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Abstract Low-frequency repetitive transcranial magnetic stimulation (rTMS) has emerged as an effective intervention for alleviating symptoms of psychiatric disorders, particularly schizophrenia characterized by persistent auditory verbal hallucinations (AVH). However, the underlying mechanism of its action remain elusive. This study employed a randomized controlled design to investigate the impact of low-frequency rTMS on the neural connectivity at the stimulate site, specifically left temporoparietal junction (TPJ), in schizophrenia patients with suffering from AVH. Using Dynamic Causal Modeling (DCM), this study assessed changes in directed connectivity patterns and their correlations with clinical symptomatology. The results demonstrated significant improvements in AVH. Notably, significant changes in connectivity were observed, including both abnormal functional connectivity and effective connectivity among multiple brain regions. Particularly, the inhibition effects from the left precentral gyrus and left medial superior frontal gyrus to the left TPJ were closely associated with improvements in AVH. These findings underscore the potential of rTMS to effectively modulate neural pathways implicated in hallucinations in schizophrenia, thereby providing a neurobiological foundation for its therapeutic effects.

Introduction Major depressive disorder (MDD) is a common mental disorder that is characterised by high morbidity, high rates of relapse, high rates of disability and, in severe cases, suicide ideas or even behaviour causing significant distress and burden. Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique widely used in the clinical treatment of MDD. Nevertheless, due to the imprecise selection and positioning of stimulation targets, their response rate is not as satisfactory. This trial was designed to treat MDD based on functional connectivity with individual target-TMS (IT-TMS) to stimulate the dorsolateral prefrontal cortex (DLPFC) where it correlates most negatively with the pregenual anterior cingulate cortex (pgACC). We will validate the safety and efficacy of IT-TMS for MDD using pgACC as an effector target, analyse the underlying antidepressant mechanism of the DLPFC-ACC brain network and search for neuroimaging markers that predict the efficacy of TMS.Methods and analysis This is a single-centre, randomised, double-blind and sham-stimulation-controlled clinical trial. We aim to recruit approximately 68 depressed patients with MDD aged 18–60 years. Eligible participants will be randomised into the DLPFC-pgACC localisation and sham stimulation groups. The IT-TMS treatment will last 10 days and will be combined with antidepressant medication. Assessments will be confirmed at baseline, on day 5 of treatment and at the end of treatment with follow-up at weeks 2, 4 and 8 after the end of treatment. The primary outcome measure is the difference in the Hamilton Depression Scale score between baseline and end of treatment.Ethics and dissemination The Ethics Committee of the First Affiliated Hospital of the Air Force Medical University has approved this clinical trial (project code: XJLL-KY20222111). The trial’s results will be published in international peer-reviewed journals and presented at academic conferences.Trial registration number ClinicalTrials.gov PRS (ID: NCT05577481).

Abstract To elucidate the brain‐wide information interactions that vary and contribute to individual differences in schizophrenia (SCZ), an information‐resolved method is employed to construct individual synergistic and redundant interaction matrices based on regional pairwise BOLD time‐series from 538 SCZ and 540 normal controls (NC). This analysis reveals a stable pattern of regionally‐specific synergy dysfunction in SCZ. Furthermore, a hierarchical Bayesian model is applied to deconstruct the patterns of whole‐brain synergy dysfunction into three latent factors that explain symptom heterogeneity in SCZ. Factor 1 exhibits a significant positive correlation with Positive and Negative Syndrome Scale (PANSS) positive scores, while factor 3 demonstrates significant negative correlations with PANSS negative and general scores. By integrating the neuroimaging data with normative gene expression information, this study identifies that each of these three factors corresponded to a subset of the SCZ risk gene set. Finally, by combining data from NeuroSynth and open molecular imaging sources, along with a spatially heterogeneous mean‐field model, this study delineates three SCZ synergy factors corresponding to distinct symptom profiles and implicating unique cognitive, neurodynamic, and neurobiological mechanisms.

Glycophagy has evolved from an alternative glycogen degradation pathway into a multifaceted pivot to regulate cellular metabolic hemostasis in peripheral tissues. However, the pattern of glycophagy in the brain and its potential therapeutic impact on ischemic stroke remain unknown. Here, we observed that the dysfunction of astrocytic glycophagy was caused by the downregulation of the GABA type A receptor-associated protein like 1 (GABARAPL1) during reperfusion in ischemic stroke patients and mice. PI3K-Akt pathway activation is involved in driving GABARAPL1 downregulation during cerebral reperfusion. Moreover, glycophagy dysfunction-induced glucosamine deficiency suppresses the nuclear translocation of specificity protein 1 and TATA binding protein, the transcription factors for GABARAPL1, by decreasing their O-GlcNAcylation levels, and accordingly feedback inhibits GABARAPL1 in astrocytes during reperfusion. Restoring astrocytic glycophagy by overexpressing GABARAPL1 decreases DNA damage and oxidative injury in astrocytes and improves the survival of surrounding neurons during reperfusion. In addition, a hypocaloric diet in the acute phase after cerebral reperfusion can enhance astrocytic glycophagic flux and accelerate neurological recovery. In summary, glycophagy in the brain links autophagy, metabolism, and epigenetics together, and glycophagy dysfunction exacerbates reperfusion injury after ischemic stroke.

Introduction Post-traumatic stress disorder (PTSD) is a prevalent and severe psychiatric disorder. Repetitive transcranial magnetic stimulation (rTMS) targeting the dorsolateral prefrontal cortex provides limited relief for symptoms of PTSD. This study will be conducted to validate the efficacy of MRI-guided rTMS in targeting the sites most closely associated with the amygdala for patients with PTSD. We hypothesise that the intervention will improve clinical symptoms by decreasing amygdala activity in patients.Methods and analysis A randomised, double-blind, sham-controlled trial will be conducted. Forty-eight eligible patients with PTSD will be randomly assigned to receive either active or sham MRI-guided rTMS for 10 consecutive days after the initial MRI scans. MRI scans will be recollected at the end of the intervention. Clinical assessments will be performed at baseline, treatment day 5, treatment day 10, and 2 weeks, 4 weeks, 8 weeks after completion of the intervention to monitor changes in clinical symptoms. The primary assessment outcome is the change in PTSD symptoms between baseline and treatment day 10, as measured by the PTSD Checklist for DSM-5. Repeated measures analysis of variance will be performed using statistical software SPSS V.26.0. The significance level will be set at 0.05.Ethics and dissemination Ethical approval has been obtained from the Ethics Committee of Xijing Hospital in Xi'an, China (KY20222176-X-1), and the trial has been registered on ClinicalTrials.gov. The findings of this trial will be disseminated at academic conferences or published in peer-reviewed scientific journals.Trial registration number NCT05544110.

