Ventral Striatum Functional Connectivity as a Predictor of Adolescent Depressive Disorder in a Longitudinal Community-Based Sample

Ventral striatal-cingulate resting-state functional connectivity in healthy adolescents relates to later depression symptoms in adulthood

BACKGROUND

Depression is a significant public health concern. Identifying biopsychosocial risk factors for depression is important for developing targeted prevention. Studies have demonstrated that blunted striatal activation during reward processing is a risk factor for depression; however, few have prospectively examined whether adolescent reward-related resting-state functional connectivity (rsFC) predicts depression symptoms in adulthood and how this relates to known risk factors (e.g., childhood trauma).

METHODS

At baseline, 66 adolescents (mean age = 14.7, SD = 1.4, 68 % female) underwent rsFC magnetic resonance imaging and completed the Children's Depression Inventory (CDI). At follow-up (mean time between adolescent scan and adult follow-up = 10.1 years, SD = 1.6, mean adult age = 24.8 years, SD = 1.7), participants completed the Childhood Trauma Questionnaire (CTQ) and Beck Depression Inventory- Second Edition (BDI-2). Average rsFC was calculated between nodes in mesocorticolimbic reward circuitry: ventral striatum (VS), rostral anterior cingulate cortex (rACC), medial orbitofrontal cortex, and ventral tegmental area. Linear regressions assessed associations between rsFC, BDI-2, and CTQ, controlling for adolescent CDI, sex assigned at birth, and scan age (Bonferroni corrected).

RESULTS

Greater childhood trauma was associated with higher adulthood depression symptoms. Stronger VS-rACC rsFC during adolescence was associated with greater depression symptoms in adulthood and greater childhood trauma.

LIMITATIONS

The small sample size, limited depression severity, and seed-based approach are limitations.

CONCLUSIONS

The associations between adolescent striatal-cingulate rsFC and childhood trauma and adult depression symptoms suggest this connectivity may be an early neurobiological risk factor for depression and that early life experience plays an important role. Increased VS-rACC connectivity may represent an over-regulatory response on the striatum, commonly reported in depression, and warrants further investigation.

Exploring causal mechanisms of psychosis risk

Robust epidemiological evidence of risk and protective factors for psychosis is essential to inform preventive interventions. Previous evidence syntheses have classified these risk and protective factors according to their strength of association with psychosis. In this critical review we appraise the distinct and overlapping mechanisms of 25 key environmental risk factors for psychosis, and link these to mechanistic pathways that may contribute to neurochemical alterations hypothesised to underlie psychotic symptoms. We then discuss the implications of our findings for future research, specifically considering interactions between factors, exploring universal and subgroup-specific factors, improving understanding of temporality and risk dynamics, standardising operationalisation and measurement of risk and protective factors, and developing preventive interventions targeting risk and protective factors.

Causal relationship between resting-state networks and depression: a bidirectional two-sample mendelian randomization study

BACKGROUND

Cerebral resting-state networks were suggested to be strongly associated with depressive disorders. However, the causal relationship between cerebral networks and depressive disorders remains controversial. In this study, we aimed to investigate the effect of resting-state networks on depressive disorders using a bidirectional Mendelian randomization (MR) design.

METHODS

Updated summary-level genome-wide association study (GWAS) data correlated with resting-state networks were obtained from a meta-analysis of European-descent GWAS from the Complex Trait Genetics Lab. Depression-related GWAS data were obtained from the FinnGen study involving participants with European ancestry. Resting-state functional magnetic resonance imaging and multiband diffusion imaging of the brain were performed to measure functional and structural connectivity in seven well-known networks. Inverse-variance weighting was used as the primary estimate, whereas the MR-Pleiotropy RESidual Sum and Outliers (PRESSO), MR-Egger, and weighted median were used to detect heterogeneity, sensitivity, and pleiotropy.

RESULTS

In total, 20,928 functional and 20,573 structural connectivity data as well as depression-related GWAS data from 48,847 patients and 225,483 controls were analyzed. Evidence for a causal effect of the structural limbic network on depressive disorders was found in the inverse variance-weighted limbic network (odds ratio, [Formula: see text]; 95% confidence interval, [Formula: see text]; [Formula: see text]), whereas the causal effect of depressive disorders on SC LN was not found(OR=1.0025; CI,1.0005-1.0046; P=0.012). No significant associations between functional connectivity of the resting-state networks and depressive disorders were found in this MR study.

CONCLUSIONS

These results suggest that genetically determined structural connectivity of the limbic network has a causal effect on depressive disorders and may play a critical role in its neuropathology.

An empirical analysis of structural neuroimaging profiles in a staging model of depression

We examine structural brain characteristics across three diagnostic categories: at risk for serious mental illness; first-presenting episode and recurrent major depressive disorder (MDD). We investigate whether the three diagnostic groups display a stepwise pattern of brain changes in the cortico-limbic regions. Integrated clinical and neuroimaging data from three large Canadian studies were pooled (total n = 622 participants, aged 12-66 years). Four clinical profiles were used in the classification of a clinical staging model: healthy comparison individuals with no history of depression (HC, n = 240), individuals at high risk for serious mental illness due to the presence of subclinical symptoms (SC, n = 80), first-episode depression (FD, n = 82), and participants with recurrent MDD in a current major depressive episode (RD, n = 220). Whole-brain volumetric measurements were extracted with FreeSurfer 7.1 and examined using three different types of analyses. Hippocampal volume decrease and cortico-limbic thinning were the most informative features for the RD vs HC comparisons. FD vs HC revealed that FD participants were characterized by a focal decrease in cortical thickness and global enlargement in amygdala volumes. Greater total amygdala volumes were significantly associated with earlier onset of illness in the FD but not the RD group. We did not confirm the construct validity of a tested clinical staging model, as a differential pattern of brain alterations was identified across the three diagnostic groups that did not parallel a stepwise clinical staging approach. The pathological processes during early stages of the illness may fundamentally differ from those that occur at later stages with clinical progression.

Abnormal effective connectivity of reward network in first-episode schizophrenia with auditory verbal hallucinations

OBJECTIVE

Auditory verbal hallucinations (AVHs) in schizophrenia is proved to be associated with dysfunction of mesolimbic-cortical circuits, especially during abnormal salient and internal verbal resource monitoring processing procedures. However, the information flow among areas involved in coordinated interaction implicated the pathophysiology of AVHs remains unclear.

METHODS

We used spectral dynamic causal modeling (DCM) to quantify connections among eight critical hubs of reward network in 86 first-episode drug-naïve schizophrenia patients with AVHs (AVH), 93 patients without AVHs (NAVH), and 88 matched normal controls (NC) using resting-state functional magnetic resonance imaging. Group-level connection coefficients, between-group differences and correlation analysis between image measures and symptoms were performed.

RESULT

DCM revealed weaker effective connectivity (EC) from right ventral striatum (RVS) to ventral tegmental area (VTA) in AVH compared to NAVH. AVH showed stronger EC from left anterior insula (AI) to RVS, stronger EC from RVS to anterior cingulate cortex (ACC), and stronger EC from VTA to posterior cingulate cortex (PCC) compared to NC. The correlation analysis results were mostly visible in the negative correlation between EC from right AI to ACC and positive sub-score, P1 sub-score, and P3 sub-score of PNASS in group-level.

CONCLUSION

These findings suggest that neural causal interactions between the reward network associated with AVHs are disrupted, expanding the evidence for potential neurobiological mechanisms of AVHs. Particularly, dopamine-dependent salience attribution and top-down monitoring impairments and compensatory effects of enhanced excitatory afferents to ACC, which may provide evidence for a therapeutic target based on direct in vivo of AVHs in schizophrenia.

Functional Connectivity of the Nucleus Accumbens across Variants of Callous-Unemotional Traits: A Resting-State fMRI Study in Children and Adolescents

A large body of literature suggests that the primary (high callousness-unemotional traits [CU] and low anxiety) and secondary (high CU traits and anxiety) variants of psychopathy significantly differ in terms of their clinical profiles. However, little is known about their neurobiological differences. While few studies showed that variants differ in brain activity during fear processing, it remains unknown whether they also show atypical functioning in motivational and reward system. Latent Profile Analysis (LPA) was conducted on a large sample of adolescents (n = 1416) to identify variants based on their levels of callousness and anxiety. Seed-to-voxel connectivity analysis was subsequently performed on resting-state fMRI data to compare connectivity patterns of the nucleus accumbens across subgroups. LPA failed to identify the primary variant when using total score of CU traits. Using a family-wise cluster correction, groups did not differ on functional connectivity. However, at an uncorrected threshold the secondary variant showed distinct functional connectivity between the nucleus accumbens and posterior insula, lateral orbitofrontal cortex, supplementary motor area, and parietal regions. Secondary LPA analysis using only the callousness subscale successfully distinguish both variants. Group differences replicated results of deficits in functional connectivity between the nucleus accumbens and posterior insula and supplementary motor area, but additionally showed effect in the superior temporal gyrus which was specific to the primary variant. The current study supports the importance of examining the neurobiological markers across subgroups of adolescents at risk for conduct problems to precise our understanding of this heterogeneous population.

