Longitudinal changes in resting-state functional connectivity as markers of vulnerability or resilience in first-degree relatives of patients with bipolar disorder.

BACKGROUND: There is a significant contribution of genetic factors to the etiology of bipolar disorder (BD). Unaffected first-degree relatives of patients (UR) with BD are at increased risk of developing mental disorders and may manifest cognitive impairments and alterations in brain functional and connective dynamics, akin to their affected relatives. METHODS: In this prospective longitudinal study, resting-state functional connectivity was used to explore stable and progressive markers of vulnerability i.e. abnormalities shared between UR and BD compared to healthy controls (HC) and resilience i.e. features unique to UR compared to HC and BD in full or partial remission (UR n = 72, mean age = 28.0 ± 7.2 years; HC n = 64, mean age = 30.0 ± 9.7 years; BD patients n = 91, mean age = 30.6 ± 7.7 years). Out of these, 34 UR, 48 BD, and 38 HC were investigated again following a mean time of 1.3 ± 0.4 years. RESULTS: At baseline, the UR showed lower connectivity values within the default mode network (DMN), frontoparietal network, and the salience network (SN) compared to HC. This connectivity pattern in UR remained stable over the follow-up period and was not present in BD, suggesting a resilience trait. The UR further demonstrated less negative connectivity between the DMN and SN compared to HC, abnormality that remained stable over time and was also present in BD, suggesting a vulnerability marker. CONCLUSION: Our findings indicate the coexistence of both vulnerability-related abnormalities in resting-state connectivity, as well as adaptive changes possibly promoting resilience to psychopathology in individual at familial risk.

Lateralized grey matter volume changes in adolescents versus adults with major depression: SDM-PSI meta-analysis.

The current study is the first meta-analysis to examine grey matter volume (GMV) changes in adolescents and across the lifespan in major depressive disorder (MDD). Seed-based d mapping-with permutation of subject images (SDM-PSI) has advantages over previous coordinate-based meta-analytical methods (CBMA), such as reducing bias (via the MetaNSUE algorithm) and including non-statistically significant unreported effects. SDM-PSI was used to analyze 105 whole-brain GMV voxel-based morphometry (VBM) studies comparing 6,530 individuals with MDD versus 6,821 age-matched healthy controls (HC). A laterality effect was observed in which adults with MDD showed lower GMV than adult HC in left fronto-temporo-parietal structures (superior temporal gyrus, insula, Rolandic operculum, and inferior frontal gyrus). However, these abnormalities were not statistically significant for adolescent MDD versus adolescent HC. Instead, adolescent MDD showed lower GMV than adult MDD in right temporo-parietal structures (angular gyrus and middle temporal gyrus). These regional differences may be used as potential biomarkers to predict and monitor treatment outcomes as well as to choose the most effective treatments in adolescents versus adults. Finally, due to the paucity of youth, older adult, and longitudinal studies, future studies should attempt to replicate these GMV findings and examine whether they correlate with treatment response and illness severity.

Should perception of emotions be classified according to threat detection rather than emotional valence? An updated meta-analysis for a whole-brain atlas of emotional faces processing.

