Neural signatures of default mode network in major depression disorder after electroconvulsive therapy.

Functional abnormalities of default mode network (DMN) have been well documented in major depressive disorder (MDD). However, the association of DMN functional reorganization with antidepressant treatment and gene expression is unclear. Moreover, whether the functional interactions of DMN could predict treatment efficacy is also unknown. Here, we investigated the link of treatment response with functional alterations of DMN and gene expression with a comparably large sample including 46 individuals with MDD before and after electroconvulsive therapy (ECT) and 46 age- and sex-matched healthy controls. Static and dynamic functional connectivity (dFC) analyses showed increased intrinsic/static but decreased dynamic functional couplings of inter- and intra-subsystems and between nodes of DMN. The changes of static functional connections of DMN were spatially correlated with brain gene expression profiles. Moreover, static and dFC of the DMN before treatment as features could predict depressive symptom improvement following ECT. Taken together, these results shed light on the underlying neural and genetic basis of antidepressant effect of ECT and the intrinsic functional connectivity of DMN have the potential to serve as prognostic biomarkers to guide accurate personalized treatment.

Volume of hippocampus-amygdala transition area predicts outcomes of electroconvulsive therapy in major depressive disorder: high accuracy validated in two independent cohorts.

BACKGROUND: Although many previous studies reported structural plasticity of the hippocampus and amygdala induced by electroconvulsive therapy (ECT) in major depressive disorder (MDD), yet the exact roles of both areas for antidepressant effects are still controversial. METHODS: In the current study, segmentation of amygdala and hippocampal sub-regions was used to investigate the longitudinal changes of volume, the relationship between volume and antidepressant effects, and prediction performances for ECT in MDD patients before and after ECT using two independent datasets. RESULTS: As a result, MDD patients showed selectively and consistently increased volume in the left lateral nucleus, right accessory basal nucleus, bilateral basal nucleus, bilateral corticoamygdaloid transition (CAT), bilateral paralaminar nucleus of the amygdala, and bilateral hippocampus-amygdala transition area (HATA) after ECT in both datasets, whereas marginally significant increase of volume in bilateral granule cell molecular layer of the head of dentate gyrus, the bilateral head of cornu ammonis (CA) 4, and left head of CA 3. Correlation analyses revealed that increased volume of left HATA was significantly associated with antidepressant effects after ECT. Moreover, volumes of HATA in the MDD patients before ECT could be served as potential biomarkers to predict ECT remission with the highest accuracy of 86.95% and 82.92% in two datasets (The predictive models were trained on Dataset 2 and the sensitivity, specificity and accuracy of Dataset 2 were obtained from leave-one-out-cross-validation. Thus, they were not independent and very likely to be inflated). CONCLUSIONS: These results not only suggested that ECT could selectively induce structural plasticity of the amygdala and hippocampal sub-regions associated with antidepressant effects of ECT in MDD patients, but also provided potential biomarkers (especially HATA) for effectively and timely interventions for ECT in clinical applications.

The Common Neural Mechanism of Somatic Symptoms of Depression and Anxiety Disorders: A Resting-State Functional Magnetic Resonance Imaging Study.

INTRODUCTION: Somatic symptoms often occur as a manifestation of depression and anxiety. The subgenual anterior cingulate cortex (sgACC) has been shown to be closely related to both depression and anxiety and plays an important role in somatic symptoms. However, little is known regarding whether the abnormal function of the sgACC contributes to the common somatic symptoms of depression and anxiety. METHODS: Resting-state functional connectivity (RSFC) analysis based on the seed of the sgACC was investigated in 23 major depressive disorder (MDD) patients with somatic symptoms, 20 generalized anxiety disorder (GAD) patients with somatic symptoms, and 22 demographically matched healthy controls (HCs). The severity of depression, anxiety, and somatic symptoms was assessed using the Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Rating Scale (HAMA), and the 15-item somatic symptom severity scale from the Patient Health Questionnaire (PHQ-15), respectively. An analysis of covariance analysis (ANCOVA) was conducted to determine RSFC alterations among GAD, MDD, and HC groups with age, gender, and head motion as covariates. Correlation analyses were conducted between the RSFC of the sgACC and PHQ-15. RESULTS: The significantly different RSFC of right sgACC among the three groups was found in right STG, left cerebellum, and right postcentral. Post hoc analysis indicated that both MDD and GAD patients showed a decreased RSFC between the right sgACC and right STG than HCs, and both were negatively correlated with the PHQ-15 scores. CONCLUSION: The abnormally decreased RSFC of the sgACC and STG may be the underlying common mechanisms of depression and anxiety combined with somatic symptoms.