Functional Abnormality of the Reward System in Depressed Adolescents and Young Adults with and without Suicidal Behavior

OBJECTIVE

To identify local and functional connectivity abnormalities in the brain's reward network in depressed adolescents and young adults with and without suicidal behavior.

METHODS

Magnetic resonance imaging data were obtained from 41 major depressive disorder (MDD) patients with suicidal behavior (sMDD, males/females: 12/29), 44 MDD patients without suicidal behavior (nMDD, males/females: 13/32), and 52 healthy controls (HCs, males/females: 17/35). The Young Mania Scale, Hamilton Depression Scale, Columbia Suicide Scale, and Scale for Suicide Ideation were used to evaluate emotional state and suicidal ideation and behaviors. The amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo) and functional connectivity of 11 regions of interest (ROIs) in the reward network were determined.

RESULTS

ALFF values in the vmPFC of the nMDD group were significantly lower than those in the HC group (p = 0.031). The ReHo values of the nMDD group were lower in the lVS but higher in the vmPFC than those of the HC group (P = 0.018 and 0.025, respectively). Functional connectivity of the AC with the vmPFC, lVS, rVS, and vmPFC was increased in the sMDD group compared with that in the nMDD group (P = 0.038, 0.034, 0.006, respectively).

CONCLUSION

Local and functional connectivity abnormalities in the reward network were found in the MDD groups. However, increased functional connectivity was found in only the sMDD group.

Altered neural activity in the reward-related circuit associated with anhedonia in mild to moderate Major Depressive Disorder

BACKGROUND

Anhedonia is a significant predictor of disease progression and treatment outcomes in Major Depressive Disorder (MDD), linked to reward network dysfunctions. However, understanding of its underlying neural mechanisms remains limited. This study aimed to investigate the brain functional mechanisms underlying MDD with anhedonia using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

The Snaith-Hamilton Pleasure Scale (SHAPS) was used to evaluation MDD with anhedonia (anMDD) and non-anhedonia MDD (non-anMDD). Forty-eight patients with anMDD, Forty-four patients with non-anMDD, and Fifty healthy controls (HCs) were enrolled for the fMRI scans. A seed-based functional connectivity (FC) method was employed to explore reward network abnormalities.

RESULTS

anMDD patients exhibited lower FC values in Ventral Striatum (VS), right lateral Ventral Tegmental Area (VTA_R), left Thalamus (THA_L), and higher FC values in Ventromedial Prefrontal Cortex (vmPFC), left Anterior Insula (AI_L), and Presupplementary Motor Area (Pre-SMA) compared to HCs. Comparing anMDD to non-anMDD, significant differences were observed in FC values of VS, vmPFC, Pre-SMA, and THA_L regions. Correlation analysis revealed positive correlations between FC values of VS_R and NAc_R, as well as THA_L and Cerebellum_Crus1_L, with SHAPS scores. Negative correlations were observed between FC values of Pre-SMA and the right caudate, and between vmPFC and Frontal_Mid_Orb_L, and SHAPS scores.

CONCLUSION

Both anMDD and non-anMDD groups demonstrated abnormal FCs in the reward network. These findings indicate distinct roles of reward-related circuits in the two subtypes, contributing to a refined understanding of depression phenotypes and potential directions for targeted interventions.

Effect of Tai Chi on Young Adults with Subthreshold Depression via a Stress-Reward Complex: A Randomized Controlled Trial

BACKGROUND

Subthreshold depression is a highly prevalent mood disorder in young adults. Mind-body exercises, such as Tai Chi, have been adopted as interventions for clinical depressive symptoms. However, the possible effect and underlying mechanism of Tai Chi on subthreshold depression of young individuals remain unclear. This randomized controlled study aimed to evaluate the effects of Tai Chi training and tested the combined stress and reward circuitry model for subthreshold depression.

RESULTS

A total of 103 participants completed this trial, with 49 in the 12-week 24-style Tai Chi group and 54 participants in control group. Our results showed significantly lower scores on depressive symptoms (P = 0.002) and anxiety symptoms (P = 0.009) and higher scores on quality of life (P = 0.002) after Tai Chi training. There were significant reductions in salivary cortisol levels (P = 0.007) and putamen gray matter volume (P < 0.001) in the Tai Chi group. The changes in cortisol levels and putamen gray matter volume had direct (bootstrapping confidence interval [- 0.91, - 0.11]) and indirect effects (bootstrapping confidence interval [- 0.65, - 0.19]) on the changes induced by Tai Chi training on depressive symptoms, respectively.

CONCLUSION

The stress-reward complex results indicated an interaction between lowering stress levels and increasing reward circuitry activity associated with the alleviation of depressive symptoms among participants. The 12-week Tai Chi training was effective in improving the symptoms and quality of life of young adults with subthreshold depression. Trial Registration Chinese Registry of Clinical Trials (Registration Number: ChiCTR1900028289, Registered December 12, 2019).

Use of mobile technology to identify behavioral mechanisms linked to mental health outcomes in Kenya: protocol for development and validation of a predictive model

OBJECTIVE

This study proposes to identify and validate weighted sensor stream signatures that predict near-term risk of a major depressive episode and future mood among healthcare workers in Kenya.

APPROACH

The study will deploy a mobile application (app) platform and use novel data science analytic approaches (Artificial Intelligence and Machine Learning) to identifying predictors of mental health disorders among 500 randomly sampled healthcare workers from five healthcare facilities in Nairobi, Kenya.

EXPECTATION

This study will lay the basis for creating agile and scalable systems for rapid diagnostics that could inform precise interventions for mitigating depression and ensure a healthy, resilient healthcare workforce to develop sustainable economic growth in Kenya, East Africa, and ultimately neighboring countries in sub-Saharan Africa. This protocol paper provides an opportunity to share the planned study implementation methods and approaches.

CONCLUSION

A mobile technology platform that is scalable and can be used to understand and improve mental health outcomes is of critical importance.

Neural substrates for dissociation of cognition inhibition in autogenous- and reactive-type obsessive-compulsive disorder

BACKGROUND

The taxonomy of autogenous- and reactive-type obsessive-compulsive disorder (OCD) (AO vs. RO) is one of the most valid subtyping approaches to the heterogeneity of OCD. The present study aimed to seek evidence of neural substrates supporting the dissociation of cognition inhibition in AO and RO which was revealed by our previous behavioral and electrophysiological work.

METHODS

A total of 165 patients with OCD (86 AO versus 79 RO), and 79 healthy controls (HC) underwent resting-state functional magnetic resonance imaging scans. Within-network connectivity, node strength, and edge-wise functional connectivity (FC) in cognition and response inhibition networks were calculated. Results from 3 cognition and 2 response inhibition network atlases were compared to confirm the robustness of the findings.

RESULTS

Both AO and RO showed lower within-network connectivity in response inhibition networks, while lower within cognition inhibition network connectivity was only detected in AO. Besides shared weaker node strength in the anterior insula (AI), anterior cingulate cortex (ACC), and supplementary motor area (SMA), AO had a broader range of nodes within cognition inhibition networks exhibiting weaker strength, including nodes in right inferior frontal gyrus (IFG), left parietal and occipital regions. Decreased FC of left AI-CC, left IFG-ACC, and frontal-parietal regions in cognition inhibition networks were found in AO.

CONCLUSIONS

Findings indicate that unlike deficits in connectivity within response inhibition networks which may reflect a common pathology in AO and RO, deficits in connectivity within cognition inhibition networks were more pronounced in AO. These findings strengthen our insight into the heterogeneity in OCD.

Stress to inflammation and anhedonia: Mechanistic insights from preclinical and clinical models

Anhedonia, as evidenced by impaired pleasurable response to reward, reduced reward motivation, and/or deficits in reward-related learning, is a common feature of depression. Such deficits in reward processing are also an important clinical target as a risk factor for depression onset. Unfortunately, reward-related deficits remain difficult to treat. To address this gap and inform the development of effective prevention and treatment strategies, it is critical to understand the mechanisms that drive impairments in reward function. Stress-induced inflammation is a plausible mechanism of reward deficits. The purpose of this paper is to review evidence for two components of this psychobiological pathway: 1) the effects of stress on reward function; and 2) the effects of inflammation on reward function. Within these two areas, we draw upon preclinical and clinical models, distinguish between acute and chronic effects of stress and inflammation, and address specific domains of reward dysregulation. By addressing these contextual factors, the review reveals a nuanced literature which might be targeted for additional scientific inquiry to inform the development of precise interventions.

