressive symptoms, the underlying psychological mechanisms remain unclear. This experimental study examined the acute effect of exercise on mood, and depressotypic memory bias and state rumination. Trait rumination was tested as a possible moderator. A sample of non-regular exercisers (N = 100) was randomized to exercise or rest. After a negative mood induction, the exercise condition cycled for 24 min at moderate intensity, while the rest condition rested. Negative and overgeneral memory bias, as well as positive and negative affect were assessed after exercise/rest. To capture the lingering of negative mood and state rumination, both were assessed multiple times throughout the study. The exercise (as compared to rest) condition reported more positive affect. However, no differences were found on overgeneral memory bias, as well as depression-specific mood or state rumination measured throughout the study. Interestingly, the exercise condition showed more negative memory bias at higher levels of rumination. Individual differences in trait rumination moderated the exercise-memory bias relation, such that exercise increased negative memory bias at higher levels of rumination. It is possible that long-term exercise protocols are necessary to change cognitive processes related to depression.

How context, mood, and emotional memory interact in depression: A study in everyday life.

Cognitive theories of depression hold that negative contextual triggers (e.g., stressful events) induce more negative and less positive mood, in turn instigating negatively biased memories. However, context-related variability in mood and emotional memory has received insufficient attention, while the dynamic interaction between these factors plays a crucial role in the kindling of new depressive episodes. Experience Sampling Method (ESM) for repeated, daily life measures of context, mood, and autobiographic emotional memory was used in 46 currently depressed, 90 remitted-depressed, and 55 never-depressed individuals. Currently depressed individuals showed strongest negative processing style and never-depressed most positive, with remitted-depressed patients scoring intermediate. The moderated mediation model indicated that context appraisal had a direct effect on the appraisal of the recalled event (i.e., our operationalization of emotional memory), which was mediated by positive (but hardly by negative) mood and was independent of depression status. This mediation strength was relatively similar to the strength of the direct effect of context on memory. Results are in line with cognitive theories of depression. Especially context seems important for emotional memory. The association between context, mood, and memory, however, may be independent of depression status. Yet, the "level" of mood, context, and event appraisal does depend on depression status. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The effectiveness of peer support for individuals with mental illness: systematic review and meta-analysis.

BACKGROUND: The benefits of peer support interventions (PSIs) for individuals with mental illness are not well known. The aim of this systematic review and meta-analysis was to assess the effectiveness of PSIs for individuals with mental illness for clinical, personal, and functional recovery outcomes. METHODS: Searches were conducted in PubMed, Embase, and PsycINFO (December 18, 2020). Included were randomized controlled trials (RCTs) comparing peer-delivered PSIs to control conditions. The quality of records was assessed using the Cochrane Collaboration Risk of Bias tool. Data were pooled for each outcome, using random-effects models. RESULTS: After screening 3455 records, 30 RCTs were included in the systematic review and 28 were meta-analyzed (4152 individuals). Compared to control conditions, peer support was associated with small but significant post-test effect sizes for clinical recovery, g = 0.19, 95% CI (0.11-0.27), I2 = 10%, 95% CI (0-44), and personal recovery, g = 0.15, 95% CI (0.04-0.27), I2 = 43%, 95% CI (1-67), but not for functional recovery, g = 0.08, 95% CI (-0.02 to 0.18), I2 = 36%, 95% CI (0-61). Our findings should be considered with caution due to the modest quality of the included studies. CONCLUSIONS: PSIs may be effective for the clinical and personal recovery of mental illness. Effects are modest, though consistent, suggesting potential efficacy for PSI across a wide range of mental disorders and intervention types.

The gut-microbiome in adult Attention-deficit/hyperactivity disorder - A Meta-analysis.

