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Abstract Cognitive deficits in schizophrenia are a major contributor to poor functional outcomes and everyday functioning, making them a promising therapeutic target. Recent years have witnessed a dramatic increase in the use of digital interventions, such as game-based therapy, targeting various domains of cognition to treat mental disorders. Game-based digital interventions have been suggested to have therapeutic value in health care for people with schizophrenia. To support this idea, a novel, online training program (Komori Life) that targets cognitive deficits in schizophrenia was tested for feasibility of use and initial efficiency. Inpatients with schizophrenia were randomized to complete 20 sessions of either Komori Life (N = 40 completers) or treatment as usual (N = 40 completers). Cognitive and clinical assessments were performed at enrollment and after completion of the training intervention for all patients. In addition, 32 healthy volunteers were recruited as controls, and an eye-tracking paradigm was employed to assess attentional biases to emotional information before and after game intervention for all subjects. The results showed that there were no group differences in cognitive or clinical assessments at baseline between the two patient groups. After game training, there were still no group × time interactions on cognitive or clinical assessment scores. Regarding eye movement measurements, both patient groups showed increased attention to threatening stimuli compared to healthy controls in terms of attentional maintenance at baseline. After game training, the game training group revealed greater improvement in attentional bias towards threatening scenes (decreased percentage of total duration and percentage of total fixations towards threatening stimuli) relative to the treatment as usual group. Moreover, our results partially indicated that training effectiveness was associated with cognitive improvement and that heightened attentional maintenance to threats was associated with worse cognitive performance. This study provides initial evidence that a remote, online cognitive training program is feasible and effective in improving cognitive function in schizophrenia. This form of training may serve as a complementary therapy to existing psychiatric care. Clinical trial registration: the trial is registered at http://www.chictr.org.cn , identifier ChiCTR2100048403.

Abstract Background Increasing evidence suggested that immune abnormalities involved in the pathophysiology of schizophrenia. However, the relationship between immunity and clinical features has not been clarified. The aim of this study was to measure the plasma levels of tumor necrosis factor alpha (TNF-α) and soluble TNF-α receptor 1 (sTNF-α R1) and to investigate their association with agitation in first episode patients with schizophrenia (FEPS). Methods The plasma TNF-α and sTNF-α R1 levels were measured using sandwich enzyme-linked immunosorbent assay (ELISA) in the FEPS with (n = 36) and without agitation (n = 49) symptoms, and healthy controls (HCs, n = 54). The psychopathology was assessed by the Positive and Negative Syndrome Scale (PANSS), and the agitation symptoms were evaluated by the PANSS excitatory component (PANSS-EC). Results The plasma TNF-α levels in patients with and without agitation symptoms were significantly higher than those in HCs. The patients with agitation had significantly higher plasma TNF-α levels compared to the patients without agitation. There were no significant differences in the sTNF-α R1 levels among the three groups. Furthermore, the plasma TNF-α levels were positively correlated with the PANSS total score, Positive and General psychopathological subscores, and PANSS-EC score in the FEPS, but the relationships were not found for the plasma sTNF-α R1 levels. Conclusions These results suggested that TNF-α might play an important role in the onset and development of agitation symptoms of schizophrenia.

Abstract Background Clozapine is an off-label drug used in most countries to prevent suicide in individuals with schizophrenia. However, few studies have reported real-world prescription practices. This study aimed to explore the association between a history of suicidal behavior and clozapine prescribing during eight weeks of hospitalization for individuals with early-stage schizophrenia. Methods This observational cohort study used routine health data collected from a mental health hospital in Beijing, China. The study included 1057 inpatients who had schizophrenia onset within 3 years. History of suicidal behavior was coded from reviewing medical notes according to the Columbia Suicide Severity Rating Scale. Information on antipsychotic use during hospitalization was extracted from the prescription records. Time to clozapine use was analyzed using Cox regression models adjusted for sociodemographic and clinical covariates. Results The prevalence rates of self-harm, suicidal behavior, and suicide attempt were 12.3%, 7.5%, and 5.4%, respectively. A history of self-harm history was positively associated with clozapine uses upon admission (4.1% vs. 0.8%, exact p = 0.009). Among those who had not used clozapine and had no clozapine contraindication, A history of suicidal behavior increased the possibility of switch to clozapine within 56 days after admission (Hazard Ratio[95% CI], 6.09[2.08–17.83]) or during hospitalization (4.18[1.62–10.78]). Conclusion The use of clozapine for early-stage schizophrenia was more frequent among those with suicidal behavior than among those without suicidal behavior in China, although the drug instructions do not label its use for suicide risk.

Abstract Background Objective and quantifiable markers are crucial for developing novel therapeutics for mental disorders by 1) stratifying clinically similar patients with different underlying neurobiological deficits and 2) objectively tracking disease trajectory and treatment response. Schizophrenia is often confounded with other psychiatric disorders, especially bipolar disorder, if based on cross-sectional symptoms. Awake and sleep EEG have shown promise in identifying neurophysiological differences as biomarkers for schizophrenia. However, most previous studies, while useful, were conducted in European and American populations, had small sample sizes, and utilized varying analytic methods, limiting comprehensive analyses or generalizability to diverse human populations. Furthermore, the extent to which wake and sleep neurophysiology metrics correlate with each other and with symptom severity or cognitive impairment remains unresolved. Moreover, how these neurophysiological markers compare across psychiatric conditions is not well characterized. The utility of biomarkers in clinical trials and practice would be significantly advanced by well-powered transdiagnostic studies. The Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project aims to address these questions through a large, multi-center cohort study involving East Asian populations. To promote transparency and reproducibility, we describe the protocol for the GRINS project. Methods The research procedure consists of an initial screening interview followed by three subsequent sessions: an introductory interview, an evaluation visit, and an overnight neurophysiological recording session. Data from multiple domains, including demographic and clinical characteristics, behavioral performance (cognitive tasks, motor sequence tasks), and neurophysiological metrics (both awake and sleep electroencephalography), are collected by research groups specialized in each domain. Conclusion Pilot results from the GRINS project demonstrate the feasibility of this study protocol and highlight the importance of such research, as well as its potential to study a broader range of patients with psychiatric conditions. Through GRINS, we are generating a valuable dataset across multiple domains to identify neurophysiological markers of schizophrenia individually and in combination. By applying this protocol to related mental disorders often confounded with each other, we can gather information that offers insight into the neurophysiological characteristics and underlying mechanisms of these severe conditions, informing objective diagnosis, stratification for clinical research, and ultimately, the development of better-targeted treatment matching in the clinic.

Abstract Background The trajectory of attention-deficit hyperactivity disorder (ADHD) symptoms in children and adolescents, encompassing descending, stable, and ascending patterns, delineates their ADHD status as remission, persistence or late onset. However, the neural and genetic underpinnings governing the trajectory of ADHD remain inadequately elucidated. Methods In this study, we employed neuroimaging techniques, behavioral assessments, and genetic analyses on a cohort of 487 children aged 6–15 from the Children School Functions and Brain Development project at baseline and two follow-up tests for 1 year each (interval 1: 1.14 ± 0.32 years; interval 2: 1.14 ± 0.30 years). We applied a Latent class mixed model (LCMM) to identify the developmental trajectory of ADHD symptoms in children and adolescents, while investigating the neural correlates through gray matter volume (GMV) analysis and exploring the genetic underpinnings using polygenic risk scores (PRS). Results This study identified three distinct trajectories (ascending-high, stable-low, and descending-medium) of ADHD symptoms from childhood through adolescence. Utilizing the linear mixed-effects (LME) model, we discovered that attention hub regions served as the neural basis for these three developmental trajectories. These regions encompassed the left anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), responsible for inhibitory control; the right inferior parietal lobule (IPL), which facilitated conscious focus on exogenous stimuli; and the bilateral middle frontal gyrus/precentral gyrus (MFG/PCG), accountable for regulating both dorsal and ventral attention networks while playing a crucial role in flexible modulation of endogenous and extrinsic attention. Furthermore, our findings revealed that individuals in the ascending-high group exhibited the highest PRS for ADHD, followed by those in the descending-medium group, with individuals in the stable-low group displaying the lowest PRS. Notably, both ascending-high and descending-medium groups had significantly higher PRS compared to the stable-low group. Conclusions The developmental trajectory of ADHD symptoms in the general population throughout childhood and adolescence can be reliably classified into ascending-high, stable-low, and descending-medium groups. The bilateral MFG/PCG, left ACC/mPFC, and right IPL may serve as crucial brain regions involved in attention processing, potentially determining these trajectories. Furthermore, the ascending-high pattern of ADHD symptoms exhibited the highest PRS for ADHD.

