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.

Concurrent validity and reliability of suicide risk assessment instruments: A meta-analysis of 20 instruments across 27 international cohorts.

OBJECTIVE: A major limitation of current suicide research is the lack of power to identify robust correlates of suicidal thoughts or behavior. Variation in suicide risk assessment instruments used across cohorts may represent a limitation to pooling data in international consortia. METHOD: Here, we examine this issue through two approaches: (a) an extensive literature search on the reliability and concurrent validity of the most commonly used instruments and (b) by pooling data (N ∼ 6,000 participants) from cohorts from the Enhancing NeuroImaging Genetics Through Meta-Analysis (ENIGMA) Major Depressive Disorder and ENIGMA-Suicidal Thoughts and Behaviour working groups, to assess the concurrent validity of instruments currently used for assessing suicidal thoughts or behavior. RESULTS: We observed moderate-to-high correlations between measures, consistent with the wide range (κ range: 0.15-0.97; r range: 0.21-0.94) reported in the literature. Two common multi-item instruments, the Columbia Suicide Severity Rating Scale and the Beck Scale for Suicidal Ideation were highly correlated with each other (r = 0.83). Sensitivity analyses identified sources of heterogeneity such as the time frame of the instrument and whether it relies on self-report or a clinical interview. Finally, construct-specific analyses suggest that suicide ideation items from common psychiatric questionnaires are most concordant with the suicide ideation construct of multi-item instruments. CONCLUSIONS: Our findings suggest that multi-item instruments provide valuable information on different aspects of suicidal thoughts or behavior but share a modest core factor with single suicidal ideation items. Retrospective, multisite collaborations including distinct instruments should be feasible provided they harmonize across instruments or focus on specific constructs of suicidality. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

How Obstructed Action Efficacy Impacts Reward-Based Decision Making in Adolescent Depression: An fMRI Study.

OBJECTIVE: Disruption of reward seeking behavior by unforeseen obstacles can promote negative affect, including frustration and irritability, in adolescents. Repeated experiences of obstructed reward may in fact contribute to the development of depression in adolescents. However, the neurocognitive mechanisms whereby goal disruption impacts reward processing in adolescent depression have not yet been characterized. The present study addresses this gap by using neuroimaging and a novel paradigm to assess how incidental action obstruction impacts reward-based decision making. METHOD: We assessed 62 unmedicated adolescents with major depressive disorder (MDD; mean age = 15.6 years, SD = 1.4 years, 67% female participants) and 68 matched healthy control participants (mean age = 15.3 years, SD = 1.4 years, 50% female participants) using functional magnetic resonance imaging (fMRI) while they played a card game in which they had to guess between 2 options to earn points, in low- and high-stake conditions. Functioning of button presses through which they made decisions was intermittently blocked, thereby blocking action efficacy. RESULTS: Participants with MDD made fewer button press repetitions in response to action efficacy obstruction, which was more apparent in the low-stake condition (rate ratio =0.85, p = .034). During response repetition across stake conditions, MDDs exhibited higher activation in regions in the ventromedial prefrontal cortex, caudate, and putamen (F1,125 = 16.4-25.6, df=1,125; p values <.001; Hedges g = 0.85-0.98). CONCLUSION: Adolescents with depression tend to exhibit less flexible behavioral orientation in the face of blocked action efficacy, and abnormalities in neural systems critical to regulating negative affect during reward-based decision making. This research highlights possible mechanisms relevant to understanding and treating affective dysregulation in adolescent depression.

Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium.

