Altered resting-state brain entropy in cerebral small vessel disease patients with cognitive impairment.

OBJECTIVE: Cerebral small vessel disease (CSVD) is a primary vascular disease of cognitive impairment. Previous studies have predominantly focused on brain linear features. However, the nonlinear measure, brain entropy (BEN), has not been elaborated. Thus, this study is aim to investigate if BEN abnormalities could manifest in CSVD patients with cognitive impairment. METHOD: 34 CSVD patients with cognitive impairment and 37 healthy controls (HCs) were recruited. Analysis of gray matter approximate entropy (ApEn) and sample entropy (SampEn) which are two indices of BEN were calculated. To explore whether BEN can provide unique information, we further performed brain linear methods, namely amplitude of low frequency fluctuation (ALFF) and regional homogeneity (ReHo), to observe their differences. The ratios of BEN/ALFF and BEN/ReHo which represent the coupling of nonlinear and linear features were introduced. Correlation analysis was conducted between imaging indices and cognition. Subsequently, the linear support vector machine (SVM) was used to assess their discriminative ability. RESULTS: CSVD patients exhibited lower ApEn and SamEn value in sensorimotor areas, which were correlated with worse memory and executive function. Additionally, the results of BEN showed little overlap with ALFF and ReHo in brain regions. Correlation analysis also revealed a relationship between the two ratios and cognition. SVM analysis utilizing BEN and its ratios as features achieved an accuracy of 74.64 % (sensitivity: 86.49 %; specificity: 61.76 %; and AUC: 0.82439). CONCLUSION: Our study reveals that the reduction of sensorimotor system complexity is correlated with cognition. BEN exhibits distinctive characteristics in brain activity. Combining BEN and the ratios can be new biomarkers to diagnose CSVD with cognitive impairment.

Brain functional specialization and cooperation in Alzheimer's disease.

BACKGROUND: Cerebral specialization and interhemispheric cooperation are two vital features of the human brain. Their dysfunction may be associated with disease progression in patients with Alzheimer's disease (AD), which is featured as progressive cognitive degeneration and asymmetric neuropathology. OBJECTIVE: This study aimed to examine and define two inherent properties of hemispheric function in patients with AD by utilizing resting-state functional magnetic resonance imaging (rs-fMRI). METHODS: Sixty-four clinically diagnosed AD patients and 52 age- and sex-matched cognitively normal subjects were recruited and underwent MRI and clinical evaluation. We calculated and compared brain specialization (autonomy index, AI) and interhemispheric cooperation (connectivity between functionally homotopic voxels, CFH). RESULTS: In comparison to healthy controls, patients with AD exhibited enhanced AI in the left middle occipital gyrus. This increase in specialization can be attributed to reduced functional connectivity in the contralateral region, such as the right temporal lobe. The CFH of the bilateral precuneus and prefrontal areas was significantly decreased in AD patients compared to controls. Imaging-cognitive correlation analysis indicated that the CFH of the right prefrontal cortex was marginally positively related to the Montreal Cognitive Assessment score in patients and the Auditory Verbal Learning Test score. Moreover, taking abnormal AI and CFH values as features, support vector machine-based classification achieved good accuracy, sensitivity, specificity, and area under the curve by leave-one-out cross-validation. CONCLUSION: This study suggests that individuals with AD have abnormal cerebral specialization and interhemispheric cooperation. This provides new insights for further elucidation of the pathological mechanisms of AD.

A Study on the Effect of Executive Control Network Functional Connection on the Therapeutic Efficacy of Repetitive Transcranial Magnetic Stimulation in Alzheimer's Disease.