BACKGROUND: Human navigation of social interactions relies on the processing of emotion on faces. This meta-analysis aimed to produce an updated brain atlas of emotional face processing from whole-brain studies based on a single emotional face-viewing paradigm (PROSPERO CRD42022251548). METHODS: We conducted a systematic literature search of Embase, MEDLINE and PsycINFO from May 2008 to October 2021. We used seed-based d mapping with permutation of subject images to conduct a quantitative meta-analysis of functional neuroimaging contrasts between emotional (e.g., angry, happy) and neutral faces. We conducted agglomerative hierarchical clustering of meta-analytic map contrasts of emotional faces relative to neutral faces. We investigated lateralization of emotional face processing. RESULTS: From 5549 studies identified, 55 data sets (1489 healthy participants) met our inclusion criteria. Relative to neutral faces, we found extensive activation clusters by fearful faces in the right inferior temporal gyrus, right fusiform area, left putamen and amygdala, right parahippocampalgyrus and cerebellum; we found smaller activation clusters by angry faces in the right cerebellum and right middle temporal gyrus (MTG) and by disgusted faces in the left MTG. Happy and sad faces did not reach statistical significance. Clustering analyses showed similar activation patterns of fearful and angry faces; activation patterns of happy and sad faces showed the least correlation with other emotional faces. Emotional face processing was predominantly left-lateralized in the amygdala and anterior insula, and right-lateralized in the ventromedial prefrontal cortex. LIMITATIONS: Reliance on discretized effect sizes based on peak coordinate location instead of statistical brain maps, and the varying level of statistical threshold reporting from original studies, could lead to underdetection of smaller clusters of activation. CONCLUSION: Processing of emotional faces appeared to be oriented toward identifying threats on faces, from highest (i.e., angry or fearful faces) to lowest level (i.e., happy or sad faces), with a more complex lateralization pattern than previously theorized. Emotional faces may be processed in latent grouping but organized by threat content rather than emotional valence.

Improved estimation of the risk of manic relapse by combining clinical and brain scan data.

INTRODUCTION: Estimating the risk of manic relapse could help the psychiatrist individually adjust the treatment to the risk. Some authors have attempted to estimate this risk from baseline clinical data. Still, no studies have assessed whether the estimation could improve by adding structural magnetic resonance imaging (MRI) data. We aimed to evaluate it. MATERIAL AND METHODS: We followed a cohort of 78 patients with a manic episode without mixed symptoms (bipolar type I or schizoaffective disorder) at 2-4-6-9-12-15-18 months and up to 10 years. Within a cross-validation scheme, we created and evaluated a Cox lasso model to estimate the risk of manic relapse using both clinical and MRI data. RESULTS: The model successfully estimated the risk of manic relapse (Cox regression of the time to relapse as a function of the estimated risk: hazard ratio (HR)=2.35, p=0.027; area under the curve (AUC)=0.65, expected calibration error (ECE)<0.2). The most relevant variables included in the model were the diagnosis of schizoaffective disorder, poor impulse control, unusual thought content, and cerebellum volume decrease. The estimations were poorer when we used clinical or MRI data separately. CONCLUSION: Combining clinical and MRI data may improve the risk of manic relapse estimation after a manic episode. We provide a website that estimates the risk according to the model to facilitate replication by independent groups before translation to clinical settings.

Aberrant resting-state functional connectivity underlies cognitive and functional impairments in remitted patients with bipolar disorder.

BACKGROUND: Bipolar disorder (BD) is commonly associated with cognitive impairments, that directly contribute to patients' functional disability. However, there is no effective treatment targeting cognition in BD. A key reason for the lack of pro-cognitive interventions is the limited insight into the brain correlates of cognitive impairments in these patients. This is the first study investigating the resting-state neural underpinnings of cognitive impairments in different neurocognitive subgroups of patients with BD. METHOD: Patients with BD in full or partial remission and healthy controls (final sample of n = 144 and n = 50, respectively) underwent neuropsychological assessment and resting-state functional magnetic resonance imaging. We classified the patients into cognitively impaired (n = 83) and cognitively normal (n = 61) subgroups using hierarchical cluster analysis of the four cognitive domains. We used independent component analysis (ICA) to investigate the differences between the neurocognitive subgroups and healthy controls in resting-state functional connectivity (rsFC) in the default mode network (DMN), executive central network (ECN), and frontoparietal network (FPN). RESULTS: Cognitively impaired patients displayed greater positive rsFC within the DMN and less negative rsFC within the ECN than healthy controls. Across cognitively impaired patients, lower positive connectivity within DMN and lower negative rsFC within ECN correlated with worse global cognitive performance. CONCLUSION: Cognitive impairments in BD seem to be associated with a hyper-connectivity within the DMN, which may explain the failure to suppress task-irrelevant DMN activity during the cognitive performance, and blunted anticorrelation in the ECN. Thus, aberrant connectivity within the DMN and ECN may serve as brain targets for pro-cognitive interventions.