Brain development is characterized by an increase in structural and functional segregation, which supports the specialization of cognitive processes within the context of network neuroscience. In this study, we investigated age-related changes in morphological segregation using individual Regional Radiomics Similarity Networks (R2SNs) constructed with a longitudinal dataset of 494 T1-weighted MR scans from 309 typically developing children aged 6.2 to 13 years at baseline. Segertation indices were defined as the relative difference in connectivity strengths within and between modules and cacluated at the global, system and local levels. Linear mixed-effect models revealed longitudinal increases in both global and system segregation indices, particularly within the limbic and dorsal attention network, and decreases within the ventral attention network. Superior performance in working memory and inhibitory control was associated with higher system-level segregation indices in default, frontoparietal, ventral attention, somatomotor and subcortical systems, and lower local segregation indices in visual network regions, regardless of age. Furthermore, gene enrichment analysis revealed correlations between age-related changes in local segregation indices and regional expression levels of genes related to developmental processes. These findings provide novel insights into typical brain developmental changes using R2SN-derived segregation indices, offering a valuable tool for understanding human brain structural and cognitive maturation.

Background: Aberrant functional connectivity is a hallmark of schizophrenia. The precise nature and mechanism of dysconnectivity in schizophrenia remains unclear, but evidence suggests that dysconnectivity is different in wake versus sleep. Microstate analysis uses electroencephalography (EEG) to investigate large-scale patterns of coordinated brain activity by clustering EEG data into a small set of recurring spatial patterns, or microstates. We hypothesized that this technique would allow us to probe connectivity between brain networks at a fine temporal resolution and uncover previously unknown sleep-specific dysconnectivity. Methods: We studied microstates during sleep in patients with schizophrenia by analyzing high-density EEG sleep data from 114 patients with schizophrenia and 79 control participants. We used a polarity-insensitive k-means analysis to extract a set of 6 microstate topographies. Results: These 6 states included 4 widely reported canonical microstates. In patients and control participants, falling asleep was characterized by a shift from microstates A, B, and C to microstates D, E, and F. Microstate F was decreased in patients during wake, and microstate E was decreased in patients during sleep. The complexity of microstate transitions was greater in patients than control participants during wake, but this reversed during sleep. Conclusions: Our findings reveal behavioral state–dependent patterns of cortical dysconnectivity in schizophrenia. Furthermore, these findings are largely unrelated to previous sleep-related EEG markers of schizophrenia such as decreased sleep spindles. Therefore, these findings are driven by previously undescribed sleep-related pathology in schizophrenia.

IntroductionA multimodal persistent topological feature extraction and classification method is proposed to enhance the recognition accuracy of first-episode schizophrenia patients. This approach addresses the limitations of traditional higher-order brain network analyses that rely on single persistent features (e.g., persistent images).MethodsThe study utilized resting-state EEG data from 198 subjects recruited at Huilongguan Hospital in Beijing, comprising 102 males and 96 females, with a mean age of 30 years and mean education of 14 years. Persistent topological features were extracted using adaptive thresholding during persistent homology (PH) filtrations. The distribution of these features was visualized through heatmaps and persistence entropies, while the generation process was elucidated using Betti curves and persistence landscapes.ResultsThe classification performance of the multimodal persistent topological features was assessed using various machine learning classifiers. The classifier yielding the highest performance was selected for comparison with traditional brain network features derived from graph theory and single persistent topological features. The results revealed significant topological changes in first-episode schizophrenia patients throughout the persistent homology filtering compared to healthy subjects. The univariate feature selection algorithm achieved a classification accuracy of 94.6% with a combination of attributes meeting the criterion of AC ≥ 0.6.DiscussionThe proposed method demonstrates clinical significance for the early identification and diagnosis of first-episode schizophrenia patients, offering a new research perspective for constructing higher-order functional connectivity networks and extracting topological structure features.

Abstract Despite the critical role of self-disturbance in psychiatric diagnosis and treatment, its diverse behavioral manifestations remain poorly understood. This investigation aimed to elucidate unique patterns of self-referential processing in affective disorders and first-episode schizophrenia. A total of 156 participants (41 first-episode schizophrenia [SZ], 33 bipolar disorder [BD], 44 major depressive disorder [MDD], and 38 healthy controls [HC]) engaged in a self-referential effect (SRE) task, assessing trait adjectives for self-descriptiveness, applicability to mother, or others, followed by an unexpected recognition test. All groups displayed preferential self- and mother-referential processing with no significant differences in recognition scores. However, MDD patients showed significantly enhanced self-referential recognition scores and increased bias compared to HC, first-episode SZ, and BD. The present study provides empirical evidence for increased self-focus in MDD and demonstrates that first-episode SZ and BD patients maintain intact self-referential processing abilities. These findings refine our understanding of self-referential processing impairments across psychiatric conditions, suggesting that it could serve as a supplementary measure for assessing treatment response in first-episode SZ and potentially function as a discriminative diagnostic criterion between MDD and BD.

Abstract The substantia nigra (SN), subthalamic nucleus (STN), and red nucleus (RN) have been widely studied as important biomarkers of degenerative diseases. However, how they develop in childhood and adolescence and are affected by emotional behavior has not been studied thus far. This population-based longitudinal cohort study used data from a representative sample followed two to five times. Emotional and behavioral problems were assessed with the Strengths and Difficulties Questionnaire (SDQ). Linear mixed models were used to map developmental trajectories and behavioral regulation. Using an innovative automated image segmentation technique, we quantified the volumes and asymmetries of the SN, STN and RN with 1226 MRI scans of a large longitudinal sample of 667 subjects aged 6–15 years and mapped their developmental trajectories. The results showed that the absolute and relative volumes of the bilateral SN and right STN showed linear increases, while the absolute volume of the right RN and relative volume of the bilateral RN decreased linearly, these effects were not affected by gender. Hyperactivity/inattention weakened the increase in SN volume and reduced the absolute volume of the STN, conduct problems impeded the RN volume from decreasing, and emotional symptoms changed the direction of SN lateralization. This longitudinal cohort study mapped the developmental trajectories of SN, STN, and RN volumes and asymmetries from childhood to adolescence, and found the association of emotional symptoms, conduct problems, and hyperactivity/inattention with these trajectories, providing guidance for preventing and intervening in cognitive and emotional behavioral problems.

In the paper, we presented a data-driven optimal control method for the sub-satellite deployment of tethered satellite systems during the release phase, with the objective of reducing the libration angle fluctuation during system work. First, the dynamic equation of the tethered satellite system was established and processed dimensionless. Considering the presence of noise when sensors were put on the satellite to measure the libration angle, the corresponding state equation was derived. Next, we estimated the system state using an unscented Kalman filter and established a performance index and the Hamilton function. Based on the index, we designed an optimal control strategy and provided sufficient conditions for the asymptotic stability of the closed-loop system. We used critic-actor neural networks based on measurement data to implement the data-driven control algorithm to approximate the performance index function and the control policy, respectively. Finally, taking a tethered satellite system as an example, a simulation showed that the unscented Kalman filter can effectively estimate the system state and improve the impact of noise on the system, and the proposed optimal control strategy ensured that the tethered satellite system is stable, which shows the applicability and effectiveness of the control strategy in reducing the tether vibration of the disturbed system.