Abstract Purpose Conceptualizing adolescent NSSI and emotional symptoms as a system of causal elements could provide valuable insights into the development of non-suicidal self-injury (NSSI) in adolescent. This study aimed to explore the intricate relationship between NSSI, depressive symptoms, and anxious symptoms in adolescents, identifying key symptoms to establish a theoretical foundation for targeted and effective interventions addressing NSSI behaviors in this population. Methods A total of 412 adolescents with NSSI behaviors were selected from outpatients. Generalized anxious disorder scale (GAD-7) and patient health questionnaire (PHQ-9) were employed to measure anxious symptoms and depressive symptoms, respectively. The adolescent non-suicidal self-injury assessment questionnaire (ANSSIAQ) was used to evaluate NSSI of adolescent. Using network analysis, the NSSI、depressive symptoms and anxious symptoms network were constructed to identify the most central symptoms and the bridge symptoms within the networks. Results The findings revealed that the NSSI functional nodes “coping with sadness and disappointment” and “relieving stress or anxious” exhibited the strongest correlation, with a regularized partial correlation coefficient was 0.401. The symptoms “having a desire to harm oneself and unable to stop” and the node “depressive symptoms” had the highest strength centrality in the network, and their strength centrality indices were 1.267 and 1.263, respectively. The bridge nodes were “having a desire to harm oneself and unable to stop” and “expressing one’s despair and hopelessness”, with expected impact indices of 0.389 and 0.396, respectively. Conclusion In adolescents, the network revealed a closer connection between NSSI and depressive symptoms. “The desire to not stop hurting oneself” is not only broadly connected to other nodes but also could activate other nodes to maintain NSSI behavior. In light of these findings, precise targets for pharmacological treatment, psychotherapy, physical therapy, etc., are identified for adolescents with NSSI. Targeting this specific aspect in interventions may contribute to preventing and reducing NSSI behavior in adolescents.

Abstract Background Emotional blunting is a symptom that has always been present in depressed patients. Repetitive transcranial magnetic stimulation (rTMS) is a safe and effective supplementary therapy for treating depression. However, the effectiveness and brain imaging processes of functional magnetic resonance imaging-guided personalized rTMS (fMRI-rTMS) in the treatment of depression with emotional blunting have not been observed in randomized controlled trials. Methods This study is a randomized, controlled, double-blind, and single-center clinical trial in which 80 eligible depressed patients with emotional blunting will be randomly assigned to two groups: a functional magnetic resonance imaging-guided personalized rTMS (fMRI-rTMS) group and a control group. Individuals in the fMRI-rTMS group (n = 40) will receive high-frequency rTMS (10 Hz, 120% MT). The main target of stimulation will be the area most relevant to the functional connectivity of the right medial prefrontal cortex (mPFC) and amygdala. The control group (n = 40) will receive sham stimulation, with a coil flipped to 90 degrees relative to the vertical scalp. All patients will receive 15 consecutive days of treatment, with each session lasting half an hour per day, followed by 8 weeks of follow-up. The primary outcome is the comparison of Oxford Depression Questionnaire (ODQ) scores between these two groups at different time points. The secondary outcomes include evaluating other clinical scales and assessing the differences in brain imaging changes between the two groups before and after treatment. Discussion This trial aims to examine the effects of functional magnetic resonance imaging-guided personalized rTMS (fMRI-rTMS) intervention on depressed patients experiencing emotional blunting and to elucidate the potential mechanism behind it. The results will provide new evidence for using fMRI-rTMS in treating depression with emotional blunting in the future. Trial registration ClinicalTrials.gov INCT05555940. Registered on 13 September 2022 at http://clinicaltrials.gov .

Although antipsychotics that act via monoaminergic neurotransmitter modulation have considerable therapeutic effect, they cannot completely relieve clinical symptoms in patients suffering from psychiatric disorders. This may be attributed to the limited range of neurotransmitters that are regulated by psychotropic drugs. Recent findings indicate the need for investigation of psychotropic medications that target less-studied neurotransmitters. Among these candidate neurotransmitters, lactate is developing from being a waste metabolite to a glial-neuronal signaling molecule in recent years. Previous studies have suggested that cerebral lactate levels change considerably in numerous psychiatric illnesses; animal experiments have also shown that the supply of exogenous lactate exerts an antidepressant effect. In this review, we have described how medications targeting newer neurotransmitters offer promise in psychiatric diseases; we have also summarized the advances in the use of lactate (and its corresponding signaling pathways) as a signaling molecule. In addition, we have described the alterations in brain lactate levels in depression, anxiety, bipolar disorder, and schizophrenia and have indicated the challenges that need to be overcome before brain lactate can be used as a therapeutic target in psychopharmacology.

Abstract Background Anhedonia, which is defined as the inability to feel pleasure, is considered a core symptom of major depressive disorder (MDD). It can lead to several adverse outcomes in adolescents, including heightened disease severity, resistance to antidepressants, recurrence of MDD, and even suicide. Specifically, patients who suffer from anhedonia may exhibit a limited response to selective serotonin reuptake inhibitors (SSRIs) and cognitive behavioral therapy (CBT). Previous researches have revealed a link between anhedonia and abnormalities within the reward circuitry, making the nucleus accumbens (NAc) a potential target for treatment. However, since the NAc is deep within the brain, repetitive transcranial magnetic stimulation (rTMS) has the potential to modulate this specific region. Recent advances have enabled treatment technology to precisely target the left dorsolateral prefrontal cortex (DLPFC) and modify the functional connectivity (FC) between DLPFC and NAc in adolescent patients with anhedonia. Therefore, we plan to conduct a study to explore the safety and effectiveness of using resting-state functional connectivity magnetic resonance imaging (fcMRI)-guided rTMS to alleviate anhedonia in adolescents diagnosed with MDD. Methods The aim of this article is to provide a study protocol for a parallel-group randomized, double-blind, placebo-controlled experiment. The study will involve 88 participants who will be randomly assigned to receive either active rTMS or sham rTMS. The primary object is to measure the percentage change in the severity of anhedonia, using the Snaith-Hamilton Pleasure Scale (SHAPS). The assessment will be conducted from the baseline to 8-week post-treatment period. The secondary outcome includes encompassing fMRI measurements, scores on the 17-item Hamilton Rating Scale for Depression (HAMD-17), the Montgomery Asberg Depression Rating Scale (MADRS), the Chinese Version of Temporal Experience of Pleasure Scale (CV-TEPS), and the Chinese Version of Beck Scale for Suicide Ideation (BSI-CV). The Clinical Global Impression (CGI) scores will also be taken into account, and adverse events will be monitored. These evaluations will be conducted at baseline, as well as at 1, 2, 4, and 8 weeks. Discussion If the hypothesis of the current study is confirmed, (fcMRI)-guided rTMS could be a powerful tool to alleviate the core symptoms of MDD and provide essential data to explore the mechanism of anhedonia. Trial registration ClinicalTrials.gov NCT05544071. Registered on 16 September 2022.

Abstract High suicide risk represents a serious problem in patients with major depressive disorder (MDD), yet treatment options that could safely and rapidly ameliorate suicidal ideation remain elusive. Here, we tested the feasibility and preliminary efficacy of the Stanford Accelerated Intelligent Neuromodulation Therapy (SAINT) in reducing suicidal ideation in patients with MDD. Thirty-two MDD patients with moderate to severe suicidal ideation participated in the current study. Suicidal ideation and depression symptoms were assessed before and after 5 days of open-label SAINT. The neural pathways supporting rapid-acting antidepressant and suicide prevention effects were identified with dynamic causal modelling based on resting-state functional magnetic resonance imaging. We found that 5 days of SAINT effectively alleviated suicidal ideation in patients with MDD with a high response rate of 65.63%. Moreover, the response rates achieved 78.13% and 90.63% with 2 weeks and 4 weeks after SAINT, respectively. In addition, we found that the suicide prevention effects of SAINT were associated with the effective connectivity involving the insula and hippocampus, while the antidepressant effects were related to connections of the subgenual anterior cingulate cortex (sgACC). These results show that SAINT is a rapid-acting and effective way to reduce suicidal ideation. Our findings further suggest that distinct neural mechanisms may contribute to the rapid-acting effects on the relief of suicidal ideation and depression, respectively.

