Default mode network coherence in treatment-resistant major depressive disorder during electroconvulsive therapy

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.

Development and validation of a multimodal neuroimaging biomarker for electroconvulsive therapy outcome in depression: a multicenter machine learning analysis

BACKGROUND

Electroconvulsive therapy (ECT) is the most effective intervention for patients with treatment resistant depression. A clinical decision support tool could guide patient selection to improve the overall response rate and avoid ineffective treatments with adverse effects. Initial small-scale, monocenter studies indicate that both structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) biomarkers may predict ECT outcome, but it is not known whether those results can generalize to data from other centers. The objective of this study was to develop and validate neuroimaging biomarkers for ECT outcome in a multicenter setting.

METHODS

Multimodal data (i.e. clinical, sMRI and resting-state fMRI) were collected from seven centers of the Global ECT-MRI Research Collaboration (GEMRIC). We used data from 189 depressed patients to evaluate which data modalities or combinations thereof could provide the best predictions for treatment remission (HAM-D score ⩽7) using a support vector machine classifier.

RESULTS

Remission classification using a combination of gray matter volume and functional connectivity led to good performing models with average 0.82-0.83 area under the curve (AUC) when trained and tested on samples coming from the three largest centers (N = 109), and remained acceptable when validated using leave-one-site-out cross-validation (0.70-0.73 AUC).

CONCLUSIONS

These results show that multimodal neuroimaging data can be used to predict remission with ECT for individual patients across different treatment centers, despite significant variability in clinical characteristics across centers. Future development of a clinical decision support tool applying these biomarkers may be feasible.

Longitudinal resting-state network connectivity changes in electroconvulsive therapy patients compared to healthy controls

OBJECTIVE

Electroconvulsive therapy (ECT) is effective for major depressive episodes. Understanding of underlying mechanisms has been increased by examining changes of brain connectivity but studies often do not correct for test-retest variability in healthy controls (HC). In this study, we investigated changes in resting-state networks after ECT in a multicenter study.

METHODS

Functional resting-state magnetic resonance imaging data, acquired before start and within one week after ECT, from 90 depressed patients were analyzed, as well as longitudinal data of 24 HC. Group-information guided independent component analysis (GIG-ICA) was used to spatially restrict decomposition to twelve canonical resting-state networks. Selected networks of interest were the default mode network (DMN), salience network (SN), and left and right frontoparietal network (LFPN, and RFPN). Whole-brain voxel-wise analyses were used to assess group differences at baseline, group by time interactions, and correlations with treatment effectiveness. In addition, between-network connectivity and within-network strengths were computed.

RESULTS

Within-network strength of the DMN was lower at baseline in ECT patients which increased after ECT compared to HC, after which no differences were detected. At baseline, ECT patients showed lower whole-brain voxel-wise DMN connectivity in the precuneus. Increase of within-network strength of the LFPN was correlated with treatment effectiveness. We did not find whole-brain voxel-wise or between-network changes.

CONCLUSION

DMN within-network connectivity normalized after ECT. Within-network increase of the LFPN in ECT patients was correlated with higher treatment effectiveness. In contrast to earlier studies, we found no whole-brain voxel-wise changes, which highlights the necessity to account for test-retest effects.

Reviewing the neurobiology of electroconvulsive therapy on a micro- meso- and macro-level

BACKGROUND

Electroconvulsive therapy (ECT) remains the one of the most effective of biological antidepressant interventions. However, the exact neurobiological mechanisms underlying the efficacy of ECT remain unclear. A gap in the literature is the lack of multimodal research that attempts to integrate findings at different biological levels of analysis METHODS: We searched the PubMed database for relevant studies. We review biological studies of ECT in depression on a micro- (molecular), meso- (structural) and macro- (network) level.

RESULTS

ECT impacts both peripheral and central inflammatory processes, triggers neuroplastic mechanisms and modulates large scale neural network connectivity.