Apathy in melancholic depression and abnormal neural activity within the reward-related circuit

Major depressive disorder is a heterogeneous syndrome, of which the most common subtype is melancholic depression (MEL). Previous studies have indicated that anhedonia is frequently a cardinal feature in MEL. As a common syndrome of motivational deficit, anhedonia is closely associated with dysfunction in reward-related networks. However, little is currently known about apathy, another syndrome of motivational deficits, and the underlying neural mechanisms in MEL and non-melancholic depression (NMEL). Herein, the Apathy Evaluation Scale (AES) was used to compare apathy between MEL and NMEL. On the basis of resting-state functional magnetic resonance imaging, functional connectivity strength (FCS) and seed-based functional connectivity (FC) were calculated within reward-related networks and compared among 43 patients with MEL, 30 patients with NMEL, and 35 healthy controls. Patients with MEL had higher AES scores than those with NMEL (t = -2.20, P = 0.03). Relative to NMEL, MEL was associated with greater FCS (t = 4.27, P < 0.001) in the left ventral striatum (VS), and greater FC of the VS with the ventral medial prefrontal cortex (t = 5.03, P < 0.001) and dorsolateral prefrontal cortex (t = 3.18, P = 0.005). Taken together the results indicate that reward-related networks may play diverse pathophysiological roles in MEL and NMEL, thus providing potential directions for future interventions in the treatment of various depression subtypes.

Frontolimbic Network Topology Associated With Risk and Presence of Depression in Adolescents: A Study Using a Composite Risk Score in Brazil

BACKGROUND

There have been significant challenges in understanding functional brain connectivity associated with adolescent depression, including the need for a more comprehensive approach to defining risk, the lack of representation of participants from low- and middle-income countries, and the need for network-based approaches to model connectivity. The current study aimed to address these challenges by examining resting-state functional connectivity of frontolimbic circuitry associated with the risk and presence of depression in adolescents in Brazil.

METHODS

Adolescents in Brazil ages 14 to 16 years were classified into low-risk, high-risk, and depressed groups using a clinical assessment and composite risk score that integrates 11 sociodemographic risk variables. After excluding participants with excessive head movement, resting-state functional magnetic resonance imaging data of 126 adolescents were analyzed. We compared group differences in frontolimbic network connectivity using region of interest-to-region of interest, graph theory, and seed-based connectivity analyses. Associations between self-reported depressive symptoms and brain connectivity were also explored.

RESULTS

Adolescents with depression showed greater dorsal anterior cingulate cortex (ACC) connectivity with the orbitofrontal cortex compared with the 2 risk groups and greater dorsal ACC global efficiency than the low-risk group. Adolescents with depression also showed reduced local efficiency and a lower clustering coefficient of the subgenual ACC compared with the 2 risk groups. The high-risk group also showed a lower subgenual ACC clustering coefficient relative to the low-risk group.

CONCLUSIONS

These findings highlight altered connectivity and topology of the ACC within frontolimbic circuitry as potential neural correlates and risk factors of developing depression in adolescents in Brazil. This study broadens our understanding of the neural connectivity associated with adolescent depression in a global context.

Depression in mothers at childhood: Direct and indirect association with problematic gaming in late adolescence/young adulthood

OBJECTIVES

Little is known about the relationship between depression in mothers and problematic gaming in their children. Therefore, we aimed to investigate the potential role of mothers' depression in childhood as a risk factor for problematic gaming in their offspring in late adolescence/young adulthood.

METHODS

We assessed data from 1557 participants on three waves (T0 collected in 2010/2011, T1 in 2013/2014, and T2 in 2018/2019) of a large Brazilian school-based cohort. Mother's depression at T0 was tested as a predictor of problematic gaming at T2 in a logistic regression model. In mediation analyses, we individually assessed internalizing or externalizing disorders at T1 as mediators in this association, with participants' sex being tested as a moderator in both models. Inverse probability weights were used to account for sample attrition at T2. All models were adjusted for maternal and participant-related covariates.

RESULTS

Mother's depression at T0 was significantly associated with problematic gaming at T2 (OR = 2.09, p < 0.001) even after adjusting for multiple confounding factors. The presence of any internalizing disorder at T1 was a partial mediator of this relationship, accounting for 8.18% (p = 0.032) of the total effect, while the presence of any externalizing disorder at T1 was not a significant mediator. Participants' sex was not a significant moderator in mediation models.

CONCLUSIONS

These findings suggest mother's depression in childhood as a risk factor for problematic gaming in later developmental stages, which may be partially mediated by internalizing psychopathology.

Polygenic risk score for attention-deficit/hyperactivity disorder and brain functional networks segregation in a community-based sample

Neuroimaging studies suggest that brain development mechanisms might explain at least some behavioural and cognitive attention-deficit/hyperactivity disorder (ADHD) symptoms. However, the putative mechanisms by which genetic susceptibility factors influence clinical features via alterations of brain development remain largely unknown. Here, we set out to integrate genomics and connectomics tools by investigating the associations between an ADHD polygenic risk score (ADHD-PRS) and functional segregation of large-scale brain networks. With this aim, ADHD symptoms score, genetic and rs-fMRI (resting-state functional magnetic resonance image) data obtained in a longitudinal community-based cohort of 227 children and adolescents were analysed. A follow-up was conducted approximately 3 years after the baseline, with rs-fMRI scanning and ADHD likelihood assessment in both stages. We hypothesised a negative correlation between probable ADHD and the segregation of networks involved in executive functions, and a positive correlation with the default-mode network (DMN). Our findings suggest that ADHD-PRS is correlated with ADHD at baseline, but not at follow-up. Despite not surviving for multiple comparison correction, we found significant correlations between ADHD-PRS and segregation of cingulo-opercular networks and DMN at baseline. ADHD-PRS was negatively correlated with the segregation level of cingulo-opercular networks but positively correlated with the DMN segregation. These directions of associations corroborate the proposed counter-balanced role of attentional networks and DMN in attentional processes. However, the association between ADHD-PRS and brain networks functional segregation was not found at follow-up. Our results provide evidence for specific influences of genetic factors on development of attentional networks and DMN. We found significant correlations between polygenic risk score for ADHD (ADHD-PRS) and segregation of cingulo-opercular networks and default-mode network (DMN) at baseline. ADHD-PRS was negatively correlated with the segregation level of cingulo-opercular networks but positively correlated with the DMN segregation.

Use of Mobile Technology to Identify Behavioral Mechanisms Linked to Mental Health Outcomes in Kenya: Protocol for Development and Validation of a Predictive Model

Objective: This study proposes to identify and validate weighted sensor stream signatures that predict near-term risk of a major depressive episode and future mood among healthcare workers in Kenya. Approach: The study will deploy a mobile app platform and use novel data science analytic approaches (Artificial Intelligence and Machine Learning) to identifying predictors of mental health disorders among 500 randomly sampled healthcare workers from five healthcare facilities in Nairobi, Kenya. Expectation: This study will lay the basis for creating agile and scalable systems for rapid diagnostics that could inform precise interventions for mitigating depression and ensure a healthy, resilient healthcare workforce to develop sustainable economic growth in Kenya, East Africa, and ultimately neighboring countries in sub-Saharan Africa. This protocol paper provides an opportunity to share the planned study implementation methods and approaches. Conclusion : A mobile technology platform that is scalable and can be used to understand and improve mental health outcomes is of critical importance.

Understanding the benefits of extrinsic emotion regulation in depression

Depression is a serious psychiatric illness that negatively affects people's feelings, thoughts, and actions. Providing emotion regulation support to others, also termed Extrinsic Emotion Regulation (EER), reduces depressive symptoms such as perseverative thinking and negative mood. In this conceptual review paper, we argue that EER may be especially beneficial for individuals with depression because it enhances the cognitive and affective processes known to be impaired in depression. Behavioral studies have shown that EER recruits processes related to cognitive empathy, intrinsic emotion regulation (IER), and reward, all impaired in depression. Neuroimaging data support these findings by showing that EER recruits brain regions related to these three processes, such as the ventrolateral prefrontal cortex which is associated with IER, the ventral striatum, which is associated with reward-related processes, and medial frontal regions related to cognitive empathy. This conceptual review paper sheds light on the mechanisms underlying the effectiveness of EER for individuals with depression and therefore offers novel avenues for treatment.