Background: Auditory Verbal Hallucinations (AVH) constitute a prominent feature of schizophrenia. Although low-frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated therapeutic benefits in ameliorating AVH, the underlying mechanisms of its efficacy necessitate further elucidation. Objective: This study investigated the cortical gradient characteristics and their associations with clinical responses in schizophrenia patients with AVH, mediated through 1 Hz rTMS targeting the left temporoparietal junction. Method: Functional gradient metrics were employed to examine the hierarchy patterns of cortical organization, capturing whole-brain functional connectivity profiles in patients and controls. Results: The 1 Hz rTMS treatment effectively ameliorated the positive symptoms in patients, specifically targeting AVH. Initial evaluations revealed expanded global gradient distribution patterns and specific principal gradient variations in certain brain regions in patients at baseline compared to a control cohort. Following treatment, these divergent global and local patterns showed signs of normalizing. Furthermore, there was observed a closer alignment in between-network dispersion among various networks after treatment, including the somatomotor, attention, and limbic networks, indicating a potential harmonization of brain functionality. Conclusion: Low-frequency rTMS induces alternations in principal functional gradient patterns, may serve as imaging markers to elucidate the mechanisms underpinning the therapeutic efficacy of rTMS on AVH in schizophrenia.

Solar active regions (ARs) provide the required magnetic energy and the topology configuration for flares. Apart from conventional static magnetic parameters, the evolution of AR magnetic flux systems should have nonnegligible effects on magnetic energy store and the trigger mechanism of eruptions, which would promote the prediction for the flare using photospheric observations conveniently. Here we investigate 322 large (M- and X-class) flares from 2010 to 2019, almost the whole solar cycle 24. The flare occurrence rate is obviously higher in the developing phase, which should be due to the stronger shearing and complex configurations caused by affluent magnetic emergences. However, the probability of flare eruptions in decaying phases of ARs is obviously higher than that in the developing phase. The confined flares were in nearly equal counts to eruptive flares in developing phases, whereas the eruptive flares were half over confined flares in decaying phases. Yearly looking at flare eruption rates demonstrates the same conclusion. The relationship between sunspot group areas and confined/erupted flares also suggested that the strong field make constraints on the mass ejection, though it can contribute to flare productions. The flare indexes also show a similar trend. It is worth mentioning that all the X-class flares in the decaying phase were erupted, without the strong field constraint. The decaying of magnetic flux systems had facilitation effects on flare eruptions, which may be consequent on the splitting of magnetic flux systems.

It is posited that cognitive and affective dysfunction in patients with major depression disorder (MDD) may be caused by dysfunctional signal propagation in the brain. By leveraging dynamic causal modeling, we investigated large-scale directed signal propagation (effective connectivity) among distributed large-scale brain networks with 43 MDD patients and 56 healthy controls. The results revealed the existence of two mutual inhibitory systems: the anterior default mode network, auditory network, sensorimotor network, salience network and visual networks formed an “emotional” brain, while the posterior default mode network, central executive networks, cerebellum and dorsal attention network formed a “rational brain”. These two networks exhibited excitatory intra-system connectivity and inhibitory inter-system connectivity. Patients were characterized by potentiated intra-system connections within the “emotional/sensory brain”, as well as over-inhibition of the “rational brain” by the “emotional/sensory brain”. The hierarchical architecture of the large-scale effective connectivity networks was then analyzed using a PageRank algorithm which revealed a shift of the controlling role of the “rational brain” to the “emotional/sensory brain” in the patients. These findings inform basic organization of distributed large-scale brain networks and furnish a better characterization of the neural mechanisms of depression, which may facilitate effective treatment.

A new analytical solution is proposed for steady seepage flow around twin circular tunnels in fully saturated anisotropic ground. The solution is an exact one that fully satisfies all the boundary conditions and precisely considers the different permeabilities along two directions and the interactions between twin tunnels. The solution provides a fast approach for the estimation of the seepage field and a useful tool for design optimization. The solution is successfully addressed using problem equivalence and the Schwartz alternating method combined with a mapping function. Using a coordinate transformation of the governing equation, the anisotropic problem of circular tunnels is first equivalent to that of isotropic elliptical tunnels, and the length of the ellipse along the anisotropic axis depends on the anisotropic permeability ratio. The Schwartz alternating method is then employed to address the solution of equivalent elliptical twin tunnel problems, where a mapping function, with which an elliptical tunnel in the half-plane can be mapped into an annulus in the image plane, is introduced to solve the single tunnel problems in each iterative step. The iterative procedure is quite simple and efficient in its calculations and achieves good convergence, and the analytical solution agrees very well with the numerical results to reflect its high precision in the entire ground. Finally, parametric studies are performed to investigate the influences of the anisotropic permeability and tunnel spacing on the seepage field. This is the first study to provide the exact analytical solution of the seepage field of twin tunnel problems in anisotropic ground, and the procedure can be extended to multiple tunnel problems.

Abstract Major depressive disorder (MDD) is the most prevalent form of depression and is becoming a great challenge for public health and medical practice. Although first-line antidepressants offer therapeutic benefits, about 35% of depressed patients are not adequately treated, creating a substantial unmet medical need. A multicenter, double-blind, randomized, placebo-controlled phase 3 clinical trial was conducted in patients with MDD in China to assess the efficacy and safety of ansofaxine (LY03005), a potential triple reuptake inhibitor of serotonin, norepinephrine, and dopamine. Eligible 588 MDD patients were included and randomly assigned (1:1:1) to 8-week treatment with ansofaxine 80 mg/day(n = 187), ansofaxine 160 mg/day(n = 186), or placebo(n = 185). The primary efficacy endpoint was the Montgomery-Åsberg Depression Rating Scale (MADRS) total score change from baseline to the end of the study. Safety indexes included adverse events, vital signs, physical examination, laboratory tests, 12-lead electrocardiogram (ECG), and evaluation of suicide tendency and sexual function. Significant differences were found in mean changes in MADRS total score at week 8 in the two ansofaxine groups (80 mg, −20.0; 160 mg, −19.9) vs. placebo (−14.6; p

Abstract Background Major depressive disorder (MDD) with atypical features, namely depression with atypical features (AFD), is one of the most common clinical specifiers of MDD, closely associated with bipolar disorder (BD). However, there is still a lack of clinical guidelines for the diagnosis, treatment, and prognosis of AFD. Our study mainly focuses on three issues about how to identify AFD, what is the appropriate individualized treatment for AFD, and what are the predictive biomarkers of conversion to BD. Methods The Study of Individualized Diagnosis and Treatment for Depression with Atypical Features (iDoT-AFD) is a multicenter, prospective, open-label study consisting of a 12-week randomized controlled trial (RCT) and a continued follow-up until 4 years or reaching the study endpoint. It is enrolling 480 patients with AFD (120 per treatment arm), 100 patients with BD, and 100 healthy controls (HC). Multivariate dimension information is collected including clinical features, cognitive function, kynurenine pathway metabolomics, and multimodal magnetic resonance imaging (MRI) data. Firstly, multivariate informatics analyses are performed to recognize patients with AFD from participants including the first-episode and recurrent atypical depression, patients with BD, and patients with HC. Secondly, patients with atypical depression are randomly allocated to one of the four treatment groups including “single application of selective serotonin reuptake inhibitor (SSRI) or serotonin-noradrenaline reuptake inhibitor (SNRI)”, “SSRI/SNRI combined with mood stabilizer,” “SSRI/SNRI combined with quetiapine (≥ 150 mg/day),” or “treatment as usual (TAU)” and then followed up 12 weeks to find out the optimized treatment strategies. Thirdly, patients with atypical depression are followed up until 4 years or switching to BD, to explore the risk factors of conversion from atypical depression to BD and eventually build the risk warning model of conversion to BD. Discussion The first enrolment was in August 2019. The iDoT-AFD study explores the clinical and biological markers for the diagnosis, treatment, and prognosis of AFD and further provides evidence for clinical guidelines of AFD. Trial registration ClinicalTrials.gov NCT04209166. Registered on December 19, 2019.