CONCLUSIONS

Integrating this vast body of existing evidence, we are tempted to speculate that ECT may have neuroplastic effects resulting in the modulation of connectivity between and among specific large-scale networks that are altered in depression. These effects could be mediated by the immunomodulatory properties of the treatment. A better understanding of the complex interactions between the micro-, meso- and macro- level might further specify the mechanisms of action of ECT.

Predicting Dimensional Antidepressant Response to Repetitive Transcranial Magnetic Stimulation using Pretreatment Resting-state Functional Connectivity

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression and has been shown to modulate resting-state functional connectivity (RSFC) of depression-relevant neural circuits. To date, however, few studies have investigated whether individual treatment-related symptom changes are predictable from pretreatment RSFC. We use machine learning to predict dimensional changes in depressive symptoms using pretreatment patterns of RSFC. We hypothesized that changes in dimensional depressive symptoms would be predicted more accurately than scale total scores. Patients with depression (n=26) underwent pretreatment RSFC MRI. Depressive symptoms were assessed with the 17-item Hamilton Depression Rating Scale (HDRS-17). Random forest regression (RFR) models were trained and tested to predict treatment-related symptom changes captured by the HDRS-17, HDRS-6 and three previously identified HDRS subscales: core mood/anhedonia (CMA), somatic disturbances, and insomnia. Changes along the CMA, HDRS-17, and HDRS-6 were predicted significantly above chance, with 9%, 2%, and 2% of out-of-sample outcome variance explained, respectively (all p<0.01). CMA changes were predicted more accurately than the HDRS-17 (p<0.05). Higher baseline global connectivity (GC) of default mode network (DMN) subregions and the somatomotor network (SMN) predicted poorer symptom reduction, while higher GC of the right dorsal attention (DAN) frontoparietal control (FPCN), and visual networks (VN) predicted reduced CMA symptoms. HDRS-17 and HDRS-6 changes were predicted with similar GC patterns. These results suggest that RSFC spanning the DMN, SMN, DAN, FPCN, and VN subregions predict dimensional changes with greater accuracy than syndromal changes following rTMS. These findings highlight the need to assess more granular clinical dimensions in therapeutic studies, particularly device neuromodulation studies, and echo earlier studies supporting that dimensional outcomes improve model accuracy.

The Role of Psychotherapy in the Management of Treatment-Resistant Depression

This article reviews the role of psychotherapy in management of treatment-resistant depression (TRD). Meta-analyses of randomized trials show that psychotherapy has a positive therapeutic benefit in TRD. There is less evidence that one type of psychotherapy approach is superior to another. However, more trials have examined cognitive-based therapies than other forms of psychotherapy. Also reviewed is the potential combination of psychotherapy modalities and medication/somatic therapies as an approach to TRD. There is significant interest in ways that psychotherapy modalities could be combined with medication/somatic therapies to harness a state of enhanced neural plasticity and improve longer-term outcomes in mood disorders.

Information flow and dynamic functional connectivity during electroconvulsive therapy in patients with depression

BACKGROUND

Electroconvulsive therapy is effectively used for treatment-resistant depression; however, its neural mechanism is largely unknown. Resting-state functional magnetic resonance imaging is promising for monitoring outcomes of electroconvulsive therapy for depression. This study aimed to explore the imaging correlates of the electroconvulsive therapy effects on depression using Granger causality analysis and dynamic functional connectivity analyses.

METHODS

We performed advanced analyses of resting-state functional magnetic resonance imaging data at the beginning and intermediate stages and end of the therapeutic course to identify neural markers that reflect or predict the therapeutic effects of electroconvulsive therapy on depression.

RESULTS

We demonstrated that information flow between the functional networks analyzed by Granger causality changes during electroconvulsive therapy, and this change was correlated with the therapeutic outcome. Information flow and the dwell time (an index reflecting the temporal stability of functional connectivity) before electroconvulsive therapy are correlated with depressive symptoms during and after treatment.