Functional and structural alterations in the pain-related circuit in major depressive disorder induced by electroconvulsive therapy.

Approximately two-thirds of major depressive disorder (MDD) patients have pain, which exacerbates the severity of depression. Electroconvulsive therapy (ECT) is an efficacious treatment that can alleviate depressive symptoms; however, treatment for pain and the underlying neural substrate is elusive. We enrolled 34 patients with MDD and 33 matched healthy controls to complete clinical assessments and neuroimaging scans. MDD patients underwent second assessments and scans after ECT. We defined a pain-related network with a published meta-analysis and calculated topological patterns to reveal topologic alterations induced by ECT. Using the amplitude of low-frequency fluctuations (ALFFs), we probed local function aberrations of pain-related circuits in MDD patients. Subsequently, we applied gray matter volume (GMV) to reveal structural alterations of ECT relieving pain. The relationships between functional and structural aberrations and pain were determined. ECT significantly alleviated pain. The neural mechanism based on pain-related circuits indicated that ECT weakened the circuit function (ALFF: left amygdala and right supplementary motor area), while augmenting the structure (GMV: bilateral amygdala/insula/hippocampus and anterior cingulate cortex). The topologic patterns became less efficient after ECT. Correlation analysis between the change in pain and GMV had negative results in bilateral amygdala/insula/hippocampus. Similarity, there was a positive correlation between a change in ALFF in the left amygdala and improved clinical symptoms. ECT improved pain by decreasing brain local function and global network patterns, while increasing structure in pain-related circuits. Functional and structural alterations were associated with improvement in pain.

Disrupted intrinsic functional brain topology in patients with major depressive disorder.

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

Direct auditory cortical input to the lateral periaqueductal gray controls sound-driven defensive behavior.

Threatening sounds can elicit a series of defensive behavioral reactions in animals for survival, but the underlying neural substrates are not fully understood. Here, we demonstrate a previously unexplored neural pathway in mice that projects directly from the auditory cortex (ACx) to the lateral periaqueductal gray (lPAG) and controls noise-evoked defensive behaviors. Electrophysiological recordings showed that the lPAG could be excited by a loud noise that induced an escape-like behavior. Trans-synaptic viral tracing showed that a great number of glutamatergic neurons, rather than GABAergic neurons, in the lPAG were directly innervated by those in layer V of the ACx. Activation of this pathway by optogenetic manipulations produced a behavior in mice that mimicked the noise-evoked escape, whereas inhibition of the pathway reduced this behavior. Therefore, our newly identified descending pathway is a novel neural substrate for noise-evoked escape and is involved in controlling the threat-related behavior.

Impaired robust interhemispheric function integration of depressive brain from REST-meta-MDD database in China.

BACKGROUND: Recently, functional homotopy (FH) architecture, defined as robust functional connectivity (FC) between homotopic regions, has been frequently reported to be altered in MDD patients (MDDs) but with divergent locations. METHODS: In this study, we obtained resting-state functional magnetic resonance imaging (R-fMRI) data from 1004 MDDs (mean age, 33.88 years; age range, 18-60 years) and 898 matched healthy controls (HCs) from an aggregated dataset from 20 centers in China. We focused on interhemispheric function integration in MDDs and its correlation with clinical characteristics using voxel-mirrored homotopic connectivity (VMHC) devised to inquire about FH patterns. RESULTS: As compared with HCs, MDDs showed decreased VMHC in visual, motor, somatosensory, limbic, angular gyrus, and cerebellum, particularly in posterior cingulate gyrus/precuneus (PCC/PCu) (false discovery rate [FDR] q < 0.002, z = -7.07). Further analysis observed that the reduction in SMG and insula was more prominent with age, of which SMG reflected such age-related change in males instead of females. Besides, the reduction in MTG was found to be a male-special abnormal pattern in MDDs. VMHC alterations were markedly related to episode type and illness severity. The higher Hamilton Depression Rating Scale score, the more apparent VMHC reduction in the primary visual cortex. First-episode MDDs revealed stronger VMHC reduction in PCu relative to recurrent MDDs. CONCLUSIONS: We confirmed a significant VMHC reduction in MDDs in broad areas, especially in PCC/PCu. This reduction was affected by gender, age, episode type, and illness severity. These findings suggest that the depressive brain tends to disconnect information exchange across hemispheres.

Reduced default mode network functional connectivity in patients with recurrent major depressive disorder.

Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.

Pre-supplementary motor network connectivity and clinical outcome of magnetic stimulation in obsessive-compulsive disorder.

A large proportion of patients with obsessive-compulsive disorder (OCD) respond unsatisfactorily to pharmacological and psychological treatments. An alternative novel treatment for these patients is repetitive transcranial magnetic stimulation (rTMS). This study aimed to investigate the underlying neural mechanism of rTMS treatment in OCD patients. A total of 37 patients with OCD were randomized to receive real or sham 1-Hz rTMS (14 days, 30 min/day) over the right pre-supplementary motor area (preSMA). Resting-state functional magnetic resonance imaging data were collected before and after rTMS treatment. The individualized target was defined by a personalized functional connectivity map of the subthalamic nucleus. After treatment, patients in the real group showed a better improvement in the Yale-Brown Obsessive Compulsive Scale than the sham group (F1,35  = 6.0, p = .019). To show the neural mechanism involved, we identified an "ideal target connectivity" before treatment. Leave-one-out cross-validation indicated that this connectivity pattern can significantly predict patients' symptom improvements (r = .60, p = .009). After real treatment, the average connectivity strength of the target network significantly decreased in the real but not in the sham group. This network-level change was cross-validated in three independent datasets. Altogether, these findings suggest that personalized magnetic stimulation on preSMA may alleviate obsessive-compulsive symptoms by decreasing the connectivity strength of the target network.

Therapeutic efficacy of connectivity-directed transcranial magnetic stimulation on anticipatory anhedonia.

BACKGROUND: There are currently no effective treatments specifically targeting anticipatory anhedonia, a major symptom of severe depression which is associated with poor outcomes. The present study investigated the efficacy of individualized repetitive transcranial magnetic stimulation (rTMS) targeting the left dorsolateral prefrontal cortex (lDLPFC)-nucleus accumbens (NAcc) network on anticipatory anhedonia in depression. METHODS: This randomized, double-blind, sham-controlled clinical trial (NCT03991572) enrolled 56 depression patients with anhedonia symptoms. Each participant received 15 once-daily sessions of rTMS at 10 Hz and 100% motor threshold. Stimulation was localized to the site of strongest IDLPFC-NAcc connectivity by functional magnetic resonance imaging. The Hamilton depression rating scale (HAMD) was used to measure depression severity, the temporal experience pleasure scale (TEPS) to measure anticipatory and consummatory anhedonia to specifically measure anticipatory/motivational anhedonia. Event-related potentials during the monetary incentive delay (MID) task were recorded to evaluate the electrophysiological correlates of reward anticipation and response. RESULTS: Patients in the Real group showed significant improvements in anticipatory anhedonia and general depression symptoms posttreatment compared to the Sham group. The Real group also demonstrated more positive going cue-N2 and cue-P3 amplitude during MID reward trials after treatment. The change in cue-P3 posttreatment was positive correlated with improved TEPS-anti score. CONCLUSION: Individualized rTMS of the lDLPFC-NAcc network can effectively alleviate anticipatory anhedonia and improved the reward seeking as evidenced by enhanced MID behavioral performance and more positive going cue-N2 and cue-P3. The lDLPFC-NAcc network plays a critical role in anticipatory reward and motivation processing.

Aberrant brain network topology in the frontoparietal-limbic circuit in bipolar disorder: a graph-theory study.

Characterizing the properties of brain networks across mood states seen in bipolar disorder (BP) can provide a deeper insight into the mechanisms involved in this type of affective disorder. In this study, graph theoretical methods were used to examine global, modular and nodal brain network topology in the resting state using functional magnetic resonance imaging data acquired from 95 participants, including those with bipolar depression (BPD; n = 30) and bipolar mania (BPM; n = 39) and healthy control (HC) subjects (n = 26). The threshold value of the individual subjects' connectivity matrix varied from 0.15 to 0.30 with steps of 0.01. We found that: (1) at the global level, BP patients showed a significantly increased global efficiency and synchronization and a decreased path length; (2) at the nodal level, BP patients showed impaired nodal parameters, predominantly within the frontoparietal and limbic sub-network; (3) at the module level, BP patients were characterized by denser FCs (edges) between Module III (the front-parietal system) and Module V (limbic/paralimbic systems); (4) at the nodal level, the BPD and BPM groups showed state-specific differences in the orbital part of the left superior-frontal gyrus, right putamen, right parahippocampal gyrus and left fusiform gyrus. These results revealed abnormalities in topological organization in the whole brain, especially in the frontoparietal-limbic circuit in both BPD and BPM. These deficits may reflect the pathophysiological processes occurring in BP. In addition, state-specific regional nodal alterations in BP could potentially provide biomarkers of conversion across different mood states.

