Major depressive disorder (MDD) is a prevalent psychiatric condition; however, candidate neural substrates related to resilience to MDD remain unclear. Resting-state functional magnetic resonance imaging (fMRI) data were collected from 113 patients with MDD, 36 unaffected siblings, and 81 healthy controls (HCs). First, degree centrality (DC) analysis was performed to identify group differences. Next, regions showing significant DC differences were used as seeds for whole-brain functional connectivity (FC) analyses. Finally, associations between these significant brain regions and depressive symptom severity were examined separately within each participant group. DC in the medial frontal gyrus and the right precentral gyrus, as well as FC between the medial frontal gyrus and the right postcentral gyrus, exhibited the pattern: patients with MDD < HCs < unaffected siblings. Correlation analyses revealed no significant relationships between depressive symptom severity and DC or FC values. Unaffected siblings exhibited both the highest DC and the strongest FC related to the medial frontal gyrus. These neuroimaging findings provide further insight into the role of the medial frontal gyrus in potential resilience mechanisms and suggest potential directions for the prevention and treatment of MDD.

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

BackgroundNegative symptoms of schizophrenia are increasingly conceptualized as dynamic networks. While intermittent theta-burst stimulation (iTBS) targeting the dorsolateral prefrontal cortex shows promise for negative symptoms, its network-level mechanisms remain unclear. We hypothesized that iTBS induces specific temporal reorganization of symptom networks.MethodsA longitudinal symptom network analysis integrating cross-sectional and cross-lagged modeling was conducted across multiple timepoints. Negative symptoms were assessed at baseline and weeks 4, 8, and 12 using the Scale for the Assessment of Negative Symptoms (SANS). Between-group differences were estimated using bootstrap-based edge comparisons.ResultsNetwork reorganization followed a staged temporal pattern. Early differences occurred in the alogia–anhedonia edge. Later timepoints revealed significant between-group differences in affective flattening–attention (week 8) and affective flattening–avolition (week 12) edges. Affective flattening emerged as a key reorganization hub. Cross-lagged analysis showed that, in the iTBS group, baseline alogia, avolition, anhedonia, and attention predicted subsequent affective flattening, with alogia autoregressive strength increasing over time. The sham group showed only sparse cross-lagged effects. Group comparisons confirmed significantly stronger cross-lagged pathways to affective flattening in the iTBS group. Network changes were therefore characterized by evolving inter-symptom coupling.ConclusionsiTBS induces stage-dependent reorganization of the negative symptom network, anchored to a temporally stable affective flattening node, with selective recalibration of emotional expression–attentional control interactions. These findings align conceptually with our prior report of enhanced dorsolateral prefrontal cortex–lingual gyrus connectivity following iTBS.

BackgroundChildhood trauma may influence clinical presentation in first-episode schizophrenia (FES), but its specific associations with cognitive function and clinical symptoms remain unclear.MethodsSeventy-one FES participants and 62 healthy controls were assessed using the Childhood Trauma Questionnaire (CTQ-SF), MATRICS Consensus Cognitive Battery (MCCB), Positive and Negative Syndrome Scale (PANSS), and Calgary Depression Scale (CDSS). Group comparisons, Spearman correlations, hierarchical regression, and mediation analyses (PROCESS macro) were performed.ResultsFES participants reported significantly higher childhood trauma (except physical abuse) and performed worse on all MCCB domains (all *p* < 0.00625). Within the clinical group, those with childhood trauma (71.8%) showed nominally lower MCCB total scores (*p* = 0.042) and a trend toward higher negative symptoms (*p* = 0.083). Exploratory analyses indicated that physical neglect was associated with attention/vigilance (r = -0.54) and overall cognition (*r* = -0.69); physical abuse with social cognition (*r* = -0.54); sexual abuse with general psychopathology (*r* = 0.56). No independent associations of trauma subtypes were found in regression analyses. Attention/vigilance was significantly associated with negative symptoms (β = -0.43, *p* = 0.002) but did not mediate the trauma-symptom relationship.ConclusionFES participants report more childhood trauma and exhibit widespread cognitive impairment, with physical neglect most strongly linked to attentional deficits. Attention/vigilance was associated with negative symptoms, suggesting that trauma-informed cognitive rehabilitation may have potential value.