LIMITATIONS

First, the sample size was small. A larger group is needed to confirm our findings. Second, the influence of concomitant pharmacotherapy on our results was not fully addressed, although we expected it to be minimal because only minor changes in pharmacotherapy occurred during electroconvulsive therapy. Third, different scanners were used the groups, although the acquisition parameters were the same; a direct comparison between patient and healthy participant data was not possible. Thus, we presented the data of the healthy participants separately from that of the patients as a reference.

CONCLUSIONS

These results show the specific properties of functional brain connectivity.

Electroconvulsive therapy induces remodeling of hippocampal co-activation with the default mode network in patients with depression

INTRODUCTION

Electroconvulsive therapy (ECT) is a highly efficient treatment for depression. Previous studies repeatedly reported an ECT-induced volume increase in the hippocampi. We assume that this also affects extended hippocampal networks. This study aims to investigate the structural and functional interplay between hippocampi, hippocampal pathways and core regions of the default mode network (DMN). Twenty patients with a current depressive episode receiving ECT-treatment and twenty age and sex matched healthy controls (HC) were included in the study. ECT-patients underwent multimodal magnetic resonance imaging (MRI)-scans (diffusion weighted imaging, resting state functional MRI) before and after an ECT-index series. HC were also scanned twice in a similar between-scan time-interval. Parahippocampal cingulum (PHC) and uncinate fasciculus (UF) were reconstructed for each participant using manual tractography. Fractional anisotropy (FA) was averaged across tracts. Furthermore, we investigated seed-based functional connectivity (FC) from bilateral hippocampi and from the PCC, a core region of the DMN. At baseline, FA in PHC and UF did not differ between groups. There was no baseline group difference of hippocampal-FC. PCC-FC was decreased in ECT-patients. ECT induced a decrease in FA in the left PHC in the ECT group. No longitudinal changes of FA were found in the UF. Furthermore, there was a decrease in hippocampal-PCC-FC, an increase in hippocampal-supplementary motor area-FC, and an increase in PCC-FC in the ECT-group, reversing group differences at baseline. Our findings suggest that ECT induces structural and functional remodeling of a hippocampal-DMN. Those changes may contribute to ECT-induced clinical response in patients with depression.

A voxel-based meta-analysis comparing medication-naive patients of major depression with treated longer-term ill cases

Structural neuroimaging studies have identified brain areas implicated in the pathogenesis of major depressive disorder (MDD). However, findings have been inconsistent, potentially due to variable illness duration and effects of antidepressant treatment. Using a meta-analytic approach, we compared gray matter (GM) volumes in patients grouped by medication status (naïve and treated) and illness duration (early course and long-term ill) to identify potential treatment and illness duration effects on brain structure. A total of 70 studies were included, including 3682 patients and 3469 controls. The pooled analysis found frontal, temporal and limbic regions with decreased GM volume in MDD patients. Additional analyses indicated that larger GM volume in the right striatum and smaller GM volume in the right precuneus are likely to be associated with drug effects, while smaller GM volume in the right temporal gyrus may correlate with longer illness duration. Similar GM decreases in bilateral medial frontal cortex between patient subgroups suggest that this alteration may persist over the course of illness and drug treatment.

Electroconvulsive therapy changes temporal dynamics of intrinsic brain activity in depressed patients

