Major depressive disorder (MDD) is common and disabling, yet reported brain structural differences vary across studies. Here we performed a large vertex-wise (point-by-point) meta-analysis of cortical thickness and surface area using harmonized magnetic resonance imaging processing across 64 cohorts from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) MDD and Depression Imaging Research Consortium (DIRECT) consortia (5,736 patients; 6,538 controls). We show significantly lower cortical thickness in patients with MDD in multiple brain regions, including the inferior parietal, lateral occipital, superior parietal, medial and lateral orbitofrontal, anterior and posterior cingulate, and precentral gyri, with cortical surface area showing no significant differences. Effects were most pronounced in adults with acute depression, whereas adolescents showed no significant case-control differences. Antidepressant medication use at scanning was associated with more extensive thinning, although effect sizes remained modest (mostly |Cohen's d| < 0.20). This high-resolution, globally generalizable map can support studies of mechanisms and help evaluate structural markers of the clinical course and treatment response.

Background:The period following discharge from psychiatric inpatient care represents a critical transition phase marked by heightened vulnerability to relapse, including increased risks of emergency department (ED) utilization. Understanding the risk factors for ED utilization after hospital discharge will help identify individuals who should be targeted for enhanced follow up care in the community. Objective:This study aimed to examine the sociodemographic and clinical factors associated with psychiatric ED utilization within six months of discharge from inpatient psychiatric care among individuals assigned to different postdischarge interventions. The goal is to identify high-risk groups to inform targeted follow up strategies and enhance transitional care planning. Methods:This study analyzed secondary data from a pragmatic stepped-wedge cluster-randomized trial which recruited patients across ten health care sites in Alberta, Canada, from March 2022 to February 2024. For the primary study, a total of 1098 psychiatric inpatients were allocated to one of three post-discharge conditions: treatment as usual (TAU), SMS, or SMS plus peer support (SMS+ PS). Sociodemographic and clinical data were collected at discharge. ED visits 6-months postdischarge were recorded. χ2 tests identified variables associated with ED utilization. Significant predictors were entered into a logistic regression model to determine adjusted odds ratios (ORs) and 95% CIs. Results:Of the 1098 participants, demographic and clinical variables were examined for association with mental health ED visits at 6-months post discharge. Univariate analysis identified six significant predictors: age, ethnicity, relationship status, employment, housing status, and prior ED use. Logistic regression analysis identified several predictors of mental health ED visits 6-months postdischarge. Compared to participants under 25 years, those aged 26-40 was less likely to revisit the ED (OR 0.66, 95% CI 0.46-0.95), as were those over 40 years (OR 0.58, 95% CI 0.37-0.92). Individuals identifying as mixed or other ethnicity were less likely than White people to return to the ED (OR 0.52, 95% CI 0.28-0.96). Unemployed participants had higher odds of ED use than those employed (OR 1.66, 95% CI 1.18-2.34). Prior ED attendance was the strongest predictor (OR 2.45, 95% CI 1.03-5.80). Housing status showed varied but nonsignificant effects. Conclusions:This study highlights key demographic and clinical factors influencing psychiatric ED use following inpatient discharge. The findings emphasize the importance of targeted transitional care interventions, particularly for high-risk groups such as younger, unemployed, and previously ED-utilizing individuals, and support the integration of scalable approaches like SMS and peer support into discharge planning.

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing 7012 participants from 31 sites (N = 2772 MDD and N = 4240 HC), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible. Future studies are needed to determine whether more sophisticated integration of information from other MRI modalities such as fMRI and DWI will lead to a higher performance in this diagnostic task.