Prolonged Longitudinal Transcutaneous Auricular Vagus Nerve Stimulation Effect on Striatal Functional Connectivity in Patients with Major Depressive Disorder

BACKGROUND

Transcutaneous auricular vagus nerve stimulation (taVNS) is effective for treating major depressive disorder (MDD). We aimed to explore the modulating effect of prolonged longitudinal taVNS on the striatal subregions' functional connectivity (FC) in MDD patients.

METHODS

Sixteen MDD patients were enrolled and treated with taVNS for 8 weeks. Sixteen healthy control subjects (HCs) were recruited without intervention. The resting-state FC (rsFC) based on striatal subregion seed points and the Hamilton Depression Scale (HAMD) were evaluated in the MDD patients and HCs at baseline and after 8 weeks. A two-way ANCOVA test was performed on each rsFC metric to obtain the (group-by-time) interactions.

RESULTS

The rsFC values between the left ventral caudate (vCa) and right ventral prefrontal cortex (vPFC), and between the right nucleus accumbens (NAc) and right dorsal medial prefrontal cortex (dmPFC) and ventrolateral prefrontal cortex (vlPFC) are lower in the MDD patients compared to the HCs at baseline, and increase following taVNS; the rsFC values between the left vCa and right, superior occipital gyrus (SOG), and between the left dorsal caudate (dCa) and right cuneus are higher in MDD patients and decrease following taVNS.

CONCLUSIONS

Prolonged longitudinal taVNS can modulate the striatum rsFC with the prefrontal cortex, occipital cortex, temporal cortex, and intra-striatum, and these changes partly underlie any symptomatic improvements. The results indicate that prolonged longitudinal taVNS may produce beneficial treatment effects by modulating the cortical striatum circuitry in patients with MDD.

Multi-level predictors of depression symptoms in the Adolescent Brain Cognitive Development (ABCD) study

BACKGROUND

While identifying risk factors for adolescent depression is critical for early prevention and intervention, most studies have sought to understand the role of isolated factors rather than across a broad set of factors. Here, we sought to examine multi-level factors that maximize the prediction of depression symptoms in US children participating in the Adolescent Brain and Cognitive Development (ABCD) study.

METHODS

A total of 7,995 participants from ABCD (version 3.0 release) provided complete data at baseline and 1-year follow-up data. Depression symptoms were measured with the Child Behavior Checklist. Predictive features included child demographic, environmental, and structural and resting-state fMRI variables, parental depression history and demographic characteristics. We used linear (elastic net regression, EN) and non-linear (gradient-boosted trees, GBT) predictive models to identify which set of features maximized prediction of depression symptoms at baseline and, separately, at 1-year follow-up.

RESULTS

Both linear and non-linear models achieved comparable results for predicting baseline (EN: MAE = 3.757; R2  = 0.156; GBT: MAE = 3.761; R2  = 0.147) and 1-year follow-up (EN: MAE = 4.255; R2  = 0.103; GBT: MAE = 4.262; R2  = 0.089) depression. Parental history of depression, greater family conflict, and shorter child sleep duration were among the top predictors of concurrent and future child depression symptoms across both models. Although resting-state fMRI features were relatively weaker predictors, functional connectivity of the caudate was consistently the strongest neural feature associated with depression symptoms at both timepoints.

CONCLUSIONS

Consistent with prior research, parental mental health, family environment, and child sleep quality are important risk factors for youth depression. Functional connectivity of the caudate is a relatively weaker predictor of depression symptoms but may represent a biomarker for depression risk.

Smaller putamen volumes are associated with greater problems in external emotional regulation in depressed adolescents with nonsuicidal self-injury

The functions of nonsuicidal self-injury (NSSI) consist of social and emotional aspects (Social influence, Sensation seeking, Internal and External emotion regulation). Previous studies have indicated that dysfunction in reward-related brain structures especially the striatum might drive this habitual behavior. However, no studies to date have investigated the associations between striatum and different functions for adolescents engaging in NSSI behaviors. Here, we recruited 35 depressed adolescents with recent NSSI behaviors and 36 healthy controls and acquired structural brain images, depressive symptoms, social, academic and family environments assessments, in addition to NSSI functions in patients only. Subcortical volumes and cortical thickness were estimated with FreeSurfer. Mixed linear regressions were performed to examine associations between striatal structures (caudate, putamen, nucleus accumbens, pallidum) and NSSI functions, with age, sex, total intracranial volume, hemisphere and depression severity included as covariates. Effect of environmental factors and potential associations with cortical thickness and other subcortical volumes were also tested. We found that, among the four functions, external emotional regulation represented the main function for NSSI engagement. Increased external emotion regulation was significantly associated with smaller putamen volume. No environmental factors biased the association with putamen. No associations with other cortical or subcortical regions were observed. Our findings suggested that smaller putamen might be a biomarker of NSSI engagement for depressed adolescents when they regulated frustrated or angry emotions. The results have potentially clinical implications in early identification and brain intervention of NSSI in youth.

Functional Connectivity of the Nucleus Accumbens and Changes in Appetite in Patients With Depression

Importance

Major depressive disorder (MDD) is characterized by a substantial burden on health, including changes in appetite and body weight. Heterogeneity of depressive symptoms has hampered the identification of biomarkers that robustly generalize to most patients, thus calling for symptom-based mapping.

Objective

To define the functional architecture of the reward circuit subserving increases vs decreases in appetite and body weight in patients with MDD by specifying their contributions and influence on disease biomarkers using resting-state functional connectivity (FC).

Design, Setting, and Participants

In this case-control study, functional magnetic resonance imaging (fMRI) data were taken from the Marburg-Münster FOR 2107 Affective Disorder Cohort Study (MACS), collected between September 2014 and November 2016. Cross-sectional data of patients with MDD (n = 407) and healthy control participants (n = 400) were analyzed from March 2018 to June 2022.

Main Outcomes and Measures

Changes in appetite during the depressive episode and their association with FC were examined using fMRI. By taking the nucleus accumbens (NAcc) as seed of the reward circuit, associations with opposing changes in appetite were mapped, and a sparse symptom-specific elastic-net model was built with 10-fold cross-validation.

Results

Among 407 patients with MDD, 249 (61.2%) were women, and the mean (SD) age was 36.79 (13.4) years. Reduced NAcc-based FC to the ventromedial prefrontal cortex (vmPFC) and the hippocampus was associated with reduced appetite (vmPFC: bootstrap r = 0.13; 95% CI, 0.02-0.23; hippocampus: bootstrap r = 0.15; 95% CI, 0.05-0.26). In contrast, reduced NAcc-based FC to the insular ingestive cortex was associated with increased appetite (bootstrap r = -0.14; 95% CI, -0.24 to -0.04). Critically, the cross-validated elastic-net model reflected changes in appetite based on NAcc FC and explained variance increased with increasing symptom severity (all patients: bootstrap r = 0.24; 95% CI, 0.16-0.31; patients with Beck Depression Inventory score of 28 or greater: bootstrap r = 0.42; 95% CI, 0.25-0.58). In contrast, NAcc FC did not classify diagnosis (MDD vs healthy control).

Conclusions and Relevance

In this study, NAcc-based FC reflected important individual differences in appetite and body weight in patients with depression that can be leveraged for personalized prediction. However, classification of diagnosis using NAcc-based FC did not exceed chance levels. Such symptom-specific associations emphasize the need to map biomarkers onto more confined facets of psychopathology to improve the classification and treatment of MDD.

Frontostriatal circuitry as a target for fMRI-based neurofeedback interventions: A systematic review

Dysregulated frontostriatal circuitries are viewed as a common target for the treatment of aberrant behaviors in various psychiatric and neurological disorders. Accordingly, experimental neurofeedback paradigms have been applied to modify the frontostriatal circuitry. The human frontostriatal circuitry is topographically and functionally organized into the “limbic,” the “associative,” and the “motor” subsystems underlying a variety of affective, cognitive, and motor functions. We conducted a systematic review of the literature regarding functional magnetic resonance imaging-based neurofeedback studies that targeted brain activations within the frontostriatal circuitry. Seventy-nine published studies were included in our survey. We assessed the efficacy of these studies in terms of imaging findings of neurofeedback intervention as well as behavioral and clinical outcomes. Furthermore, we evaluated whether the neurofeedback targets of the studies could be assigned to the identifiable frontostriatal subsystems. The majority of studies that targeted frontostriatal circuitry functions focused on the anterior cingulate cortex, the dorsolateral prefrontal cortex, and the supplementary motor area. Only a few studies (n = 14) targeted the connectivity of the frontostriatal regions. However, post-hoc analyses of connectivity changes were reported in more cases (n = 32). Neurofeedback has been frequently used to modify brain activations within the frontostriatal circuitry. Given the regulatory mechanisms within the closed loop of the frontostriatal circuitry, the connectivity-based neurofeedback paradigms should be primarily considered for modifications of this system. The anatomical and functional organization of the frontostriatal system needs to be considered in decisions pertaining to the neurofeedback targets.