While individuals with schizophrenia (SZ) exhibit deficits in social cognition, the specific profile of these deficits across multiple domains and their relationship with clinical symptoms warrants further characterization. This study aimed to systematically assess key social-cognitive domains—theory of mind (ToM), emotion recognition, attributional style, and social perception—and examine their associations with psychopathology in SZ. Sixty-eight individuals with SZ and 68 matched healthy controls (HC) completed a comprehensive battery of social-cognitive measures, including the false-belief task (assessing first- and second-order ToM), the Faux Pas task, the emotional recognition task, the attributional style questionnaire, and the social perception scale. Clinical symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS). Compared to HC, individuals with SZ showed significant deficits across all social-cognitive measures. Specifically, the SZ group exhibited deficits in emotion recognition for all negative emotions (fear, anger, sadness, disgust) but not for happiness, and in attributional style for positive but not negative events. Correlation analyses identified a statistically significant inverse relationship between attributional stability for negative events (i.e., the tendency to attribute the causes of negative events to factors that are persistent over time) and PANSS general psychopathology scores (τ = −0.25, P < 0.043). Furthermore, no other social-cognitive domains (ToM, emotion recognition, social perception) showed significant correlations with any PANSS symptom dimensions. Network analysis further characterized second-order ToM as the core deficit, exhibiting the highest strength and centrality within the social-cognitive network, with mediation effects most pronounced for sadness and happiness recognition. These findings highlight second-order ToM as a core deficit in individuals with schizophrenia and suggest that a stable attributional style may be associated with a lower overall burden of general psychopathology. These social-cognitive domains may represent promising targets for future cognitive remediation interventions for people living with schizophrenia.

The aim of the study was to systematically examine the association between psychotic-like experiences (PLEs) and non-suicidal self-injury (NSSI) in community populations through meta-analysis, with a focus on prospective evidence regarding this association and potential psychosocial correlates. A comprehensive search was conducted in PubMed, PsycINFO, and Embase from inception to August 2025. Studies reporting quantitative data on the association between PLEs and NSSI in community populations were included. A random-effects meta-analysis was performed to estimate the pooled odds ratio (OR) with 95

Major depressive disorder (MDD) imposes significant global health burdens, yet its underlying neural mechanisms remain elusive. Traditional static functional metrics inadequately capture the brain’s dynamic nature, motivating the exploration of dynamic functional metrics to understand both the temporal and spatial reconfigurations of brain networks in MDD. Leveraging the Depression Imaging Research Consortium (DIRECT) dataset, this study conducted vertex-wise dynamic analyses in a large cohort of MDD patients (n = 1660) and healthy controls (n = 1341). We identified significant alterations in temporal stability across the brain, with MDD patients exhibiting increased stability in higher-order association areas (e.g., frontoparietal and default mode networks) and decreased stability in primary sensory-motor regions. Among the regions showing altered temporal stability, brain-symptom relationships were further explored. We identified a set of brain regions including the superior frontal gyrus, postcentral gyrus and superior insular sulcus, which were potentially involved in the common abnormal dFC network and associated with insomnia, feelings of guilt, and insight symptoms in MDD. By incorporating advanced vertex-wise dynamic functional analyses and a large sample size, this study provides insights into the neural mechanisms of MDD, emphasizing the value of dynamic approaches for identifying biomarkers. Future longitudinal and task-based studies are promising to elucidate causal relationships and refine personalized therapeutic interventions targeting specific dynamic dysfunctions in MDD.

Functional magnetic resonance imaging (fMRI) allows real-time observation of brain activity through blood oxygen level-dependent (BOLD) signals and is extensively used in studies related to sex classification, age estimation, behavioral measurements prediction, and mental disorder diagnosis. However, the application of deep learning techniques to brain fMRI analysis is hindered by the small sample size of fMRI datasets. Transfer learning offers a solution to this problem, but most existing approaches are designed for large-scale 2D natural images. The heterogeneity between 4D fMRI data and 2D natural images makes direct model transfer infeasible. This study proposes a novel geometric mapping-based fMRI transfer learning method that enables transfer learning from 2D natural images to 4D fMRI brain images, bridging the transfer learning gap between fMRI data and natural images. The proposed Multi-scale Multi-domain Feature Aggregation (MMFA) module extracts effective aggregated features and reduces the dimensionality of fMRI data to 3D space. By treating the cerebral cortex as a folded Riemannian manifold in 3D space and mapping it into 2D space using surface geometric mapping, we make the transfer learning from 2D natural images to 4D brain images possible. Moreover, the topological relationships of the cerebral cortex are maintained with our method, and calculations are performed along the Riemannian manifold of the brain, effectively addressing signal interference problems. The experimental results based on the Human Connectome Project (HCP) dataset demonstrate the effectiveness of the proposed method. Our method achieved state-of-the-art performance in sex classification, age estimation, and behavioral measurement prediction tasks. Moreover, we propose a cascaded transfer learning approach for depression diagnosis, and proved its effectiveness on 23 depression datasets. In summary, the proposed fMRI transfer learning method, which accounts for the structural characteristics of the brain, is promising for applying transfer learning from natural images to brain fMRI images, significantly enhancing the performance in various fMRI analysis tasks.