Abstract Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.

Abstract From childhood to adolescence, the spatiotemporal development pattern of the human brain white matter connectome and its underlying transcriptomic and cellular mechanisms remain largely unknown. With a longitudinal diffusion MRI cohort of 604 participants, we map the developmental trajectory of the white matter connectome from global to regional levels and identify that most brain network properties followed a linear developmental trajectory. Importantly, connectome-transcriptomic analysis reveals that the spatial development pattern of white matter connectome is potentially regulated by the transcriptomic architecture, with positively correlated genes involve in ion transport- and development-related pathways expressed in excitatory and inhibitory neurons, and negatively correlated genes enriches in synapse- and development-related pathways expressed in astrocytes, inhibitory neurons and microglia. Additionally, the macroscale developmental pattern is also associated with myelin content and thicknesses of specific laminas. These findings offer insights into the underlying genetics and neural mechanisms of macroscale white matter connectome development from childhood to adolescence.

Objectives. There is a significant correlation between EEG microstate and the neurophysiological basis of mental illness, brain state, and cognitive function. Given that the unclear relationship between network dynamics and different microstates, this paper utilized microstate, brain network, and control theories to understand the microstate characteristics of short-term memory task, aiming to mechanistically explain the most influential microstates and brain regions driving the abnormal changes in brain state transitions in patients with schizophrenia. Methods. We identified each microstate and analyzed the microstate abnormalities in schizophrenia patients during short-term memory tasks. Subsequently, the network dynamics underlying the primary microstates were studied to reveal the relationships between network dynamics and microstates. Finally, using control theory, we confirmed that the abnormal changes in brain state transitions in schizophrenia patients are driven by specific microstates and brain regions. Results. The frontal-occipital lobes activity of microstate D decreased significantly, but the left frontal lobe of microstate B increased significantly in schizophrenia, when the brain was moving toward the easy-to-reach states. However, the frontal-occipital lobes activity of microstate D decreased significantly in schizophrenia, when the brain was moving toward the hard-to-reach states. Microstate D showed that the right-frontal activity had a higher priority than the left-frontal, but microstate B showed that the left-frontal priority decreased significantly in schizophrenia, when changes occur in the synchronization state of the brain. Conclusions. In conclusion, microstate D may be a biomarker candidate of brain abnormal activity during the states transitions in schizophrenia, and microstate B may represent a compensatory mechanism that maintains brain function and exchanges information with other brain regions. Microstate and brain network provide complementary perspectives on the neurodynamics, offering potential insights into brain function in health and disease.

Risk-taking often occurs in childhood as a compex outcome influenced by individual, family, and social factors. The ability to govern risky decision-making in a balanced manner is a hallmark of the integrity of cognitive and affective development from childhood to adulthood. The Triadic Neural Systems Model posits that the nuanced coordination of motivational approach, avoidance and prefrontal control systems is crucial to regulate adaptive risk-taking and related behaviors. Although widely studied in adolescence and adulthood, how these systems develop in childhood remains elusive. Here, we show heterogenous age-related differences in the triadic neural systems involved in risky decision-making in 218 school-age children relative to 80 young adults. Children were generally less reward-seeking and less risk-taking than adults, and exhibited gradual increases in risk-taking behaviors from 6 to 12 years-old, which are associated with age-related differences in brain activation patterns underlying reward and risk processing. In comparison to adults, children exhibited weaker activation in control-related prefrontal systems, but stronger activation in reward-related striatal systems. Network analyses revealed that children showed greater reward-related functional connectivity within and between the triadic systems. Our findings support an immature and unbalanced developmental view of the core neurocognitive systems involved in risky decision-making and related behaviors in middle to late childhood.

Abstract Background Cognitive and emotional impairment are among the core features of schizophrenia; assessment of vocal emotion recognition may facilitate the detection of schizophrenia. We explored the differences between cognitive and social aspects of emotion using vocal emotion recognition and detailed clinical characterization. Methods Clinical symptoms and social and cognitive functioning were assessed by trained clinical psychiatrists. A vocal emotion perception test, including an assessment of emotion recognition and emotional intensity, was conducted. One-hundred-six patients with schizophrenia (SCZ) and 230 healthy controls (HCs) were recruited. Results Considering emotion recognition, scores for all emotion categories were significantly lower in SCZ compared to HC. Considering emotional intensity, scores for anger, calmness, sadness, and surprise were significantly lower in the SCZs. Vocal recognition patterns showed a trend of unification and simplification in SCZs. A direct correlation was confirmed between vocal recognition impairment and cognition. In diagnostic tests, only the total score of vocal emotion recognition was a reliable index for the presence of schizophrenia. Conclusions This study shows that patients with schizophrenia are characterized by impaired vocal emotion perception. Furthermore, explicit and implicit vocal emotion perception processing in individuals with schizophrenia are viewed as distinct entities. This study provides a voice recognition tool to facilitate and improve the diagnosis of schizophrenia.

Abstract Background Microglia are known to regulate stress and anxiety in both humans and animal models. Psychosocial stress is the most common risk factor for the development of schizophrenia. However, how microglia/brain macrophages contribute to schizophrenia is not well established. We hypothesized that effector molecules expressed in microglia/macrophages were involved in schizophrenia via regulating stress susceptibility. Methods We recruited a cohort of first episode schizophrenia (FES) patients (n = 51) and age- and sex-paired healthy controls (HCs) (n = 46) with evaluated stress perception. We performed blood RNA-sequencing (RNA-seq) and brain magnetic resonance imaging, and measured plasma level of colony stimulating factor 1 receptor (CSF1R). Furthermore, we studied a mouse model of chronic unpredictable stress (CUS) combined with a CSF1R inhibitor (CSF1Ri) (n = 9 ~ 10/group) on anxiety behaviours and microglial biology. Results FES patients showed higher scores of perceived stress scale (PSS, p

Predicting the risk for general psychopathology (the p factor) requires the examination of multiple factors ranging from brain to cognitive skills. While an increasing number of findings have reported the roles of the cerebral cortex and executive functions, it is much less clear whether and how the cerebellum and cognitive flexibility (a core component of executive function) may be associated with the risk for general psychopathology. Based on the data from more than 400 children aged 6–12 in the Children School Functions and Brain Development (CBD) Project, this study examined whether the left cerebellar lobule VIIb and its connectivity within the cerebellum may prospectively predict the risk for general psychopathology one year later and whether cognitive flexibility may mediate such predictions in school-age children. The reduced gray matter volume in the left cerebellar lobule VIIb and the increased connectivity of this region to the left cerebellar lobule VI prospectively predicted the risk for general psychopathology and was partially mediated by worse cognitive flexibility. Deficits in cognitive flexibility may play an important role in linking cerebellar structure and function to the risk for general psychopathology.

Abstract Background About 20–30% of patients with schizophrenia develop tardive dyskinesia (TD). Oxidative stress is one potential causes of TD. CYP2E1 is considered as an oxidative stress-related gene, however, no study has been reported on the DNA methylation levels of the CYP2E1 in schizophrenia or TD. Methods A total of 35 schizophrenia patients with TD, 35 schizophrenia patients without TD (NTD), and 35 health controls (HCs) were collected in Beijing, China. DNA was extracted from peripheral blood samples. The promoter methylation levels of CYP2E1 were detected using pyrosequencing. The generalized linear model (GLM) was used to examine the methylation levels of three CpG sites among three diagnostic groups (TD vs. NTD vs. HC). Results The average methylation levels were 8.8 ± 10.0, 14.5 ± 11.9 and 15.1 ± 11.3 in TD, NTD and HC groups, respectively. The F-test in GLM revealed overall differences in the average of methylation levels of three CpG sites among three diagnostic groups (p = 0.0227) and in the third CpG site (p = 0.0026). Furthermore, the TD group had lower average methylation levels than HC and NTD groups (p = 0.0115 and 0.0268, respectively). Specifically, TD group showed lower methylation levels in the third CpG site than HC and NTD groups (p = 0.0012 and 0.0072, respectively). Additionally, associations of the methylation levels with clinical features in the TD group were observed using Spearman correlation analysis. Conclusion This study provides the first evidence of DNA methylation levels in the promoter of CYP2E1 gene associated with schizophrenia and TD. The abnormal DNA methylation might serve as a potential mechanism for TD.