Electroconvulsive therapy (ECT) has been demonstrated to be effective in treating depressed patients. Previous neuroimaging studies have focused mainly on alterations in static brain activity and connectivity to study the effects of ECT in depressed patients. However, it remains unclear whether the temporal dynamics of brain activity are associated with mechanisms of ECT in depressed patients. We measured the dynamics of spontaneous brain activity using dynamic amplitude of low-frequency fluctuation (dALFF) in healthy controls (n = 40) and patients diagnosed with unipolar depression (UD, n = 36) or bipolar disorder (BD, n = 9) before and after ECT. Furthermore, the temporal variability of intrinsic brain activity (iBA) was quantified as the variance of dALFF across sliding window. In addition, correlation analysis was performed to investigate the relationships among dALFF, depressive symptoms, and cognitive function in depressed patients. We lack second resting-state functional magnetic resonance imaging (rs-fMRI) data for healthy controls. After ECT, patients showed decreased brain dynamics (less temporal variability) in the right dorsal anterior cingulate cortex (dACC) and the right precuneus, whereas they showed increased brain dynamics in the bilateral superior medial frontal cortex (mSFC). No significant correlation was found between the dALFF and clinical variables in depressed patients. Our findings suggest that right dACC, right precuneus, and bilateral mSFC play an important role in response to ECT depressed patients from the perspective of dynamic local brain activity, indicating that the dALFF variability may be useful in further understanding the mechanisms of ECT's antidepressant effects.

Nodal degree changes induced by electroconvulsive therapy in major depressive disorder: Evidence in two independent cohorts

OBJECTIVE

Electroconvulsive therapy (ECT), a rapidly acting treatment for major depressive disorder (MDD), has been reported to regulate brain networks. Nodes and their connections are the main components of the brain network and are essential for establishing and maintaining effective information transmission. This study aimed to evaluate the role of nodes in mediating antidepressant effects of ECT.

METHODS

Voxel-based nodal degree analysis was performed in 42 patients with MDD receiving ECT and 42 matched healthy controls at two time points to identify the nodal changes induced by ECT. Verification analysis was evaluated in a second, independent cohort of 23 MDD patients.

RESULTS

MDD patients showed improved nodal degree of the bilateral angular cortex (AG), precuneus, inferior frontal gyrus (IFG) and the right superior frontal gyrus (SFG) after ECT, and the increased nodal degree index (IND) rate of the AG and precuneus were negatively correlated to the depressive changes following ECT. Furthermore, validation analysis revealed a similar pattern of IND abnormalities in the first and second cohort of MDD patients.

CONCLUSION

ECT regulates the disrupted nodal degree of the AG and precuneus to achieve an antidepressant effect. This study may provide further insights into the pathogenesis of depression and provide potential targets for antidepressant pharmacotherapies.

Enhanced default mode network functional connectivity links with electroconvulsive therapy response in major depressive disorder

BACKGROUND

Electroconvulsive therapy (ECT) is an effective neuromodulatory treatment for major depressive disorder (MDD), especially for cases resistant to antidepressant drugs. While the precise mechanisms underlying ECT efficacy are still unclear, it is speculated that ECT modulates brain connectivity. The current study aimed to investigate the longitudinal effects of ECT on resting-state functional connectivity (FC) in MDD patients and test if baseline FC can be used to predict therapeutic response.

METHOD

Resting-state functional magnetic resonance imaging data were collected at baseline and following ECT from 33 MDD patients. Whole-brain multi-voxel pattern analysis (MVPA) and region of interest-wise FC analysis were employed to fully investigate ECT effects on brain connectivity. Linear support vector regression was further utilized to predict the improvement in depressive symptoms based on baseline connectivity.

RESULTS

MVPA revealed a significant ECT effect on FC in the default mode network (DMN), central executive network (CEN), sensorimotor network (SMN), and cerebellar posterior lobe. The FCs within the DMN and between DMN and CEN were enhanced in patients after ECT, and the changed FC between the medial prefrontal cortex and ventrolateral prefrontal cortex was negatively correlated with depressive symptom improvement. Moreover, baseline FC within the DMN and between the DMN and CEN could effectively predict the improvement of depressive symptoms.

CONCLUSIONS

The findings suggest that the FCs within the DMN and between DMN and CEN may be critical therapeutic targets for effective antidepressant treatment as well as neuromarkers for predicting treatment response.