Background: Alzheimer's disease (AD) is a neurodegenerative disease characterized by brain network dysfunction. Few studies have investigated whether the functional connections between executive control networks (ECN) and other brain regions can predict the therapeutic effect of repetitive transcranial magnetic stimulation (rTMS). Objective: The purpose of this study is to examine the relationship between the functional connectivity (FC) within ECN networks and the efficacy of rTMS. Methods: We recruited AD patients for rTMS treatment. We established an ECN using baseline period fMRI data and conducted an analysis of the ECN's FC throughout the brain. Concurrently, the support vector regression (SVR) method was employed to project post-rTMS cognitive scores, utilizing the connectional attributes of the ECN as predictive markers. Results: The average age of the patients was 66.86±8.44 years, with 8 males and 13 females. Significant improvement on most cognitive measures. We use ECN connectivity and brain region functions in baseline patients as features for SVR model training and fitting. The SVR model could demonstrate significant predictability for changes in Montreal Cognitive Assessment scores among AD patients after rTMS treatment. The brain regions that contributed most to the prediction of the model (the top 10% of weights) were located in the medial temporal lobe, middle temporal gyrus, frontal lobe, parietal lobe and occipital lobe. Conclusions: The stronger the antagonism between ECN and parieto-occipital lobe function, the better the prediction of cognitive improvement; the stronger the synergy between ECN and fronto-temporal lobe function, the better the prediction of cognitive improvement.

Individual large-scale functional network mapping for major depressive disorder with electroconvulsive therapy.

Personalized functional connectivity mapping has been demonstrated to be promising in identifying underlying neurophysiological basis for brain disorders and treatment effects. Electroconvulsive therapy (ECT) has been proved to be an effective treatment for major depressive disorder (MDD) while its active mechanisms remain unclear. Here, 46 MDD patients before and after ECT as well as 46 demographically matched healthy controls (HC) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. A spatially regularized form of non-negative matrix factorization (NMF) was used to accurately identify functional networks (FNs) in individuals to map individual-level static and dynamic functional network connectivity (FNC) to reveal the underlying neurophysiological basis of therepetical effects of ECT for MDD. Moreover, these static and dynamic FNCs were used as features to predict the clinical treatment outcomes for MDD patients. We found that ECT could modulate both static and dynamic large-scale FNCs at individual level in MDD patients, and dynamic FNCs were closely associated with depression and anxiety symptoms. Importantly, we found that individual FNCs, particularly the individual dynamic FNCs could better predict the treatment outcomes of ECT suggesting that dynamic functional connectivity analysis may be better to link brain functional characteristics with clinical symptoms and treatment outcomes. Taken together, our findings provide new evidence for the active mechanisms and biomarkers for ECT to improve diagnostic accuracy and to guide individual treatment selection for MDD patients.

Decreased inter-hemispheric cooperation in major depressive disorder and its association with neurotransmitter profiles.

BACKGROUND: Inter-hemispheric cooperation is a prominent feature of the human brain, and previous neuroimaging studies have revealed aberrant inter-hemispheric cooperation patterns in patients with major depressive disorder (MDD). Typically, inter-hemispheric cooperation is examined by calculating the functional connectivity (FC) between each voxel in one hemisphere and its anatomical (structurally homotopic) counterpart in the opposite hemisphere. However, bilateral hemispheres are actually asymmetric in anatomy. METHODS: In the present study, we utilized connectivity between functionally homotopic voxels (CFH) to investigate abnormal inter-hemispheric cooperation in 96 MDD patients compared to 173 age- and sex-matched healthy controls (HCs). In addition, we analyzed the spatial correlations between abnormal CFH and the density maps of 13 neurotransmitter receptors and transporters. RESULTS: The CFH values in bilateral orbital frontal gyri and bilateral postcentral gyri were abnormally decreased in patients with MDD. Furthermore, these CFH abnormalities were correlated with clinical symptoms. In addition, the abnormal CFH pattern in MDD patients was spatially correlated with the distribution pattern of 5-HT1AR. LIMITATIONS: drug effect; the cross-sectional research design precludes causal inferences; the neurotransmitter atlases selected were constructed from healthy individuals rather than MDD patients. CONCLUSION: These findings characterized the abnormal inter-hemispheric cooperation in MDD using a novel method and the underlying neurotransmitter mechanism, which promotes our understanding of the pathophysiology of depression.

Reviving Bistable Perception in Patients With Depression by Decreasing the Overestimation of Prior Precision.