Meta-analysis of the effects of adjuvant drugs in co-occurring bipolar and substance use disorder.

BACKGROUND: Individuals with bipolar disorder (BD) often have co-occurring substance use disorders (SUDs), which substantially impoverish the course of illness. Despite the importance of this dual diagnosis, the evidence of the efficacy and safety of adjuvant treatments is mostly unknown. OBJECTIVE: To perform a meta-analysis to evaluate the efficacy and safety of adjuvant drugs in patients with co-occurring BD and SUD. METHODS: We searched PubMed, Scopus, and Web of Knowledge until 30th April 2022 for randomized clinical trials (RCT) evaluating the efficacy and safety of adjuvant drugs compared to placebo in patients with a dual diagnosis of BD and SUD. We meta-analyzed the effect of adjuvant drugs on general outcomes (illness severity, mania, depression, anxiety, abstinence, substance craving, substance use, gamma-GT, adherence, and adverse events) and used the results to objectively assess the quality of the evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. For completeness, we also report the specific effects of specific adjuvant drugs in patients with specific substance disorders. RESULTS: We included 15 RCT studies (9 alcohol, 3 cocaine, 2 nicotine, and 1 cannabis) comprising 628 patients allocated to treatment and 622 to placebo. There was low-quality evidence that adjuvant drugs may reduce illness severity (g=-0.25, 95% CI: -0.44, -0.06), and very-low quality evidence that they may decrease substance use (g=-0.23, 95% CI: -0.44, -0.02) and increase substance abstinence (g=0.21, 95% CI: 0.04, 0.38). DISCUSSION: There is low-quality evidence that adjuvant drugs may help reduce illness severity, probably via facilitating abstinence and lower substance use. However, the evidence is weak; thus, these results should be considered cautiously until better evidence exists.

Transdiagnostic risk of mental disorders in offspring of affected parents: a meta-analysis of family high-risk and registry studies.

The offspring of parents with mental disorders are at increased risk for developing mental disorders themselves. The risk to offspring may extend transdiagnostically to disorders other than those present in the parents. The literature on this topic is vast but mixed. To inform targeted prevention and genetic counseling, we performed a comprehensive, PRISMA 2020-compliant meta-analysis. We systematically searched the literature published up to September 2022 to retrieve original family high-risk and registry studies reporting on the risk of mental disorders in offspring of parents with any type of mental disorder. We performed random-effects meta-analyses of the relative risk (risk ratio, RR) and absolute risk (lifetime, up to the age at assessment) of mental disorders, defined according to the ICD or DSM. Cumulative incidence by offspring age was determined using meta-analytic Kaplan-Meier curves. We measured heterogeneity with the I2 statistic, and risk of bias with the Quality In Prognosis Studies (QUIPS) tool. Sensitivity analyses addressed the impact of study design (family high-risk vs. registry) and specific vs. transdiagnostic risks. Transdiagnosticity was appraised with the TRANSD criteria. We identified 211 independent studies that reported data on 3,172,115 offspring of parents with psychotic, bipolar, depressive, disruptive, attention-deficit/hyperactivity, anxiety, substance use, eating, obsessive-compulsive, and borderline personality disorders, and 20,428,575 control offspring. The RR and lifetime risk of developing any mental disorder were 3.0 and 55% in offspring of parents with anxiety disorders; 2.6 and 17% in offspring of those with psychosis; 2.1 and 55% in offspring of those with bipolar disorder; 1.9 and 51% in offspring of those with depressive disorders; and 1.5 and 38% in offspring of those with substance use disorders. The offspring's RR and lifetime risk of developing the same mental disorder diagnosed in their parent were 8.4 and 32% for attention-deficit/hyperactivity disorder; 5.8 and 8% for psychosis; 5.1 and 5% for bipolar disorder; 2.8 and 9% for substance use disorders; 2.3 and 14% for depressive disorders; 2.3 and 1% for eating disorders; and 2.2 and 31% for anxiety disorders. There were 37 significant transdiagnostic associations between parental mental disorders and the RR of developing a different mental disorder in the offspring. In offspring of parents with psychosis, bipolar and depressive disorder, the risk of the same disorder onset emerged at 16, 5 and 6 years, and cumulated to 3%, 19% and 24% by age 18; and to 8%, 36% and 46% by age 28. Heterogeneity ranged from 0 to 0.98, and 96% of studies were at high risk of bias. Sensitivity analyses restricted to prospective family high-risk studies confirmed the pattern of findings with similar RR, but with greater absolute risks compared to analyses of all study types. This study demonstrates at a global, meta-analytic level that offspring of affected parents have strongly elevated RR and lifetime risk of developing any mental disorder as well as the same mental disorder diagnosed in the parent. The transdiagnostic risks suggest that offspring of parents with a range of mental disorders should be considered as candidates for targeted primary prevention.