Identifying brain alterations associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and improving early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth. We performed analyses in three separate stages, in samples ranging from most to least homogeneous in terms of suicide assessment instrument and mental disorder. First, in a sample of 577 young people with mood disorders, in which STBs were assessed with the Columbia Suicide Severity Rating Scale (C-SSRS). Second, in a sample of young people with mood disorders, in which STB were assessed using different instruments, MRI metrics were compared among healthy controls without STBs (HC; N = 519), clinical controls with a mood disorder but without STBs (CC; N = 246) and young people with current suicidal ideation (N = 223). In separate analyses, MRI metrics were compared among HCs (N = 253), CCs (N = 217), and suicide attempters (N = 64). Third, in a larger transdiagnostic sample with various assessment instruments (HC = 606; CC = 419; Ideation = 289; HC = 253; CC = 432; Attempt=91). In the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and a history of actual suicide attempts (N = 163) than those without a lifetime suicide attempt (N = 323; FDR-p = 0.035, Cohen's d = 0.34). No associations with suicidal ideation were found. When examining more heterogeneous samples, we did not observe significant associations. Lower frontal pole surface area may represent a vulnerability for a (non-interrupted and non-aborted) suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk.

Virtual Ontogeny of Cortical Growth Preceding Mental Illness.

BACKGROUND: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. METHODS: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. RESULTS: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. CONCLUSIONS: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.

The effect of obstructed action efficacy on reward-based decision-making in healthy adolescents: a novel functional MRI task to assay frustration.

Frustration is common in adolescence and often interferes with executive functioning, particularly reward-based decision-making, and yet very little is known about how incidental frustrating events (independent of task-based feedback) disrupt the neural circuitry of reward processing in this important age group. While undergoing functional magnetic resonance imaging (fMRI), 45 healthy adolescents played a card game in which they had to guess between two options to earn points, in low- and high-stake conditions. Functioning of button presses through which they made decisions was intermittently blocked, thereby increasing frustration potential. Neural deactivation of the precuneus, a Default Mode Network region, was observed during obstructed action blocks across stake conditions, but less so on high- relative to low-stake trials. Moreover, less deactivation in goal-directed reward processing regions (i.e., caudate), frontoparietal "task control" regions, and interoceptive processing regions (i.e., somatosensory cortex, thalamus) were observed on high-stake relative to low-stake trials. These findings are consistent with less disruption of goal-directed reward seeking during blocked action efficacy in high-stake conditions among healthy adolescents. These results provide a roadmap of neural systems critical to the processing of frustrating events during reward-based decision-making in youths and could help to characterize how frustration regulation is altered in a range of pediatric psychopathologies.

Mentalizing imagery therapy for depressed family dementia caregivers: Feasibility, clinical outcomes and brain connectivity changes.

BACKGROUND: Family dementia caregivers experience high rates of depression and anxiety that often go untreated due to time demands. We aimed to determine the feasibility of a brief, 4-week Mentalizing Imagery Therapy intervention, which couples mindfulness with guided imagery practices aimed at bolstering mentalizing capacity, to reduce caregiver psychological symptoms and to explore potential impact on dorsolateral prefrontal cortex connectivity. METHODS: Twenty-four family dementia caregivers with moderate depression symptoms (a score of 10 in Patient Health Questionnaire-9) were assigned to either group Mentalizing Imagery Therapy (MIT, n = 12) or a waitlist augmented by optional relaxation exercises (n = 12). Participants completed questionnaires to measure depression and anxiety at baseline and followup, and those eligible also underwent resting state functional magnetic resonance (fMRI) brain imaging at these time points. RESULTS: Eleven of 12 caregivers assigned to MIT completed the intervention and attended weekly groups 98% of the time. MIT home practice logs indicated average practice of 5 ± 2 sessions per week for 23 ± 8 min per session. All participants in waitlist completed the post-assessment. MIT participants exhibited significantly greater improvement than waitlist on self-reported depression and anxiety symptoms (p<.05) after 4 weeks. Neuroimaging results revealed increased dorsolateral prefrontal cortex connectivity with a putative emotion regulation network in the MIT group (p = .05) but not in waitlist (p = 1.0). LIMITATIONS: Sample size limitations necessitate validation of findings in larger, randomized controlled trials. CONCLUSIONS: A 4-week group MIT program was feasible for caregivers, with high levels of participation in weekly group meetings and home practice exercises.

Brain Correlates of Suicide Attempt in 18,925 Participants Across 18 International Cohorts.