Abstract Accumulating evidence suggests that hypothalamic-pituitary-adrenal axis dysfunction might play an important role in the pathophysiology of schizophrenia. The aim of this study was to explore the cortisol response to psychological stress in patients with schizophrenia. In this study, patients with schizophrenia (n = 104) and healthy volunteers (n = 59) were asked to complete psychological stress challenge tasks, which included the Paced Auditory Serial Addition Task and Mirror-Tracing Persistence Task, and pre- and post-task saliva samples were collected to measure cortisol levels. Emotions and psychopathology were assessed by the Positive and Negative Affect Schedule and Positive and Negative Syndrome Scale. The results showed (1) that the cortisol response and negative emotions in patients with schizophrenia differed significantly from those in healthy volunteers, (2) there were significant interactions between the sampling time and diagnosis for saliva cortisol levels, (3) there were significant interactions between the scoring time and diagnosis for the negative affect score of the PANAS, and (4) the changes in salivary cortisol levels and negative affect scores before and after the psychological stress challenge tasks were not correlated with clinical symptoms in patients with schizophrenia. These findings indicated an abnormal cortisol profile in patients with schizophrenia, which might be a biological characteristic of the disease.

Abstract Background Working memory deficits are one of the core and most characteristic clinical features of cognitive impairment in schizophrenia. Cognitive training can improve the cognitive function of patients with schizophrenia. However, the overall and transfer effects of working memory treatment (WMT) require improvement. Numerous studies have confirmed that transcranial direct current stimulation (tDCS) enhances neuroplasticity in the brain, providing a new treatment approach for cognitive impairment in patients with schizophrenia. We hypothesize that a training mode combining “preheating” (tDCS, which changes the neural activity of working memory-related brain regions) and “ironing” (WMT) affords greater cognitive improvements than WMT alone. In addition, this study aims to examine the mechanisms underlying the superiority of tDCS combined with WMT in improving cognitive function in patients with schizophrenia. Methods This study will include 120 patients with schizophrenia aged 18–60 years. The patients will be randomized into four groups: the study group (tDCS + WMT), tDCS group (tDCS + simple response training, SRT), WMT group (sham tDCS + WMT), and control group (sham tDCS + SRT). Patients will receive 20-min, 2 mA sessions of active or sham tDCS twice a day on weekdays for 2 weeks. Each stimulation will be immediately followed by a 1 − 2-min rest and 40 min of WMT or SRT. The primary outcome is cognitive function, measured using Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and some subscales of the MATRICS Consensus Cognitive Battery (MCCB). The secondary outcomes are other behavioral measures, variations in brain imaging, and serum levels of brain-derived neurotrophic factor (BDNF). All outcomes will be measured at baseline, post-treatment, and 3-month follow-up, except for brain imaging and BDNF levels, which will be measured at baseline and post-treatment only. Discussion If tDCS combined with WMT results in significant improvements and prolonged effects on working memory, this method could be considered as a first-line clinical treatment for schizophrenia. Moreover, these results could provide evidence-based support for the development of other approaches to improve cognitive function in patients with schizophrenia, especially by enhancing WMT effects. Trial registration Chictr.org.cn; ChiCTR2200063844. Registered on September 19, 2022.

Abstract Objectives Executive function in people with depression is linked to the integrity of white matter fibers in the brain. We hypothesized that the maze tests in neuropsychological tests assessed reasoning and problem‐solving abilities dependent on the integrity of brain white matter fibers, and assessed this relationship using diffusion tensor imaging (DTI) in depressed patients and healthy controls. Methods Participants aged from 18 to 50 years were recruited from Zhumadian Second People's Hospital from July 2018 to August 2019. The sample included 33 clinically diagnosed individuals with major depressive disorder (MDD) and 24 healthy volunteers (HVs). All subjects underwent Neuropsychological assessment battery (NAB) maze tests and DTI. Tract‐based spatial statistics technology in FSL software was used to process DTI data, and threshold‐free cluster enhancement (TFCE) was used to perform multiple comparison corrections. The fractional anisotropy (FA) of white matter fibers in the MDD group and HVs group were compared and extracted. Pearson correlation was used to analyze the relationship between FA and NAB scores and HAMD scores. Results The mean NAB maze test score for the MDD group was lower than the HVs group, and the difference was statistically significant (F = 11.265, p = .037). The FA value of the body of corpus callosum and cerebral peduncle right in the depression group was lower than that in the healthy control group, and the difference was statistically significant (p

ObjectiveOur study aimed to investigate the associations between the serum level of kynurenine pathway (KP) metabolites and P50 auditory gating in non-smoking patients with first-episode schizophrenia (FES).Materials and methodsIn this study, 82 non-smoking patients with FES and 73 healthy controls (HC). P50 auditory gating was measured using a fully functional digital 64-channel EEG system, and the components included S1 amplitude, S2 amplitude, gating ratio (S2/S1), and amplitude difference (S1–S2). Serum levels of kynurenine and kynurenine acid were assessed using a combination of liquid chromatography with tandem mass spectrometry. Psychopathology was assessed by the Positive and Negative Syndrome Scale (PANSS).ResultsThe serum kynurenine (251.46 ± 65.93 ng/ml vs. 320.65 ± 65.89 ng/ml, t = –6.38, p < 0.001), and kynurenine acid levels (5.19 ± 2.22 ng/ml vs. 13.26 ± 4.23 ng/ml, t = –14.73, p < 0.001), S1 amplitude [2.88 (1.79, 3.78) μV vs. 3.08 (2.46, 4.56) μV, Z = –2.17, p = 0.030] and S1–S2 [1.60 (0.63, 2.49) μV vs. 1.92 (1.12, 2.93) μV, Z = –2.23, p = 0.026] in patients with FES were significantly lower than those in HC. The serum kynurenine and kynurenine acid levels were negatively associated with S1–S2 (r = –0.32, p = 0.004 and r = –0.42, p < 0.001; respectively) and positively correlated with S2/S1 ratio (r = 0.34, p = 0.002 and r = 0.35, p = 0.002; respectively) in patients.ConclusionOur findings suggested that neuroactive metabolites of the KP might play an important role in sensory gating deficit in first episode patients with schizophrenia. Furthermore, metabolites of the KP may be a new target for the treatment of cognitive impairments in schizophrenia.

With the development of network science and graph theory, brain network research has unique advantages in explaining those mental diseases, the neural mechanism of which is unclear. Additionally, it can provide a new perspective in revealing the pathophysiological mechanism of brain diseases from the system level. The selection of threshold plays an important role in brain networks construction. There are no generally accepted criteria for determining the proper threshold. Therefore, based on the topological data analysis of persistent homology theory, this study developed a multi-scale brain network modeling analysis method, which enables us to quantify various persistent topological features at different scales in a coherent manner. In this method, the Vietoris–Rips filtering algorithm is used to extract dynamic persistent topological features by gradually increasing the threshold in the range of full-scale distances. Subsequently, the persistent topological features are visualized using barcodes and persistence diagrams. Finally, the stability of persistent topological features is analyzed by calculating the Bottleneck distances and Wasserstein distances between the persistence diagrams. Experimental results show that compared with the existing methods, this method can extract the topological features of brain networks more accurately and improves the accuracy of diagnostic and classification. This work not only lays a foundation for exploring the higher-order topology of brain functional networks in schizophrenia patients, but also enhances the modeling ability of complex brain systems to better understand, analyze, and predict their dynamic behaviors.