Correlation between emotion dysregulation and mood symptoms of bipolar disorder: A systematic review and meta-analysis.

BACKGROUND: Emotion dysregulation (ED) is a transdiagnostic construct characterized by difficulties regulating intense emotions. People with bipolar disorder (BD) are more likely to show ED and use maladaptive emotion regulation strategies than adaptive ones. However, little is known about whether ED in BD is a trait or it is rather an epiphenomenon of mood symptoms. METHODS: We conducted a systematic review and meta-analysis of the evidence across major literature databases reporting correlations between measures of emotion regulation (overall ED and different emotion regulation strategies) and measures of depressive and (hypo)manic symptoms in BD from inception until April 12th, 2022. RESULTS: Fourteen studies involving 1371 individuals with BD were included in the qualitative synthesis, of which 11 reported quantitative information and were included in the meta-analysis. ED and maladaptive strategies were significantly higher during periods with more severe mood symptoms, especially depressive ones, while adaptive strategies were lower. CONCLUSION: ED significantly correlates with BD symptomatology, and it mainly occurs during mood alterations. ED may be a target for specific psychotherapeutic and pharmacological treatments, according to precision psychiatry. However, further studies are needed, including patients with mood episodes and longitudinal design, to provide more robust evidence and explore the causal direction of the associations.

Differences in facial emotion recognition between bipolar disorder and other clinical populations: A systematic review and meta-analysis.

Facial emotion (or expression) recognition (FER) is a domain of affective cognition impaired across various psychiatric conditions, including bipolar disorder (BD). We conducted a systematic review and meta-analysis searching for eligible articles published from inception to April 26, 2023, in PubMed/MEDLINE, Scopus, EMBASE, and PsycINFO to examine whether and to what extent FER would differ between people with BD and those with other mental disorders. Thirty-three studies comparing 1506 BD patients with 1973 clinical controls were included in the present systematic review, and twenty-six of them were analyzed in random-effects meta-analyses exploring the discrepancies in discriminating or identifying emotional stimuli at a general and specific level. Individuals with BD were more accurate in identifying each type of emotion during a FER task compared to individuals diagnosed with schizophrenia (SCZ) (SMD = 0.27; p-value = 0.006), with specific differences in the perception of anger (SMD = 0.46; p-value = 1.19e-06), fear (SMD = 0.38; p-value = 8.2e-04), and sadness (SMD = 0.33; p-value = 0.026). In contrast, BD patients were less accurate than individuals with major depressive disorder (MDD) in identifying each type of emotion (SMD = -0.24; p-value = 0.014), but these differences were more specific for sad emotional stimuli (SMD = -0.31; p-value = 0.009). No significant differences were observed when BD was compared with children and adolescents diagnosed with attention-deficit/hyperactivity disorder. FER emerges as a potential integrative instrument for guiding diagnosis by enabling discrimination between BD and SCZ or MDD. Enhancing the standardization of adopted tasks could further enhance the accuracy of this tool, leveraging FER potential as a therapeutic target.