BACKGROUND: Neuroimaging studies of suicidal behavior have so far been conducted in small samples, prone to biases and false-positive associations, yielding inconsistent results. The ENIGMA-MDD Working Group aims to address the issues of poor replicability and comparability by coordinating harmonized analyses across neuroimaging studies of major depressive disorder and related phenotypes, including suicidal behavior. METHODS: Here, we pooled data from 18 international cohorts with neuroimaging and clinical measurements in 18,925 participants (12,477 healthy control subjects and 6448 people with depression, of whom 694 had attempted suicide). We compared regional cortical thickness and surface area and measures of subcortical, lateral ventricular, and intracranial volumes between suicide attempters, clinical control subjects (nonattempters with depression), and healthy control subjects. RESULTS: We identified 25 regions of interest with statistically significant (false discovery rate < .05) differences between groups. Post hoc examinations identified neuroimaging markers associated with suicide attempt including smaller volumes of the left and right thalamus and the right pallidum and lower surface area of the left inferior parietal lobe. CONCLUSIONS: This study addresses the lack of replicability and consistency in several previously published neuroimaging studies of suicide attempt and further demonstrates the need for well-powered samples and collaborative efforts. Our results highlight the potential involvement of the thalamus, a structure viewed historically as a passive gateway in the brain, and the pallidum, a region linked to reward response and positive affect. Future functional and connectivity studies of suicidal behaviors may focus on understanding how these regions relate to the neurobiological mechanisms of suicide attempt risk.

Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group.

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Reduced anxiety and changes in amygdala network properties in adolescents with training for awareness, resilience, and action (TARA).

Mindfulness-based approaches show promise to improve emotional health in youth and may help treat and prevent adolescent depression and anxiety. However, there is a fundamental gap in understanding the neural reorganization that takes place as a result of such interventions. The Training for Awareness, Resilience, and Action (TARA) program, initially developed for depressed adolescents, uses a framework drawn from neuroscience, mindfulness, yoga, and modern psychotherapeutic techniques to promote emotional health. The goal of this study was to assess the effects of the TARA training on emotional health and structural white matter brain networks in healthy youth. We analyzed data from 23 adolescents who underwent the 12-week TARA training in a controlled within-subject study design and whose brain networks were assessed using diffusion MRI connectomics. Compared to the control time period, adolescents showed a significant decrease in anxiety symptoms with TARA (Cohen's d = -0.961, p = 0.006); moreover, the node strength of the Right Amygdala decreased significantly after TARA (Cohen's d = -1.026, p = 0.004). Post-hoc analyses indicated that anxiety at baseline before TARA was positively correlated with Right Amygdala node strength (r = 0.672, p = 0.001). While change in Right Amygdala node strength with TARA was not correlated with change in anxiety (r = 0.146, p = 0.51), it was associated with change in depression subscale of Anhedonia / Negative Affect (r = 0.575, p = 0.004, exploratory analysis), possibly due to overlapping constructs captured in our anxiety and depression scales. Our results suggest that increased structural connectivity of Right Amygdala may underlie increased anxiety in adolescents and be lowered through anxiety-reducing training such as TARA. The results of this study contribute to our understanding of the neural mechanisms of TARA and may facilitate neuroscience-based prevention and treatment of adolescent anxiety and depression.

Gray Matter Changes in Adolescents Participating in a Meditation Training.

Meditation has shown to benefit a wide range of conditions and symptoms, but the neural mechanisms underlying the practice remain unclear. Magnetic resonance imaging (MRI) studies have investigated the structural brain changes due to the practice by examining volume, density, or cortical thickness changes. However, these studies have focused on adults; meditation's structural effects on the adolescent brain remain understudied. In this study, we investigated how meditation training affects the structure of the adolescent brain by scanning a group of 38 adolescents (16.48 ± 1.29 years) before and after participating in a 12-week meditation training. Subjects underwent Training for Awareness, Resilience, and Action (TARA), a program that mainly incorporates elements from mindfulness meditation and yoga-based practices. A subset of the adolescents also received an additional control scan 12 weeks before TARA. We conducted voxel-based morphometry (VBM) to assess gray matter volume changes pre- to post-training and during the control period. Subjects showed significant gray matter (GM) volume decreases in the left posterior insula and to a lesser extent in the left thalamus and left putamen after meditation training. There were no significant changes during the control period. Our results support previous findings that meditation affects regions associated with physical and emotional awareness. However, our results are different from previous morphometric studies in which meditation was associated with structural increases. We posit that this discrepancy may be due to the differences between the adolescent brain and the adult brain.