We report an M9.3 flare and filaments activities from NOAA Active Region 11261 that are strongly modulated by the 3D magnetic skeleton. Magnetic field extrapolation from the vector magnetic field suggests complex magnetic connectivity and the existence of a high coronal null point southeast of the active region. A small filament over the inversed V-shaped polarity inversion line erupted and resulted in the M9.3 flare associated with a weak ejection in the EUV hot channel and the formation of a relatively large filament. Both the weak ejection and the eruption of the large filament were toward the southeast. Comparative analyses have disclosed the following new facts. First, the trajectory of looptop hard X-ray emission provides solid evidence that the magnetic reconnection site propagated up toward the coronal null point as the flare and filaments erupted. Second, the EVU observations show coronal mass ejection-like eruption features in the ejection region of the magnetic skeleton. Third, the closed fan confined the west end of the large filament and the corresponding flare ribbons. We demonstrate a spatiotemporal relationship between the magnetic skeleton and the flare filament activity. We conclude that the magnetic skeleton can modulate and determine almost all the characteristics of the studied activity in the corresponding scale.

The formation mechanism of light bridges (LBs) is strongly related to the dynamic evolution of solar active regions (ARs). To study the relationship between LB formation and AR evolution phases, we employ 109 LB samples from 69 ARs in 2014 using observational data from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. LBs are well matched with the weak field lanes (WFLs), except those aligned on the polarity inversion line of δ sunspots. For penumbral intrusion (type-A) and umbral-dot emergence (type-C) LBs, the WFLs represent the splitting of magnetic flux systems. The sunspots tend to decay and split into several parts after type-A and type-C LBs are formed. For sunspot/umbra-merging (type-B) LBs, the declining WFLs are caused by collisions of flux systems. The sunspots merged and remained stable after type-B LBs formed. We conclude that type-B LBs are formed by collisions of flux systems, while type-A and type-C LBs are generated by splits. The time differences ( δ T ) between LBs appearing and ARs peaking have an average value of 1.06, −1.60, and 1.82 days for type-A, B, and C LBs, with the standard deviations of 3.27, 2.17, and 1.89, respectively. A positive value of δ T means that the LB appears after the AR peaks, whereas a negative δ T means it appears before the peak. Type-A LBs tend to form in the decaying phase or around the peak time. Type-B LBs are more likely to be formed in the developing phase. Type-C LBs mostly take shape in the decaying phase of ARs.

PurposeRepetitive transcranial magnetic stimulation (rTMS) is an effective therapy in improving depressive symptoms in MDD patients, but the intrinsic mechanism is still unclear. In this study, we investigated the influence of rTMS on brain gray matter volume for alleviating depressive symptoms in MDD patients using structural magnetic resonance imaging (sMRI) data.MethodsPatients with first episode, unmedicated patients with MDD (n = 26), and healthy controls (n = 31) were selected for this study. Depressive symptoms were assessed before and after treatment by using the HAMD-17 score. High-frequency rTMS treatment was conducted in patients with MDD over 15 days. The rTMS treatment target is located at the F3 point of the left dorsolateral prefrontal cortex. Structural magnetic resonance imaging (sMRI) data were collected before and after treatment to compare the changes in brain gray matter volume.ResultsBefore treatment, patients with MDD had significantly reduced gray matter volumes in the right fusiform gyrus, left and right inferior frontal gyrus (triangular part), left inferior frontal gyrus (orbital part), left parahippocampal gyrus, left thalamus, right precuneus, right calcarine fissure, and right median cingulate gyrus compared with healthy controls (P < 0.05). After rTMS treatment, significant growth in gray matter volume of the bilateral thalamus was observed in depressed patients (P < 0.05).ConclusionBilateral thalamic gray matter volumes were enlarged in the thalamus of MDD patients after rTMS treatment and may be the underlying neural mechanism for the treatment of rTMS on depression.

Introduction: Compelling evidence indicates that a single sub-anesthetic dose of (S)-ketamine elicits rapid and robust antidepressant effects. However, the underlying mechanisms behind the antidepressant effects of (S)-ketamine remain unclear.Methods: Here, using a chronic variable stress (CVS) model in mice, we analyzed changes inthe lipid compositions of the hippocampus and prefrontal cortex (PFC) with a mass spectrometry-based lipidomic approach.Results: Similar to previous research outcomes, the current study also showed that (S)-ketamine reversed depressive-like behaviors in mice produced by CVS procedures. Moreover, CVS induced changes inthe lipid compositions of the hippocampus and PFC, notably in the contents of sphingolipids, glycerolipids, and fatty acyls. With the administration of (S)-ketamine, CVS-induced lipid disturbances were partially normalized, particularly in the hippocampus.Conclusion: Altogether, our results indicated that (S)-ketamine could rescue CVS-induced depressive-like behaviors in mice through region-specific modulation of the brain lipidome, contributing to the understanding of (S)-ketamine’s antidepressant effects.

The human brain comprises a large-scale structural network of regions and interregional pathways, including a selectively defined set of highly central and interconnected hub regions, often referred to as the “rich club”, which may play a pivotal role in the integrative processes of the brain. A quintessential symptom of schizophrenia, auditory verbal hallucinations (AVH) have shown a decrease in severity following low-frequency repetitive transcranial magnetic stimulation (rTMS). However, the underlying mechanism of rTMS in treating AVH remains elusive. This study investigated the effect of low-frequency rTMS on the rich-club organization within the brain in patients diagnosed with schizophrenia who experience AVH using diffusion tensor imaging data. Through by constructing structural connectivity networks, we identified several critical rich hub nodes, which constituted a rich-club subnetwork, predominantly located in the prefrontal cortices. Notably, our findings revealed enhanced connection strength and density within the rich-club subnetwork following rTMS treatment. Furthermore, we found that the decreased connectivity within the subnetwork components, including the rich-club subnetwork, was notably enhanced in patients following rTMS treatment. In particular, the increased connectivity strength of the right median superior frontal gyrus, which functions as a critical local bridge, with the right postcentral gyrus exhibited a significant correlation with improvements in both positive symptoms and AVH. These findings provide valuable insights into the role of rTMS in inducing reorganizational changes within the rich-club structural network in schizophrenia and shed light on potential mechanisms through which rTMS may alleviate AVH.

