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.

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.

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.

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.

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.

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.].

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.

Dynamic and static changes of amplitude of low-frequency fluctuations in anti­N­methyl­D­aspartate receptor encephalitis.

BACKGROUND: Previous neuroimaging research has examined static local brain activity changes in patients with anti-N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis. However, the dynamic properties of local brain activity in anti-NMDAR encephalitis remain unknown. METHODS: This study used a combination of the amplitude of low-frequency fluctuation (ALFF) method and a sliding-window dynamic analysis approach to examine the time-varying local brain activity changes in anti-NMDAR encephalitis. RESULTS: Results showed that patients with anti-NMDAR encephalitis exhibited increased dynamic ALFF (dALFF) variability in the left inferior occipital gyrus compared to healthy controls (HCs), while the patients exhibited decreased sALFF in widespread regions, including the left inferior frontal gyrus, left medial frontal gyrus, bilateral putamen, left medial superior frontal gyrus. dALFF had superior classification performance in distinguishing anti-NMDAR encephalitis patients from HCs over sALFF, but sALFF was correlated with multiple clinical and neuropsychological measures. CONCLUSIONS: These findings may shed light on anti-NMDAR encephalitis brain dysfunction from the perspective of dynamic local brain activity. sALFF and dALFF analyses provide complementary information, emphasizing the potential usefulness of combining sALFF and dALFF in elucidating the neuropathological mechanisms of autoimmune encephalitis and may ultimately inform future disease diagnosis.

White Matter Changes as an Independent Predictor of Alzheimer's Disease.

BACKGROUND: Abnormalities in white matter (WM) may be a crucial physiologic feature of Alzheimer's disease (AD). However, neuroimaging's ability to visualize the underlying functional degradation of the WM region in AD is unclear. OBJECTIVE: This study aimed to explore the differences in amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) in the WM region of patients with AD and healthy controls (HC) and to investigate further whether these values can provide supplementary information for diagnosing AD. METHODS: Forty-eight patients with AD and 46 age-matched HC were enrolled and underwent resting-state functional magnetic resonance imaging and a neuropsychological battery assessment. We analyzed the differences in WM activity between the two groups and further explored the correlation between WM activity in the different regions and cognitive function in the AD group. Finally, a machine learning algorithm was adopted to construct a classifier in detecting the clinical classification ability of the values of ALFF/ALFF in the WM. RESULTS: Compared with HCs, patients with AD had lower WM activity in the right anterior thalamic radiation, left frontal aslant tract, and left forceps minor, which are all positively related to global cognitive function, memory, and attention function (all p < 0.05). Based on the combined WM ALFF and fALFF characteristics in the different regions, individuals not previously assessed were classified with moderate accuracy (75%), sensitivity (71%), specificity (79%), and area under the receiver operating characteristic curve (85%). CONCLUSION: Our results suggest that WM activity is reduced in AD and can be used for disease classification.

Case Report: Ofatumumab treatment in a patient with rituximab-intolerant refractory autoimmune GFAP astrocytopathy.

Background: Ofatumumab, a fully humanized anti-CD20 monoclonal antibody, has shown promising efficacy in limited cases of neuromyelitis optica spectrum disorder, but there is a lack of studies on its use in autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy. We present a case of refractory GFAP astrocytopathy with poor response to conventional immunosuppressants and rituximab who responded well to subcutaneous ofatumumab. Case report: The patient is a 36-year-old woman with a diagnosis of GFAP astrocytopathy and high disease activity. She experienced five relapses over three years despite immunosuppressive treatment with oral prednisone, azathioprine, mycophenolate mofetil, and intravenous rituximab. Additionally, her circulating B cells were not completely depleted during the second administration of rituximab and an allergic reaction occurred. Based on insufficient B cell depletion and allergic reaction to rituximab, subcutaneous ofatumumab was introduced. After twelve injections of ofatumumab without injection-related reactions, she had no further relapses and was sufficiently depleted of the circulating B cells. Discussion: This case illustrates the effective use and good tolerance of ofatumumab in GFAP astrocytopathy. Further studies are needed to investigate the efficacy and safety of ofatumumab in refractory GFAP astrocytopathy or those intolerant to rituximab.