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental condition that persists into adulthood in the majority of individuals. While the gut-microbiome seems to be relevant for ADHD, the few publications on gut-microbial alterations in ADHD are inconsistent, in the investigated phenotypes, sequencing method/region, preprocessing, statistical approaches, and findings. To identify gut-microbiome alterations in adult ADHD, robust across studies and statistical approaches, we harmonized bioinformatic pipelines and analyses of raw 16S rRNA sequencing data from four adult ADHD case-control studies (N ADHD =312, N NoADHD =305). We investigated diversity and differential abundance of selected genera (logistic regression and ANOVA-like Differential Expression tool), corrected for age and sex, and meta-analyzed the study results. Converging results were investigated for association with hyperactive/impulsive and inattentive symptoms across all participants. Beta diversity was associated with ADHD diagnosis but showed significant heterogeneity between cohorts, despite harmonized analyses. Several genera were robustly associated with adult ADHD; e.g., Ruminococcus_torques_group (LogOdds=0.17, p fdr =4.42×10 -2 ), which was more abundant in adults with ADHD, and Eubacterium_xylanophilum_group (LogOdds= -0.12, p fdr =6.9 x 10 -3 ), which was less abundant in ADHD. Ruminococcus_torques_group was further associated with hyperactivity/impulsivity symptoms and Eisenbergiella with inattention and hyperactivity/impulsivity (p fdr <0.05). The literature points towards a role of these genera in inflammatory processes. Irreproducible results in the field of gut-microbiota research, due to between study heterogeneity and small sample sizes, stress the need for meta-analytic approaches and large sample sizes. While we robustly identified genera associated with adult ADHD, that might overall be considered beneficial or risk-conferring, functional studies are needed to shed light on these properties.

The effects of daily autobiographical memory training on memory bias, mood and stress resilience in dysphoric individuals.

Negative memory bias refers to the enhanced recall of negative memories and is a prominent cognitive factor causing and maintaining depression. Surprisingly few studies modify this negative recall. The current study used a smartphone-based autobiographical memory training to increase positive memory recall and thereby alter negative memory bias. A total of 96 dysphoric (≥ 13 BDI-II) participants were randomly allocated to a positive, sham or no-training condition, conducted over a period of 6 days. Positive memory bias (i.e., recalled event evaluation) significantly increased from pre- to post-training after positive and sham intervention, suggesting an unspecific training effect. No transfer to memory specificity, implicit memory bias or depressive symptoms was found, nor was the training effect modulated by pre-existing level of positive memory bias. A post-hoc follow-up measurement during the initial COVID-19 crisis revealed that subjects who benefitted most from either of the trainings maintained their stress levels better during a natural stressful period, compared to those who responded least to the training. Future studies should carefully consider the impact of sham training design. Moreover, it is important to examine transfer effects of bias training as practice in daily life.

Striatal connectopic maps link to functional domains across psychiatric disorders.

Transdiagnostic approaches to psychiatry have significant potential in overcoming the limitations of conventional diagnostic paradigms. However, while frameworks such as the Research Domain Criteria have garnered significant enthusiasm among researchers and clinicians from a theoretical angle, examples of how such an approach might translate in practice to understand the biological mechanisms underlying complex patterns of behaviors in realistic and heterogeneous populations have been sparse. In a richly phenotyped clinical sample (n = 186) specifically designed to capture the complex nature of heterogeneity and comorbidity within- and between stress- and neurodevelopmental disorders, we use exploratory factor analysis on a wide range of clinical questionnaires to identify four stable functional domains that transcend diagnosis and relate to negative valence, cognition, social functioning and inhibition/arousal before replicating them in an independent dataset (n = 188). We then use connectopic mapping to map inter-individual variation in fine-grained topographical organization of functional connectivity in the striatum-a central hub in motor, cognitive, affective and reward-related brain circuits-and use multivariate machine learning (canonical correlation analysis) to show that these individualized topographic representations predict transdiagnostic functional domains out of sample (r = 0.20, p = 0.026). We propose that investigating psychiatric symptoms across disorders is a promising path to linking them to underlying biology, and can help bridge the gap between neuroscience and clinical psychiatry.

User Engagement Within an Online Peer Support Community (Depression Connect) and Recovery-Related Changes in Empowerment: Longitudinal User Survey.