Functional neuroimaging in psychiatry and the case for failing better

Psychiatric disorders encompass complex aberrations of cognition and affect and are among the most debilitating and poorly understood of any medical condition. Current treatments rely primarily on interventions that target brain function (drugs) or learning processes (psychotherapy). A mechanistic understanding of how these interventions mediate their therapeutic effects remains elusive. From the early 1990s, non-invasive functional neuroimaging, coupled with parallel developments in the cognitive neurosciences, seemed to signal a new era of neurobiologically grounded diagnosis and treatment in psychiatry. Yet, despite three decades of intense neuroimaging research, we still lack a neurobiological account for any psychiatric condition. Likewise, functional neuroimaging plays no role in clinical decision making. Here, we offer a critical commentary on this impasse and suggest how the field might fare better and deliver impactful neurobiological insights.

Prediction of the trajectories of depressive symptoms among children in the adolescent brain cognitive development (ABCD) study using machine learning approach

BACKGROUND

Depression often first emerges during adolescence and evidence shows that the long-term patterns of depressive symptoms over time are heterogeneous. It is meaningful to predict the trajectory of depressive symptoms in adolescents to find early intervention targets.

METHODS

Based on the Adolescent Brain Cognitive Development Study, we included 4962 participants aged 9-10 who were followed-up for 2 years. Trajectories of depressive symptoms were identified by Latent Class Growth Analyses (LCGA). Four types of machine learning models were built to predict the identified trajectories and to obtain variables with predictive value based on the best performance model.

RESULTS

Of all participants, 536 (10.80%) were classified as increasing, 269 (5.42%) as persistently high, 433 (8.73%) as decreasing, and 3724 (75.05%) as persistently low by LCGA. Gradient Boosting Machine (GBM) model got the highest discriminant performance. Sleep quality, parental emotional state and family financial adversities were the most important predictors and three resting state functional magnetic resonance imaging functional connectivity data were also helpful to distinguish trajectories.

LIMITATION

We only have depressive symptom scores at three time points. Some valuable predictors are not specific to depression. External validation is an important next step. These predictors should not be interpreted as etiology and some variables were reported by parents/caregivers.

CONCLUSION

Using GBM combined with baseline characteristics, the trajectories of depressive symptoms with two years among adolescents aged 9-10 years can be well predicted, which might further facilitate the identification of adolescents at high risk of depressive symptoms and development of effective early interventions.

Adolescent depression and resting-state fMRI brain networks: a scoping review of longitudinal studies

The neurobiological factors associated with the emergence of major depressive disorder (MDD) in adolescence are still unclear. Previous cross-sectional studies have documented aberrant connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) networks. However, whether these findings precede MDD onset has not been established. This scoping review mapped key methodological aspects and main findings of longitudinal rs-fMRI studies of MDD in adolescence. Three sets of neuroimaging methods to analyze rs-fMRI data were identified: seed-based analysis, independent component analysis, and network-based approaches. Main findings involved aberrant connectivity within and between the default mode network (DMN), the cognitive control network (CCN), and the salience network (SN). Accordingly, we utilized Menon's (2011) triple-network model for neuropsychiatric disorders to summarize key results. Adolescent MDD was associated with hyperconnectivity within the SN and between DMN and SN, as well as hypoconectivity within the CCN. These findings suggested that dysfunctional connectivity among the three main large-scale brain networks preceded MDD onset. However, there was high heterogeneity in neuroimaging methods and sampling procedures, which may limit comparisons between studies. Future studies should consider some level of harmonization for clinical instruments and neuroimaging methods.

Toward a Better Understanding of the Mechanisms and Pathophysiology of Anhedonia: Are We Ready for Translation?

Anhedonia-the loss of pleasure or lack of reactivity to pleasurable stimuli-remains a formidable treatment challenge across neuropsychiatric disorders. In major depressive disorder, anhedonia has been linked to poor disease course, worse response to psychological, pharmacological, and neurostimulation treatments, and increased suicide risk. Moreover, although some neural abnormalities linked to anhedonia normalize after successful treatment, several persist-for example, blunted activation of the ventral striatum to reward-related cues and reduced functional connectivity involving the ventral striatum. Critically, some of these abnormalities have also been identified in unaffected, never-depressed children of parents with major depressive disorder and have been found to prospectively predict the first onset of major depression. Thus, neural abnormalities linked to anhedonia may be promising targets for prevention. Despite increased appreciation of the clinical importance of anhedonia and its underlying neural mechanisms, important gaps remain. In this overview, the author first summarizes the extant knowledge about the pathophysiology of anhedonia, which may provide a road map toward novel treatment and prevention strategies, and then highlights several priorities to facilitate clinically meaningful breakthroughs. These include a need for 1) appropriately controlled clinical trials, especially those embracing an experimental therapeutics approach to probe target engagement; 2) novel preclinical models relevant to anhedonia, with stronger translational value; and 3) clinical scales that incorporate neuroscientific advances in our understanding of anhedonia. The author concludes by highlighting important future directions, emphasizing the need for an integrated, collaborative, cross-species, and multilevel approach to tackling anhedonic phenotypes.

Longitudinal Trajectory of the Link Between Ventral Striatum and Depression in Adolescence

OBJECTIVE

Research in adolescent depression has found aberrant intrinsic functional connectivity (iFC) among the ventral striatum (VS) and several brain regions implicated in reward processing. The present study probes this question by taking advantage of the availability of data from a large youth cohort, the IMAGEN Consortium.

METHODS

iFC data from 303 adolescents (48% of them female) were used to examine associations of VS connectivity at baseline (at age 14) with depressive disorders at baseline and at 2-year (N=250) and 4-year (N=219) follow-ups. Eleven regions of interest, key nodes of the reward system, were used to probe the reward network and calculate the connectivity strength of the VS within this network (VS connectivityrw). The main analyses assessed associations of VS connectivityrw with depressive disorders, anhedonia, and low mood using logistic regression. Autoregressive models accounting for carryover effects over time were conducted to further evaluate these brain-behavior associations.

RESULTS

Higher right VS connectivityrw was associated with higher probability of depressive disorders at baseline (odds ratio=2.65, 95% CI=1.40, 5.05). This finding was confirmed in the autoregressive model, adjusting for carryover effects of the depressive disorders across the three time points. VS connectivityrw was not predictive of depressive disorders at follow-up assessments. Longitudinal associations between VS connectivityrw and anhedonia emerged in the structural equation model: left VS connectivityrw was associated with anhedonia at 2 years (odds ratio=2.20, 95% CI=1.54, 3.14), and right VS connectivityrw was linked to anhedonia at 4 years (odds ratio=1.87, 95% CI=1.09, 3.21). VS connectivityrw did not predict low mood at any time point in the structural equation model.

CONCLUSIONS

The connectivity strength of the VS within the reward network showed distinct patterns of association with depressive disorders and anhedonia from mid to late adolescence, suggesting that the role of this circuitry in depression changes with age. This study replicates, in an independent sample, the association between the VS and depression previously reported in younger adolescents. The findings suggest a role of VS connectivityrw in anhedonia but not in low mood.

Computational modelling of the speed-accuracy tradeoff: No evidence for an association with depression symptomatology

Successful decision making often requires finding the right balance between the speed and accuracy of responding: Emphasising speed can lead to error-prone performance, yet emphasising accuracy leads to a slowing of performance. Such speed-accuracy tradeoffs (SATs) therefore require establishing appropriate response settings to optimise performance in response to changing environmental demands. Such strategic adaptation of response settings relies on the striatum component of the basal ganglia, an area implicated in depression. The current study explored the association between depression symptomatology and SAT performance. Two experiments presented participants with an SAT paradigm embedded within a simple decision-making task, together with measures of depression symptomatology. Experiment 1 (N = 349) was correlational, whereas Experiment 2 was a two-phase experiment where participants (N = 501) were first pre-screened on depression symptomatology and extreme-low and extreme-high responders (total N = 91) were invited to Phase 2. Behavioural data were modelled with a drift diffusion model. Behavioural data and associated diffusion modelling showed large and robust SAT effects. Emphasising accuracy led to an increase in boundary separation, an increase in drift rate, and an increase in non-decision time. However, the magnitude of the changes of these parameters with SAT instructions was not associated with measures of depression symptomatology. The results suggest that the strategic adaptation of response settings in response to environmental changes in speed-accuracy instructions does not appear to be associated with depression symptomatology.

