Multiscale heterogeneity of white matter morphometry in psychiatric disorders.

BACKGROUND: Interindividual variability in neurobiological and clinical characteristics in mental illness is often overlooked by classical group mean case control studies. Studies using normative modelling to infer person specific deviations of grey matter volume have indicated that group means are not representative of most individuals. The extent to which this variability is present in white matter morphometry, which is integral to brain function, remains unclear. METHODS: We applied Warped Bayesian Linear Regression normative models to T1 weighted magnetic resonance imaging data and mapped interindividual variability in person specific white matter volume deviations in 1,294 cases (58% male) diagnosed with one of six disorders (attention-deficit/hyperactivity, autism, bipolar, major depressive, obsessive compulsive and schizophrenia) and 1,465 matched controls (54% male) recruited across 25 scan sites. We developed a framework to characterize deviation heterogeneity at multiple spatial scales, from individual voxels, through inter-regional connections, specific brain regions, and spatially extended brain networks. RESULTS: The specific locations of white matter volume deviations were highly heterogeneous across participants, affecting the same voxel in fewer than 8% of individuals with the same diagnosis. For autism and schizophrenia, negative deviations (i.e., areas where volume is lower than normative expectations) aggregated into common tracts, regions and large scale networks in up to 35% of individuals. CONCLUSIONS: The prevalence of white matter volume deviations was lower than previously observed in grey matter, and the specific location of these deviations was highly heterogeneous when considering voxelwise spatial resolution. Evidence of aggregation within common pathways and networks was apparent in schizophrenia and autism but not other disorders.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

An analysis of real-time suicidal ideation and its relationship with retrospective reports among young people with borderline personality disorder.

INTRODUCTION: This study aimed to analyze the real-time variability of suicidal ideation intensity and the relationship between real-time and retrospective reports of suicidal ideation made on the Beck Scale for Suicidal Ideation (BSS), among young people with borderline personality disorder (BPD). METHODS: Young people (15-25-year olds) with BPD (N = 46), recruited from two government-funded mental health services, rated the intensity of their suicidal ideation six times per day for 7 days before completing the BSS. RESULTS: For 70% of participants, suicidal ideation changed in intensity approximately five times across the week, both within and between days. BSS ratings were most highly correlated with the highest real-time ratings of suicidal ideation. However, this was not significantly different from the relationship between the BSS and both the average and most recent ratings. Median ratings of suicidal ideation intensity were higher on the BSS compared with an equivalent question asked in real time. CONCLUSION: Findings suggest that young people with BPD experience high levels of fluctuation in their intensity of suicidal ideation across a week and that retrospective reports of suicidal ideation might be more reflective of the most intense experience of suicidal ideation across the week.

Major depressive disorder associated alterations in the effective connectivity of the face processing network: a systematic review.

Major depressive disorder (MDD) is marked by altered processing of emotional stimuli, including facial expressions. Recent neuroimaging research has attempted to investigate how these stimuli alter the directional interactions between brain regions in those with MDD; however, methodological heterogeneity has made identifying consistent effects difficult. To address this, we systematically examined studies investigating MDD-associated differences present in effective connectivity during the processing of emotional facial expressions. We searched five databases: PsycINFO, EMBASE, PubMed, Scopus, and Web of Science, using a preregistered protocol (registration number: CRD42021271586). Of the 510 unique studies screened, 17 met our inclusion criteria. These studies identified that compared with healthy controls, participants with MDD demonstrated (1) reduced connectivity from the dorsolateral prefrontal cortex to the amygdala during the processing of negatively valenced expressions, and (2) increased inhibitory connectivity from the ventromedial prefrontal cortex to amygdala during the processing of happy facial expressions. Most studies investigating the amygdala and anterior cingulate cortex noted differences in their connectivity; however, the precise nature of these differences was inconsistent between studies. As such, commonalities observed across neuroimaging modalities warrant careful investigation to determine the specificity of these effects to particular subregions and emotional expressions. Future research examining longitudinal connectivity changes associated with treatment response may provide important insights into mechanisms underpinning therapeutic interventions, thus enabling more targeted treatment strategies.

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures.

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.

Altered task-related decoupling of the rostral anterior cingulate cortex in depression.