BackgroundAuditory verbal hallucinations (AVH) are a core symptom of schizophrenia. Low-frequency (e.g., 1 Hz) repetitive transcranial magnetic stimulation (rTMS) targeting language processing regions (e.g., left TPJ) has been evident as a potential treatment for AVH. However, the underlying neural mechanisms of the rTMS treatment effect remain unclear. The present study aimed to investigate the effects of 1 Hz rTMS on functional connectivity (FC) of the temporoparietal junction area (TPJ) seed with the whole brain in schizophrenia patients with AVH.MethodsUsing a single-blind placebo-controlled randomized clinical trial, 55 patients with AVH were randomly divided into active treatment group (n = 30) or placebo group (n = 25). The active treatment group receive 15-day 1 Hz rTMS stimulation to the left TPJ, whereas the placebo group received sham rTMS stimulation to the same site. Resting-state fMRI scans and clinical measures were acquired for all patients before and after treatment. The seed-based (left TPJ) static and DFC was used to assess the connectivity characteristics during rTMS treatment in patients with AVH.ResultsOverall, symptom improvement following 1 Hz rTMS treatment was found in the active treatment group, whereas no change occurred in the placebo group. Moreover, decreased static FC (SFC) of the left TPJ with the right temporal lobes, as well as increased SFC with the prefrontal cortex and subcortical structure were observed in active rTMS group. Increased dynamic FC (DFC) of the left TPJ with frontoparietal areas was also found in the active rTMS group. However, seed-based SFC and DFC were reduced to a great extent in the placebo group. In addition, these changed FC (SFC) strengths in the active rTMS group were associated with reduced severity of clinical outcomes (e.g., positive symptoms).ConclusionThe application of 1 Hz rTMS over the left TPJ may affect connectivity characteristics of the targeted region and contribute to clinical improvement, which shed light on the therapeutic effect of rTMS on schizophrenia with AVH.

Abstract Even though the prevalence of benefit finding (BF) has been empirically shown to exist among breast cancer (BC) survivals, how does benefit finding evolve over time remains inadequately investigated. The objective of this cohort study is to examine how BF evolves over time among Chinese breast cancer survivals and determine the demographic, medical and psychosocial factors that can sustain BF increase over time. Participants were 486 women with different stages of breast cancer (stages I, II and III) followed from completion of primary treatment. Analysis were performed on the data collected during 2014–2019. During the assessment, each participant completed self-report questionnaires of characteristics and benefit finding at six time points with the interval of 6 months since BC diagnosis. The relationships between demographic, medical and psychosocial characteristics and benefit finding evolution over time were examined using mixed models. Participants reported mixed results on the evolving patterns of benefit finding: 28% reported an upward trend in BF scoring over time, 49% instead reported an downward trend, and the remaining 23% reported no obvious change. Our study has shown that some well-known covariates of benefit finding, e.g. education, income, and social support, are not associated with BF trends. In comparison, levels of spirituality and disease coping at diagnosis can more reliably predict BF evolution over time. Identifying the sustaining factors of benefit finding in the experience of breast cancer is the key to design effective psycho clinical solutions for patients’ long-term post-traumatic growth. As time goes by, breast cancer patients may experience less benefit finding. Our results strongly indicate that benefit finding can be sustained and increased by encouraging attempts at meaning-making and active disease coping during breast cancer treatment. To the best of our knowledge, this study is among the first to examine the evolution trends of benefit finding over time on breast cancer survivals and determine their psychosocial predictors in developing countries.

IntroductionUnderstanding the neurological basis of autism spectrum disorder (ASD) is important for the diagnosis and treatment of this mental disorder. Emerging evidence has suggested aberrant functional connectivity of large-scale brain networks in individuals with ASD. However, whether the effective connectivity which measures the causal interactions of these networks is also impaired in these patients remains unclear.ObjectsThe main purpose of this study was to investigate the effective connectivity of large-scale brain networks in patients with ASD during resting state.Materials and methodsThe subjects were 42 autistic children and 127 age-matched normal children from the ABIDE II dataset. We investigated effective connectivity of 7 large-scale brain networks including visual network (VN), default mode network (DMN), cerebellum, sensorimotor network (SMN), auditory network (AN), salience network (SN), frontoparietal network (FPN), with spectral dynamic causality model (spDCM). Parametric empirical Bayesian (PEB) was used to perform second-level group analysis and furnished group commonalities and differences in effective connectivity. Furthermore, we analyzed the correlation between the strength of effective connectivity and patients’ clinical characteristics.ResultsFor both groups, SMN acted like a hub network which demonstrated dense effective connectivity with other large-scale brain network. We also observed significant causal interactions within the “triple networks” system, including DMN, SN and FPN. Compared with healthy controls, children with ASD showed decreased effective connectivity among some large-scale brain networks. These brain networks included VN, DMN, cerebellum, SMN, and FPN. In addition, we also found significant negative correlation between the strength of the effective connectivity from right angular gyrus (ANG_R) of DMN to left precentral gyrus (PreCG_L) of SMN and ADOS-G or ADOS-2 module 4 stereotyped behaviors and restricted interest total (ADOS_G_STEREO_BEHAV) scores.ConclusionOur research provides new evidence for the pathogenesis of children with ASD from the perspective of effective connections within and between large-scale brain networks. The attenuated effective connectivity of brain networks may be a clinical neurobiological feature of ASD. Changes in effective connectivity of brain network in children with ASD may provide useful information for the diagnosis and treatment of the disease.

Abstract Schizophrenia (SZ) is a neurodevelopmental disorder. There remain significant gaps in understanding the neural trajectory across development in SZ. A major research focus is to clarify the developmental functional changes of SZ and to identify the specific timing, the specific brain regions, and the underlying mechanisms of brain alterations during SZ development. Regional homogeneity (ReHo) characterizing brain function was collected and analyzed on humans with SZ (hSZ) and healthy controls (HC) cross-sectionally, and methylazoxymethanol acetate (MAM) rats, a neurodevelopmental model of SZ, and vehicle rats longitudinally from adolescence to adulthood. Metabolomic and proteomic profiling in adult MAM rats and vehicle rats was examined and bioanalyzed. Compared to HC or adult vehicle rats, similar ReHo alterations were observed in hSZ and adult MAM rats, characterized by increased frontal (medial prefrontal and orbitofrontal cortices) and decreased posterior (visual and associated cortices) ReHo. Longitudinal analysis of MAM rats showed aberrant ReHo patterns as decreased posterior ReHo in adolescence and increased frontal and decreased posterior ReHo in adulthood. Accordingly, it was suggested that the visual cortex was a critical locus and adolescence was a sensitive window in SZ development. In addition, metabolic and proteomic alterations in adult MAM rats suggested that central carbon metabolism disturbance and mitochondrial dysfunction were the potential mechanisms underlying the ReHo alterations. This study proposed frontal-posterior functional imbalance and aberrant function developmental patterns in SZ, suggesting that the adolescent visual cortex was a critical locus and a sensitive window in SZ development. These findings from linking data between hSZ and MAM rats may have a significant translational contribution to the development of effective therapies in SZ.

Low-frequency repetitive transcranial magnetic stimulation (rTMS) has been shown to reduce the severity of auditory verbal hallucinations (AVH) and induce beneficial functional and structural alternations of the brain in schizophrenia patients with AVH. The nucleus accumbens (NAcc) as an important component of the ventral striatum is implicated with the pathology in AVH. However, the induced characteristic patterns of NAcc by low-frequency rTMS in schizophrenia with AVH are seldom explored. We investigated the functional and structural characteristic patterns of NAcc by using seed-based functional connectivity (FC) analysis and gray matter volume (GMV) measurement in schizophrenia patients with AVH during 1 Hz rTMS treatment. Although low-frequency rTMS treatment did not affect the volumetric changes of NAcc, the abnormal FC patterns of NAcc, including increased FC of NAcc with the temporal lobes and decreased FC of NAcc with the frontal cortices in the pretreatment patients compared to healthy controls, were normalized or reversed after treatment. These FC changes were associated with improvements in clinical symptoms and neurocognitive functions. Our findings may extend our understanding of the NAcc in the pathology of schizophrenia with AVH and might be a biomarker of clinical effect for low-frequency rTMS treatment in schizophrenia.