Shared and specific patterns of dynamic functional connectivity variability of striato-cortical circuitry in unmedicated bipolar and major depressive disorders

BACKGROUND

Accumulating studies have found structural and functional abnormalities of the striatum in bipolar disorder (BD) and major depressive disorder (MDD). However, changes in intrinsic brain functional connectivity dynamics of striato-cortical circuitry have not been investigated in BD and MDD. This study aimed to investigate the shared and specific patterns of dynamic functional connectivity (dFC) variability of striato-cortical circuitry in BD and MDD.

METHODS

Brain resting-state functional magnetic resonance imaging data were acquired from 128 patients with unmedicated BD II (current episode depressed), 140 patients with unmedicated MDD, and 132 healthy controls (HCs). Six pairs of striatum seed regions were selected: the ventral striatum inferior (VSi) and the ventral striatum superior (VSs), the dorsal-caudal putamen (DCP), the dorsal-rostral putamen (DRP), and the dorsal caudate and the ventral-rostral putamen (VRP). The sliding-window analysis was used to evaluate dFC for each seed.

RESULTS

Both BD II and MDD exhibited increased dFC variability between the left DRP and the left supplementary motor area, and between the right VRP and the right inferior parietal lobule. The BD II had specific increased dFC variability between the right DCP and the left precentral gyrus compared with MDD and HCs. The MDD had increased dFC variability between the left VSi and the left medial prefrontal cortex compared with BD II and HCs.

CONCLUSIONS

The patients with BD and MDD shared common dFC alteration in the dorsal striatal-sensorimotor and ventral striatal-cognitive circuitries. The patients with MDD had specific dFC alteration in the ventral striatal-affective circuitry.

The Potential of KCNQ Potassium Channel Openers as Novel Antidepressants

Major depressive disorder (MDD) is a leading cause of disability worldwide and less than one-third of patients with MDD achieve stable remission of symptoms, despite currently available treatments. Although MDD represents a serious health problem, a complete understanding of the neurobiological mechanisms underlying this condition continues to be elusive. Accumulating evidence from preclinical and animal studies provides support for the antidepressant potential of modulators of KCNQ voltage-gated potassium (K⁺) channels. KCNQ K⁺ channels, through regulation of neuronal excitability and activity, contribute to neurophysiological mechanisms underlying stress resilience, and represent potential targets of drug discovery for depression. The present article focuses on the pharmacology and efficacy of KCNQ2/3 K⁺ channel openers as novel therapeutic agents for depressive disorders from initial studies conducted on animal models showing depressive-like behaviors to recent work in humans that examines the potential for KCNQ2/3 channel modulators as novel antidepressants. Data from preclinical work suggest that KCNQ-type K⁺ channels are an active mediator of stress resilience and KCNQ2/3 K⁺ channel openers show antidepressant efficacy. Similarly, evidence from clinical trials conducted in patients with MDD using the KCNQ2/3 channel opener ezogabine (retigabine) showed significant improvements in depressive symptoms and anhedonia. Overall, KCNQ channel openers appear a promising target for the development of novel therapeutics for the treatment of psychiatric disorders and specifically for MDD.

Anhedonia in Depression and Bipolar Disorder

Anhedonia is a hallmark feature of depression and is highly prevalent among individuals with mood disorders. The history and neurobiology of anhedonia has been most extensively studied in the context of unipolar Major Depressive Disorder (MDD), with converging lines of evidence indicating that marked anhedonia heralds a more chronic and treatment-refractory illness course. Furthermore, findings from neuroimaging studies suggest that anhedonia in MDD is associated with aberrant reward-related activation in key brain reward regions, particularly blunted reward anticipation-related activation in the ventral striatum. However, the ongoing clinical challenge of treating anhedonia in the context of Bipolar Disorder (BD) also highlights important gaps in our understanding of anhedonia's prevalence, severity, and pathophysiology along the entire mood disorder spectrum. In addition, although current theoretical models posit a key role for reward hyposensitivity in BD depression, unlike studies in MDD, studies in BD do not clearly show evidence for reduced reward-related activation in striatal or other brain regions. Although further research is needed, the evidence to date hints at a divergent pathophysiology for anhedonia in unipolar and bipolar mood disorders, which, if better understood, could lead to significant improvements in the diagnosis and treatment of MDD and BD.

Abnormal core functional connectivity on the pathology of MDD and antidepressant treatment: A systematic review

RATIONALE/IMPORTANCE

Researches have highlighted communication deficits between resting-state brain networks in major depressive disorder (MDD), as reflected in abnormal functional connectivity (FC). However, it is unclear whether impaired FC is associated with MDD pathology or is simply incidental to MDD symptoms. Moreover, there is no generalized theory to analyze the impact of treatment modalities on MDD.

OBJECTIVES

To address the issues, we conducted a systematic review of 49 eligible papers to provide insight into the pathological mechanisms of MDD patients by summarizing resting-state FC alterations involving mood and cognitive abnormalities and the effects of medications on them.

RESULTS

Mood disorders in MDD were characterized by abnormal FC between the amygdala, insula, anterior cingulate cortex (ACC), and prefrontal cortex (PFC). Cognitive impairment manifests as deficits in executive function, attention, memory, and rumination, primarily modulated by dysfunction between the fronto-parietal network and default mode network. Especially, we proposed the set of core abnormal FC (CA-FC) contributing to mood and cognitive impairment in MDD, currently including ACC-left precuneus/amygdala, rostral ACC-left dorsolateral PFC, left subgenual ACC-left cerebellar, left PFC- anterior subcallosal, and left precuneus-left pulvinar. After treatment, patients with normalized CA-FC showed remission of depressive symptoms.

CONCLUSIONS

We propose a CA-FC set for possible causative principle of MDD, which unifies the FC results from specific, difficult-to-analyze conditions into one outcome set for screening. Furthermore, CA-FC varies from person to person, and the low success rate of a single treatment may be due to the inability to cover too many CA-FC.

Prefrontal cortex and depression

The prefrontal cortex (PFC) has emerged as one of the regions most consistently impaired in major depressive disorder (MDD). Although functional and structural PFC abnormalities have been reported in both individuals with current MDD as well as those at increased vulnerability to MDD, this information has not translated into better treatment and prevention strategies. Here, we argue that dissecting depressive phenotypes into biologically more tractable dimensions - negative processing biases, anhedonia, despair-like behavior (learned helplessness) - affords unique opportunities for integrating clinical findings with mechanistic evidence emerging from preclinical models relevant to depression, and thereby promises to improve our understanding of MDD. To this end, we review and integrate clinical and preclinical literature pertinent to these core phenotypes, while emphasizing a systems-level approach, treatment effects, and whether specific PFC abnormalities are causes or consequences of MDD. In addition, we discuss several key issues linked to cross-species translation, including functional brain homology across species, the importance of dissecting neural pathways underlying specific functional domains that can be fruitfully probed across species, and the experimental approaches that best ensure translatability. Future directions and clinical implications of this burgeoning literature are discussed.

Detecting Suicide Ideation in the Era of Social Media: The Population Neuroscience Perspective

Social media platforms are increasingly used across many population groups not only to communicate and consume information, but also to express symptoms of psychological distress and suicidal thoughts. The detection of suicidal ideation (SI) can contribute to suicide prevention. Twitter data suggesting SI have been associated with negative emotions (e.g., shame, sadness) and a number of geographical and ecological variables (e.g., geographic location, environmental stress). Other important research contributions on SI come from studies in neuroscience. To date, very few research studies have been conducted that combine different disciplines (epidemiology, health geography, neurosciences, psychology, and social media big data science), to build innovative research directions on this topic. This article aims to offer a new interdisciplinary perspective, that is, a Population Neuroscience perspective on SI in order to highlight new ways in which multiple scientific fields interact to successfully investigate emotions and stress in social media to detect SI in the population. We argue that a Population Neuroscience perspective may help to better understand the mechanisms underpinning SI and to promote more effective strategies to prevent suicide timely and at scale.

The impact of child psychiatric conditions on future educational outcomes among a community cohort in Brazil

AIMS

Mental health problems early in life can negatively impact educational attainment, which in turn have negative long-term effects on health, social and economic opportunities. Our aims were to: (i) estimate the impacts of different types of psychiatric conditions on educational outcomes and (ii) to estimate the proportion of adverse educational outcomes which can be attributed to psychiatric conditions.