Dysfunctional activity of the rostral anterior cingulate cortex (rACC) - an extensively connected hub region of the default mode network - has been broadly linked to cognitive and affective impairments in depression. However, the nature of aberrant task-related rACC suppression in depression is incompletely understood. In this study, we sought to characterize functional connectivity of rACC activity suppression ('deactivation') - an essential feature of rACC function - during external task engagement in depression. Specifically, we aimed to explore neural patterns of functional decoupling and coupling with the rACC during its task-driven suppression. We enrolled 81 15- to 25-year-old young people with moderate-to-severe major depressive disorder (MDD) before they commenced a 12-week clinical trial that assessed the effectiveness of cognitive behavioral therapy plus either fluoxetine or placebo. Ninety-four matched healthy controls were also recruited. Participants completed a functional magnetic resonance imaging face matching task known to elicit rACC suppression. To identify brain regions associated with the rACC during its task-driven suppression, we employed a seed-based functional connectivity analysis. We found MDD participants, compared to controls, showed significantly reduced 'decoupling' of the rACC with extended task-specific regions during task performance. Specifically, less decoupling was observed in the occipital and fusiform gyrus, dorsal ACC, medial prefrontal cortex, cuneus, amygdala, thalamus, and hippocampus. Notably, impaired decoupling was apparent in participants who did not remit to treatment, but not treatment remitters. Further, we found MDD participants showed significant increased coupling with the anterior insula cortex during task engagement. Our findings indicate that aberrant task-related rACC suppression is associated with disruptions in adaptive neural communication and dynamic switching between internal and external cognitive modes that may underpin maladaptive cognitions and biased emotional processing in depression.

The Addition of Fish Oil to Cognitive Behavioral Case Management for Youth Depression: A Randomized, Double-Blind, Placebo-Controlled, Multicenter Clinical Trial.

BACKGROUND: Clinical trials suggest that long-chain omega-3 polyunsaturated fatty acids (n-3 PUFAs) (fish oil) may reduce depressive symptoms in adults with major depressive disorder. Therefore, n-3 PUFAs may be a potential treatment for depression in youth. METHODS: Participants were 15- to-25 year-old individuals with major depressive disorder who sought care in one of three government-funded mental health services for young people in metropolitan Melbourne, Perth, or Sydney, Australia. Participants were randomly assigned in a double-blind, parallel-arm design to receive either fish oil (840 mg of eicosapentaenoic acid and 560 mg of docosahexaenoic acid) or placebo capsules as adjunct to cognitive behavioral case management. All participants were offered 50-minute cognitive behavioral case management sessions every 2 weeks delivered by qualified therapists (treatment as usual) at the study sites during the intervention period. The primary outcome was change in the interviewer-rated Quick Inventory of Depressive Symptomatology, Adolescent Version, score at 12 weeks. Erythrocyte n-3 PUFA levels were assessed pre-post intervention. RESULTS: A total of 233 young people were randomized to the treatment arms: 115 participants to the n-3 PUFA group and 118 to the placebo group. Mean change from baseline in the Quick Inventory of Depressive Symptomatology score was -5.8 in the n-3 PUFA group and -5.6 in the placebo group (mean difference, 0.2; 95% CI, -1.1 to 1.5; p = .75). Erythrocyte PUFA levels were not associated with depression severity at any time point. The incidence and severity of adverse events were similar in the two groups. CONCLUSIONS: This placebo-controlled trial and biomarker analysis found no evidence to support the use of fish oil for treatment in young people with major depressive disorder.

The self, neuroscience and psychosis study: Testing a neurophenomenological model of the onset of psychosis.

AIM: Basic self disturbance is a putative core vulnerability marker of schizophrenia spectrum disorders. The primary aims of the Self, Neuroscience and Psychosis (SNAP) study are to: (1) empirically test a previously described neurophenomenological self-disturbance model of psychosis by examining the relationship between specific clinical, neurocognitive, and neurophysiological variables in UHR patients, and (2) develop a prediction model using these neurophenomenological disturbances for persistence or deterioration of UHR symptoms at 12-month follow-up. METHODS: SNAP is a longitudinal observational study. Participants include 400 UHR individuals, 100 clinical controls with no attenuated psychotic symptoms, and 50 healthy controls. All participants complete baseline clinical and neurocognitive assessments and electroencephalography. The UHR sample are followed up for a total of 24 months, with clinical assessment completed every 6 months. RESULTS: This paper presents the protocol of the SNAP study, including background rationale, aims and hypotheses, design, and assessment procedures. CONCLUSIONS: The SNAP study will test whether neurophenomenological disturbances associated with basic self-disturbance predict persistence or intensification of UHR symptomatology over a 2-year follow up period, and how specific these disturbances are to a clinical population with attenuated psychotic symptoms. This may ultimately inform clinical care and pathoaetiological models of psychosis.