Slower perceptual alternations, a notable perceptual effect observed in psychiatric disorders, can be alleviated by antidepressant therapies that affect serotonin levels in the brain. While these phenomena have been well documented, the underlying neurocognitive mechanisms remain to be elucidated. Our study bridges this gap by employing a computational cognitive approach within a Bayesian predictive coding framework to explore these mechanisms in depression. We fitted a prediction error (PE) model to behavioral data from a binocular rivalry task, uncovering that significantly higher initial prior precision and lower PE led to a slower switch rate in patients with depression. Furthermore, serotonin-targeting antidepressant treatments significantly decreased the prior precision and increased PE, both of which were predictive of improvements in the perceptual alternation rate of depression patients. These findings indicated that the substantially slower perception switch rate in patients with depression was caused by the greater reliance on top-down priors and that serotonin treatment's efficacy was in its recalibration of these priors and enhancement of PE. Our study not only elucidates the cognitive underpinnings of depression, but also suggests computational modeling as a potent tool for integrating cognitive science with clinical psychology, advancing our understanding and treatment of cognitive impairments in depression.

Molecular mechanisms underlying structural plasticity of electroconvulsive therapy in major depressive disorder.

Although previous studies reported structural changes associated with electroconvulsive therapy (ECT) in major depressive disorder (MDD), the underlying molecular basis of ECT remains largely unknown. Here, we combined two independent structural MRI datasets of MDD patients receiving ECT and transcriptomic gene expression data from Allen Human Brain Atlas to reveal the molecular basis of ECT for MDD. We performed partial least square regression to explore whether/how gray matter volume (GMV) alterations were associated with gene expression level. Functional enrichment analysis was conducted using Metascape to explore ontological pathways of the associated genes. Finally, these genes were further assigned to seven cell types to determine which cell types contribute most to the structural changes in MDD patients after ECT. We found significantly increased GMV in bilateral hippocampus in MDD patients after ECT. Transcriptome-neuroimaging association analyses showed that expression levels of 726 genes were positively correlated with the increased GMV in MDD after ECT. These genes were mainly involved in synaptic signaling, calcium ion binding and cell-cell signaling, and mostly belonged to excitatory and inhibitory neurons. Moreover, we found that the MDD risk genes of CNR1, HTR1A, MAOA, PDE1A, and SST as well as ECT related genes of BDNF, DRD2, APOE, P2RX7, and TBC1D14 showed significantly positive associations with increased GMV. Overall, our findings provide biological and molecular mechanisms underlying structural plasticity induced by ECT in MDD and the identified genes may facilitate future therapy for MDD.

Development and validation of a machine learning-based predictive model for assessing the 90-day prognostic outcome of patients with spontaneous intracerebral hemorrhage.

BACKGROUND: Spontaneous intracerebral hemorrhage (sICH) is associated with significant mortality and morbidity. Predicting the prognosis of patients with sICH remains an important issue, which significantly affects treatment decisions. Utilizing readily available clinical parameters to anticipate the unfavorable prognosis of sICH patients holds notable clinical significance. This study employs five machine learning algorithms to establish a practical platform for the prediction of short-term prognostic outcomes in individuals afflicted with sICH. METHODS: Within the framework of this retrospective analysis, the model underwent training utilizing data gleaned from 413 cases from the training center, with subsequent validation employing data from external validation center. Comprehensive clinical information, laboratory analysis results, and imaging features pertaining to sICH patients were harnessed as training features for machine learning. We developed and validated the model efficacy using all the selected features of the patients using five models: Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), XGboost and LightGBM, respectively. The process of Recursive Feature Elimination (RFE) was executed for optimal feature screening. An internal five-fold cross-validation was employed to pinpoint the most suitable hyperparameters for the model, while an external five-fold cross-validation was implemented to discern the machine learning model demonstrating the superior average performance. Finally, the machine learning model with the best average performance is selected as our final model while using it for external validation. Evaluation of the machine learning model's performance was comprehensively conducted through the utilization of the ROC curve, accuracy, and other relevant indicators. The SHAP diagram was utilized to elucidate the variable importance within the model, culminating in the amalgamation of the above metrics to discern the most succinct features and establish a practical prognostic prediction platform. RESULTS: A total of 413 patients with sICH patients were collected in the training center, of which 180 were patients with poor prognosis. A total of 74 patients with sICH were collected in the external validation center, of which 26 were patients with poor prognosis. Within the training set, the test set AUC values for SVM, LR, RF, XGBoost, and LightGBM models were recorded as 0.87, 0.896, 0.916, 0.885, and 0.912, respectively. The best average performance of the machine learning models in the training set was the RF model (average AUC: 0.906 ± 0.029, P < 0.01). The model still maintains a good performance in the external validation center, with an AUC of 0.817 (95% CI 0.705-0.928). Pertaining to feature importance for short-term prognostic attributes of sICH patients, the NIHSS score reigned supreme, succeeded by AST, Age, white blood cell, and hematoma volume, among others. In culmination, guided by the RF model's variable importance weight and the model's ROC curve insights, the NIHSS score, AST, Age, white blood cell, and hematoma volume were integrated to forge a short-term prognostic prediction platform tailored for sICH patients. CONCLUSION: We constructed a prediction model based on the results of the RF model incorporating five clinically accessible predictors with reliable predictive efficacy for the short-term prognosis of sICH patients. Meanwhile, the performance of the external validation set was also more stable, which can be used for accurate prediction of short-term prognosis of sICH patients.