Importance:There is an urgent need for algorithm trials that address treatment steps in schizophrenia sequentially. Moreover, there is a debate about whether clozapine should be used after 1 failed antipsychotic drug trial. Objective:To investigate whether switching to clozapine is effective in patients with first-episode psychosis (FEP) who have not responded to 1 previous antipsychotic drug. Design, Setting, and Participants:This was a sequential, assessor-blind trial with 2 randomizations conducted across 7 centers in China from February 2019 to October 2022. Included were individuals aged 16 to 45 years and with FEP (schizophrenia, schizophreniform disorder, or schizoaffective disorder). In phase 1, patients with FEP were randomized to receive oral olanzapine, risperidone, amisulpride, aripiprazole, or perphenazine for 8 weeks. In phase 2, nonresponders were rerandomized to receive olanzapine, amisulpride, or clozapine for another 8 weeks. Responders entered a 1-year naturalistic follow-up. Study data were analyzed from February to August 2025. Interventions:Specific antipsychotic drugs. Main Outcomes and Measures:The primary outcomes were as follows (1) symptomatic response, defined as the proportion of patients achieving a greater than or equal to 40% reduction in Positive and Negative Syndrome Scale (PANSS) total score and (2) time to all-cause discontinuation, defined as discontinuation of antipsychotic drugs for any reason. Results:A total of 762 participants were randomized, and 654 (mean [SD] age, 26.9 [7.5] years; 328 male [50.2%]) were eligible for the study. Of the eligible participants, 556 (85.4%) completed phase 1, and 359 (55.1%) responded to treatment. Response rates were 60.5% (78 of 129) for olanzapine, 63.4% (83 of 131) for risperidone, 61.8% (81 of 131) for amisulpride, 44.3% (58 of 131) for aripiprazole, and 45.7% (59 of 129) for perphenazine (χ2 = 18.3; P = .001). In phase 2, 111 nonresponders were rerandomized (41 taking olanzapine, 38 taking amisulpride, and 32 taking clozapine). A total of 92 patients (82.9%) completed phase 2, and the following achieved a response: 13 (31.7%) taking olanzapine vs 17 (44.7%) taking amisulpride and 20 (62.5%) taking clozapine (χ2 = 6.9; P = .03). Conclusions and Relevance:The majority of patients with FEP responded to an initial antipsychotic drug trial, with risperidone and amisulpride being superior to aripiprazole and perphenazine. In those who initially did not respond to antipsychotic treatment, clozapine was more efficacious than olanzapine and amisulpride based on the PANSS ratings criteria outcome. This study provides some evidence for clinicians to consider regarding use of clozapine as the next sequential treatment after patients have failed an adequate trial with 1 of the more traditional antipsychotics. Trial Registration:ClinicalTrials.gov Identifier: NCT03510325.