Ensuring the affordable becomes accessible-lessons from ketamine, a new treatment for severe depression.

In this paper, the case study of ketamine as a new treatment for severe depression is used to outline the challenges of repurposing established medicines and we suggest potential solutions. The antidepressant effects of generic racemic ketamine were identified over 20 years ago, but there were insufficient incentives for commercial entities to pursue its registration, or support for non-commercial entities to fill this gap. As a result, the evaluation of generic ketamine was delayed, piecemeal, uncoordinated, and insufficient to gain approval. Meanwhile, substantial commercial investment enabled the widespread registration of a patented, intranasal s-enantiomeric ketamine formulation (Spravato®) for depression. However, Spravato is priced at $600-$900/dose compared to ~$5/dose for generic ketamine, and the ~AUD$100 million annual government investment requested in Australia (to cover drug costs alone) has been rejected twice, leaving this treatment largely inaccessible for Australian patients 2 years after Therapeutic Goods Administration approval. Moreover, emerging evidence indicates that generic racemic ketamine is at least as effective as Spravato, but no comparative trials were required for regulatory approval and have not been conducted. Without action, this story will repeat regularly in the next decade with a new wave of psychedelic-assisted psychotherapy treatments, for which the original off-patent molecules could be available at low-cost and reduce the overall cost of treatment. Several systemic reforms are required to ensure that affordable, effective options become accessible; these include commercial incentives, public and public-private funding schemes, reduced regulatory barriers and more coordinated international public funding schemes to support translational research.

A brain model of altered self-appraisal in social anxiety disorder.

The brain's default mode network has a central role in the processing of information concerning oneself. Dysfunction in this self-referential processing represents a key component of multiple mental health conditions, particularly social anxiety disorder (SAD). This case-control study aimed to clarify alterations to network dynamics present during self-appraisal in SAD participants. A total of 38 adolescents and young adults with SAD and 72 healthy control participants underwent a self-referential processing fMRI task. The task involved two primary conditions of interest: direct self-appraisal (thinking about oneself) and reflected self-appraisal (thinking about how others might think about oneself). Dynamic causal modeling and parametric empirical Bayes were then used to explore differences in the effective connectivity of the default mode network between groups. We observed connectivity differences between SAD and healthy control participants in the reflected self-appraisal but not the direct self-appraisal condition. Specifically, SAD participants exhibited greater excitatory connectivity from the posterior cingulate cortex (PCC) to medial prefrontal cortex (MPFC) and greater inhibitory connectivity from the inferior parietal lobule (IPL) to MPFC. In contrast, SAD participants exhibited reduced intrinsic connectivity in the absence of task modulation. This was illustrated by reduced excitatory connectivity from the PCC to MPFC and reduced inhibitory connectivity from the IPL to MPFC. As such, participants with SAD showed changes to afferent connections to the MPFC which occurred during both reflected self-appraisal as well as intrinsically. The presence of connectivity differences in reflected and not direct self-appraisal is consistent with the characteristic fear of negative social evaluation that is experienced by people with SAD.

The Study of Ketamine for Youth Depression (SKY-D): study protocol for a randomised controlled trial of low-dose ketamine for young people with major depressive disorder.

BACKGROUND: Existing treatments for young people with severe depression have limited effectiveness. The aim of the Study of Ketamine for Youth Depression (SKY-D) trial is to determine whether a 4-week course of low-dose subcutaneous ketamine is an effective adjunct to treatment-as-usual in young people with major depressive disorder (MDD). METHODS: SKY-D is a double-masked, randomised controlled trial funded by the Australian Government's National Health and Medical Research Council (NHMRC). Participants aged between 16 and 25 years (inclusive) with moderate-to-severe MDD will be randomised to receive either low-dose ketamine (intervention) or midazolam (active control) via subcutaneous injection once per week for 4 weeks. The primary outcome is change in depressive symptoms on the Montgomery-Åsberg Depression Rating Scale (MADRS) after 4 weeks of treatment. Further follow-up assessment will occur at 8 and 26 weeks from treatment commencement to determine whether treatment effects are sustained and to investigate safety outcomes. DISCUSSION: Results from this trial will be important in determining whether low-dose subcutaneous ketamine is an effective treatment for young people with moderate-to-severe MDD. This will be the largest randomised trial to investigate the effects of ketamine to treat depression in young people. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ID: ACTRN12619000683134. Registered on May 7, 2019. https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377513 .