BACKGROUND: The chronic nature of depression and limited availability of evidence-based treatments emphasize the need for complementary recovery-oriented services, such as peer support interventions (PSIs). Peer support is associated with positive effects on clinical and personal recovery from mental illness, but little is known about the processes of engagement that foster change, and studies targeting individuals with depression specifically are limited. OBJECTIVE: This study aimed to evaluate whether the level of user engagement, assessed on several dimensions, in an online peer support community for individuals with depression promotes empowerment and the use of self-management strategies and reduces symptom severity and disability. METHODS: In a longitudinal survey conducted from June 2019 to September 2020, we analyzed the data of the users of Depression Connect (DC), an online peer support community hosted by the Dutch Patient Association for Depression and the Pro Persona Mental Health Care institute, on measures of empowerment, self-management, depression, and disability. Of the 301 respondents, 49 (16.3%) respondents completed the survey again after 3 months and 74 (24.6%) respondents, after 6 months. Analysis of 3 parameters (ie, total time spent on the platform, number of page views, and number of posts) derived from their data logs yielded 4 engagement profiles. Linear mixed models were fitted to determine whether the outcomes had significantly changed over time and differed for the various profiles. RESULTS: Baseline engagement with the online peer support community was "very low" (177/301, 58.8%) or "low" (87/301, 28.9%) for most of the participants, with few showing "medium" (30/301, 9.9%) or "high" engagement patterns (7/301, 2.3%), while user profiles did not differ in demographic and clinical characteristics. Empowerment, self-management, depressive symptoms, and disability improved over time, but none were associated with the intensity or nature of user engagement. CONCLUSIONS: With most DC members showing very low to low engagement and only a few being identified as high-engaged users, it is likely that this flexibility in use frequency is what provides value to online PSI users. In other more formal supportive environments for depression, a certain level of engagement is predetermined either by their organizational or by their societal context; at DC, users can adapt the intensity and nature of their engagement to their current needs on their personal road to recovery. This study added to the current knowledge base on user engagement for PSIs because previous studies targeting depression with an online format focused on active users, precluding passive and flexible engagement. Future studies should explore the content and quality of the interactions in online PSIs to identify optimal user engagement as a function of current, self-reported clinical parameters and reasons to engage in the PSI.

Neural correlates of repetitive negative thinking: Dimensional evidence across the psychopathological continuum.

Repetitive negative thinking (RNT) captures an important transdiagnostic factor that predisposes to a maladaptive stress response and contributes to diverse psychiatric disorders. Although RNT can best be seen as a continuous symptom dimension that cuts across boundaries from health to various psychiatric disorders, the neural mechanisms underlying RNT have almost exclusively been studied in health and stress-related disorders, such as depression and anxiety disorders. We set out to study RNT from a large-scale brain network perspective in a diverse population consisting of healthy subjects and patients with a broader range of psychiatric disorders. We studied 46 healthy subjects along with 153 patients with a stress-related and/or neurodevelopmental disorder. We focused on three networks, that are associated with RNT and diverse psychiatric disorders: the salience network, default mode network (DMN) and frontoparietal network (FPN). We investigated the relationship of RNT with both network connectivity strength at rest and with the stress-induced changes in connectivity. Across our whole sample, the level of RNT was positively associated with the connectivity strength of the left FPN at rest, but negatively associated with stress-induced changes in DMN connectivity. These findings may reflect an upregulation of the FPN in an attempt to divert attention away from RNT, while the DMN result may reflect a less flexible adaptation to stress, related to RNT. Additionally, we discuss how our findings fit into the non-invasive neurostimulation literature. Taken together, our results provide initial insight in the neural mechanisms of RNT across the spectrum from health to diverse psychiatric disorders.

Amygdala sensitivity for negative information as a neural marker for negative memory bias across psychiatric diagnoses.