This randomized clinical trial investigates if clozapine is more efficacious than olanzapine or amisulpride in patients who fail to respond to an initial antipsychotic drug trial. QuestionsIs clozapine more efficacious than olanzapine or amisulpride in patients who fail to respond to an initial antipsychotic drug trial?FindingsIn this randomized clinical trial including 654 participants, clozapine was found to be more efficacious than olanzapine or amisulpride, and there was no clear difference in all-cause treatment discontinuation between treatment groups.MeaningClozapine may be considered as a preferred subsequent option for patients with first-episode psychosis who have not responded to an initial antipsychotic drug. ImportanceThere is an urgent need for algorithm trials that address treatment steps in schizophrenia sequentially. Moreover, there is a debate about whether clozapine should be used after 1 failed antipsychotic drug trial.ObjectiveTo investigate whether switching to clozapine is effective in patients with first-episode psychosis (FEP) who have not responded to 1 previous antipsychotic drug.Design, Setting, and ParticipantsThis was a sequential, assessor-blind trial with 2 randomizations conducted across 7 centers in China from February 2019 to October 2022. Included were individuals aged 16 to 45 years and with FEP (schizophrenia, schizophreniform disorder, or schizoaffective disorder). In phase 1, patients with FEP were randomized to receive oral olanzapine, risperidone, amisulpride, aripiprazole, or perphenazine for 8 weeks. In phase 2, nonresponders were rerandomized to receive olanzapine, amisulpride, or clozapine for another 8 weeks. Responders entered a 1-year naturalistic follow-up. Study data were analyzed from February to August 2025.InterventionsSpecific antipsychotic drugs.Main Outcomes and MeasuresThe primary outcomes were as follows (1) symptomatic response, defined as the proportion of patients achieving a greater than or equal to 40% reduction in Positive and Negative Syndrome Scale (PANSS) total score and (2) time to all-cause discontinuation, defined as discontinuation of antipsychotic drugs for any reason.ResultsA total of 762 participants were randomized, and 654 (mean [SD] age, 26.9 [7.5] years; 328 male [50.2%]) were eligible for the study. Of the eligible participants, 556 (85.4%) completed phase 1, and 359 (55.1%) responded to treatment. Response rates were 60.5% (78 of 129) for olanzapine, 63.4% (83 of 131) for risperidone, 61.8% (81 of 131) for amisulpride, 44.3% (58 of 131) for aripiprazole, and 45.7% (59 of 129) for perphenazine (chi 2 = 18.3; P = .001). In phase 2, 111 nonresponders were rerandomized (41 taking olanzapine, 38 taking amisulpride, and 32 taking clozapine). A total of 92 patients (82.9%) completed phase 2, and the following achieved a response: 13 (31.7%) taking olanzapine vs 17 (44.7%) taking amisulpride and 20 (62.5%) taking clozapine (chi 2 = 6.9; P = .03).Conclusions and RelevanceThe majority of patients with FEP responded to an initial antipsychotic drug trial, with risperidone and amisulpride being superior to aripiprazole and perphenazine. In those who initially did not respond to antipsychotic treatment, clozapine was more efficacious than olanzapine and amisulpride based on the PANSS ratings criteria outcome. This study provides some evidence for clinicians to consider regarding use of clozapine as the next sequential treatment after patients have failed an adequate trial with 1 of the more traditional antipsychotics.Trial RegistrationClinicalTrials.gov Identifier: NCT03510325

Objective Although previous studies have reported structural brain alterations in major depressive disorder (MDD) patients at risk of suicide, no wide consensus has been reached. This study aimed to elucidate structural brain differences between MDD patients with and without suicide risk using data from the DIRECT Consortium, advancing our understanding of the neurophysiological mechanisms underlying suicide risk in MDD patients. Methods A total of 203 healthy controls (HCs), 208 MDD patients without suicide risk (MDD-NSR), and 376 MDD patients with suicide risk (MDD-SR) were included. T1-weighted MRI data were processed using DPABISurf to quantify cortical surface area, thickness, and cortical gray matter (CGM) volume. Results The MDD-SR and MDD-NSR groups demonstrated reduced surface area in the right orbitofrontal cortex (OFC), and reduced CGM volume in the left ACC and the right OFC compared with the HC group. The left ACC CGM volume decreased in a gradient, with the MDD-SR group showing significantly lower values than both the MDD-NSR and HC groups. While the SVM model showed limited differentiation between MDD-SR and MDD-NSR, the left ACC CGM volume was identified as the most critical feature in SHAP analysis. Conclusion MDD patients with suicide risk exhibited alterations in cortical surface area and CGM volume in the frontal lobe. The CGM volume reduction in the left ACC may serve as a potential biomarker for predicting suicide risk in MDD patients.