BACKGROUND:Externalizing and internalizing disorders are common in youth but are often studied separately, preventing researchers from identifying shared (i.e., transdiagnostic) alterations in brain structure. Using data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium, we conducted a mega-analysis to identify shared and distinct cortical and subcortical brain alterations across internalizing (anxiety disorders and depression) and externalizing (attention-deficit/hyperactivity disorder [ADHD] and conduct disorder [CD]) disorders in youth. METHODS:3D T1-weighted magnetic resonance imaging data from youths (age range 4-21 years) with anxiety disorders (n = 1044), depression (n = 504), ADHD (n = 1317), and CD (n = 1172) along with healthy control participants (n = 4743) were analyzed. We assessed group differences in regional cortical thickness, surface area (SA), and subcortical volume using linear models, adjusted for site, age, and sex, as well as total intracranial volume in the SA and subcortical volume models. RESULTS:We observed transdiagnostic associations, with both internalizing and externalizing disorders characterized by lower SA in the insula, entorhinal cortex, and middle temporal gyrus and lower amygdala volume (Cohen's ds = -0.07 to -0.24) as well as total SA and intracranial volume (ds = -0.11 to -0.25). Externalizing-specific reductions in SA were observed in frontoparietal regions (ds = -0.08 to -0.13), but no internalizing-specific associations were identified. Disorder-specific alterations were identified for ADHD, CD, and anxiety disorders but not depression. CONCLUSIONS:Both common and disorder-specific alterations were identified, with regions involved in salience attribution and emotion processing implicated across internalizing and externalizing disorders. These novel findings can guide future research targeting common biological processes across youth psychiatric disorders as well as features unique to individual disorders.

According to diathesis-stress models, individual differences in traits, such as brain structure, may moderate the effects of stressors on the development of symptoms of psychopathology; however, findings in the literature have been inconsistent. The COVID-19 pandemic, which impacted almost all individuals around the world, presented a unique opportunity to address these gaps. The present study investigated whether whole brain cortical thickness and surface area moderate the effects of stress from the COVID-19 pandemic on the development of depressive symptoms in a longitudinal sample of adolescents.

Background. The caudate and putamen have previously been implicated in Attention-Deficit/Hyperactivity Disorder (ADHD). However, previous studies have not investigated the relationship between the caudate and putamen with executive function (EF). The current study investigated the clinical relevance of the caudate and putamen with respect to EF. Method. We studied 49 children (24 ADHD/25 typically developing children (TDC)). All participants in the ADHD group had to undergo a 48-hour stimulant medication washout period. Participants completed cognitive tasks related to working memory/inhibition and underwent a T1-weighted MRI sequence. All parents completed behaviour rating scales using the Behavior Rating Inventory of Executive Function, Second Edition (BRIEF-2). Data were analyzed using multivariate analysis of covariance, Pearson correlations, and linear regressions. Results. Children with ADHD demonstrated a higher frequency of perseverative errors compared to TDC (p <.05), and their parents reported significantly more EF challenges (p <.001). No difference was observed in the working memory tasks. No significant volumetric differences were seen in the caudate or the putamen. A linear regression model suggested that the right caudate volume accounted for 10.3% of the variance in emotion regulation as reported by parents on the BRIEF-2 in the overall sample. Discussion. We observed significant EF challenges without volumetric differences. However, the right caudate was correlated to parent ratings of emotional regulation, highlighting the need to consider emotional regulation difficulties in ADHD. ### Competing Interest Statement The authors have declared no competing interest.

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.

Neuromodulatory interventions are relatively novel and approaches to studying harms and tolerability have varied. Using a checklist based on guidelines from Good Clinical Practice and the Harms Extension of the CONSORT (Consolidated Standards of Reporting Trials) Statement, we identified how adverse events are measured, assessed, and reported in studies evaluating neuromodulation for the treatment of mental and neurodevelopmental disorders among children and adolescents. A systematic literature review identified 56 experimental and quasi-experimental studies evaluating transcranial magnetic stimulation (TMS), transcranial alternating (tACS) or direct (tDCS) current stimulation, transcranial pulse stimulation (TPS), and vagus or trigeminal nerve stimulation (VNS or TNS). For 22 studies (39%), the types of adverse events to be monitored were identified, and for 31 studies (55%), methods for collecting adverse event data were described. Methods for assessing adverse events were less commonly described with 23 studies (41%) having details on assessing event severity, and 11 studies (20%) having details on assessing event causality. Among 31 studies with reported results, headache, skin irritation, and general pain or discomfort were the most reported across studies. Seizure, untoward medical occurrences, and intracranial bleeding, edema, or other intracranial pathology were considered serious events, but these events were not reported as occurring in any results-based papers. Taken together, the findings from this review indicate that most studies of pediatric neuromodulatory interventions did not include descriptions of adverse event monitoring and evaluation. Comprehensive event monitoring and reporting across studies can significantly augment the current knowledge base.