Molecular basis underlying changes of brain entropy and functional connectivity in major depressive disorders after electroconvulsive therapy.

INTRODUCTION: Electroconvulsive therapy (ECT) is widely used for treatment-resistant depression. However, it is unclear whether/how ECT can be targeted to affect brain regions and circuits in the brain to dynamically regulate mood and cognition. METHODS: This study used brain entropy (BEN) to measure the irregular levels of brain systems in 46 major depressive disorder (MDD) patients before and after ECT treatment. Functional connectivity (FC) was further adopted to reveal changes of functional couplings. Moreover, transcriptomic and neurotransmitter receptor data were used to reveal genetic and molecular basis of the changes of BEN and functional connectivities. RESULTS: Compared to pretreatment, the BEN in the posterior cerebellar lobe (PCL) significantly decreased and FC between the PCL and the right temporal pole (TP) significantly increased in MDD patients after treatment. Moreover, we found that these changes of BEN and FC were closely associated with genes' expression profiles involved in MAPK signaling pathway, GABAergic synapse, and dopaminergic synapse and were significantly correlated with the receptor/transporter density of 5-HT, norepinephrine, glutamate, etc. CONCLUSION: These findings suggest that loops in the cerebellum and TP are crucial for ECT regulation of mood and cognition, which provides new evidence for the antidepressant effects of ECT and the potential molecular mechanism leading to cognitive impairment.

Electroconvulsive Therapy Regulates Brain Connectome Dynamics in Patients With Major Depressive Disorder.

BACKGROUND: Electroconvulsive therapy (ECT) is an effective treatment for patients with major depressive disorder (MDD), but its underlying neural mechanisms remain largely unknown. The aim of this study was to identify changes in brain connectome dynamics after ECT in MDD and to explore their associations with treatment outcome. METHODS: We collected longitudinal resting-state functional magnetic resonance imaging data from 80 patients with MDD (50 with suicidal ideation [MDD-SI] and 30 without [MDD-NSI]) before and after ECT and 37 age- and sex-matched healthy control participants. A multilayer network model was used to assess modular switching over time in functional connectomes. Support vector regression was used to assess whether pre-ECT network dynamics could predict treatment response in terms of symptom severity. RESULTS: At baseline, patients with MDD had lower global modularity and higher modular variability in functional connectomes than control participants. Network modularity increased and network variability decreased after ECT in patients with MDD, predominantly in the default mode and somatomotor networks. Moreover, ECT was associated with decreased modular variability in the left dorsal anterior cingulate cortex of MDD-SI but not MDD-NSI patients, and pre-ECT modular variability significantly predicted symptom improvement in the MDD-SI group but not in the MDD-NSI group. CONCLUSIONS: We highlight ECT-induced changes in MDD brain network dynamics and their predictive value for treatment outcome, particularly in patients with SI. This study advances our understanding of the neural mechanisms of ECT from a dynamic brain network perspective and suggests potential prognostic biomarkers for predicting ECT efficacy in patients with MDD.