A common variant of the NOTCH4 gene modulates functional connectivity of the occipital cortex and its relationship with schizotypal traits.

BACKGROUND: Schizotypal traits are considered as inheritable traits and the endophenotype for schizophrenia. A common variant in the NOTCH4 gene, rs204993, has been linked with schizophrenia, but the neural underpinnings are largely unknown. METHODS: In present study, we compared the differences of brain functions between different genotypes of rs204993 and its relationship with schizotypal traits among 402 Chinese Han healthy volunteers. The brain function was evaluated with functional connectivity strength (FCS) using the resting-state functional magnetic resonance image(rs-fMRI). The schizotypal traits were measured by the schizotypal personality questionnaire (SPQ). RESULTS: Our results showed that carriers with the AA genotype showed reduced FCS in the left occipital cortex when compared with carriers with the AG and GG genotypes, and the carriers with the AG genotype showed reduced FCS in the left occipital cortex when compared with carriers with the GG genotype. The FCS values in the left occipital lobe were negatively associated with the SPQ scores and its subscale scores within the carriers with the GG genotype, but not within the carriers with AA or AG genotype. CONCLUSION: Our results suggested that the common variant in the NOTCH4 gene, rs204993, modulates the function of the occipital cortex, which may contribute to schizotypal traits. These findings provide insight for genetic effects on schizotypal traits and its potential neural substrate.

Functional plasticity of the dorsomedial prefrontal cortex in depression reorganized by electroconvulsive therapy: Validation in two independent samples.

Previous studies have implied a key role for the prefrontal cortex in the antidepressive effect of electroconvulsive therapy (ECT). However, there is still ubiquitous inconsistency across these studies, partly due to several confounding effects induced by the use of different samples. Studies with independent samples are necessary for validations to minimize confounding effects. In the current study, resting-state magnetic resonance imaging of 84 participants was collected using two scanners and two types of scanning parameters. One sample consisted of 28 patients and 23 healthy controls, and the other sample consisted of 33 patients. The local activity (indexed by the amplitude of low-frequency fluctuations) and functional connectivity were used to examine functional plasticity in the two independent samples before and after ECT. Both samples showed increased local activity of the dorsomedial prefrontal cortex (DMPFC) and enhanced connectivity of the DMPFC with the posterior cingulate cortex (PCC) following ECT. The enhanced connectivity between the DMPFC and PCC was positively associated with clinical improvement for both samples. These findings provide relatively strong evidence to support the functional plasticity of the dorsomedial prefrontal cortex and reorganization by ECT. The functional plasticity of the DMPFC-PCC may underlie the antidepressive effect of ECT.

Classification of schizophrenia by intersubject correlation in functional connectome.

Functional connectomes have been suggested as fingerprinting for individual identification. Accordingly, we hypothesized that subjects in the same phenotypic group have similar functional connectome features, which could help to discriminate schizophrenia (SCH) patients from healthy controls (HCs) and from depression patients. To this end, we included resting-state functional magnetic resonance imaging data of SCH, depression patients, and HCs from three centers. We first investigated the characteristics of connectome similarity between individuals, and found higher similarity between subjects belonging to the same group (i.e., SCH-SCH) than different groups (i.e., HC-SCH). These findings suggest that the average connectome within group (termed as group-specific functional connectome [GFC]) may help in individual classification. Consistently, significant accuracy (75-77%) and area under curve (81-86%) were found in discriminating SCH from HC or depression patients by GFC-based leave-one-out cross-validation. Cross-center classification further suggests a good generalizability of the GFC classification. We additionally included normal aging data (255 young and 242 old subjects with different scanning sequences) to show factors could be improved for better classification performance, and the findings emphasized the importance of increasing sample size but not temporal resolution during scanning. In conclusion, our findings suggest that the average functional connectome across subjects contained group-specific biological features and may be helpful in clinical diagnosis for schizophrenia.

Resting-State Functional Connectivity Between Centromedial Amygdala and Insula as Related to Somatic Symptoms in Depressed Patients: A Preliminary Study.