Abnormal functional connectivity of the anterior cingulate cortex subregions mediates the association between anhedonia and sleep quality in major depressive disorder

BACKGROUND

The anterior cingulate cortex (ACC) is a crucial region in the pathophysiology of major depressive disorder (MDD). However, the relationship between functional alterations of the ACC subregions, anhedonia and sleep quality remains unclear in MDD patients.

METHODS

The resting-state functional connectivity (rsFC) of ACC subregions was measured in 41 first-episode medication-naïve MDD patients and 63 healthy controls who underwent functional magnetic resonance imaging. Between-group differences were examined using two-sample t-test. Furthermore, correlation and mediation analyses were carried out to investigate the relationships between the aberrant rsFC of ACC subregions, anhedonia and sleep quality in the patients and controls.

RESULTS

Compared to healthy controls, the MDD patients exhibited increased rsFC of ACC subregions to areas of the anterior default mode network (DMN) and showed decreased rsFC of the right subgenual ACC to left precuneus (PCUN), which belongs to the posterior DMN. In MDD group, the sleep quality and consummatory anhedonia are correlated with some rsFC, which involves the angular gyrus (ANG) and superior frontal gyrus (SFG). More importantly, the rsFC between the right perigenual ACC and left SPG mediates the association between anhedonia and sleep quality in MDD.

LIMITATIONS

The cross-sectional design and the subjective questionaries for assessment.

CONCLUSION

These findings confirm the functional alterations of the ACC subregions and reveal the mediating role of ACC subregions in sleep and reward dysfunction in MDD.

Neuronal network mechanisms associated with depressive symptom improvement following electroconvulsive therapy

BACKGROUND

Electroconvulsive therapy (ECT) is the most effective antidepressant treatment for severe depression. Although recent structural magnetic resonance imaging (MRI) studies have consistently reported ECT-induced hippocampal volume increases, most studies did not find the association of the hippocampal volume changes with clinical improvement. To understand the underlying mechanisms of ECT action, we aimed to identify the longitudinal effects of ECT on hippocampal functional connectivity (FC) and their associations with clinical improvement.

METHODS

Resting-state functional MRI was acquired before and after bilateral ECT in 27 depressed individuals. A priori hippocampal seed-based FC analysis and a data-driven multivoxel pattern analysis (MVPA) were conducted to investigate FC changes associated with clinical improvement. The statistical threshold was set at cluster-level false discovery rate-corrected p < 0.05.

RESULTS

Depressive symptom improvement after ECT was positively associated with the change in the right hippocampus-ventromedial prefrontal cortex FC, and negatively associated with the right hippocampus-superior frontal gyrus FC. MVPA confirmed the results of hippocampal seed-based analyses and identified the following additional clusters associated with clinical improvement following ECT: the thalamus, the sensorimotor cortex, and the precuneus.

CONCLUSIONS

ECT-induced change in the right frontotemporal connectivity and thalamocortical connectivity, and changes in the nodes of the default mode network were associated with clinical improvement. Modulation of these networks may explain the underlying mechanisms by which ECT exert its potent and rapid antidepressant effect.

Increased subcortical region volume induced by electroconvulsive therapy in patients with schizophrenia

Electroconvulsive therapy (ECT) has been widely used to treat patients with schizophrenia. However, the underlying mechanisms of ECT remain unknown. In the present study, the treatment effects of ECT on brain structure in patients with schizophrenia were explored. Seventy patients with schizophrenia were scanned using structural magnetic resonance imaging. Patients in the drug group were scanned at baseline (time 1) and follow-up (time 2, 6 weeks of treatment). Patients in the ECT group were scanned before ECT treatment (baseline, time 1) and 10-12 h after the last ECT treatment (time 2). Voxel-based morphometry was applied to analyze the imaging data. Patients in the ECT group showed significantly increased gray matter volume (GMV) in the bilateral hippocampus/amygdala and left superior temporal gyrus (STG)/middle temporal gyrus (MTG) after ECT combined with antipsychotic therapy at time 2. In contrast, patients in the drug group showed decreased GMV in widespread brain regions. Correlation analysis results showed significantly negative correlations between the increased GMV in the bilateral hippocampus/amygdala and PANSS scores at baseline in the ECT group. ECT may modulate brain structure in patients with schizophrenia. The GMV in distinct subcortical regions was related to the individual therapeutic response in patients with schizophrenia.