METHODS

Participants (N = 2511) were from a school-based community cohort of Brazilian children and adolescents aged 6-14 years enriched for high family risk of psychiatric conditions. We examined the impact of fear- (panic, separation and social anxiety disorder, specific phobia, agoraphobia and anxiety conditions not otherwise specified), distress- (generalised anxiety disorder, major depressive disorder and depressive disorder not otherwise specified, bipolar, obsessive-compulsive, tic, eating and post-traumatic stress disorder) and externalising-related conditions (attention deficit and hyperactivity disorder, conduct and oppositional-defiant conditions) on grade repetition, dropout, age-grade distortion, literacy performance and bullying perpetration, 3 years later. Psychiatric conditions were ascertained by psychiatrists, using the Development and Well-Being Behaviour Assessment. Propensity score and inverse probability weighting were used to adjust for potential confounders, including comorbidity, and sample attrition. We calculated the population attributable risk percentages to estimate the proportion of adverse educational outcomes in the population which could be attributed to psychiatric conditions. Analyses were conducted separately for males and females.

RESULTS

Fear and distress conditions in males were associated with school dropout (odds ratio (OR) = 2.76; 95% confidence interval (CI) = 1.06, 7.22; p < 0.05) and grade repetition (OR = 2.76; 95% CI = 1.32, 5.78; p < 0.01), respectively. Externalising conditions were associated with grade repetition in males (OR = 1.66; 95% CI = 1.05, 2.64; p < 0.05) and females (OR = 2.03; 95% CI = 1.15, 3.58; p < 0.05), as well as age-grade distortion in males (OR = 1.66; 95% CI = 1.05, 2.62; p < 0.05) and females (OR = 2.88; 95% CI = 1.61, 5.14; p < 0.001). Externalising conditions were also associated with lower literacy levels (β = -0.23; 95% CI = -0.34, -0.12; p < 0.001) and bullying perpetration (OR = 3.12; 95% CI = 1.50, 6.51; p < 0.001) in females. If all externalising conditions were prevented or treated, we estimate that 5.0 and 4.8% of grade repetition would not have occurred in females and males, respectively, as well as 10.2 (females) and 5.3% (males) of age-grade distortion cases and 11.4% of female bullying perpetration.

CONCLUSIONS

The study provides evidence of the negative impact of psychiatric conditions on educational outcomes in a large Brazilian cohort. Externalising conditions had the broadest and most robust negative impacts on education and these were particularly harmful to females which are likely to limit future socio-economic opportunities.

No associations in preregistered study of youth depression and functional connectivity of fronto-parietal and default mode networks

Adolescence is characterized by vulnerability to the onset of major depressive disorder (MDD). The goal of this preregistered study was to assess neural correlates of depression symptoms in young adolescents, both cross-sectionally and longitudinally. The default mode network (DMN) is believed to support internal attention towards self-referential thoughts, while the fronto-parietal network (FPN) is theorized to support cognitive control and regulation of attention. As MDD diagnosis has been associated with heightened connectivity within DMN regions and diminished connectivity within FPN regions relative to healthy controls, our study builds upon group-difference analyses by using dimensional measures of depression severity. Our preregistered hypotheses were that within-DMN functional connectivity would be positively associated with concurrent depression severity, while within-FPN functional connectivity would be negatively associated with concurrent depression severity. Preregistered analyses also examined between DMN-FPN connectivity as an alternative predictor variable, and assessed the longitudinal associations between all three functional connectivity measures and change in depression severity over three subsequent waves. Multiple regression models tested cross-sectional analyses and hierarchical linear models tested longitudinal analyses. One hundred and twenty-four youth completed a resting state functional MRI. Their depression severity was assessed at the time of the scan and at three follow-up sessions. None of the predictor variables were associated with concurrent depression severity, nor with the slope of depression symptom trajectories in longitudinal analyses. These negative results add to extant cross-sectional studies, and may inform future investigations of brain correlates of depression psychopathology in youth.

Multilevel growth curve analyses of behavioral activation for anhedonia (BATA) and mindfulness-based cognitive therapy effects on anhedonia and resting-state functional connectivity: Interim results of a randomized trial✰

BACKGROUND

The neural mechanisms associated with anhedonia treatment response are poorly understood. Additionally, no study has investigated changes in resting-state functional connectivity (rsFC) accompanying psychosocial treatment for anhedonia.

METHODS

We evaluated a novel psychotherapy, Behavioral Activation Therapy for Anhedonia (BATA, n = 38) relative to Mindfulness-Based Cognitive Therapy (MBCT, n = 35) in a medication-free, transdiagnostic, anhedonic sample in a parallel randomized controlled trial. Participants completed up to 15 sessions of therapy and up to four 7T MRI scans before, during, and after treatment (n = 185 scans). Growth curve models estimated change over time in anhedonia and in rsFC using average region-of-interest (ROI)-to-ROI connectivity within the default mode network (DMN), frontoparietal network (FPN), salience network, and reward network. Changes in rsFC from pre- to post-treatment were further evaluated using whole-network seed-to-voxel and ROI-to-ROI edgewise analyses.

RESULTS

Growth curve models showed significant reductions in anhedonia symptoms and in average rsFC within the DMN and FPN over time, across BATA and MBCT. There were no differences in anhedonia reductions between treatments. Within-person, changes in average rsFC were unrelated to changes in anhedonia. Between-person, higher than average FPN rsFC was related to less anhedonia across timepoints. Seed-to-voxel and edgewise rsFC analyses corroborated reductions within the DMN and between the DMN and FPN over time, across the sample.

CONCLUSIONS

Reductions in rsFC within the DMN, FPN, and between these networks co-occurred with anhedonia improvement across two psychosocial treatments for anhedonia. Future anhedonia clinical trials with a waitlist control group should disambiguate treatment versus time-related effects on rsFC.

Long-term stability of the cortical volumetric profile and the functional human connectome throughout childhood and adolescence

There is compelling evidence showing that between-subject variability in several functional and structural brain features is sufficient for unique identification in adults. However, individuation of brain functional connectomes depends on the stabilization of neurodevelopmental processes during childhood and adolescence. Here, we aimed to (1) evaluate the intra-subject functional connectome stability over time for the whole brain and for large scale functional networks and (2) determine the long-term identification accuracy or 'fingerprinting' for the cortical volumetric profile and the functional connectome. For these purposes, we analysed a longitudinal cohort of 239 children and adolescents scanned in two sessions with an interval of approximately 3 years (age range 6-15 years at baseline and 9-18 years at follow-up). Corroborating previous results using short between-scan intervals in children and adolescents, we observed a moderate identification accuracy (38%) for the whole functional profile. In contrast, identification accuracy using cortical volumetric profile was 95%. Among the large-scale networks, the default-mode (26.8%), the frontoparietal (23.4%) and the dorsal-attention (27.6%) networks were the most discriminative. Our results provide further evidence for a protracted development of specific individual structural and functional connectivity profiles.

Transdiagnostic neuroimaging of reward system phenotypes in ADHD and comorbid disorders

ADHD is a disorder characterized by changes in the reward system and which is highly comorbid with other mental disorders, suggesting common neurobiological pathways. Transdiagnostic neuroimaging findings could help to understand whether a dysregulated reward pathway might be the actual link between ADHD and its comorbidities. We here synthesize ADHD neuroimaging findings on the reward system with findings in obesity, depression, and substance use disorder including their comorbid appearance regarding neuroanatomical features (structural MRI) and activation patterns (resting-state and functional MRI). We focus on findings from monetary-incentive-delay (MID) and delay-discounting (DD) tasks and then review data on striatal connectivity and volumetry. Next, for better understanding of comorbidity in adult ADHD, we discuss these neuroimaging features in ADHD, obesity, depression and substance use disorder and ask whether ADHD heterogeneity and comorbidity are reflected by a common dysregulation in the reward system. Finally, we highlight conceptual issues related to heterogeneous paradigms, different phenotyping, longitudinal prediction and highlight some promising future directions for using striatal reward functioning as a clinical biomarker.

Data-driven parcellation and graph theory analyses to study adolescent mood and anxiety symptoms

Adolescence is a period of rapid brain development when psychiatric symptoms often first emerge. Studying adolescents may therefore facilitate the identification of neural alterations early in the course of psychiatric conditions. Here, we sought to utilize new, high-quality brain parcellations and data-driven graph theory approaches to characterize associations between resting-state networks and the severity of depression, anxiety, and anhedonia symptoms-salient features across psychiatric conditions. As reward circuitry matures considerably during adolescence, we examined both Whole Brain and three task-derived reward networks. Subjects were 87 psychotropic-medication-free adolescents (age = 12-20) with diverse psychiatric conditions (n = 68) and healthy controls (n = 19). All completed diagnostic interviews, dimensional clinical assessments, and 3T resting-state fMRI (10 min/2.3 mm/TR = 1 s). Following high-quality Human Connectome Project-style preprocessing, multimodal surface matching (MSMAll) alignment, and parcellation via the Cole-Anticevic Brain-wide Network Partition, weighted graph theoretical metrics (Strength Centrality = C_Str; Eigenvector Centrality = C_Eig; Local Efficiency = E_Loc) were estimated within each network. Associations with symptom severity and clinical status were assessed non-parametrically (two-tailed p_FWE < 0.05). Across subjects, depression scores correlated with ventral striatum C_Str within the Reward Attainment network, while anticipatory anhedonia correlated with C_Str and E_Loc in the subgenual anterior cingulate, dorsal anterior cingulate, orbitofrontal cortex, caudate, and ventral striatum across multiple networks. Group differences and associations with anxiety were not detected. Using detailed functional and clinical measures, we found that adolescent depression and anhedonia involve increased influence and communication efficiency in prefrontal and limbic reward areas. Resting-state network properties thus reflect positive valence system anomalies related to discrete reward sub-systems and processing phases early in the course of illness.