Anxiety and depression played a central role in the COVID-19 mental distress: A network analysis.

INTRODUCTION: Psychological, socio-demographics, and clinical factors play an important role in patients with COVID-19, but their relationship is complex. The network approach might be used to disentangle complex interactions in different systems. Using data from a multicentre, cross-sectional, survey among patients with COVID-19 in Spain (July-November 2020), we investigated the network structure of mental disorders symptoms, social support, and psychological resilience, and changes in network structures according to the presence of a pre-existing mental disorder or hospitalization for COVID-19. METHODS: Subjects completed a survey to evaluate sociodemographic characteristics, COVID-19 infection status, resilience, social support, and symptoms of depression, anxiety disorders, post-traumatic stress disorder, panic attacks, and substance use disorder. 2084 patients with COVID-19 were included in the analysis. Network analysis was conducted to evaluate network and bridge centrality, and the network properties were compared between COVID-19 patients with and without a history of lifetime mental disorder, and between hospitalized and non-hospitalized patients. LIMITATIONS: Generalization of our findings may be difficult since differences in network connectivity may exist in different populations or samples. RESULTS: Anxiety and depression showed high centrality in patients with COVID-19 and anxiety showed the highest bridge influence in the network. Resilience and social support showed a low influence on mental disorder symptoms. Global network estimations show no statistically significant changes between patients with and without pre-existing mental disorders or between hospitalized and non-hospitalized patients. CONCLUSIONS: Anxiety might be a key treatment target in patients with COVID-19 since its treatment might prevent other mental health adverse outcomes.

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).

Functional neuroanatomy of craving in heroin use disorder: voxel-based meta-analysis of functional magnetic resonance imaging (fMRI) drug cue reactivity studies.

Background: The neuroanatomy of craving, typically investigated using the functional magnetic resonance imaging (fMRI) drug cue reactivity (FDCR) paradigm, has been shown to involve the mesocorticolimbic, nigrostriatal, and corticocerebellar systems in several substances. However, the neuroanatomy of craving in heroin use disorder is still unclear.Objective: The current meta-analysis examines previous research on the neuroanatomy of craving in abstinent individuals with opioid use disorder (OUD).Method: Seven databases were searched for studies comparing abstinent OUD versus healthy controls on drug > neutral contrast interaction at the whole-brain level. Voxel-based meta-analysis was performed using seed-based d mapping with permuted subject images (SDM-PSI). Thresholds were set at a family-wise error rate of less than 5% with the default pre-processing parameters of SDM-PSI.Results: A total of 10 studies were included (296 OUD and 187 controls). Four hyperactivated clusters were identified with Hedges' g of peaks that ranged from 0.51 to 0.82. These peaks and their associated clusters correspond to the three systems identified in the previous literature: a) mesocorticolimbic, b) nigrostriatal, and c) corticocerebellar. There were also newly revealed hyperactivation regions including the bilateral cingulate, precuneus, fusiform gyrus, pons, lingual gyrus, and inferior occipital gyrus. The meta-analysis did not reveal areas of hypoactivation.Conclusion: Recommendations based on the functional neuroanatomical findings of this meta-analysis include pharmacological interventions such as buprenorphine/naloxone and cognitive-behavioral treatments such as cue-exposure combined with HRV biofeedback. In addition, research should utilize FDCR as pre- and post-measurement to determine the effectiveness and mechanism of action of such interventions.

Development and Validation of a Smartphone-Based App for the Longitudinal Assessment of Anxiety in Daily Life.