BACKGROUND:Identifying neuroimaging correlates of insomnia severity could provide insights into the underlying biological mechanisms of major depressive disorder (MDD). However, related findings remain inconsistent, and the functional connectivity patterns associated with insomnia severity are unclear. METHODS:This study analyzed resting-state fMRI data from 385 patients with MDD and 336 healthy controls (HCs) sourced from nine sites of the DIRECT Consortium. Patients were stratified into high insomnia (MDDHI; HAMD insomnia subscale ≥ 4, n = 226) and low insomnia (MDDLI; HAMD insomnia subscale ≤ 3, n = 159) groups. Among patients with MDDHI, MDDLI and HCs, we first examined network-level functional connectivity abnormalities using the Craddock 200 atlas, and then local brain function was assessed using the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo) and degree centrality (DC). Finally, we adopted multiple analytical approaches to verify the robustness of the significant findings. RESULTS:Compared to both patients with MDDHI and HCs, patients with MDDLI exhibited significantly reduced functional connectivity between the left angular gyrus (AG) and the right middle frontal gyrus (MFG). Both patients with MDDHI and MDDLI showed significantly decreased ALFF and ReHo values relative to HCs across multiple brain regions, including bilateral angular gyrus/precuneus/cerebellum posterior lobe and so on. For DC, patients with MDDHI showed significantly decreased values relative to HCs in all identified clusters, whereas patients with MDDLI showed significant DC reductions in a subset of these clusters. When these results were validated using multiple analytical approaches, the primary findings remained consistent. CONCLUSIONS:Reduced functional connectivity between the left AG and the right MFG may be a candidate neuroimaging marker for sleep-related heterogeneity in MDD. However, widespread local brain function abnormalities may reflect core depressive pathology of MDD. These findings advance our understanding of the neurobiology of MDD.

Major depressive disorder (MDD) has been increasingly characterized as a network dysconnectivity syndrome. Although single-subject morphological networks are advantageous in studying the brain connectome, extant research on MDD is limited by either small samples or a lack of integration of multi-feature across different morphological features. We used the largest structural MRI data from 1442 MDD patients and 1277 controls to construct individual-level cortical morphological networks based on cortical thickness (CT), cortical volume (CV), surface area (SA), and sulcal depth (SD). Group comparisons in interregional morphological connectivity (MC) and graph-theoretical nodal properties were performed. Furthermore, support vector machine (SVM) was applied to evaluate whether the network alterations could distinguish patients from controls. As a result, MDD patients presented widespread alterations in MC, with distinct alteration patterns observed across four morphological networks. Specifically, CT-based networks exhibited reduced MC primarily within and between higher-order networks involving the default mode and frontoparietal networks, whereas CV-based networks showed increased MC predominantly within the default mode network. By contrast, both SA- and SD-based networks demonstrated enhanced MC mainly within and between lower-order networks implicating the somatomotor and visual networks. Similar patterns of MC alterations were observed in first-episode, drug-naive MDD patients. Concurrently, nodal property analysis revealed increased betweenness centrality in multiple cortical regions in MDD. Moreover, SVM models based on the altered MC achieved moderate-to-good classification performance in distinguishing patients from controls. Overall, our findings of individual-level morphological network alterations in depressed patients may corroborate the dysconnectivity hypothesis of MDD and could further inform its more accurate diagnosis.

Background:Suicide is the primary cause of death in patients with major depressive disorder (MDD) or bipolar disorder (BD). Among various personality traits, neuroticism is particularly relevant to suicide risk. However, its role in MDD and BD has not been examined sufficiently. This study characterized neuroticism in patients with MDD or BD, and analyzed the association between neuroticism and suicide risk in these patients. Methods:This study collected demographic information and personality traits of MDD and BD patients. Group differences were assessed using t-tests, chi-square tests, and Mann-Whitney U tests. To identify factors associated with suicide risk, correlation analysis was first conducted, followed by bivariate and generalized ordered logistic regression for significant variables, including neuroticism. Sensitivity analyses were performed by progressively excluding potential confounders to evaluate the robustness of neuroticism's effect. Additionally, simple mediation analyses using a bootstrap approach were conducted to examine whether depressive symptoms mediated the association between neuroticism and suicide risk in MDD and BD separately. A two-tailed P < 0.05 was considered statistically significant. Results:The study population comprised 88 MDD patients and 90 BD patients. Lifetime suicide risk was present in 39.3% of the study population. In the entire sample, neuroticism was significantly associated with both lifetime (r = 0.18, P = 0.018) and current suicide risk (r = 0.17, P = 0.024). In patients with MDD, through mediation analysis, neuroticism predicted both depressive symptom severity (B = 0.25, P < 0.001) and current suicide risk (B = 0.02, P = 0.022), while also indirectly influencing current suicide risk through depressive symptoms (B = 0.01, 95% CI = 0.01-0.02). In BD patients, neuroticism predicted depressive symptoms (B = 0.13, P = 0.002) but not current suicide risk (B < 0.01, P = 0.714), while depressive symptoms fully mediated this relationship (B = 0.06, P < 0.001). Conclusion:Neuroticism plays a significant role in influencing suicide risk among MDD and BD, through its effect on depressive symptoms. Interventions for neuroticism can reduce depressive symptoms and suicide risk. This highlights the necessity of identification and management of neuroticism in suicide prevention strategies.