BACKGROUND:According to person-by-environment models, individual differences in traits may moderate the association between stressors and the development of psychopathology; however, findings in the literature have been inconsistent and little literature has examined adolescent brain structure as a moderator of the effects of stress on adolescent internalizing symptoms. The COVID-19 pandemic presented a unique opportunity to examine the associations between stress, brain structure, and psychopathology. Given links of cortical morphology with adolescent depression and anxiety, the current study investigated whether cortical morphology moderated the relationship between stress from the COVID-19 pandemic and the development of internalizing symptoms in familial high-risk adolescents. METHODS:Prior to the COVID-19 pandemic, 72 adolescents (27 male) completed a measure of depressive and anxiety symptoms and underwent magnetic resonance imaging. T1-weighted images were acquired to assess cortical thickness and surface area. Approximately 6 to 8 months after COVID-19 was declared a global pandemic, adolescents reported their depressive and anxiety symptoms and pandemic-related stress. RESULTS:Adjusting for pre-pandemic depressive and anxiety symptoms and stress, increased pandemic-related stress was associated with increased depressive but not anxiety symptoms. This relationship was moderated by cortical thickness and surface area in the anterior cingulate and cortical thickness in the medial orbitofrontal cortex such that increased stress was only associated with increased depressive and anxiety symptoms among adolescents with lower cortical surface area and higher cortical thickness in these regions. CONCLUSIONS:Results further our understanding of neural vulnerabilities to the associations between stress and internalizing symptoms in general and during the COVID-19 pandemic in particular.

Negative symptoms are often found in youth at clinical high risk (CHR) for psychosis. The present study explored the feasibility of using tDCS in conjunction with CBT in the treatment of negative symptoms in 5 youths at CHR. We sought to determine whether the protocol was feasible given the requirement for repeated visits over a three-week period, and to determine if measures of neurobiological change could be included, both acutely and following three weeks of stimulation. The results from this study suggest that the protocol is feasible for these youth, and the inclusion of MRI scanning sessions yielded good quality data.

BACKGROUND: According to person-by-environment models, individual differences in traits may moderate the association between stressors and the development of psychopathology; however, findings in the literature have been inconsistent and little literature has examined adolescent brain structure as a moderator of the effects of stress on adolescent internalizing symptoms. The COVID-19 pandemic presented a unique opportunity to examine the associations between stress, brain structure, and psychopathology. Given links of cortical morphology with adolescent depression and anxiety, the current study investigated whether cortical morphology moderated the relationship between stress from the COVID-19 pandemic and the development of internalizing symptoms in familial high-risk adolescents. METHODS: Prior to the COVID-19 pandemic, 72 adolescents (27 male) completed a measure of depressive and anxiety symptoms and underwent magnetic resonance imaging. T1-weighted images were acquired to assess cortical thickness and surface area. Approximately 6 to 8 months after COVID-19 was declared a global pandemic, adolescents reported their depressive and anxiety symptoms and pandemic-related stress. RESULTS: Adjusting for pre-pandemic depressive and anxiety symptoms and stress, increased pandemic-related stress was associated with increased depressive but not anxiety symptoms. This relationship was moderated by cortical thickness and surface area in the anterior cingulate and cortical thickness in the medial orbitofrontal cortex such that increased stress was only associated with increased depressive and anxiety symptoms among adolescents with lower cortical surface area and higher cortical thickness in these regions. CONCLUSIONS: Results further our understanding of neural vulnerabilities to the associations between stress and internalizing symptoms in general and during the COVID-19 pandemic in particular.

OBJECTIVES:Recent research has focused on the effects of legalization on cannabis-related emergency department visits, but the considerable healthcare costs of cannabis-related hospitalizations merit attention. We will examine the association between recreational cannabis legalization and cannabis-related hospitalizations. METHODS:A cohort of 3,493,864 adults from Alberta was examined (October 2015-May 2021) over three periods: pre-legalization, post-legalization of flowers and herbs (phase one), and post-legalization of edibles, extracts, and topicals (phase two). Interrupted time series analyses were used to detect changes. RESULTS:The study found an increase in hospitalization rates among younger adults (18-24) before legalization, yet no increased risk was associated with cannabis legalization, for either younger (18-24) or older adults (25+). CONCLUSIONS:Clinicians should be aware of the increased risk in younger groups and may benefit from early identification and intervention strategies, including screening and brief interventions in primary care settings.