Towards a youth mental health paradigm: a perspective and roadmap.

Most mental disorders have a typical onset between 12 and 25 years of age, highlighting the importance of this period for the pathogenesis, diagnosis, and treatment of mental ill-health. This perspective addresses interactions between risk and protective factors and brain development as key pillars accounting for the emergence of psychopathology in youth. Moreover, we propose that novel approaches towards early diagnosis and interventions are required that reflect the evolution of emerging psychopathology, the importance of novel service models, and knowledge exchange between science and practitioners. Taken together, we propose a transformative early intervention paradigm for research and clinical care that could significantly enhance mental health in young people and initiate a shift towards the prevention of severe mental disorders.

Regional, circuit and network heterogeneity of brain abnormalities in psychiatric disorders.

The substantial individual heterogeneity that characterizes people with mental illness is often ignored by classical case-control research, which relies on group mean comparisons. Here we present a comprehensive, multiscale characterization of the heterogeneity of gray matter volume (GMV) differences in 1,294 cases diagnosed with one of six conditions (attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, obsessive-compulsive disorder and schizophrenia) and 1,465 matched controls. Normative models indicated that person-specific deviations from population expectations for regional GMV were highly heterogeneous, affecting the same area in <7% of people with the same diagnosis. However, these deviations were embedded within common functional circuits and networks in up to 56% of cases. The salience-ventral attention system was implicated transdiagnostically, with other systems selectively involved in depression, bipolar disorder, schizophrenia and attention-deficit/hyperactivity disorder. Phenotypic differences between cases assigned the same diagnosis may thus arise from the heterogeneous localization of specific regional deviations, whereas phenotypic similarities may be attributable to the dysfunction of common functional circuits and networks.

Effectiveness of atypical antipsychotics for unipolar and bipolar depression in adolescents and young adults: A systematic review and meta-analysis.

BACKGROUND: Antipsychotic medications are increasingly used for difficult-to-treat depression in young people. However, the evidence-base for this is unclear. Our aim was to assess the evidence for the efficacy of atypical antipsychotics in treating unipolar and bipolar depression in adolescents and young adults. METHOD: We conducted a comprehensive systematic review and meta-analysis of randomized-control-trial studies (RCTs) of antipsychotic medications for 10- to 25-year-olds with unipolar and bipolar depression. The primary outcome of interest was change in depressive symptoms from baseline to trial endpoint. RESULTS: No studies were identified that evaluated the use of antipsychotics in the treatment of unipolar depression. However, we identified four studies, of quetiapine, lurasidone and olanzapine/fluoxetine combination, comprising a total of 866 randomized patients, that evaluated treatment of bipolar depression. All studies used the Children's Depression Rating Scale-Revised (CDRS-R). Our meta-analysis revealed the weighted mean difference (WMD) was -4.58 (95 % CI, -6.59 to -2.57) between antipsychotic and placebo-treated groups. Response and remission rates were also significantly in favor of antipsychotic treatment. LIMITATIONS: There were few studies, several did not address risk-of-bias domains and there was a lack of non-industry sponsored studies. CONCLUSION: There is an absence of evidence for the use of antipsychotic medications in treatment of youth unipolar depression, and no recommendations can be made. There is some evidence for the efficacy of antipsychotics, specifically lurasidone and olanzapine/fluoxetine combination, in the treatment of young people with bipolar depression. However, this evidence is limited and more studies investigating the use of these medications in young people are needed.

Frontoamygdalar Effective Connectivity in Youth Depression and Treatment Response.