The aim of this study was to develop a brief version of cognitive assessment test for evaluating the efficacy of treatments targeting cognitive impairments in Chinese schizophrenia patients, to examine its reliability, and establish normative data. Stratified according to age, gender, and educational level, healthy adult subjects were recruited from fifteen institutions in seven administrative regions of China and 723 valid samples were obtained, of which 50 were retested. Generalized Linear Models were conducted to analyze the effects of age, sex, and education. There was no significant difference between genders, while significant effects were demonstrated respectively among age and education on the normative data of C-BCT. The Cronbach α of C-BCT is 0.75, and the test-retest reliability (ICC) ranged from 0.62 to 0.76. Normative data of C-BCT were generated by gender, age and education, and the effects of these demographic factors were analyzed. It revealed good internal consistency and test-retest reliability of C-BCT.

ObjectiveRepetitive transcranial magnetic stimulation (rTMS) can effectively improve depression symptoms in patients with major depressive disorder (MDD); however, its mechanism of action remains obscure. This study explored the neuralimaging mechanisms of rTMS in improving depression symptoms in patients with MDD.MethodsIn this study, MDD patients with first-episode, drug-naive (n = 29) and healthy controls (n = 33) were enrolled. Depression symptoms before and after rTMS treatment were assessed using the Hamilton Depression Rating Scale (HAMD-17). Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected both before and after the treatment. Changes in the brain function after the treatment were compared using the following two indices: the amplitude of the low-frequency fluctuation (ALFF) and regional homogeneity (ReHo), which are sensitive for evaluating spontaneous neuronal activity. The brain region with synchronous changes was selected as the seed point, and the differences in the causal connectivity between the seed point and whole brain before and after rTMS treatment were investigated via Granger causality analysis (GCA).ResultsBefore treatment, patients with MDD had significantly lower ALFF in the left superior frontal gyrus (p < 0.01), higher ALFF in the left middle frontal gyrus and left precuneus (p < 0.01), and lower ReHo in the left middle frontal and left middle occipital gyri (p < 0.01) than the values observed in healthy controls. After the rTMS treatment, the ALFF was significantly increased in the left superior frontal gyrus (p < 0.01) and decreased in the left middle frontal gyrus and left precuneus (p < 0.01). Furthermore, ReHo was significantly increased in the left middle frontal and left middle occipital gyri (p < 0.01) in patients with MDD. Before treatment, GCA using the left middle frontal gyrus (the brain region with synchronous changes) as the seed point revealed a weak bidirectional causal connectivity between the middle and superior frontal gyri as well as a weak causal connectivity from the inferior temporal to the middle frontal gyri. After treatment, these causal connectivities were strengthened. Moreover, the causal connectivity from the inferior temporal gyrus to the middle frontal gyri negatively correlated with the total HAMD-17 score (r = −0.443, p = 0.021).ConclusionrTMS treatment not only improves the local neural activity in the middle frontal gyrus, superior frontal gyrus, and precuneus but also strengthens the bidirectional causal connectivity between the middle and superior frontal gyri and the causal connectivity from the inferior temporal to the middle frontal gyri. Changes in these neuroimaging indices may represent the neural mechanisms underlying rTMS treatment in MDD.Clinical Trial RegistrationThis study was registered in the Chinese Clinical Trial Registry (Registration number: ChiCTR1800019761).

Emotional blunting is frequently reported by patients with major depressive disorder (MDD) and has been identified as one of the most prominent side effects of antidepressants leading to medication discontinuation. However, antidepressant-induced emotional blunting remains largely unexplored—there lacks a clinical definition of this condition, and no agreeing conclusion has been reached regarding its etiology. Current research suggests that the onset of diminished emotional response may be related to antidepressant dose, with higher doses being more likely to induce emotional blunting. Consequently, most clinicians either reduce the dose or switch to another drug when treating this symptom. Overall, more comprehensive clinical assessments or interviews specifically designed to evaluate antidepressant-induced emotional blunting in MDD patients are in need to elucidate the neuropsychological mechanisms behind this increasingly prevalent symptom.

Suicidal ideation increases precipitously in patients with depression, contributing to the risk of suicidal attempts. Despite the recent advancement in transcranial magnetic stimulation, its effectiveness in depression disorder and its wide acceptance, the network mechanisms of the clinical response to suicidal ideation in major depressive disorder remain unclear. Independent component analysis for neuroimaging data allows the identification of functional network connectivity which may help to explore the neural basis of suicidal ideation in major depressive disorder. Resting-state functional magnetic resonance imaging data and clinical scales were collected from 30 participants (15 major depressive patients with suicidal ideation and 15 healthy subjects). Individual target-transcranial magnetic stimulation (IT-TMS) was then used to decrease the subgenual anterior cingulate cortex activity through the left dorsolateral prefrontal cortex. Thirty days post IT-TMS therapy, seven of 15 patients (46.67%) met suicidal remission criteria, and 12 patients (80.00%) met depression remission criteria. We found that IT-TMS could restore the abnormal functional network connectivity between default mode network and precuneus network, left executive control network and sensory-motor network. Furthermore, the changes in functional network connectivity between the default mode network and precuneus network were associated with suicidal ideation, and depressive symptoms were related to connectivity between left executive control network and sensory-motor network. These findings illustrate that IT-TMS is an effective protocol for the accurate restoration of impaired brain networks, which is consistent with clinical symptoms.

BackgroundLow-frequency transcranial magnetic stimulation (rTMS) over the left temporoparietal cortex reduces the auditory verbal hallucination (AVH) in schizophrenia. However, the underlying neural basis of the rTMS treatment effect for schizophrenia remains not well understood. This study investigates the rTMS induced brain functional and structural alternations and their associations with clinical as well as neurocognitive profiles in schizophrenia patients with AVH.MethodsThirty schizophrenia patients with AVH and thirty-three matched healthy controls were enrolled. The patients were administered by 15 days of 1 Hz rTMS delivering to the left temporoparietal junction (TPJ) area. Clinical symptoms and neurocognitive measurements were assessed at pre- and post-rTMS treatment. The functional (amplitude of low-frequency fluctuation, ALFF) and structural (gray matter volume, GMV) alternations were compared, and they were then used to related to the clinical and neurocognitive measurements after rTMS treatment.ResultsThe results showed that the positive symptoms, including AVH, were relieved, and certain neurocognitive measurements, including visual learning (VisLearn) and verbal learning (VerbLearn), were improved after the rTMS treatment in the patient group. Furthermore, the rTMS treatment induced brain functional and structural alternations in patients, such as enhanced ALFF in the left superior frontal gyrus and larger GMV in the right inferior temporal cortex. The baseline ALFF and GMV values in certain brain areas (e.g., the inferior parietal lobule and superior temporal gyrus) could be associated with the clinical symptoms (e.g., positive symptoms) and neurocognitive performances (e.g., VerbLearn and VisLearn) after rTMS treatment in patients.ConclusionThe low-frequency rTMS over the left TPJ area is an efficacious treatment for schizophrenia patients with AVH and could selectively modulate the neural basis underlying psychiatric symptoms and neurocognitive domains in schizophrenia.

The protective effects of repetitive transcranial magnetic stimulation (rTMS) on myelin integrity have been extensively studied, and growing evidence suggests that rTMS is beneficial in improving cognitive functions and promoting myelin repair. However, the association between cognitive improvement due to rTMS and changes in brain lipids remains elusive. In this study, we used the Y-maze and 3-chamber tests, as well as a mass spectrometry-based lipidomic approach in a CPZ-induced demyelination model in mice to assess the protective effects of rTMS on cuprizone (CPZ)-induced cognitive impairment and evaluate changes in lipid composition in the hippocampus, prefrontal cortex, and striatum. We found that CPZ induced cognitive impairment and remarkable changes in brain lipids, specifically in glycerophospholipids. Moreover, the changes in lipids within the prefrontal cortex were more extensive, compared to those observed in the hippocampus and striatum. Notably, rTMS ameliorated CPZ-induced cognitive impairment and partially normalized CPZ-induced lipid changes. Taken together, our data suggest that rTMS may reverse cognitive behavioral changes caused by CPZ-induced demyelination by modulating the brain lipidome, providing new insights into the therapeutic mechanism of rTMS.