Evidence for a novel subcortical mechanism for posterior cingulate cortex atrophy in HIV peripheral neuropathy.

We previously reported that neuropathic pain was associated with smaller posterior cingulate cortical (PCC) volumes, suggesting that a smaller/dysfunctional PCC may contribute to development of pain via impaired mind wandering. A gap in our previous report was lack of evidence for a mechanism for the genesis of PCC atrophy in HIV peripheral neuropathy. Here we investigate if volumetric differences in the subcortex for those with neuropathic paresthesia may contribute to smaller PCC volumes, potentially through deafferentation of ascending white matter tracts resulting from peripheral nerve damage in HIV neuropathy. Since neuropathic pain and paresthesia are highly correlated, statistical decomposition was used to separate pain and paresthesia symptoms to determine which regions of brain atrophy are associated with both pain and paresthesia and which are associated separately with pain or paresthesia. HIV+ individuals (N = 233) with and without paresthesia in a multisite study underwent structural brain magnetic resonance imaging. Voxel-based morphometry and a segmentation/registration tool were used to investigate regional brain volume changes associated with paresthesia. Analysis of decomposed variables found that smaller midbrain and thalamus volumes were associated with paresthesia rather than pain. However, atrophy in the PCC was related to both pain and paresthesia. Peak thalamic atrophy (p = 0.004; MNI x = - 14, y = - 24, z = - 2) for more severe paresthesia was in a region with reciprocal connections with the PCC. This provides initial evidence that smaller PCC volumes in HIV peripheral neuropathy are related to ascending white matter deafferentation caused by small fiber damage observed in HIV peripheral neuropathy.

Interactive impact of childhood maltreatment, depression, and age on cortical brain structure: mega-analytic findings from a large multi-site cohort.

BACKGROUND: Childhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age. METHODS: Within the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer. RESULTS: CM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions. CONCLUSIONS: Severity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind.

White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group.

Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12-88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen's d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen's d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD.

Application of machine learning to structural connectome to predict symptom reduction in depressed adolescents with cognitive behavioral therapy (CBT).

PURPOSE: Adolescent major depressive disorder (MDD) is a highly prevalent, incapacitating and costly illness. Many depressed teens do not improve with cognitive behavioral therapy (CBT), a first-line treatment for adolescent MDD, and face devastating consequences of increased risk of suicide and many negative health outcomes. "Who will improve with CBT?" is a crucial question that remains unanswered, and treatment planning for adolescent depression remains biologically unguided. The purpose of this study was to utilize machine learning applied to patients' brain imaging data in order to help predict depressive symptom reduction with CBT. METHODS: We applied supervised machine learning to diffusion MRI-based structural connectome data in order to predict symptom reduction in 30 depressed adolescents after three months of CBT. A set of 21 attributes was chosen, including the baseline depression score, age, gender, two global network properties, and node strengths of brain regions previously implicated in depression. The practical and robust J48 pruned tree classifier was utilized with a 10-fold cross-validation. RESULTS: The classification resulted in an 83% accuracy of predicting depressive symptom reduction. The resulting tree of size seven with only three attributes highlights the role of the right thalamus in predicting depressive symptom reduction with CBT. Additional analysis showed a significant negative correlation between the change in the depressive symptoms and the node strength of the right thalamus. CONCLUSIONS: Our results demonstrate that a machine learning algorithm that exclusively uses structural connectome data and the baseline depression score can predict with a high accuracy depressive symptom reduction in adolescent MDD with CBT. This knowledge can help improve treatment planning for adolescent depression.

Cortisol, moderated by age, is associated with antidepressant treatment outcome and memory improvement in Major Depressive Disorder: A retrospective analysis.