Learning to read may result in network reorganization in the developing brain. The thalamus and striatum are two important subcortical structures involved in learning to read. It remains unclear whether the thalamus and striatum may form two independent cortico-subcortical reading pathways during reading acquisition. In this prospective longitudinal study, we aimed to identify whether there may be two independent cortico-subcortical reading pathways involving the thalamus and striatum and to examine the longitudinal predictions between these two cortico-subcortical pathways and reading development in school-age children using cross-lagged panel modeling. A total of 334 children aged 6–12 years completed two reading assessments and resting functional imaging scans at approximately 12-month intervals. The results showed that there were two independent cortico-subcortical pathways, the thalamo-occipital and fronto-striatal circuits. The former may be part of a visual pathway and was predicted longitudinally by reading ability, and the prediction was stronger in children in lower grades and weaker in children in higher grades. The latter may be part of a cognitive pathway related to attention, memory, and reasoning, which was bidirectionally predicted with reading ability, and the predictive effect gradually increasing with reading development. These results extend previous findings on the relationship between functional connectivity and reading competence in children, highlighting the dynamic relationships between the thalamo-occipital and fronto-striatal circuits and reading acquisition.

ObjectiveTo analyse differences in sex, age, depression, insomnia, psychological stress, resilience, and perceived social support among patients with medically unexplained symptoms (MUS) in a psychological clinic of a general hospital, and to explore the influencing factors of MUS.MethodsThis is a cross-sectional study. Seven hundred forty-six first-time patients were assessed with the integrated psychosomatic comprehensive evaluation system (IPS) to evaluate their MUS, depression, insomnia, psychological stress, resilience, and perceived social support. The psychological characteristics were compared with regard to sex and age group (45 years, high age group). The relationships between age and MUS were explored, and how psychological stress affects MUS was analyzed using the mediator effect model.ResultsDifferent age groups had significant differences in sex, MUS, depression, psychological stress, resilience, and perceived social support. In further pairwise comparison, no significant difference existed in depression, psychological stress, resilience and perceived social support in the middle and low age groups, depression and psychological stress were higher than those in the high age group, resilience and perceived social support were lower than those of the high age group. MUS were higher in the middle age group than in the low age group. No significant difference existed between the two groups and the high age group. Age, severity of MUS, and perceived social support were significantly different between the sexes. Differences in MUS between men and women in different age groups were analyzed using two-factor analysis of variance. It revealed no interaction between sex and different age groups on MUS. The main effect analysis showed that the effects of different age groups on MUS were statistically significant. Based on pairwise comparative analysis, the MUS score in the low age group was lower than that in the middle age group. To clarify a nonlinear relationship between age and MUS, threshold effect analysis was conducted. The results indicated that the piecewise linear regression model could better depict the relationship between age and MUS. The inflection point was at the age of 60 years. Before the age of 60 years, MUS increased with age. No significant correlation existed between age and MUS after the age of 60 years. To understand the influencing factors of MUS, the intermediary effect model was analyzed using MUS as the dependent variable, psychological stress as the independent variable, resilience as mediator variable M1, perceived social support as mediator variable M2, and depression as mediator variable M3. Resilience, perceived social support, and depression had significant mediator effects on the effects of psychological stress on MUS with a total indirect effect of 69.81%.ConclusionThe middle age group had greater MUS than the low age group. Before the age of 60 years, MUS increased with increasing age. Women had more severe MUS than men. Resilience, perceived social support, and depression had significant mediating effects on the effects of perceived stress on MUS. These findings suggest that clinicians should make more comprehensive and detailed evaluations and timely intervention for middle-aged and female patients. Improving psychological resilience and social support can reduce the impact of psychological stress on MUS. Therefore, psychotherapy and multidisciplinary comprehensive treatment are very important for patients is very important for patients.

ObjectivePrevious studies have implicated intricate interactions between innate immunity and the brain in schizophrenia. Monocytic Toll-like receptor (TLR) 4 signaling, a crucial “sensor” of innate immunity, was reported to be over-activated in link with cognitive impairment in schizophrenia. As TLR4 is predominantly expressed on gliocytes prior to expression in neurons, we hypothesized that higher TLR4 levels may contribute to cognitive deterioration by affecting white matter microstructure.MethodsForty-four patients with stable chronic schizophrenia (SCS) and 59 healthy controls (HCs) were recruited in this study. The monocytic function was detected with lipopolysaccharide (LPS) stimulation to simulate bacterial infection. Basal and LPS- stimulated levels of TLR4, nuclear factor-kappa B (NF-κB), and interleukin (IL)-1β were quantified with flow cytometry. Cognitive function was assessed by the MATRICS Consensus Cognitive Battery (MCCB) and psychopathological symptoms were evaluated by the Positive and Negative Syndrome Scale (PANSS). We employed diffusion tensor imaging with a 3-T scanner and evaluated white-matter integrity with fractional anisotropy (FA). Subcortical volume and cortical thickness were also assessed.ResultsThe TLR4/NF-κB/IL-1β signaling pathway was activated in patients with SCS, but responded sluggishly to LPS stimulation when compared with HCs. Furthermore, monocytic TLR4 expressions were inversely correlated with cognitive function and white matter FA, but not with cortical thickness or subcortical gray matter volume in schizophrenia.ConclusionOur findings support altered TLR4 signaling pathway activity in association with deficits in cognition and white matter integrity in schizophrenia.

BackgroundThe high prevalence of Internet gaming disorder among children and adolescents and its severe psychological, health, and social consequences have become a public emergency. A high efficiency and cost-effective early recognition method are urgently needed.ObjectiveWe aim to develop and internally validate a nomogram model for predicting Internet gaming disorder (IGD) risk in Chinese adolescents and children.MethodsThrough an online survey, 780 children and adolescents aged 7–18 years who participated in the survey from June to August 2021 were selected. The least absolute shrinkage and selection operator regression model was used to filter the factors. Multivariate logistic regression analysis was used to establish the prediction model and generate nomograms and a website calculator. The area under the receiver operating characteristic curve, calibration plot, and decision curve analysis were used to evaluate the model's discrimination, calibration, and clinical utility. Bootstrapping validation was used to verify the model internally.ResultsMale sex and experience of game consumption were the two most important predictors. Both models exhibited good discrimination, with an area under the curve >0.80. The calibration plots were both close to the diagonal line (45°). Decision curve analyses revealed that two nomograms were clinically useful when the threshold probability for the intervention was set to 5–75%.ConclusionTwo prediction models appear to be reliable tools for Internet gaming disorder screening in children and adolescents, which can also help clinicians to personalize treatment plans. Moreover, from the standpoint of simplification and cost, Model 2 appears to be a better alternative.

Abstract A number of tryptophan metabolites known to be neuroactive have been examined for their potential associations with cognitive deficits in schizophrenia. Among these metabolites, kynurenic acid (KYNA), 5-hydroxyindole (5-HI), and quinolinic acid (QUIN) are documented in their diverse effects on α-7 nicotinic acetylcholine receptor (α7nAChR) and/or N-methyl-D-aspartate receptor (NMDAR), two of the receptor types thought to contribute to cognitive impairment in schizophrenia. In this study, serum levels of KYNA, 5-HI, and QUIN were measured in 195 patients with schizophrenia and in 70 healthy controls using liquid chromatography-tandem mass spectrometry; cognitive performance in MATRICS Consensus Cognitive Battery and cortical thickness measured by magnetic resonance imaging were obtained. Patients with schizophrenia had significantly lower serum KYNA (p

Abstract Schizophrenia results in poor functional outcomes owing to numerous factors. This study provides the first test of a bottom-up causal model of functional outcome in schizophrenia, using neurocognition, vocal emotional cognition, alexithymia, and negative symptoms as predictors of functional outcome. We investigated a cross-sectional sample of 135 individuals with schizophrenia and 78 controls. Using a series of structural equation modelling analyses, a single pathway was generated among scores from the MATRICS Consensus Cognitive Battery (MCCB), vocal emotion recognition test, Toronto Alexithymia Scale (TAS), Brief Negative Symptom Scale, and the Personal and Social Performance Scale. The scores for each dimension of the MCCB in the schizophrenia group were significantly lower than that in the control group. The recognition accuracy for different emotions (anger, disgust, fear, sadness, surprise, and satire, but not calm was significantly lower in the schizophrenia group than in the control group. Moreover, the scores on the three dimensions of TAS were significantly higher in the schizophrenia group than in the control group. On path analysis modelling, the proposed bottom-up causal model showed a strong fit with the data and formed a single pathway, from neurocognition to vocal emotional cognition, to alexithymia, to negative symptoms, and to poor functional outcomes. The study results strongly support the proposed bottom-up causal model of functional outcome in schizophrenia. The model could be used to better understand the causal factors related to the functional outcome, as well as for the development of intervention strategies to improve functional outcomes in schizophrenia.