Background: Current fMRI-based classification approaches mostly use functional connectivity or spatial maps as input, instead of exploring the dynamic time courses directly, which does not leverage the full temporal information. Methods: Motivated by the ability of recurrent neural networks (RNN) in capturing dynamic information of time sequences, we propose a multi-scale RNN model, which enables classification between 558 schizophrenia and 542 healthy controls by using time courses of fMRI independent components (ICs) directly. To increase interpretability, we also propose a leave-one-IC-out looping strategy for estimating the top contributing ICs. Findings: Accuracies of 83·2% and 80·2% were obtained respectively for the multi-site pooling and leave-one-site-out transfer classification. Subsequently, dorsal striatum and cerebellum components contribute the top two group-discriminative time courses, which is true even when adopting different brain atlases to extract time series. Interpretation: This is the first attempt to apply a multi-scale RNN model directly on fMRI time courses for classification of mental disorders, and shows the potential for multi-scale RNN-based neuroimaging classifications. Fund: Natural Science Foundation of China, the Strategic Priority Research Program of the Chinese Academy of Sciences, National Institutes of Health Grants, National Science Foundation. Keywords: Recurrent neural network (RNN), Schizophrenia, Multi-site classification, fMRI, Striatum, Cerebellum, Deep learning

To overcome the disadvantage of clinical manual sleep staging, a convenient, economical, and efficient multi-class automatic sleep staging method is proposed based on long short-term memory network (LSTM) using single-lead electrocardiogram signals. From electrocardiogram signals, heart rate variability and respiratory signals were calculated, and, then, totally 25 features were extracted. Four different classifiers, including the two-class classifier to distinguish between wake and sleep, the three-class classifier to distinguish wake, non-rapid eye movement sleep, and rapid eye movement, the four-class classifier to distinguish wake, light sleep, slow wave sleep, and rapid eye movement, and the five-class classifier to distinguish wake, sleep stage N1, sleep stage N2, sleep stage N3, and rapid eye movement, were constructed using the LSTM. The single-lead electrocardiogram data from 238 patients with full sleep stages during sleep were used for the training set and the data from other 60 patients were regarded as a validation set. The rest of 75 patients have left aside for testing set. The accuracy of two-class, three-class, four-class, and five-class sleep staging was 89.84%, 84.07%, 77.76% and 71.16% and the Cohen's kappa statistic k was 0.52, 0.58, 0.55, and 0.52, respectively, which realized the moderate agreement with clinical analysis. When expanding the dataset to extra 1068 patients with missing sleep stages, the accuracy has no obvious reduction but the Cohen's kappa statistic k dropped to 0.51, 0.52, 0.48 and 0.43, respectively. The proposed method, in this paper, is promising for low-cost, efficient, and convenient sleep staging in home care monitoring.

ObjectivesTo investigate the improvement effect of occipital repetitive transcranial magnetic stimulation (rTMS) combined with escitalopram oxalate tablets on pre-attentive processing in patients with first-episode, medication-naive depression.MethodsPatients who were hospitalized between January and December 2019 were selected. They were randomly allocated to real occipital rTMS stimulation group with 27 cases receiving intermittent theta-burst (iTBS) and sham stimulation group with 24 cases over 20 days. The rTMS treatment target is located at the Oz point of the occipital region. Both groups took escitalopram oxalate tablets, and the average daily drug dose was 15.294 ± 5.041 mg. Hamilton Depression Rating Scale (HAMD) was used to assess the symptoms of depression before and after treatment, and mismatch negativity (MMN) was used to assess the improvement of pre-attentive processing before and after treatment.ResultsAfter 20 days of treatment, the total score of HAMD (13.495 ± 3.700) in both groups was significantly lower than that before treatment [21.910 ± 3.841, F(1, 49) = 46, 3.690, p < 0.001]. After treatment, the latency of MMN in the real stimulation group (182.204 ± 31.878 ms) was significantly lower than that in the sham stimulation group (219.896 ± 42.634 ms, p < 0.001), and the amplitude of MMN in the real stimulation group (−7.107 ± 3.374 ms) was significantly higher than that in the sham stimulation group (−2.773 ± 3.7 32 ms, p < 0.001).ConclusionOccipital rTMS treatment can enhance the early therapeutic effect and effectively improve the pre-attentive processing of patients with depression and provide a scientific basis for the new target of rTMS therapy in clinical patients with depression.

The aim of the current resting-state functional magnetic resonance imaging (fMRI) study was to investigate the potential mechanism of schizophrenia through the posterior–anterior cerebrum imbalance in methylazoxymethanol acetate (MAM) rats and to evaluate the effectiveness of repetitive transcranial magnetic stimulation (rTMS) as an early-stage intervention. The rats were divided into four groups: the MAM-sham group, vehicle-sham group, MAM-rTMS group, and vehicle-rTMS group. The rTMS treatment was targeted in the visual cortex (VC) in adolescent rats. Granger Causality Analysis (GCA) was used to evaluate the effective connectivity between regions of interest. Results demonstrated a critical right VC–nucleus accumbens (Acb)–orbitofrontal cortex (OFC) pathway in MAM rats; significant differences of effective connectivity (EC) were found between MAM-sham and vehicle-sham groups (from Acb shell to OFC: t = −2.553, p = 0.021), MAM-rTMS and MAM-sham groups (from VC to Acb core: t = −2.206, p = 0.043; from Acb core to OFC: t = 4.861, p < 0.001; from Acb shell to OFC: t = 4.025, p = 0.001), and MAM-rTMS and vehicle-rTMS groups (from VC to Acb core: t = −2.482, p = 0.025; from VC to Acb shell: t = −2.872, p = 0.012; from Acb core to OFC: t = 4.066, p = 0.001; from Acb shell to OFC: t = 3.458, p = 0.004) in the right hemisphere. Results of the early-stage rTMS intervention revealed that right nucleus accumbens played the role as a central hub, and VC was a potentially novel rTMS target region during adolescent schizophrenia. Moreover, the EC of right nucleus accumbens shell and orbitofrontal cortex was demonstrated to be a potential biomarker. To our knowledge, this was the first resting-state fMRI study using GCA to assess the deficits of a visual-reward neural pathway and the effectiveness of rTMS treatment in MAM rats. More randomized controlled trials in both animal models and schizophrenia patients are needed to further elucidate the disease characteristics.

Previous brain structural magnetic resonance imaging studies reported that patients with schizophrenia have brain structural abnormalities, which have been used to discriminate schizophrenia patients from normal controls. However, most existing studies identified schizophrenia patients at a single site, and the genetic features closely associated with highly heritable schizophrenia were not considered. In this study, we performed standardized feature extraction on brain structural magnetic resonance images and on genetic data to separate schizophrenia patients from normal controls. A total of 1010 participants, 508 schizophrenia patients and 502 normal controls, were recruited from 8 independent sites across China. Classification experiments were carried out using different machine learning methods and input features. We tested a support vector machine, logistic regression, and an ensemble learning strategy using 3 feature sets of interest: (1) imaging features: gray matter volume, (2) genetic features: polygenic risk scores, and (3) a fusion of imaging features and genetic features. The performance was assessed by leave-one-site-out cross-validation. Finally, some important brain and genetic features were identified. We found that the models with both imaging and genetic features as input performed better than models with either alone. The average accuracy of the classification models with the best performance in the cross-validation was 71.6%. The genetic feature that measured the cumulative risk of the genetic variants most associated with schizophrenia contributed the most to the classification. Our work took the first step toward considering both structural brain alterations and genome-wide genetic factors in a large-scale multisite schizophrenia classification. Our findings may provide insight into the underlying pathophysiology and risk mechanisms of schizophrenia.