Abstract Background Prospective memory (PM) deficit is one of the most common cognitive impairments of patients with schizophrenia spectrum disorders (SSDs). PM deficits have been associated with social functioning impairment, poor adherence to drugs and adverse clinical outcome. Previous studies have atributed the PM deficits in schizophrenia to the failure of cue detection and intention retrieval. In healthy people, these cognitive processes reflect the ability of strategic monitoring, which heavily rely on the functional network of anterior prefrontal cortex (aPFC) and related brain regions. This suggests that PM deficits in SSDs patients may be due to aPFC functional connectivity impairments. Aims & Objectives The aim of the present study is to compare the resting-state aPFC functional connectivity between patients with SSDs and healthy controls, and to examine whether the PM deficits in SSDs patients are due to aPFC functional connectivity impairments. Method Sixty-three SSDs patients and 32 healthy controls (HCs) formed the study sample. Time- and event-based PM (TBPM and EBPM) performance were measured with the Chinese version of the Cambridge Prospective Memory Test (C-CAMPROMPT). Patients' clinical symptoms were evaluated with the Positive and Negative Symptom Scale (PANSS). All participants underwent resting-state functional magnetic resonance imaging (fMRI). Left and right BA 10 were chosen as seeds to perform seed-based whole brain voxels resting-state functional connectivity analyses. Results Compared to HCs, SSDs patients demonstrated significantly worse PM performance and attenuated functional connectivity between right aPFC and precuneus (x= -9, y= -51, z=45), a key hub of the default mode. The correlation analysis results showed that the aforementioned functional connectivity in the SSDs group was significantly positively correlated with EBPM parformance (r= 0.319, P=0.013). No significant correlation analysis results were found between the functional connectivity and EBPM within the HC group. Discussion & Conclusion The results indicate that aPFC resting-state networks are affected in SSDs patients. The reduced magnitude of resting state functional connectivity between right aPFC and precuneus is a key marker of information processing failure underlying PM impairments in SSDs patients.

OBJECTIVES:Working memory impairments represent fundamental cognitive deficits in schizophrenia (SZ). Although transcranial direct current stimulation (tDCS) has demonstrated potential in enhancing working memory in SZ, its neural mechanisms and optimized strategies remain to be elucidated. This study explored the effects of tDCS with concurrent cognitive performance targeting the dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC) on electroencephalography (EEG) microstates in SZ. METHODS:This analysis is based on a randomized, double-blind clinical trial of tDCS with concurrent cognitive performance in SZ. Sixty participants were assigned to three groups: active DLPFC, active PPC, and sham stimulation groups. tDCS was administered concurrently with a visual working memory task. The spatial span test was used to assess working memory at baseline, week 1, and week 2, with resting-state EEG data collected at each time point. RESULTS:No significant differences were detected in the characteristics of the four microstates (A, B, C, and D) at baseline. Compared with the sham stimulation group, the active DLPFC and PPC groups exhibited significant improvements in the duration, occurrence, and coverage of microstate B at week 2. However, the changes in the parameters of microstate B at week 2 were not significantly correlated with working memory improvement. CONCLUSIONS:This study suggests that neuromodulation targeting different nodes within the task-induced network may influence the same subnetworks in SZ. This work provides new insights into network-based interventions and contributes to the development of multitarget intervention strategies under task conditions.