Modulation of hemispheric asymmetry in executive control of attention in schizophrenia with atypical antipsychotic treatment: Potential benefits of olanzapine.

Deficits in executive control of attention have been reported in schizophrenia patients, but can be ameliorated by treatment of atypical antipsychotics along with the symptoms. However, it remains unclear whether this effect is related to a modulation of hemispheric asymmetry in executive control by the medicine. In this behavioral study, we employed a lateralized version of the attention network test to examine the hemispheric asymmetry of executive control in schizophrenia patients before and after olanzapine treatment, compared to matched healthy controls. Executive control was measured as a conflict effect, indexed as the response time (RT) difference between incongruent versus congruent flanker conditions, and was compared between stimuli presented in the left and the right visual field (i.e., processed by right versus left hemisphere of the brain). Results showed that pre-treatment schizophrenia patients revealed a right hemisphere superiority in conflict effect (i.e., a smaller effect in the right hemisphere than in the left hemisphere), driven by the incongruent condition. Olanzapine treatment reduced this right hemisphere superiority by improving the efficiency of the left hemisphere in the incongruent condition. These results suggested that olanzapine treatment may improve the efficiency of executive control in the left hemisphere in schizophrenia patients.

Asymptomatic spinal lesions in patients with AQP4-IgG-positive NMOSD: A real-world cohort study.

OBJECTIVE: This study aims to explore the frequency and influencing factors of asymptomatic spinal lesions (ASLs) and their impact on subsequent relapses in patients with AQP4-IgG-positive NMOSD (AQP4-NMOSD) in a real-world setting. METHODS: We retrospectively reviewed clinical information and spinal MRI data from AQP4-NMOSD patients who had at least one spinal cord MRI during their follow-ups. Kaplan-Meier curves and Cox proportional hazards models were employed to ascertain potential predictors of remission ASLs and to investigate factors associated with subsequent relapses. RESULTS: In this study, we included 129 patients with AQP4-NMOSD and reviewed 173 spinal MRIs during attacks and 89 spinal MRIs during remission. Among these, 6 ASLs (3.5%) were identified during acute attacks, while 8 ASLs (9%) were found during remission. Remission ASLs were linked to the use of immunosuppressive agents, particularly conventional ones, whereas no patients using rituximab developed ASLs (p = 0.005). Kaplan-Meier curve analysis indicated that patients with ASLs had a significantly higher relapse risk (HR = 4.658, 95% CI: 1.519-14.285, p = 0.007) compared to those without. Additionally, the use of mycophenolate mofetil (HR = 0.027, 95% CI: 0.003-0.260, p = 0.002) and rituximab (HR = 0.035, 95% CI: 0.006-0.203, p < 0.001) significantly reduced the relapse risk. However, after accounting for other factors, the presence of ASLs did not exhibit a significant impact on subsequent relapses (HR = 2.297, 95% CI: 0.652-8.085, p = 0.195). INTERPRETATION: ASLs may be observed in patients with AQP4-NMOSD. The presence of ASLs may signify an underlying inflammatory activity due to insufficient immunotherapy. The administration of immunosuppressive agents plays a key role in the presence of remission ASLs and the likelihood of subsequent relapses.

Changed brain entropy and functional connectivity patterns induced by electroconvulsive therapy in majoy depression disorder.

OBJECTIVE: Our objective is to innovatively integrate both linear and nonlinear characteristics of brain signals in Electroconvulsive Therapy (ECT) research, with the goal of uncovering deeper insights into the pathogenesis of Major Depressive Disorder (MDD) and identifying novel targets for other physical intervention therapies. METHODS: We measured brain entropy (BEN) in 42 MDD patients and 42 matched healthy controls (HC) using rs-fMRI data. Brain regions that differed significantly in patients with MDD before and after ECT were extracted. Then, we use these brain regions as seed points to investigate the differences in whole-brain resting-state functional connectivity (RSFC) patterns before and after ECT. RESULTS: Compared to HCs, patients had higher BEN levels in the right precuneus (PCUN.R) and right angular gyrus (ANG.R). After ECT, patients had lower BEN levels in the PCUN.R and ANG.R. Compared with before ECT, patients showed significantly increased RSFC after ECT between the PCUN.R and right middle temporal gyrus and ANG.R. Significantly increased RSFC was observed between the ANG.R and right middle frontal gyrus and right supramarginal gyrus after ECT. CONCLUSION: Combining the linear and nonlinear characteristics of brain signals can effectively explore the pathogenesis of depression and provide new targets for ECT.