Schizophrenia (SCZ) is an inherited disease, with the familial risk being among the most important factors when evaluating an individual’s risk for SCZ. However, robust imaging biomarkers for the disease that can be used for diagnosis and determination of the prognosis are lacking. Here, we explore the potential of functional connectivity (FC) for use as a biomarker for the early detection of high-risk first-degree relatives (FDRs). Thirty-eight first-episode SCZ patients, 38 healthy controls (HCs), and 33 FDRs were scanned using resting-state functional magnetic resonance imaging. The subjects’ brains were parcellated into 200 regions using the Craddock atlas, and the FC between each pair of regions was used as a classification feature. Multivariate pattern analysis using leave-one-out cross-validation achieved a correct classification rate of 88.15% [sensitivity 84.06%, specificity 92.18%, and area under the receiver operating characteristic curve (AUC) 0.93] for differentiating SCZ patients from HCs. FC located within the default mode, frontal-parietal, auditory, and sensorimotor networks contributed mostly to the accurate classification. The FC patterns of each FDR were input into each classification model as test data to obtain a corresponding prediction label (a total of 76 individual classification scores), and the averaged individual classification score was then used as a robust measure to characterize whether each FDR showed an SCZ-type or HC-type FC pattern. A significant negative correlation was found between the average classification scores of the FDRs and their semantic fluency scores. These findings suggest that FC combined with a machine learning algorithm could help to predict whether FDRs are likely to show an SCZ-specific or HC-specific FC pattern.

The Advanced Space-based Solar Observatory (ASO-S) is a mission aiming at exploring solar flares, coronal mass ejections (CMEs), solar magnetic field and their relationships. To fulfill its major scientific objectives, ASO-S has three elaborately-designed payloads onboard: the Full-disk vector MagnetoGraph (FMG), the Lyman-alpha Solar Telescope (LST), and the Hard X-ray Imager (HXI) dedicated to observe vector magnetic fields, CMEs, and flares, respectively. Beside the scientific objectives, we have an operational objective to observe solar eruptions and magnetic field for making related space weather forecasts. More specifically, we have set a priority for the downlink of CME data observed by LST, and will distribute those data to different space weather prediction centers in China within 2 h once the Science Operation and Data Center (SODC) of ASO-S receive the data. After data downlink and archiving, different automatic detection, tracking, and cataloging procedures are planned to run for the most critical solar eruptive features. On the other hand, based on the distributed and downloaded data, different space weather prediction centers are to activate their forecast systems for the ASO-S observed solar eruption events. Our particular interests are currently focused on nowcast of different eruption events, prediction of CME arrivals, forecast of solar flares and the onset of solar eruptions. We are also working on further forecast potentials using the ASO-S data to make contributions to other possible important issues of space weather.

Background: In the past decades, substantial effort has been made to explore the genetic influence on brain structural/functional abnormalities in schizophrenia, as well as cognitive impairments. In this work, we aimed to extend previous studies to explore the internal mediation pathway among genetic factor, brain features and cognitive scores in a large Chinese dataset. Methods: Gray matter (GM) volume, fractional amplitude of low-frequency fluctuations (fALFF), and 4522 schizophrenia-susceptible single nucleotide polymorphisms (SNP) from 905 Chinese subjects were jointly analyzed, to investigate the multimodal association. Based on the identified imaging-genetic pattern, correlations with cognition and mediation analysis were then conducted to reveal the potential mediation pathways. Findings: One linked imaging-genetic pattern was identified to be group discriminative, which was also associated with working memory performance. Particularly, GM reduction in thalamus, putamen and bilateral temporal gyrus in schizophrenia was associated with fALFF decrease in medial prefrontal cortex, both were also associated with genetic factors enriched in neuron development, synapse organization and axon pathways, highlighting genes including CSMD1, CNTNAP2, DCC, GABBR2 etc. This linked pattern was also replicated in an independent cohort (166 subjects), which although showed certain age and clinical differences with the discovery cohort. A further mediation analysis suggested that GM alterations significantly mediated the association from SNP to fALFF, while fALFF mediated the association from SNP and GM to working memory performance. Interpretation: This study has not only verified the impaired imaging-genetic association in schizophrenia, but also initially revealed a potential genetic-brain-cognition mediation pathway, indicating that polygenic risk factors could exert impact on phenotypic measures from brain structure to function, thus could further affect cognition in schizophrenia. Keywords: Schizophrenia, Multimodal fusion, Genetic-brain-cognition pathway, Working memory, Mediation analysis

Background: A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. Methods: A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Findings: Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. Interpretation: The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the “disconnectivity” model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Keywords: Schizophrenia, Deep learning, Connectome, fMRI, Striatum, Cerebellum

Many studies have focused on patients with schizophrenia with or without auditory verbal hallucinations (AVHs), but due to the complexity of schizophrenia, biologically based diagnosis of patients with schizophrenia remains unsolved. The objectives of this study are to classify between first-episode drug-naïve patients with schizophrenia and healthy controls, and to classify between patients with and without AVHs. Resting state fMRI data from 41 patients with schizophrenia (22 with and 19 without AVHs) and 23 normal controls (NC) were included to compute functional connectivity between brain regions. Classifiers based on support vector machine (SVM) were developed to classify patients with schizophrenia from NC, as well as between the two subgroups of patients. The classification accuracy was evaluated with a leave-one-out cross-validation (LOOCV) strategy. The accuracy in discriminating both subgroups of patients from NC was 81.3%, with 92.0% (sensitivity) and 65.2% (specificity) for the patients and NC, respectively. The classification accuracy in discriminating patients with and without AVHs was 75.6%, with 77.3% (sensitivity) and 73.9% (specificity) for patients with and without AVHs, respectively. The results suggest that functional connectivity provided good discriminative power not only for identifying patients with schizophrenia among NC, but also in discriminating patients with schizophrenia with and without AVHs. Keywords: First episode schizophrenia, Auditory verbal hallucinations, Functional connectivity, Support vector machine

The plasmapause locations determined from the Chang’e-3 (CE-3) Extreme Ultraviolet Camera (EUVC) images and the auroral boundaries determined from the Defense Meteorological Satellite Program (DMSP) Special Sensor Ultraviolet Spectrographic Imager (SSUSI) images are used to investigate the plasmaspheric evolutions during substorms. The most important finding is a nightside pointing plasmaspheric plume observed at 23:05 UT on 21 April 2014 under quiet solar wind and geomagnetic conditions, which drifted from the dusk sector. High correlations between the plasmapause evolutions and the auroral signatures exist during substorms. After substorm onset, the plasmapause erosion and the equatorward expansion of the auroral oval occur almost simultaneously in both MLT and UT, and then both the erosion and the expansion propagate westward and eastward. It is suggested that the plasmaspheric erosion and its MLT propagations are induced by the enhanced earthward plasma convection during substorm period, and the substorm dipolarization causes pitch-angle scattering of plasma sheet electrons and the resulting precipitation excites aurora emissions at the same time.