BACKGROUND: Emotion regulation deficits are characteristic of youth depression and are underpinned by altered frontoamygdalar function. However, the causal dynamics of frontoamygdalar pathways in depression and how these dynamics relate to treatment prognosis remain unexplored. This study aimed to assess frontoamygdalar effective connectivity during cognitive reappraisal in youths with depression and to test whether pathway dynamics are predictive of individual response to combined cognitive behavioral therapy plus treatment with fluoxetine or placebo. METHODS: One hundred seven young people with moderate to severe depression and 94 healthy control participants completed a functional magnetic resonance imaging cognitive reappraisal task. After the task, 87 participants with depression were randomized and received 12 weeks of cognitive behavioral therapy plus either fluoxetine or placebo. Dynamic causal modeling was used to map frontoamygdalar effective connectivity during reappraisal and to assess the predictive capacity of baseline frontoamygdalar effective connectivity on depression diagnosis and posttreatment depression remission. RESULTS: Young people with depression showed weaker inhibitory modulation of ventrolateral prefrontal cortex to amygdala connectivity during reappraisal (0.29 Hz, posterior probability = 1.00). Leave-one-out cross-validation demonstrated that this effect was sufficiently large to predict individual diagnostic status (r = 0.20, p = .003). Posttreatment depression remission was associated with weaker excitatory ventromedial prefrontal cortex to amygdala connectivity (-0.56 Hz, posterior probability = 1.00) during reappraisal at baseline, though this effect did not predict individual remission status (r = -0.02, p = .561). CONCLUSIONS: Frontoamygdalar effective connectivity shows promise in identifying youth depression diagnosis, and circuits responsible for negative affect regulation are implicated in responsiveness to first-line depression treatments.

Altered interaction of physiological activity and behavior affects risky decision-making in ADHD.

Background: Adult attention-deficit/hyperactivity disorder (ADHD) is often associated with risky decision-making behavior. However, current research studies are often limited by the ability to adequately reflect daily behavior in a laboratory setting. Over the lifespan impairments in cognitive functions appear to improve, whereas affective functions become more severe. We assume that risk behavior in ADHD arises predominantly from deficits in affective processes. This study will therefore aim to investigate whether a dysfunction in affective pathways causes an abnormal risky decision-making (DM) behavior in adult ADHD. Methods: Twenty-eight participants with ADHD and twenty-eight healthy controls completed a battery of questionnaires regarding clinical symptoms, self-assessment of behavior and emotional competence. Furthermore, skin conductance responses were measured during the performance in a modified version of the Balloon Analogue Risk Task. A linear mixed-effects model analysis was used to analyze emotional arousal prior to a decision and after feedback display. Results: Results showed higher emotional arousal in ADHD participants before decision-making (ß = -0.12, SE = 0.05, t = -2.63, p < 0.001) and after feedback display (ß = -0.14, SE = 0.05, t = -2.66, p = 0.008). Although risky behavior was greater in HC than in ADHD, we found a significant interaction effect of group and anticipatory skin conductance responses regarding the response behavior (ß = 107.17, SE = 41.91, t = 2.56, p = 0.011). Post hoc analyses revealed a positive correlation between anticipatory skin conductance responses and reaction time in HC, whereas this correlation was negative in ADHD. Self-assessment results were in line with the objective measurements. Conclusion: We found altered changes in physiological activity during a risky decision-making task. The results confirm the assumption of an aberrant relationship between bodily response and risky behavior in adult ADHD. However, further research is needed with respect to age and gender when considering physiological activities.

Differential engagement of the posterior cingulate cortex during cognitive restructuring of negative self- and social beliefs.

Negative self-beliefs are a core feature of psychopathology, encompassing both negative appraisals about oneself directly (i.e. self-judgment) and negative inferences of how the self is appraised by others (i.e. social judgment). Challenging maladaptive self-beliefs via cognitive restructuring is a core treatment mechanism of gold-standard psychotherapies. However, the neural mechanisms underlying the restructuring of these two kinds of negative self-beliefs are poorly understood. Eighty-six healthy participants cognitively restructured self-judgment and social-judgment negative self-belief statements during 7 Tesla functional magnetic resonance imaging scanning. Cognitive restructuring broadly elicited activation in the core default mode network (DMN), salience and frontoparietal control regions. Restructuring self-judgment relative to social-judgment beliefs was associated with comparatively higher activation in the ventral posterior cingulate cortex (PCC)/retrosplenial cortex, while challenging social-judgment statements was associated with higher activation in the dorsal PCC/precuneus. While both regions showed increased functional connectivity with the supplementary and pre-supplementary motor areas during restructuring, the dorsal PCC displayed greater task-dependent connectivity with distributed regions involved in salience, attention and social cognition. Our findings indicate distinct patterns of PCC engagement contingent upon self- and social domains, highlighting a specialized role of the dorsal PCC in supporting neural interactions between the DMN and frontoparietal/salience networks during cognitive restructuring.