Current methods to assess human anxiety often ignore that anxiety is a dynamic process and have limitations such as high recall bias and low generalizability to real life. Smartphone apps using ecological momentary assessment (EMA) may overcome such limitations. We developed a smartphone app for the longitudinal evaluation of anxiety symptoms using EMA. We assessed the feasibility (retention and compliance) and psychometric properties (reliability and validity) of the app over 6 months in a sample of 99 participants with different levels of anxiety. The EMA-based smartphone app was highly feasible. It showed excellent within-person and between-person reliability, high convergent and moderate discriminant validity, and significant incremental validity. Assessing anxiety longitudinally using a smartphone and following EMA principles is feasible and can be reliable and valid. Studies combining EMA-based anxiety longitudinal assessments with other assessment methods deserve further research and may offer novel insights into human anxiety.

Psychological trauma as a transdiagnostic risk factor for mental disorder: an umbrella meta-analysis.

This umbrella review is the first to systematically examine psychological trauma as a transdiagnostic risk factor across psychiatric conditions. We searched Pubmed, Scopus, and PsycNET databases from inception until 01/05/2021 for systematic reviews/meta-analyses evaluating the association between psychological trauma and at least one diagnosed mental disorder. We re-calculated the odds ratio (OR), then classified the association as convincing, highly suggestive, suggestive, or weak, based on the number of cases and controls with and without psychological trauma, random-effects p value, the 95% confidence interval of the largest study, heterogeneity between studies, 95% prediction interval, small-study effect, and excess significance bias. Additional outcomes were the association between specific trauma types and specific mental disorders, and a sensitivity analysis for childhood trauma. Transdiagnosticity was assessed using TRANSD criteria. The review was pre-registered in Prospero CRD42020157308 and followed PRISMA/MOOSE guidelines. Fourteen reviews met inclusion criteria, comprising 16,277 cases and 77,586 controls. Psychological trauma met TRANSD criteria as a transdiagnostic factor across different diagnostic criteria and spectra. There was highly suggestive evidence of an association between psychological trauma at any time-point and any mental disorder (OR = 2.92) and between childhood trauma and any mental disorder (OR = 2.90). Regarding specific trauma types, convincing evidence linked physical abuse (OR = 2.36) and highly suggestive evidence linked sexual abuse (OR = 3.47) with a range of mental disorders, and convincing evidence linked emotional abuse to anxiety disorders (OR = 3.05); there were no data for emotional abuse with other disorders. These findings highlight the importance of preventing early traumatic events and providing trauma-informed care in early intervention and psychiatric services.

Removing the effects of the site in brain imaging machine-learning - Measurement and extendable benchmark.

Multisite machine-learning neuroimaging studies, such as those conducted by the ENIGMA Consortium, need to remove the differences between sites to avoid effects of the site (EoS) that may prevent or fraudulently help the creation of prediction models, leading to impoverished or inflated prediction accuracy. Unfortunately, we have shown earlier that current Methods Aiming to Remove the EoS (MAREoS, e.g., ComBat) cannot remove complex EoS (e.g., including interactions between regions). And complex EoS may bias the accuracy. To overcome this hurdle, groups worldwide are developing novel MAREoS. However, we cannot assess their effectiveness because EoS may either inflate or shrink the accuracy, and MAREoS may both remove the EoS and degrade the data. In this work, we propose a strategy to measure the effectiveness of a MAREoS in removing different types of EoS. FOR MAREOS DEVELOPERS, we provide two multisite MRI datasets with only simple true effects (i.e., detectable by most machine-learning algorithms) and two with only simple EoS (i.e., removable by most MAREoS). First, they should use these datasets to fit machine-learning algorithms after applying the MAREoS. Second, they should use the formulas we provide to calculate the relative accuracy change associated with the MAREoS in each dataset and derive an EoS-removal effectiveness statistic. We also offer similar datasets and formulas for complex true effects and EoS that include first-order interactions. FOR MACHINE-LEARNING RESEARCHERS, we provide an extendable benchmark website to show: a) the types of EoS they should remove for each given machine-learning algorithm and b) the effectiveness of each MAREoS for removing each type of EoS. Relevantly, a MAREoS only able to remove the simple EoS may suffice for simple machine-learning algorithms, whereas more complex algorithms need a MAREoS that can remove more complex EoS. For instance, ComBat removes all simple EoS as needed for predictions based on simple lasso algorithms, but it leaves residual complex EoS that may bias the predictions based on standard support vector machine algorithms.