# Introduction Adolescence is a period of remarkable development as children’s brains change to resemble adult brains. Resting state fMRI measures fluctuations in blood-oxygen signal from which we can infer functional connectivity (FC). Graph theory is a branch of mathematics that can quantify the complex patterns of connectivity and network architecture inherent in the functional connectome. An ideal graph theory analysis explores edges that are weighted, directional, and heterogenous (can be positive or negative). Recent developmental studies have applied graph theory to the functional connectome, yet due to the considerable complexity added by each facet, most ignore one or more aspects of an ideal graph theory analysis (directionality and heterogeneity). # Methods The present cross-sectional study measured FC in typically developing children, adolescents, and young adults (age 6-24 years) using 150+ echo-planar volumes (3.6mm isotropic voxels, repetition/echo time=2000/30ms) acquired at rest. A standard pre-processing pipeline was used, and the functional connectome was quantified using a weighted, directed graph analysis, including both positive and negative connections. Five different graph theory metrics were utilized to quantify developmental trajectories: connection density, modularity, clustering coefficient, global efficiency, and betweenness centrality. Positive and negative connections were analyzed separately, and age and sex associations were explored. # Results The total sample comprised 219 participants (mean age (SD) \[range] = 14.1 (3.3) \[6.5-24.0] years, 50% female). For positive connections, modularity and betweenness centrality increased with age (both p<0.001), while connection density, clustering coefficient, and global efficiency decreased with age (all p<0.001). By contrast, for negative connections, modularity and betweenness centrality decreased with age (p=0.002, p=0.003), while connection density, clustering coefficient , and global efficiency increased with age (p<0.001, p<0.001, p=0.003). Effects of sex, hemisphere, and their interaction were minimal, though global efficiency for negative connections was higher in the right hemisphere than the left (p<0.001). # Conclusion Graph theory appears to be a useful tool for quantifying the complex development of the functional connectome. The developmental changes presented here may be driven by an intrinsic pressure to balance functionality with low metabolic cost to maintain the network. The positive connection network appears to shift towards a more efficient conformation resembling “small-world” architecture. In contrast, the negative connection network seems to shift away from such efficient architecture, possibly to prioritize improving functionality before later refinement.

Developmental lateralization of brain function is imperative for behavioral specialization, yet few studies have investigated differences between hemispheres in structural connectivity patterns, especially over the course of development. The present study compares the lateralization of structural connectivity patterns, or topology, across children, adolescents, and young adults. We applied a graph theory approach to quantify key topological metrics in each hemisphere including efficiency of information transfer between regions (global efficiency), clustering of connections between regions (clustering coefficient [CC]), presence of hub-nodes (betweenness centrality [BC]), and connectivity between nodes of high and low complexity (hierarchical complexity [HC]) and investigated changes in these metrics during development. Further, we investigated BC and CC in seven functionally defined networks. Our cross-sectional study consisted of 211 participants between the ages of 6 and 21 years with 93% being right-handed and 51% female. Global efficiency, HC, and CC demonstrated a leftward lateralization, compared to a rightward lateralization of BC. The sensorimotor, default mode, salience, and language networks showed a leftward asymmetry of CC. BC was only lateralized in the salience (right lateralized) and dorsal attention (left lateralized) networks. Only a small number of metrics were associated with age, suggesting that topological organization may stay relatively constant throughout school-age development, despite known underlying changes in white matter properties. Unlike many other imaging biomarkers of brain development, our study suggests topological lateralization is consistent across age, highlighting potential nonlinear mechanisms underlying developmental specialization.