OBJECTIVE:Antipsychotic drugs are the mainstay of schizophrenia treatment; yet, controversy persists regarding their relative efficacy and side effects, and guideline recommendations on efficacy differences are particularly vague. The aim of this trial was to compare seven antipsychotics in acutely ill patients with schizophrenia. METHODS:The authors performed a multicenter (32 hospitals), industry-independent, parallel, assessor-blinded, flexible-dosage randomized trial (Schizophrenia in Non-Occidental Participants). Eligible inpatients 18-45 years of age with schizophrenia experiencing acute exacerbation were recruited and randomized to 6 weeks of monotherapy with one of seven antipsychotic drugs: olanzapine, risperidone, quetiapine, aripiprazole, ziprasidone, perphenazine, and haloperidol. RESULTS:A total of 3,067 patients were randomized, of whom 82% completed follow-up. The mixed model indicated significant differences in the primary outcome percentage change in Positive and Negative Syndrome Scale (PANSS) score between the antipsychotics. At week 6, olanzapine and risperidone showed a significantly higher percentage change in PANSS score than aripiprazole, ziprasidone, and quetiapine (mean differences: 5.52-7.93) but not haloperidol or perphenazine. Olanzapine was associated with the highest risk of weight gain (relative risk: 1.44-3.22). Aripiprazole was associated with lower risk of hyperprolactinemia than all the other drugs (relative risks: 0.11-0.21). Ziprasidone and aripiprazole were associated with lower risks of weight gain and metabolic side effects. Haloperidol was associated with a higher risk of extrapyramidal symptoms than all other drugs (relative risks: 0.13-0.61). Aripiprazole was least sedating (relative risks: 0.30-0.39). Olanzapine and risperidone showed lower all-cause discontinuation rates than ziprasidone and haloperidol (hazard ratios: 0.61-0.73). CONCLUSIONS:This trial fills important knowledge gaps in acute antipsychotic treatment of schizophrenia. It confirms hierarchies in efficacy and side effects of antipsychotics from related evidence.

BACKGROUND:The efficacy of non-invasive brain stimulation in ameliorating schizophrenia's negative symptoms remains to be validated. The mesocortical pathway, mostly comprising the ventral tegmental area (VTA) and prefrontal cortex, is the core neural circuit underlying negative symptoms. This study aimed to assess the clinical and biological effects of accelerated intermittent theta burst stimulation (iTBS) targeted to the dorsolateral prefrontal cortex (dlPFC), guided by personalised dlPFC-VTA functional connectivity (FC). METHODS:Eighty schizophrenia patients with predominant negative symptoms received 40 sessions of either active (n = 40) or sham (n = 40) accelerated iTBS (1800 pulses) in two weeks, targeting the region of the left dlPFC most functionally correlated with the VTA. Clinical and cognitive follow-ups occurred at week 4, 8, and 12. The primary outcome was the alteration in PANSS negative symptom (PANSS-NS) scores at week 4, while secondary outcomes included additional clinical, cognitive assessments and neuroimaging alterations. RESULTS:At week 4, the active group showed a significant reduction in PANSS-NS compared to the sham group, with a significant group × time interaction effect (P < 0.001, mean difference = 4.10, Cohen's d = 0.83). At week 2, compared to the sham group, the active group exhibited reduced left temporal middle gyrus (TMG) (r = -0.29, p = 0.01) activation and FC between the VTA and left TMG (r = -0.34, p = 0.003), and both were negatively correlated with PANSS-NS changes in both groups. CONCLUSION:Accelerated iTBS targeting the personalised region determined by dlPFC-VTA FC is an effective intervention to alleviate negative symptoms of schizophrenia.

Background: This study aimed to investigate the relationship between abnormal functional connectivity (FC) patterns in the reward circuitry of the brain and negative symptoms and cognitive impairment in individuals with first-episode schizophrenia (FES). Methods: Fifty-two FES patients and 59 healthy controls (HCs) were recruited for this cross-sectional study. Thirteen brain regions associated with the reward circuitry were defined as regions of interest (ROIs), and FCs between each ROI and the whole brain were analyzed. Cognitive function was assessed by the MATRICS Consensus Cognitive Battery. Results: Within-network analyses indicated that, compared to HCs, FES patients exhibited increased FCs between the left ventrolateral prefrontal cortex and left thalamus, which negatively correlated with negative symptoms. Whole-brain analyses revealed some weakened FCs in FES patients compared to those in HCs. The FCs between the right nucleus accumbens and right insular lobe and between the right putamen and both the left anterior cingulate cortex and left precentral gyrus positively correlated with attention/vigilance only in HCs. Additionally, the FC between the left putamen nucleus and left inferior frontal gyrus positively correlated with verbal and visual learning only in HCs. Conclusion: These findings highlight the differential FC patterns in the reward circuitry in FES patients and indicate that the enhanced within-network FC observed in these patients may contribute to their negative symptoms. The absence of correlations between certain FCs and attention, verbal learning, and visual learning can be explained by decoupling of the reward circuitry from the cognitive control brain regions.