Study protocol - elucidating the neural correlates of functional remediation for older adults with bipolar disorder.

Introduction: Beyond mood abnormalities, bipolar disorder (BD) includes cognitive impairments that worsen psychosocial functioning and quality of life. These deficits are especially severe in older adults with BD (OABD), a condition expected to represent most individuals with BD in the upcoming years. Restoring the psychosocial functioning of this population will thus soon represent a public health priority. To help tackle the problem, the Bipolar and Depressive Disorders Unit at the Hospital Clínic of Barcelona has recently adapted its Functional Remediation (FR) program to that population, calling it FROA-BD. However, while scarce previous studies localize the neural mechanisms of cognitive remediation interventions in the dorsal prefrontal cortex, the specific mechanisms are seldom unknown. In the present project, we will investigate the neural correlates of FR-OABD to understand its mechanisms better and inform for potential optimization. The aim is to investigate the brain features and changes associated with FROA-BD efficacy. Methods: Thirty-two individuals with OABD in full or partial remission will undergo a magnetic resonance imaging (MRI) session before receiving FR-OABD. After completing the FR-OABD intervention, they will undergo another MRI session. The MRI sessions will include structural, diffusion-weighted imaging (DWI), functional MRI (fMRI) with working memory (n-back) and verbal learning tasks, and frontal spectroscopy. We will correlate the pre-post change in dorsolateral and dorsomedial prefrontal cortices activation during the n-back task with the change in psychosocial functioning [measured with the Functioning Assessment Short Test (FAST)]. We will also conduct exploratory whole-brain correlation analyses between baseline or pre-post changes in MRI data and other clinical and cognitive outcomes to provide more insights into the mechanisms and explore potential brain markers that may predict a better treatment response. We will also conduct separate analyses by sex. Discussion: The results of this study may provide insights into how FROA-BD and other cognitive remediations modulate brain function and thus could optimize these interventions.

Upward trends in eating disorders, self-harm, and suicide attempt emergency admissions in female adolescents after COVID-19 lockdown.

INTRODUCTION: Increased mental health problems have been reported in children and adolescents related to the COVID-19 lockdown and its immediate aftermath, especially among adolescent females. However, the longer-term impact of persistent quarantine measures and social restrictions on this population is yet to be further explored. MATERIALS AND METHODS: We compared the number of children/adolescents admissions to the psychiatric emergency department (ED) of Hospital Clínic de Barcelona during the COVID-19 lockdown and the following year with the numbers of admissions the year before lockdown, adjusting for variations in the population. We also conducted separate analyses by gender, age group, and diagnostic categories. Finally, we also repeated the analyses considering the cumulated deficit/excess since the start of the lockdown. Statistical significance was estimated using binomial tests with Bonferroni correction. RESULTS: A total of 2425 admissions were recorded. Globally, admission rates decreased during the lockdown (46%) and progressively increased during the one-year aftermath (43% by spring 2021). This increase was particularly high in adolescent females (85%) while unclear in children and/or males. The main diagnostic categories involved were anxiety, depressive, and eating disorders, as well as self-harm behavior, suicidal ideation, and suicide attempts. The increase in eating disorders, self-harm behavior, and suicide attempts admissions in female adolescents remained statistically significant when considering the cumulated deficit/excess. CONCLUSIONS: We found increased ED admissions during the aftermath of the COVID-19 lockdown among adolescent females. We recommend strengthening the attention to this population to provide adequate specialized care and prevention strategies.

Precuneus and insular hypoactivation during cognitive processing in first-episode psychosis: Systematic review and meta-analysis of fMRI studies.