Depression and anxiety are associated with grey matter changes in subcortical regions in adults and adolescents. Parent psychopathology is associated with offspring brain structure, but it's unclear whether altered brain structure in children is associated with severity of parental depression and anxiety symptoms. We examined 123 youth (Mean age = 13.64; 62% female) with no clinically significant history of depression or anxiety and one parent diagnosed with current or past depressive or anxiety disorders. Parents completed the Mini International Neuropsychiatric Interview to assess diagnostic status and the Beck Depression Inventory-II, and the Generalized Anxiety Disorder-7 to assess current symptom severity. Youth underwent T1 weighted structural Magnetic Resonance Imaging scans. Bivariate analyses revealed higher parental depressive severity was not significantly associated with offspring grey matter. Parental anxiety severity was significantly associated with less left global surface area. When controlling for offspring age, sex and intracranial volume (ICV), offspring right surface area was negatively associated with parental depressive severity at a trend level. In previously depressed parents, greater parental depressive severity was significantly associated with offspring decreased left and right surface area. There were no significant associations between parental anxiety severity in previously depressed parents and offspring subcortical or cortical brain regions. These results highlight associations between parental depressive symptom severity and offspring brain structure and suggest that even within an already high-risk group of adolescents, there may be altered cortical surface area depending on parent symptom severity. This may help identify youth most at risk for developing a mood disorder and could help further early intervention and identification efforts.

The Tourette OCD Alberta Network (TOAN) supports mental health therapists to improve the delivery of care to patients with Tourette syndrome (TS) and OCD in Alberta. We evaluated the professional development needs of health care workers to develop a continuing professional development (CPD) webinar series. Health care workers demonstrated an urgent need to access a CPD program grounded in evidenced based knowledge about TS and OCD. While 80% of health care workers treated children with TS and OCD, 50% had no formal training. A curriculum consisting of a series of twelve live, online webinars was developed and delivered between September 2020 and June 2021, covering a range of clinical topics. The webinars were attended on average by 63 attendees, with the outcome of a positive knowledge gain. In future, the educational program will need to reflect the ongoing developing clinical understanding of TS and OCD.

Canada legalized recreational cannabis on October 17, 2018. Since then, only one Canadian study (in Quebec) examined the impact of legalization on cannabis-related hospitalizations. That study focused on youth (0–19) using 5.5 months of post-legalization data, which precluded understanding the impact on trends over a longer period after legalization. While a number of recent studies have examined the impact of legalization on cannabis-related emergency department (ED) visits in Canada, cannabis-related hospitalizations should not be ignored since substance-related in-patient care is required in the most severe spectrum of cases and they contribute to significant healthcare costs. The multi-phased approach of cannabis legalization in Ontario provides an opportunity to examine the impact of the different phases of cannabis sales regulation on cannabisrelated hospitalizations. The Ontario legal cannabis availability approach involves a hybrid model of government operated online sales and licensed private retail stores. Implementation of the model was phased, with Phase 1 of legalization (October 2018-March 2020) associated with flower and herb sales online and limited private retail storefronts; Phase 2 involved increased storefronts and availability of edibles (Mar 2020-May 2021). The aim of this study is to investigate the association between Phase 1 and 2 of legalization and cannabis-related hospitalizations in Ontario.

This study aimed at evaluating the efficacy of an online CBT intervention with limited therapist contact targeting a range of posttraumatic symptoms among evacuees from the 2016 Fort McMurray wildfires. One hundred and thirty-six residents of Fort McMurray who reported either moderate PTSD symptoms (PCL-5 > 23) or mild PTSD symptoms (PCL-5 > 10) with mod-erate depression (PHQ-9 > 10) or subthreshold insomnia symptoms (ISI > 8) were randomized either to a treatment (n = 69) or a waitlist condition (n = 67). Participants were on average 45 years old, and mostly identified as White (82%) and as women (76%). Primary outcomes were PTSD, depression, and insomnia symptoms. Secondary outcomes were anxiety symptoms and disability. Signifi-cant Assessment Time x Treatment Condition interactions were observed on all outcomes, indicating that access to the treatment led to a decrease in posttraumatic stress (F[1,117.04] =12.128, p = .001; d = .519, 95% CI = .142- .895),depression (F[1,118.29] = 9.978, p = .002; d = .519, 95% CI = .141-.898) insomnia (F[1,117.60] = 4.574, p = .035; d = .512, 95% CI = .132-.892), and anxiety (F[1,119.64] = 5.465, p = .021; d = .421, 95% CI = .044- .797) symptom severity and disability (F[1,111.55] = 7.015, p = .009; d = .582, 95% CI = .200-.963). Larger effect sizes (d = 0.823-1.075) were observed in participants who completed at least half of the treatment. The RESILI-ENT online treatment platform was successful to provide access to specialized evidence-based mental health care after a disaster.