Abstract Cognitive impairment is a core characteristic of schizophrenia, but its underlying neural mechanisms remain poorly understood. Reduced brain-derived neurotrophic factor (BDNF), a protein critical for neural plasticity and synaptic signaling, is one of the few molecules consistently associated with cognitive deficits in schizophrenia although the etiological pathway leading to BDNF reduction in schizophrenia is unclear. We examined microRNA-195 (miR-195), a known modulator of BDNF protein expression, as a potential mechanistic component. One-hundred and eighteen first-episode patients with schizophrenia either antipsychotic medication-naïve or within two weeks of antipsychotic medication exposure and forty-seven age- and sex-matched healthy controls were enrolled. MiR-195 and BDNF mRNA and BDNF protein levels in peripheral blood were tested. Cognitive function was assessed using the MATRICS Consensus Cognitive Battery (MCCB). MiR-195 was significantly higher (p = 0.01) whereas BDNF mRNA (p

Motivated by the potential of objective neurophysiological markers to index thalamocortical function in patients with severe psychiatric illnesses, we comprehensively characterized key non-rapid eye movement (NREM) sleep parameters across multiple domains, their interdependencies, and their relationship to waking event-related potentials and symptom severity. In 72 schizophrenia (SCZ) patients and 58 controls, we confirmed a marked reduction in sleep spindle density in SCZ and extended these findings to show that fast and slow spindle properties were largely uncorrelated. We also describe a novel measure of slow oscillation and spindle interaction that was attenuated in SCZ. The main sleep findings were replicated in a demographically distinct sample, and a joint model, based on multiple NREM components, statistically predicted disease status in the replication cohort. Although also altered in patients, auditory event-related potentials elicited during wake were unrelated to NREM metrics. Consistent with a growing literature implicating thalamocortical dysfunction in SCZ, our characterization identifies independent NREM and wake EEG biomarkers that may index distinct aspects of SCZ pathophysiology and point to multiple neural mechanisms underlying disease heterogeneity. This study lays the groundwork for evaluating these neurophysiological markers, individually or in combination, to guide efforts at treatment and prevention as well as identifying individuals most likely to benefit from specific interventions.

Abstract Background Working memory deficit is one of the most critical complex cognitive impairments in schizophrenia. Repetitive transcranial magnetic stimulation (rTMS) is an effective adjuvant therapy, but not still unsatisfactory. Intermittent theta burst stimulation (iTBS), which has recently been used in clinical practice, may have faster and stronger effects comparing the traditional model (10-Hz high-frequency rTMS). A large number of studies have showed that rTMS, especially iTBS, can enhance the neural plasticity of the brain, and cognitive training can improve the cognitive function of schizophrenia. Is there any facilitation effect of iTBS add on cognitive training (such as working memory training, WMT) on cognitive function enhancement in schizophrenia is still unknown. Methods/design The proposed study is designed of a double-center, double-blinded, randomized controlled trial that will include 200 schizophrenia patients between 18 and 45 years of age. The patients will be randomized to four groups, i.e., the study group (iTBS+WMT), WMS control group (iTBS+ Simple Response Training (SRT)), iTBS control group (sham iTBS+WMT), and placebo control (sham iTBS+SRT). The patients will receive 3 min 20 s of real or sham stimulation, followed by a short 1–2-min rest and 40 min of WMT training or SRT immediately. Neuropsychological and clinical symptom assessments, with functional and structural MRI, will be performed on baseline, post-treatment, and 3- and 6-month follow-up periods. The primary outcome is cognitive function measured by the MATRICS Consensus Cognitive Battery (MCCB). The secondary outcomes are changes in neuroplasticity, as measured by MRI and other behavioral assessments. Discussion The aim of our study is to explore the facilitation effects of iTBS added on WMT in improving cognitive function of schizophrenia. That means, patients with schizophrenia will benefit more in cognitive function improvement from the combination training mode of “preheating (iTBS stimulation changes the neural activity of working memory-related brain regions) and ironning (working memory training).” And the long-term effects of this combined training model will be assessed at a 6-month follow-up period. In case of a significant improvement of working memory with a prolonged effect, the iTBS combined with WMT protocol could be considered as a first-line clinical protocol in schizophrenia treatment. More broadly, the potential for increased universality and efficiency of rTMS with the iTBS model to enhance the neural plasticity of the brain should have a more positive effect on cognitive function in schizophrenia. Trial registration chictr.org.cn ChiCTR1900023405 . Registered on 25 May 2019

Patients with bipolar disorder have deficits in self-referenced information. The brain functional connectivity during social cognitive processing in bipolar disorder is unclear. Electroencephalogram (EEG) was recorded in 23 patients with bipolar disorder and 19 healthy comparison subjects. We analyzed the time-frequency distribution of EEG power for each electrode associated with self, other, and font reflection conditions and used the phase lag index to characterize the functional connectivity between electrode pairs for 4 frequency bands. Then, the network properties were assessed by graph theoretic analysis. The results showed that bipolar disorder induced a weaker response power and phase lag index values over the whole brain in both self and other reflection conditions. Moreover, the characteristic path length was increased in patients during self-reflection processing, whereas the global efficiency and the node degree were decreased. In addition, when discriminating patients from normal controls, we found that the classification accuracy was high. These results suggest that patients have impeded integration of attention, memory, and other resources of the whole brain, resulting in a deficit of efficiency and ability in self-referential processing.

Background It is difficult to make a precise diagnosis to distinguish patients with Major Depressive Disorder (MDD) from patients with Bipolar Depressive Disorder (current depressive episode, BD). This study will explore the difference in time perception between MDD and BD using a temporal bisection task. Methods In this temporal bisection task, 30 MDD patients, 30 BD patients, and 30 healthy controls (HC) had to categorize a signal duration, between 400 and 1600 milliseconds (ms), as either short or long. A repeated measurement analysis of variance with 3 (subject type) × 7 (time interval) was performed on the long response ratio with Bonferroni correction for multiple comparisons. Origin software was used to calculate the subjective bisection point (BP), difference limen (DL), and Weber ratio (WR). The Hamilton Depression Rating Scale for depression-17 was used to assess depressive symptoms in the patients. Results The data showed that the interaction effect between subject type and duration was significant (F(6,498) = 4.656, p Limitations Severity of depression not divided and analyzed according to the Hamilton Depression Rating Scale score. Conclusion The time perception of the MDD and BD groups was different from that of the HC group, they overestimated short time periods. Compared with the BD group, the MDD group had a smaller time bisector, and these patients felt that time passed more slowly. The time sensitivity of MDD group and BD group were less than the HC group. However, there was no statistical difference in time sensitivity between the MDD and BD groups.