Somatosensory cortex and central amygdala regulate neuropathic pain-mediated peripheral immune response via vagal projections to the spleen.

Pain involves neuroimmune crosstalk, but the mechanisms of this remain unclear. Here we showed that the splenic T helper 2 (TH2) immune cell response is differentially regulated in male mice with acute versus chronic neuropathic pain and that acetylcholinergic neurons in the dorsal motor nucleus of the vagus (AChDMV) directly innervate the spleen. Combined in vivo recording and immune cell profiling revealed the following two distinct circuits involved in pain-mediated peripheral TH2 immune response: glutamatergic neurons in the primary somatosensory cortex (GluS1HL)→AChDMV→spleen circuit and GABAergic neurons in the central nucleus of the amygdala (GABACeA)→AChDMV→spleen circuit. The acute pain condition elicits increased excitation from GluS1HL neurons to spleen-projecting AChDMV neurons and increased the proportion of splenic TH2 immune cells. The chronic pain condition increased inhibition from GABACeA neurons to spleen-projecting AChDMV neurons and decreased splenic TH2 immune cells. Our study thus demonstrates how the brain encodes pain-state-specific immune responses in the spleen.

Heterogeneous Brain Abnormalities in Schizophrenia Converge on a Common Network Associated With Symptom Remission.

BACKGROUND AND HYPOTHESIS: There is a huge heterogeneity of magnetic resonance imaging findings in schizophrenia studies. Here, we hypothesized that brain regions identified by structural and functional imaging studies of schizophrenia could be reconciled in a common network. STUDY DESIGN: We systematically reviewed the case-control studies that estimated the brain morphology or resting-state local function for schizophrenia patients in the literature. Using the healthy human connectome (n = 652) and a validated technique "coordinate network mapping" to identify a common brain network affected in schizophrenia. Then, the specificity of this schizophrenia network was examined by independent data collected from 13 meta-analyses. The clinical relevance of this schizophrenia network was tested on independent data of medication, neuromodulation, and brain lesions. STUDY RESULTS: We identified 83 morphological and 60 functional studies comprising 7389 patients with schizophrenia and 7408 control subjects. The "coordinate network mapping" showed that the atrophy and dysfunction coordinates were functionally connected to a common network although they were spatially distant from each other. Taking all 143 studies together, we identified the schizophrenia network with hub regions in the bilateral anterior cingulate cortex, insula, temporal lobe, and subcortical structures. Based on independent data from 13 meta-analyses, we showed that these hub regions were specifically connected with regions of cortical thickness changes in schizophrenia. More importantly, this schizophrenia network was remarkably aligned with regions involving psychotic symptom remission. CONCLUSIONS: Neuroimaging abnormalities in cross-sectional schizophrenia studies converged into a common brain network that provided testable targets for developing precise therapies.

Corrigendum: Plasma exchange for two patients with autoimmune GFAP astrocytopathy with rapid progression to respiratory failure: a case report.

[This corrects the article DOI: 10.3389/fimmu.2023.1265609.].

Effects of a periodic intermittent theta burst stimulation in Alzheimer's disease.