INTRODUCTION: The neural correlates of the cognitive dysfunction in first-episode psychosis (FEP) are still unclear. The present review and meta-analysis provide an update of the location of the abnormalities in the fMRI-measured brain response to cognitive processes in individuals with FEP. METHODS: Systematic review and voxel-based meta-analysis of cross-sectional fMRI studies comparing neural responses to cognitive tasks between individuals with FEP and healthy controls (HC) according to PRISMA guidelines. RESULTS: Twenty-six studies were included, comprising 598 individuals with FEP and 567 HC. Individual studies reported statistically significant hypoactivation in the dorsolateral prefrontal cortex (6 studies), frontal lobe (8 studies), cingulate (6 studies) and insula (5 studies). The meta-analysis showed statistically significant hypoactivation in the left anterior insula, precuneus and bilateral striatum. CONCLUSIONS: While the studies tend to highlight frontal hypoactivation during cognitive tasks in FEP, our meta-analytic results show that the left precuneus and insula primarily display aberrant activation in FEP that may be associated with salience attribution to external stimuli and related to deficits in perception and regulation.

Precuneus and insular hypoactivation during cognitive processing in first-episode psychosis: Systematic review and meta-analysis of fMRI studies / Hipoactivación precúnea e insular durante el procesamiento cognitivo en el primer episodio psicótico: revisión sistemática y metaanálisis de estudios de fMRI

Introduction: The neural correlates of the cognitive dysfunction in first-episode psychosis (FEP) are still unclear. The present review and meta-analysis provide an update of the location of the abnormalities in the fMRI-measured brain response to cognitive processes in individuals with FEP.Methods: Systematic review and voxel-based meta-analysis of cross-sectional fMRI studies comparing neural responses to cognitive tasks between individuals with FEP and healthy controls (HC) according to PRISMA guidelines.Results: Twenty-six studies were included, comprising 598 individuals with FEP and 567 HC. Individual studies reported statistically significant hypoactivation in the dorsolateral prefrontal cortex (6 studies), frontal lobe (8 studies), cingulate (6 studies) and insula (5 studies). The meta-analysis showed statistically significant hypoactivation in the left anterior insula, precuneus and bilateral striatum.Conclusions: While the studies tend to highlight frontal hypoactivation during cognitive tasks in FEP, our meta-analytic results show that the left precuneus and insula primarily display aberrant activation in FEP that may be associated with salience attribution to external stimuli and related to deficits in perception and regulation. (AU)

Introducción:Los correlatos neurales de la disfunción cognitiva en el primer episodio psicótico (PEP) aún no están claros. Esta revisión y este metaanálisis proporcionan una actualización de la localización de las anormalidades en la respuesta cerebral medida por fMRI a los procesos cognitivos en individuos con PEP.Métodos: Revisión sistemática y metaanálisis basado en vóxeles de estudios cros-seccionales de fMRI que comparen respuestas neuronales a tareas cognitivas entre individuos con PEP y controles sanos de acuerdo con las guías PRISMA.Resultados: Se incluyeron 26 estudios, que comprendían 598 individuos con PEP y 567 controles sanos. Los estudios individuales reportaban hipoactivación estadísticamente significativa en la corteza prefrontal dorsolateral (6 estudios), el lóbulo frontal (8 estudios), el cíngulo (6 estudios) y la ínsula (5 estudios). El metaanálisis mostró hipoactivación estadísticamente significativa en la ínsula anterior izquierda, el precúneo y el cuerpo estriado bilateral.Conclusiones: Si bien los estudios tienden a resaltar la hipoactivación frontal durante las tareas cognitivas en PEP, nuestros resultados metaanalíticos muestran que el precúneo izquierdo y la ínsula presentan principalmente una activación aberrante en PEP que puede estar asociada con la atribución de saliencia a estímulos externos y relacionada con déficits en la percepción y la regulación. (AU)