Background: Previous studies have found that alexithymia plays an important role in the pathogenesis of Internet addiction. However, the effect of alexithymia on both metacognition and Internet addiction has yet to be examined.Methods: The Toronto Alexithymia Scale, Metacognition Questionnaire, and Internet Addiction Test were used to assess a sample of 356 college students. A parallel mediator effect analysis was applied to test the hypothesis that metacognition mediates the relationship between alexithymia and Internet addiction.Results: The parallel multiple mediator models showed that alexithymia predicted the five dimensions of metacognition and Internet addiction, and that three dimensions—cognitive confidence, positive beliefs about worry, and the need to control thoughts—partially mediated this relationship.Conclusion: Alexithymia could directly and indirectly predict Internet addiction via metacognition.

ObjectiveTo explore differences and similarities in relationships between subcortical structure volumes and neurocognition among the four subject groups, including first-episode schizophrenia (FES), bipolar disorder (BD), major depression disorder (MDD), and healthy controls (HCs).MethodsWe presented findings from subcortical volumes and neurocognitive analyses of 244 subjects (109 patients with FES; 63 patients with BD, 30 patients with MDD, and 42 HCs). Using the FreeSurfer software, volumes of 16 selected subcortical structures were automatically segmented and analyzed for relationships with results from seven neurocognitive tests from the MATRICS (Measurement and Treatment Research to Improve Cognition in Schizophrenia) Cognitive Consensus Battery (MCCB).ResultsLarger left lateral ventricle volumes in FES and BD, reduced bilateral hippocampus and amygdala volumes in FES, and lower bilateral amygdala volumes in BD and MDD were presented compared with HCs, and both FES and BD had a lower bilateral amygdala volume than MDD; there were seven cognitive dimension, five cognitive dimension, and two cognitive dimension impairments in FES, BD, and MDD, respectively; significant relationships were found between subcortical volumes and neurocognition in FES and BD but not in MDD and HCs; besides age and years of education, some subcortical volumes can predict neurocognitive performances variance.ConclusionThe different degrees of subcortical volume lessening may contribute to the differences in cognitive impairment among the three psychiatric disorders.

Objective: To explore the characteristics of expression recognition and spontaneous activity of the resting state brain in major depressive disorder (MDD) patients to find the neural basis of expression recognition and emotional processing.Methods: In this study, two of the six facial expressions (happiness, sadness, anger, fear, aversion, and surprise) were presented in quick succession using a short expression recognition test. The differences in facial expression recognition between MDD patients and healthy people were compared. Further, the differences in ReHo values between the two groups were compared using a resting-state functional magnetic resonance imaging (fMRI) scan to investigate the characteristics of spontaneous brain activity in the resting state and its relationship with clinical symptoms and the accuracy of facial expression recognition in patients with MDD.Results: (1) The accuracy of facial expression recognition in patients with MDD was lower than that of the HC group. There were differences in facial expression recognition between the two groups in sadness-anger (p = 0.026), surprise-aversion (p = 0.038), surprise-happiness (p = 0.014), surprise-sadness (p = 0.019), fear-happiness (p = 0.027), and fear-anger (p = 0.009). The reaction time for facial expression recognition in the patient group was significantly longer than that of the HC group. (2) Compared with the HC group, the ReHo values decreased in the left parahippocampal gyrus, left thalamus, right putamen, left putamen, and right angular gyrus, and increased in the left superior frontal gyrus, left middle temporal gyrus, left medial superior frontal gyrus, and right medial superior frontal gyrus in the patient group. (3) Spearman correlation analysis showed no statistical correlation between ReHo and HAMD-17 scores in MDD patients (p > 0.05). The ReHo value of the left putamen was negatively correlated with the recognition of fear-surprise (r = −0.429, p = 0.016), the ReHo value of the right angular gyrus was positively correlated with the recognition of sadness-anger (r = 0.367, p = 0.042), and the ReHo value of the right medial superior frontal gyrus was negatively correlated with the recognition of fear-anger (r = −0.377, p = 0.037).Conclusion: In view of the different performance of patients with MDD in facial expression tasks, facial expression recognition may have some suggestive effect on the diagnosis of depression and has clinical guiding significance. Many brain regions, including the frontal lobe, temporal lobe, striatum, hippocampus, and thalamus, in patients with MDD show extensive ReHo abnormalities in the resting state. These brain regions with abnormal spontaneous neural activity are important components of LCSPT and LTC circuits, and their dysfunctional functions cause disorder of emotion regulation. The changes in spontaneous activity in the left putamen, right angular gyrus, and right medial superior frontal gyrus may represent the abnormal pattern of spontaneous brain activity in the neural circuits related to emotion perception and may be the neural basis of facial expression recognition.

Impairments in self-representation are relevant to the expression of psychosis. To date, the characteristics and neural mechanisms of self-impairment in schizophrenia remain unclear. To this end, we used event-related potentials (ERPs) to measure brain activity in 56 first-episode patients with schizophrenia and 56 healthy controls. Participants judged personal trait adjectives regarding themselves, their mothers, or a public person, followed by an unexpected old/new recognition test. The recognition score for mother-reference adjectives was lower than that for self-reference adjectives in patients, while the control group showed comparatively high recognition scores for both self- and mother-referential adjectives. In addition, control subjects recognized more negative words, while patients remembered more positive words. ERP data revealed that controls exhibited typical task effects (self-reference = mother-reference > other-reference) during both automatic attention and effortful encoding periods [indexed by P2 and the late positive potential (LPP), respectively]. In contrast, patients only exhibited the task effect in the P2 amplitude. Moreover, controls exhibited larger P2 amplitudes during encoding negative than positive words, whereas patients had enhanced LPP amplitudes during memory retrieval of positive compared to negative words. These findings demonstrated self-representation dysfunction in first-episode schizophrenic patients in mother (the intimate other) referential processing and the absence of a negative memory bias.

The default-mode network (DMN) is a set of functionally connected regions that play crucial roles in internal cognitive processing. Previous resting-state fMRI studies have demonstrated that the intrinsic functional organization of the DMN undergoes remarkable reconfigurations during childhood and adolescence. However, these studies have mainly focused on cross-sectional designs with small sample sizes, limiting the consistency and interpretations of the findings. Here, we used a large sample of longitudinal resting-state fMRI data comprising 305 typically developing children (6–12 years of age at baseline, 491 scans in total) and graph theoretical approaches to delineate the developmental trajectories of the functional architecture of the DMN. For each child, the DMN was constructed according to a prior parcellation with 32 brain nodes. We showed that the overall connectivity increased in strength from childhood to adolescence and became spatially similar to that in the young adult group (N = 61, 18–28 years of age). These increases were primarily located in the midline structures. Global and local network efficiency in the DMN also increased with age, indicating an enhanced capability in parallel information communication within the brain system. Based on the divergent developmental rates of nodal centrality, we identified three subclusters within the DMN, with the fastest rates in the cluster mainly comprising the anterior medial prefrontal cortex and posterior cingulate cortex. Together, our findings highlight the developmental patterns of the functional architecture in the DMN from childhood to adolescence, which has implications for the understanding of network mechanisms underlying the cognitive development of individuals.

In this paper, from the perspective of complex network dynamics we investigated the formation of the synchronization state of the brain networks. Based on the Lyapunov stability theory of complex networks, a synchronous steady-state model suitable for application to complex dynamic brain networks was proposed. The synchronization stability problem of brain network state equation was transformed into a convex optimization problem with Block Coordinate Descent (BCD) method. By using Random Apollo Network (RAN) method as a node selection rule, the brain network constructs its subnet work dynamically. We also analyzes the change of the synchronous stable state of the subnet work constructed by this method with the increase of the size of the network. Simulation EEG data from alcohol addicts patients and Real experiment EEG data from schizophrenia patients were used to verify the robustness and validity of the proposed model. Differences in the synchronization characteristics of the brain networks between normal and alcoholic patients were analyzed, so as differences between normal and schizophrenia patients. The experimental results indicated that the establishment of a synchronous steady state model in this paper could be used to verify the synchronization of complex dynamic brain networks and potentially be of great value in the further study of the pathogenic mechanisms of mental illness.