BACKGROUND: Studies testing the relationship between cortisol levels, depression, and antidepressant treatment response have yielded divergent results suggesting the possibility of moderators of a cortisol effect. Several studies indicate that age may moderate the relationship between cortisol and depression. In patients with Major Depressive Disorder (MDD), we studied the interactive effects of age and cortisol in association with MDD diagnostic status and mood and memory response to antidepressant treatment. METHODS: Serum cortisol levels in 66 unmedicated patients with MDD and 75 matched healthy controls (HC) were measured at baseline and retrospectively analyzed. Logistic regression was used to determine an association of age, cortisol and their interaction with MDD diagnosis in the pooled sample of MDD and HC participants. Thirty-four of the MDD participants (age range: 19-65 years; median: 36) underwent treatment with a selective serotonin reuptake inhibitor (SSRl) for 8 weeks. Clinician and self-ratings of depression symptoms, as well as tests of verbal and visual delayed recall were obtained at baseline and post treatment. Moderation analyses determined the effect of age on the relationship between baseline cortisol and treatment outcome. RESULTS: Cortisol, moderated by age, was associated with MDD diagnosis (p < .05), treatment-associated reduction of depression symptoms (p < .001) and improvement of delayed recall (p < .001). Modeling the Cortisol × Age interaction suggested that for participants below the median age of our sample, lower cortisol levels were associated with a lower rate of MDD diagnosis and higher antidepressant effects. On the contrary, in those above the median sample age, lower cortisol was associated with a higher rate of MDD and less improvement in depression symptoms and memory performance. CONCLUSIONS: Our results add to the body of literature suggesting that age might be an important factor in moderating the relationship between peripheral cortisol levels, depression, cognition, and prognosis. These results indicate that previous disparities in the literature linking peripheral cortisol levels with depression characteristics and treatment response may critically relate, at least in part, to the age of the participants studied.

No Alterations of Brain Structural Asymmetry in Major Depressive Disorder: An ENIGMA Consortium Analysis.

OBJECTIVE: Asymmetry is a subtle but pervasive aspect of the human brain, and it may be altered in several psychiatric conditions. MRI studies have shown subtle differences of brain anatomy between people with major depressive disorder and healthy control subjects, but few studies have specifically examined brain anatomical asymmetry in relation to this disorder, and results from those studies have remained inconclusive. At the functional level, some electroencephalography studies have indicated left fronto-cortical hypoactivity and right parietal hypoactivity in depressive disorders, so aspects of lateralized anatomy may also be affected. The authors used pooled individual-level data from data sets collected around the world to investigate differences in laterality in measures of cortical thickness, cortical surface area, and subcortical volume between individuals with major depression and healthy control subjects. METHODS: The authors investigated differences in the laterality of thickness and surface area measures of 34 cerebral cortical regions in 2,256 individuals with major depression and 3,504 control subjects from 31 separate data sets, and they investigated volume asymmetries of eight subcortical structures in 2,540 individuals with major depression and 4,230 control subjects from 32 data sets. T1-weighted MRI data were processed with a single protocol using FreeSurfer and the Desikan-Killiany atlas. The large sample size provided 80% power to detect effects of the order of Cohen's d=0.1. RESULTS: The largest effect size (Cohen's d) of major depression diagnosis was 0.085 for the thickness asymmetry of the superior temporal cortex, which was not significant after adjustment for multiple testing. Asymmetry measures were not significantly associated with medication use, acute compared with remitted status, first episode compared with recurrent status, or age at onset. CONCLUSIONS: Altered brain macro-anatomical asymmetry may be of little relevance to major depression etiology in most cases.

Grief, Mindfulness and Neural Predictors of Improvement in Family Dementia Caregivers.