OBJECTIVE: Somatic symptoms are prevalent in patients with depression. The centromedial amygdala (CMA) is a key brain region that mediates autonomic and somatic responses. Abnormal function in the CMA may contribute to the development of somatic symptoms in depressed patients. METHODS: We compared the resting-state functional connectivity (RSFC) based on the seed of the left and right CMA between 37 patients with depression and 30 healthy controls. The severity of depressive and somatic symptoms was assessed using the Hamilton Depression Rating Scale (HDRS) and the 15-item somatic symptom severity scale of the Patient Health Questionnaire (PHQ-15). Correlation analysis was performed to investigate the relationship between the RSFC and clinical variables (HDRS and PHQ-15) in depressed patients. RESULTS: Compared with healthy controls, patients with depression exhibited decreased RSFC between the CMA and insula, and superior temporal gyrus. In addition, functional connectivity between the left CMA and left insula was negatively correlated with PHQ-15 (r = -0.348, p = .037) in depressed patients. No significant relation was found between the RSFC and HDRS in depressed patients. CONCLUSIONS: Functional connectivity between the CMA and insula is reduced in depressive patients, which is associated with the severity of somatic symptoms. Our findings may provide a potential neural substrate to interpret the co-occurrence of depression with somatic symptoms.

Hippocampal-subregion functional alterations associated with antidepressant effects and cognitive impairments of electroconvulsive therapy.

BACKGROUND: Electroconvulsive therapy (ECT), an effective antidepressive treatment, is frequently accompanied by cognitive impairment (predominantly memory), usually transient and self-limited. The hippocampus is a key region involved in memory and emotion processing, and in particular, the anterior-posterior hippocampal subregions has been shown to be associated with emotion and memory. However, less is known about the relationship between hippocampal-subregion alterations following ECT and antidepressant effects or cognitive impairments. METHODS: Resting-state functional connectivity (RSFC) based on the seeds of hippocampal subregions were investigated in 45 pre- and post-ECT depressed patients. Structural connectivity between hippocampal subregions and corresponding functionally abnormal regions was also conducted using probabilistic tractography. Antidepressant effects and cognitive impairments were measured by the Hamilton Depressive Rating Scale (HDRS) and the Category Verbal Fluency Test (CVFT), respectively. Their relationships with hippocampal-subregions alterations were examined. RESULTS: After ECT, patients showed increased RSFC in the hippocampal emotional subregion (HIPe) with the left middle occipital gyrus (LMOG) and right medial temporal gyrus (RMTG). Decreased HDRS was associated with increased HIPe-RMTG RSFC (r = -0.316, p = 0.035) significantly and increased HIPe-LMOG RSFC at trend level (r = -0.283, p = 0.060). In contrast, the hippocampal cognitive subregion showed decreased RSFC with the bilateral angular gyrus, and was correlated with decreased CVFT (r = 0.418, p = 0.015 for left; r = 0.356, p = 0.042 for right). No significant changes were found in structural connectivity. CONCLUSION: The hippocampal-subregions functional alterations may be specially associated with the antidepressant and cognitive effects of ECT.

Functional reorganization of intra- and internetwork connectivity in major depressive disorder after electroconvulsive therapy.

Electroconvulsive therapy (ECT) is an effective and rapid treatment for major depressive disorder (MDD). However, the neurobiological underpinnings of ECT are still largely unknown. Recent studies have identified dysregulated brain networks in MDD. Therefore, we hypothesized that ECT may improve MDD symptoms through reorganizing these networks. To test this hypothesis, we used resting-state functional connectivity to investigate changes to the intra- and internetwork architecture of five reproducible resting-state networks: the default mode network (DMN), dorsal attention network (DAN), executive control network (CON), salience network (SAL), and sensory-motor network. Twenty-three MDD patients were assessed before and after ECT, along with 25 sex-, age-, and education-matched healthy controls. At the network level, enhanced intranetwork connectivities were found in the CON in MDD patients after ECT. Furthermore, enhanced internetwork connectivities between the DMN and SAL, and between the CON and DMN, DAN, and SAL were also identified. At the nodal level, the posterior cingulate cortex had increased connections with the left posterior cerebellum, right posterior intraparietal sulcus (rpIPS), and right anterior prefrontal cortex. The rpIPS had increased connections with the medial PFC (mPFC) and left anterior cingulate cortex. The left lateral parietal had increased connections with the dorsal mPFC (dmPFC), left anterior prefrontal cortex, and right anterior cingulate cortex. The dmPFC had increased connection with the left anterolateral prefrontal cortex. Our findings indicate that enhanced interactions in intra- and internetworks may contribute to the ECT response in MDD patients. These findings provide novel and important insights into the neurobiological mechanisms underlying ECT.

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.

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.