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

ObjectivesMany studies reported structural brain changes in patients with alcohol dependence (PADs). However, no studies identified structural correlates of apathy that might aggravate alcohol misuse. Here, we explored regional differences in cortical thickness in PADs relative to healthy controls (HCs), and examined the potential correlation of regional thickness with the severity of apathy.MethodsMagnetic resonance imaging data were collected from 33 male PADs and 35 male age- and education-matched HCs. We used the FreeSurfer software to investigate group differences in cortical thickness across 148 regions. Apathy was evaluated using the Lille Apathy Rating Scale-Informant (LARS-I). Regression analyses examined the relationship between cortical thickness of regions of interest and apathy score in PADs.ResultsCompared to HCs, PADs showed significant decreases in the cortical thickness of occipito-temporal cortex (OTC), including the left middle occipital gyrus and occipital pole, right superior occipital gyri, and bilateral lingual gyrus; bilateral superior parietal cortex (SPC), including the right intraparietal sulcus; and bilateral inferior parietal cortex (IPC). Furthermore, the cortical thickness of all of the three regions was negatively correlated with the apathy total scores. The cortical thickness of the IPC was also negatively correlated with the action initiation subscore of the LARS-I.ConclusionsThe current results suggest the thickness of bilateral parietal and occipital temporal cortices as neural markers of apathy in PADs. These findings add to the literature by identifying the neural bases of a critical clinical feature of individuals with alcoholism.

Altered resting-state functional connectivity (rsFC) of the amygdala has been demonstrated to be implicated in schizophrenia neuronal pathophysiology. However, whether rsFC of amygdala subregions is differentially affected in schizophrenia remains unclear. This study compared the functional networks of each amygdala subdivision between healthy controls (HC) and patients with first-episode schizophrenia (FES). In total, 47 HC and 78 patients with FES underwent resting-state functional magnetic resonance imaging. The amygdala was divided into the following three subregions using the Juelich histological atlas: basolateral amygdala (BLA), centromedial amygdala (CMA), and superficial amygdala (SFA). The rsFC of the three amygdala subdivisions was computed and compared between the two groups. Significantly increased rsFC of the right CMA with the right postcentral gyrus and decreased rsFC of the right BLA with the left precentral gyrus were observed in the FES group compared with the HC group. Notably, the right BLA-left precentral gyrus connectivity was negatively correlated with positive symptoms and conceptual disorganization in patients with FES. In conclusion, this study found that patients with FES had abnormal functional connectivity in the amygdala subregions, and the altered rsFC was associated with positive symptoms. The present findings demonstrate the disruptive rsFC patterns of amygdala subregional-sensorimotor networks in FES and may provide new insights into the neuronal pathophysiology of FES.

Abstract Tardive dyskinesia (TD) is a devastating motor disorder associated with the etiological process of schizophrenia or antipsychotic medication treatments. To examine whether cerebral morphological changes may manifest in TD, we used voxel-based morphometry to analyze high-resolution T1-weighted brain structural magnetic resonance images from 32 schizophrenics with TD (TD group), 31 schizophrenics without TD (non-TD group), and 32 healthy controls (HC group). We also assessed psychopathological symptoms with the Positive and Negative Syndrome Scale (PANSS), and TD severity with the Abnormal Involuntary Movement Scale (AIMS). We compared gray matter volumes (GMVs) among groups, and tested for correlations between GMV changes and psychopathological symptoms or TD severity. The results showed significant differences in GMV in the frontal and temporal cortices, insula and cerebellum among the three groups. Brainstem and inferior frontal and precentral gyri GMVs were significantly larger, whereas cuneus and lingual gyrus GMVs were significantly smaller in the TD group as compared to non-TD group. Further, the cuneus and lingual gyrus GMVs were positively correlated with AIMS scores in the TD group. The current results suggest that TD may be associated with the alterations in GMV that are different from that of schizophrenics without TD. Further studies are needed to confirm and to examine the functional significance of these structural findings.

The microstructures and mechanical properties of dissimilar weld joints between T92 and Super 304H steels were investigated. Dissimilar weld joints with four groove angles were constructed using gas tungsten arc welding. The results showed that post-weld heat treatment improved the mechanical properties of the dissimilar weld joints. The optimal groove angle for T92/Super 304H dissimilar weld joints was found to be 20°, considering mechanical properties. Furthermore, the transformation from equiaxed dendrites to columnar dendrites was observed in the weld metal. Epitaxial growth and delta ferrites were found around the fusion line between the Super 304H and the weld metal.

Abstract Using Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), previous study showed significant gender differences for cognitive deficits in immediate and delayed memory in schizophrenia patients. However, RBANS does not include reasoning and problem solving, and social cognition. These cognitive functions can significantly affect the outcomes and daily life in patients. This study examined the gender differences of cognition using the measurement and treatment research to improve cognition in schizophrenia (MATRICS) consensus cognitive battery (MCCB), especially focusing on reasoning and problem solving, and social cognition in schizophrenia patients. The results showed that healthy controls exemplified better cognition than patients in both genders in all examined MCCB scores. Male healthy controls had better reasoning and problem solving and working memory than females, but these gender differences were not presented in schizophrenia patients. Also, male schizophrenia patients showed worse cognition than females on social cognition, processing speed, verbal learning and visual learning. Our results support that male schizophrenia patients had more cognitive impairment than females on reasoning and problem solving, social cognition, processing speed, working memory, verbal learning and visual learning.

Abstract This study aimed to test how an 8-week training using computerized cognitive remediation therapy (CCRT) would modify resting brain functional activity and improve cognitive function in patients with schizophrenia. Twenty-seven patients with schizophrenia were recruited and randomized into two groups: CCRT or treatment-as-usual (TAU). The CCRT group received 40 sessions of computerized cognitive training over an eight-week period. There was a significant treatment group × time interaction on the processing speed (trail making test: F = 8.14, P = 0.01) and a trend in problem solving (mazes test: P = 0.06). Post-hoc tests showed that CCRT but not TAU significantly improved scores from baseline to end-of-treatment on these two cognitive assessments. For the resting brain functional activity, significant group × time interaction effect was found in the medial prefrontal cortex (mPFC)/anterior cingulate cortex (ACC) and brainstem pons region. Post-hoc tests showed that there was significant increased activity in the mPFC/ACC in CCRT but not TAU group. In this small sample study, computerized cognitive remediation therapy is shown to enhance mPFC/ACC activity even at resting state and improve cognitive function in patients with schizophrenia. If replicated, this community and clinic accessible therapy may assist cognitive remediation effort for people with schizophrenia.

Schizophrenia patients exhibited a psychological abnormal appearance when they recognized objects related to themselves. This cognitive process is associated with self-referential processing. In this study, the self-referential memory (SRM) task was performed by 18 schizophrenia patients and 18 healthy controls. In the encoding stage of the SRM task, the behavioral experiment data and electroencephalogram (EEG) data were recorded in three experimental conditions (self-referential condition, other-referential condition, and physical condition). For data analysis, the electrophysiological performance of the time-frequency distribution, phase lag index (PLI) strengths, phase synchronization connectivity, and brain-network properties were assessed in schizophrenia patients compared to healthy controls. We found that schizophrenia patients exhibited abnormal alpha oscillation characteristics at the time of 100–300 ms poststimulus during the self-referential condition, which consisted of diminished time-frequency distributions over the prefrontal, parietal, and occipital regions; lower functional connectivity strengths of the PLI in the parietal and occipital areas; higher global efficiency and the lower characteristic path length; and nodal efficiency of local areas (increased nodal efficiency in temporal regions and decreased nodal efficiency in occipital region) for dynamic network topology properties. Furthermore, the evoked power of the alpha band during the self-referential condition was significantly correlated with the SRM bias score in the patients (r = 0.595, p = 0.009). These results provided electrophysiological evidence and supported the hypothesis that an abnormal alpha rhythm might be the principal factor of dysfunctional self-referential processing in schizophrenia patients.