Covid-19 and Mental Health: Could Visual Art Exposure Help?

A worldwidemental health crisis is expected, as millions worldwide fear death and disease while being forced into repeated isolation. Thus, there is a need for new proactive approaches to improve mental resilience and prevent mental health conditions. Since the 1990s, art has emerged as an alternative mental health therapy in the United States and Europe, becoming part of the social care agenda. This article focuses on how visual esthetic experiences can create similar patterns of neuronal activity as those observed when the reward system is activated. The activation of the reward structures could have a stress buffering effect, given the interdependence observed between the reward and stress systems. Therefore, could visual esthetic experiences stimulate mental resilience? And if this were the case, could art-based interventions be offered for mental health in the context of COVID-19 and beyond?

Mind the brain gap: The worldwide distribution of neuroimaging research on adolescent depression

Adolescents comprise one fourth of the world’s population, with about 90% of them living in low- and middle-income countries (LMICs). The incidence of depression markedly increases during adolescence, making the disorder a leading cause of disease-related disability in this age group. However, most research on adolescent depression has been performed in high-income countries (HICs). To ascertain the extent to which this disparity operates in neuroimaging research, a systematic review of the literature was performed. A total of 148 studies were identified, with neuroimaging data available for 4,729 adolescents with depression. When stratified by income group, 122 (82%) studies originated from HICs, while 26 (18%) were conducted in LMICs, for a total of 3,705 and 1,024 adolescents with depression respectively. A positive Spearman rank correlation was observed between country per capita income and sample size (r_s =0.673, p = 0.023). Our results support the previous reports showing a large disparity between the number of studies and the adolescent population per world region. Future research comparing neuroimaging findings across populations from HICs and LMICs may provide unique insights to enhance our understanding of the neurobiological processes underlying the development of depression.

Social experience calibrates neural sensitivity to social feedback during adolescence: A functional connectivity approach

The adaptive calibration model suggests exposure to highly stressful or highly supportive early environments sensitizes the brain to later environmental input. We examined whether family and peer experiences predict neural sensitivity to social cues in 85 adolescent girls who completed a social feedback task during a functional brain scan and an interview assessing adversity. Whole-brain functional connectivity (FC) analyses revealed curvilinear associations between social experiences and FC between the ventral striatum and regions involved in emotion valuation, social cognition, and salience detection (e.g., insula, MPFC, dACC, dlPFC) during social reward processing, such that stronger FC was found at both very high and very low levels of adversity. Moreover, exposure to adversity predicted stronger FC between the amygdala and regions involved in salience detection, social cognition, and emotional memory (e.g., sgACC, precuneus, lingual gyrus, parahippocampal gyrus) during social threat processing. Analyses also revealed some evidence for blunted FC (VS-PCC for reward; amygdala-parahippocampal gyrus for threat) at very high and low levels of adversity. Overall, results suggest social experiences may play a critical role in shaping neural sensitivity to social feedback during adolescence. Future work will need to elucidate the implications of these patterns of neural function for the development of psychopathology.

A Social Affective Neuroscience Model of Risk and Resilience in Adolescent Depression: Preliminary Evidence and Application to Sexual and Gender Minority Adolescents

Depression is a disorder of dysregulated affective and social functioning, with attenuated response to reward, heightened response to threat (perhaps especially social threat), excessive focus on negative aspects of the self, ineffective engagement with other people, and difficulty modulating all of these responses. Known risk factors provide a starting point for a model of developmental pathways to resilience, and we propose that the interplay of social threat experiences and neural social-affective systems is critical to those pathways. We describe a model of risk and resilience, review supporting evidence, and apply the model to sexual and gender minority adolescents, a population with high disparities in depression and unique social risk factors. This approach illustrates the fundamental role of a socially and developmentally informed clinical neuroscience model for understanding a population disproportionately affected by risk factors and psychopathology outcomes. We consider it a public health imperative to apply conceptual models to high-need populations to elucidate targets for effective interventions to promote healthy development and enhance resilience.

Psychiatric neuroimaging research in Brazil: historical overview, current challenges, and future opportunities

The last four decades have witnessed tremendous growth in research studies applying neuroimaging methods to evaluate pathophysiological and treatment aspects of psychiatric disorders around the world. This article provides a brief history of psychiatric neuroimaging research in Brazil, including quantitative information about the growth of this field in the country over the past 20 years. Also described are the various methodologies used, the wealth of scientific questions investigated, and the strength of international collaborations established. Finally, examples of the many methodological advances that have emerged in the field of in vivo neuroimaging are provided, with discussion of the challenges faced by psychiatric research groups in Brazil, a country of limited resources, to continue incorporating such innovations to generate novel scientific data of local and global relevance.

Translational application of neuroimaging in major depressive disorder: a review of psychoradiological studies

Major depressive disorder (MDD) causes great decrements in health and quality of life with increments in healthcare costs, but the causes and pathogenesis of depression remain largely unknown, which greatly prevent its early detection and effective treatment. With the advancement of neuroimaging approaches, numerous functional and structural alterations in the brain have been detected in MDD and more recently attempts have been made to apply these findings to clinical practice. In this review, we provide an updated summary of the progress in translational application of psychoradiological findings in MDD with a specified focus on potential clinical usage. The foreseeable clinical applications for different MRI modalities were introduced according to their role in disorder classification, subtyping, and prediction. While evidence of cerebral structural and functional changes associated with MDD classification and subtyping was heterogeneous and/or sparse, the ACC and hippocampus have been consistently suggested to be important biomarkers in predicting treatment selection and treatment response. These findings underlined the potential utility of brain biomarkers for clinical practice.

Ketamine modulates fronto-striatal circuitry in depressed and healthy individuals

Ketamine improves motivation-related symptoms in depression but simultaneously elicits similar symptoms in healthy individuals, suggesting that it might have different effects in health and disease. This study examined whether ketamine affects the brain's fronto-striatal system, which is known to drive motivational behavior. The study also assessed whether inflammatory mechanisms-which are known to influence neural and behavioral motivational processes-might underlie some of these changes. These questions were explored in the context of a double-blind, placebo-controlled, crossover trial of ketamine in 33 individuals with treatment-resistant major depressive disorder (TRD) and 25 healthy volunteers (HVs). Resting-state functional magnetic resonance imaging (rsfMRI) was acquired 2 days post-ketamine (final sample: TRD n = 27, HV n = 19) and post-placebo (final sample: TRD n = 25, HV n = 18) infusions and was used to probe fronto-striatal circuitry with striatal seed-based functional connectivity. Ketamine increased fronto-striatal functional connectivity in TRD participants toward levels observed in HVs while shifting the connectivity profile in HVs toward a state similar to TRD participants under placebo. Preliminary findings suggest that these effects were largely observed in the absence of inflammatory (C-reactive protein) changes and were associated with both acute and sustained improvements in symptoms in the TRD group. Ketamine thus normalized fronto-striatal connectivity in TRD participants but disrupted it in HVs independently of inflammatory processes. These findings highlight the potential importance of reward circuitry in ketamine's mechanism of action, which may be particularly relevant for understanding ketamine-induced shifts in motivational symptoms.

Influence of ovarian hormones on value-based decision-making systems: Contribution to sexual dimorphisms in mental disorders

Women and men exhibit differences in behavior when making value-based decisions. Various hypotheses have been proposed to explain these findings, stressing differences in functional lateralization of the brain, functional activation, neurotransmitter involvement and more recently, sex hormones. While a significant interaction of neurotransmitter systems and sex hormones has been shown for both sexes, decision-making in women might be particularly affected by variations of ovarian hormones. In this review we have gathered information from animal and human studies on how ovarian hormones affect decision-making processes in females by interacting with neurotransmitter systems at functionally relevant brain locations and thus modify the computation of decision aspects. We also review previous findings on impaired decision-making in animals and clinical populations with substance use disorder and depression, emphasizing how little we know about the role of ovarian hormones in aberrant decision-making.