Background: Family dementia caregivers often suffer from an immense toll of grief while caring for their loved ones. We sought to identify the clinical relationship between grief, depression and mindfulness and identify neural predictors of symptomatology and improvement. Methods: Twenty three family dementia caregivers were assessed at baseline for grief, mindfulness and depression, of which 17 underwent functional magnetic resonance imaging (fMRI). During fMRI, caregivers were shown faces of either their dementia-stricken relative or that of a stranger, paired with grief-related or neutral words. In nine subjects, post fMRI scans were also obtained after 4 weeks of either guided imagery or relaxation. Robust regression was used to predict changes in symptoms with longitudinal brain activation (BA) changes as the dependent variable. Results: Grief and depression symptoms were correlated (r = 0.50, p = 0.01), and both were negatively correlated with mindfulness (r = -0.70, p = 0.0002; r = -0.52, p = 0.01). Relative to viewing strangers, caregivers showed pictures of their loved ones (picture factor) exhibited increased activation in the dorsal anterior cingulate gyrus and precuneus. Improvement in grief but not mindfulness or depression was predicted by increased relative BA in the precuneus and anterior cingulate (different subregions from baseline). Viewing grief-related vs. neutral words elicited activity in the medial prefrontal cortex and precuneus. Conclusions: Caregiver grief, depression and mindfulness are interrelated but have at least partially nonoverlapping neural mechanisms. Picture and word stimuli related to caregiver grief evoked brain activity in regions previously identified with bereavement grief. These activation foci might be useful as biomarkers of treatment response.

Test-Retest Reliability of Graph Theoretic Metrics in Adolescent Brains.

Graph theory analysis of structural brain networks derived from diffusion tensor imaging (DTI) has become a popular analytical method in neuroscience, enabling advanced investigations of neurological and psychiatric disorders. The purpose of this study was to investigate (1) the effects of edge weighting schemes and (2) the effects of varying interscan periods on graph metrics within the adolescent brain. We compared a binary (B) network definition with three weighting schemes: fractional anisotropy (FA), streamline count, and streamline count with density and length correction (SDL). Two commonly used global and two local graph metrics were examined. The analysis was conducted with two groups of adolescent volunteers who received DTI scans either 12 weeks apart (16.62 ± 1.10 years) or within the same scanning session (30 min apart) (16.65 ± 1.14 years). The intraclass correlation coefficient was used to assess test-retest reliability and the coefficient of variation (CV) was used to assess precision. On average, each edge scheme produced reliable results at both time intervals. Weighted measures outperformed binary measures, with SDL weights producing the most reliable metrics. All edge schemes except FA displayed high CV values, leaving FA as the only edge scheme that consistently showed high precision while also producing reliable results. Overall findings suggest that FA weights are more suited for DTI connectome studies in adolescents.

An exploratory examination of reappraisal success in depressed adolescents: Preliminary evidence of functional differences in cognitive control brain regions.

BACKGROUND: Most neuroimaging studies of adolescent depression employ tasks not designed to engage brain regions necessary for the cognitive control of emotion, which is central to many behavioral therapies for depression. Depressed adults demonstrate less effective activation of these regions and greater amygdala activation during cognitive reappraisal; we examined whether depressed adolescents show similar patterns of brain activation. METHODS: We collected functional magnetic resonance imaging (fMRI) data during cognitive reappraisal in 41 adolescents with major depressive disorder (MDD) and 34 matched controls (ages 13-17). We examined group differences in (1) activations associated with reappraisal and reappraisal success (i.e., negative affect reduction during reappraisal) using whole brain and amygdala region-of-interest analyses, and (2) functional connectivity of regions from the group-by-reappraisal success interaction. RESULTS: We found no significant group differences in whole brain or amygdala analyses during reappraisal. In the group-by-reappraisal success interaction, activations in the left dorsomedial prefrontal cortex (dmPFC) and left dorsolateral PFC (dlPFC) were associated with reappraisal success in healthy controls but not depressed adolescents. Depressed adolescents demonstrated reduced connectivity between the left dmPFC and the anterior insula/inferior frontal gyri bilaterally (AI/IFG) and between left dlPFC and left AI/IFG. LIMITATIONS: Our results should be considered exploratory given our less conservative statistical threshold in the group-by-reappraisal interaction. CONCLUSIONS: We find preliminary evidence that depressed adolescents engage cognitive control regions less efficiently than healthy controls, suggesting delayed maturation of regulatory prefrontal cortex regions; more research is needed to determine whether cognitive therapies improve functioning of these regions in depressed youth.