Self-referent negative memory bias is a known risk factor for depression, but recent evidence suggests its function as a transdiagnostic cognitive depressotypic marker. The amygdala's sensitivity for negative information is considered a neurobiological depressotypic marker. However, their relationship remains unknown. We transdiagnostically investigated the association between the amygdala's sensitivity, self-referent negative memory bias and its two components: negative endorsement bias and negative recall bias. Patients (n= 125) with (multimorbid) stress-related and neurodevelopmental psychiatric disorders and healthy controls (n= 78) performed an fMRI task to assess the amygdala's sensitivity for negative information and a task outside the scanner for the biases. Linear regression models assessed their associations. The left amygdala's sensitivity for negative information was significantly positively associated with negative recall bias in patients, but not controls. There were no significant associations with self-referent negative memory bias or negative endorsement bias or between the two depressotypic markers. Thus, the left amygdala's sensitivity for negative information may be considered a neural marker of negative memory bias across psychiatric diagnoses. Further research on the interactons with known determinants such as genetic predisposition is required to fully understand the relationship between the amygdala's sensitivity for negative information and these biases.

Depressive Symptoms Account for Loss of Positive Attention Bias in ADHD Patients: An Eye-Tracking Study.

OBJECTIVES: Depression and ADHD often co-occur and are both characterized by altered attentional processing. Differences and overlap in the profile of attention to emotional information may help explain the co-occurence. We examined negative attention bias in ADHD as neurocognitive marker for comorbid depression. METHODS: Patients with depression (n = 63), ADHD (n = 43), ADHD and depression (n = 25), and non-psychiatric controls (n = 68) were compared on attention allocation toward emotional faces. The following eye-tracking indices were used: gaze duration, number of revisits, and location and duration of first fixation. RESULTS: Controls revisited the happy faces more than the other facial expressions. Both the depression and the comorbid group showed significantly less revisits of the happy faces compared to the ADHD and the control group. Interestingly, after controlling for depressive symptoms, the groups no longer differed on the number of revisits. CONCLUSION: ADHD patients show a relative positive attention bias, while negative attention bias in ADHD likely indicates (sub)clinical comorbid depression.

Challenging the negative learning bias hypothesis of depression: reversal learning in a naturalistic psychiatric sample.

BACKGROUND: Classic theories posit that depression is driven by a negative learning bias. Most studies supporting this proposition used small and selected samples, excluding patients with comorbidities. However, comorbidity between psychiatric disorders occurs in up to 70% of the population. Therefore, the generalizability of the negative bias hypothesis to a naturalistic psychiatric sample as well as the specificity of the bias to depression, remain unclear. In the present study, we tested the negative learning bias hypothesis in a large naturalistic sample of psychiatric patients, including depression, anxiety, addiction, attention-deficit/hyperactivity disorder, and/or autism. First, we assessed whether the negative bias hypothesis of depression generalized to a heterogeneous (and hence more naturalistic) depression sample compared with controls. Second, we assessed whether negative bias extends to other psychiatric disorders. Third, we adopted a dimensional approach, by using symptom severity as a way to assess associations across the sample. METHODS: We administered a probabilistic reversal learning task to 217 patients and 81 healthy controls. According to the negative bias hypothesis, participants with depression should exhibit enhanced learning and flexibility based on punishment v. reward. We combined analyses of traditional measures with more sensitive computational modeling. RESULTS: In contrast to previous findings, this sample of depressed patients with psychiatric comorbidities did not show a negative learning bias. CONCLUSIONS: These results speak against the generalizability of the negative learning bias hypothesis to depressed patients with comorbidities. This study highlights the importance of investigating unselected samples of psychiatric patients, which represent the vast majority of the psychiatric population.

A piece of the puzzle: Does bipolarity partly explain the high prevalence of treatment resistance in depression?

In this cross-sectional study we examined whether the prevalence of treatment resistant depression (TRD) can be partly attributed to level of bipolarity. We included data of 201 patients with either episodic depression or TRD, who received treatment for their depression at either an outpatient or 2nd opinion/daytime setting, within a specialised mental healthcare department in the Netherlands. Whether level of TRD, assessed by the 'Dutch Measure for quantification of Treatment Resistance in Depression', can be partly explained by level of bipolarity, assessed by 'the Bipolarity Index', was examined using linear regression. We found no direct association between level of TRD and level of bipolarity, nor did comorbid anxiety disorders obscure an existing association. In this study we found no evidence for overlooked bipolarity contributing to the high prevalence of TRD. If replicated, we could state that additional screening on bipolarity with an instrument such as the 'Bipolarity Index' in the specialised mental health care is unnecessary.