Apathy in melancholic depression and abnormal neural activity within the reward-related circuit.

Major depressive disorder is a heterogeneous syndrome, of which the most common subtype is melancholic depression (MEL). Previous studies have indicated that anhedonia is frequently a cardinal feature in MEL. As a common syndrome of motivational deficit, anhedonia is closely associated with dysfunction in reward-related networks. However, little is currently known about apathy, another syndrome of motivational deficits, and the underlying neural mechanisms in MEL and non-melancholic depression (NMEL). Herein, the Apathy Evaluation Scale (AES) was used to compare apathy between MEL and NMEL. On the basis of resting-state functional magnetic resonance imaging, functional connectivity strength (FCS) and seed-based functional connectivity (FC) were calculated within reward-related networks and compared among 43 patients with MEL, 30 patients with NMEL, and 35 healthy controls. Patients with MEL had higher AES scores than those with NMEL (t = -2.20, P = 0.03). Relative to NMEL, MEL was associated with greater FCS (t = 4.27, P < 0.001) in the left ventral striatum (VS), and greater FC of the VS with the ventral medial prefrontal cortex (t = 5.03, P < 0.001) and dorsolateral prefrontal cortex (t = 3.18, P = 0.005). Taken together the results indicate that reward-related networks may play diverse pathophysiological roles in MEL and NMEL, thus providing potential directions for future interventions in the treatment of various depression subtypes.

Altered brain entropy and functional connectivity patterns in generalized anxiety disorder patients.

BACKGROUND: Generalized anxiety disorder (GAD) is a highly prevalent disease characterized by chronic, pervasive, and intrusive worry. Previous resting-state functional MRI (fMRI) studies on GAD have mainly focused on conventional static linear features. Entropy analysis of resting-state functional magnetic resonance imaging (rs-fMRI) has recently been adopted to characterize brain temporal dynamics in some neuropsychological or psychiatric diseases. However, the nonlinear dynamic complexity of brain signals has been rarely explored in GAD. METHODS: We measured the approximate entropy (ApEn) and sample entropy (SampEn) of the resting-state fMRI data from 38 GAD patients and 37 matched healthy controls (HCs). The brain regions with significantly different ApEn and SampEn values between the two groups were extracted. Using these brain regions as seed points, we also investigated whether there are differences in whole brain resting-state function connectivity (RSFC) pattern between GADs and HCs. Correlation analysis was subsequently conducted to investigate the association between brain entropy, RSFC and the severity of anxiety symptoms. A linear support vector machine (SVM) was used to assess the discriminative power of BEN and RSFC features among GAD patients and HCs. RESULTS: Compared to the HCs, patients with GAD showed increased levels of ApEn in the right angular cortex (AG) and increased levels of SampEn in the right middle occipital gyrus (MOG) as well as the right inferior occipital gyrus (IOG). Contrarily, compared to the HCs, patients with GAD showed decreased RSFC between the right AG and the right inferior parietal gyrus (IPG). The SVM-based classification model achieved 85.33 % accuracy (sensitivity: 89.19 %; specificity: 81.58 %; and area under the receiver operating characteristic curve: 0.9018). The ApEn of the right AG and the SVM-based decision value was positively correlated with the Hamilton Anxiety Scale (HAMA). LIMITATIONS: This study used cross-sectional data and sample size was small. CONCLUSION: Patients with GAD showed increased level of nonlinear dynamical complexity of ApEn in the right AG and decreased linear features of RSFC in the right IPG. Combining the linear and nonlinear features of brain signals may be used to effectively diagnose psychiatric disorders.