Background: Previous studies have demonstrated that excitatory repetitive transcranial magnetic stimulation (rTMS) can improve the cognitive function of patients with Alzheimer's disease (AD). Intermittent theta burst stimulation (iTBS) is a novel excitatory rTMS protocol for brain activity stimulation with the ability to induce long-term potentiation-like plasticity and represents a promising treatment for AD. However, the long-term effects of iTBS on cognitive decline and brain structure in patients with AD are unknown. Aims: We aimed to explore whether repeating accelerated iTBS every three months could slow down the cognitive decline in patients with AD. Methods: In this randomised, assessor-blinded, controlled trial, iTBS was administered to the left dorsolateral prefrontal cortex (DLPFC) of 42 patients with AD for 14 days every 13 weeks. Measurements included the Montreal Cognitive Assessment (MoCA), a comprehensive neuropsychological battery, and the grey matter volume (GMV) of the hippocampus. Patients were evaluated at baseline and after follow-up. The longitudinal pipeline of the Computational Anatomy Toolbox for SPM was used to detect significant treatment-related changes over time. Results: The iTBS group maintained MoCA scores relative to the control group (t=3.26, p=0.013) and reduced hippocampal atrophy, which was significantly correlated with global degeneration scale changes. The baseline Mini-Mental State Examination (MMSE) score, apolipoprotein E genotype and Clinical Dementia Rating were indicative of MoCA scores at follow-up. Moreover, the GMV of the left (t=0.08, p=0.996) and right (t=0.19, p=0.977) hippocampus were maintained in the active group but significantly declined in the control group (left: t=4.13, p<0.001; right: t=5.31, p<0.001). GMV change in the left (r=0.35, p=0.023) and right (r=0.36, p=0.021) hippocampus across the intervention positively correlated with MoCA changes; left hippocampal GMV change was negatively correlated with global degeneration scale (r=-0.32, p=0.041) changes. Conclusions: DLPFC-iTBS may be a feasible and easy-to-implement non-pharmacological intervention to slow down the progressive decline of overall cognition and quality of life in patients with AD, providing a new AD treatment option. Trial registration number: NCT04754152.

Electroconvulsive therapy enhances degree centrality in the orbitofrontal cortex in depressive rumination.

Depressive rumination has been implicated in the onset, duration, and treatment response of refractory depression. Electroconvulsive therapy (ECT) is remarkably effective in treatment of refractory depression by modulating the functional coordination between brain hubs. However, the mechanisms by which ECT regulates depressive rumination remain unsolved. We investigated degree centrality (DC) in 32 pre- and post-ECT depression patients as well as 38 matched healthy controls. An identified brain region was defined as the seed to calculate functional connectivity (FC) in whole brains. Rumination was measured by the Ruminative Response Scale (RRS) and its relationships with identified DC and FC alterations were examined. We found a significant negative correlation between DC of the right orbitofrontal cortex (rOFC) before ECT and brooding level before and after treatment. Moreover, rOFC DC increased after ECT. DC of the left superior temporal gyrus (lSTG) was positively correlated with reflective level before intervention, while lSTG DC decreased after ECT. Patients showed elevated FC in the rOFC with default mode network. No significant association was found between decreased RRS scores and changes in DC and FC. Our findings suggest that functional changes in rOFC and lSTG may be associated with the beneficial effects of ECT on depressive rumination.

Plasma exchange for two patients with autoimmune GFAP astrocytopathy with rapid progression to respiratory failure: a case report.

Background: Patients with autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy can present with early neurological deterioration, but rapidly progressive respiratory failure is rarely reported. We present the cases of two patients with autoimmune GFAP astrocytopathy who experienced rapid progression to respiratory failure and were effectively treated using plasma exchange therapy. Case report: Two patients were diagnosed with autoimmune GFAP astrocytopathy. Their initial symptoms were consistent with those of previously observed cases of autoimmune GFAP astrocytopathy. However, they experienced rapid progression to respiratory failure due to their lesion location. Specifically, case 1 had lesions in the medulla oblongata, and case 2 had lesions in the high cervical spinal cord, which are both common sites of lesions causing respiratory failure. The patients did not respond well to intravenous methylprednisolone and intravenous immunoglobulin initially and could not be withdrawn from ventilator support. Fortunately, subsequent plasma exchange therapy led to significant clinical improvements and successful withdrawal from ventilator support. Discussion: Patients with autoimmune GFAP astrocytopathy can present with rapidly progressive respiratory failure. Early treatment with plasma exchange can be beneficial in withdrawing patients from ventilator support.