Dynamic Functional Connectivity Predicts Treatment Response to Electroconvulsive Therapy in Major Depressive Disorder

Background: Electroconvulsive therapy (ECT) is one of the most effective treatments for major depressive disorder. Recently, there has been increasing attention to evaluate the effect of ECT on resting-state functional magnetic resonance imaging (rs-fMRI). This study aims to compare rs-fMRI of depressive disorder (DEP) patients with healthy participants, investigate whether pre-ECT dynamic functional network connectivity network (dFNC) estimated from patients rs-fMRI is associated with an eventual ECT outcome, and explore the effect of ECT on brain network states.

Method: Resting-state functional magnetic resonance imaging (fMRI) data were collected from 119 patients with depression or depressive disorder (DEP) (76 females), and 61 healthy (HC) participants (34 females), with an age mean of 52.25 (N = 180) years old. The pre-ECT and post-ECT Hamilton Depression Rating Scale (HDRS) were 25.59 ± 6.14 and 11.48 ± 9.07, respectively. Twenty-four independent components from default mode (DMN) and cognitive control network (CCN) were extracted, using group-independent component analysis from pre-ECT and post-ECT rs-fMRI. Then, the sliding window approach was used to estimate the pre-and post-ECT dFNC of each subject. Next, k-means clustering was separately applied to pre-ECT dFNC and post-ECT dFNC to assess three distinct states from each participant. We calculated the amount of time each subject spends in each state, which is called “occupancy rate” or OCR. Next, we compared OCR values between HC and DEP participants. We also calculated the partial correlation between pre-ECT OCRs and HDRS change while controlling for age, gender, and site. Finally, we evaluated the effectiveness of ECT by comparing pre- and post-ECT OCR of DEP and HC participants.

Results: The main findings include (1) depressive disorder (DEP) patients had significantly lower OCR values than the HC group in state 2, where connectivity between cognitive control network (CCN) and default mode network (DMN) was relatively higher than other states (corrected p = 0.015), (2) Pre-ECT OCR of state, with more negative connectivity between CCN and DMN components, is linked with the HDRS changes (R = 0.23 corrected p = 0.03). This means that those DEP patients who spent less time in this state showed more HDRS change, and (3) The post-ECT OCR analysis suggested that ECT increased the amount of time DEP patients spent in state 2 (corrected p = 0.03).

Conclusion: Our finding suggests that dynamic functional network connectivity (dFNC) features, estimated from CCN and DMN, show promise as a predictive biomarker of the ECT outcome of DEP patients. Also, this study identifies a possible underlying mechanism associated with the ECT effect on DEP patients.

Movement, mood and cognition: Preliminary insights into the therapeutic effects of electroconvulsive therapy for depression through a resting-state connectivity analysis

BACKGROUND

Electroconvulsive therapy (ECT) is a highly effective treatment for depression but how it achieves its clinical effects remains unclear.

METHODS

We set out to study the brain's response to ECT from a large-scale brain-network perspective. Using a voxelwise analysis, we looked at resting-state functional connectivity before and after a course of ECT at the whole-brain and the between- and within-network levels in 17 patients with a depressive episode. Using a group-independent component analysis approach, we focused on four networks known to be affected in depression: the salience network (SN), the default mode network (DMN), the cognitive executive network (CEN), and a subcortical network (SCN). Our clinical measures included mood, cognition, and psychomotor symptoms.

RESULTS

We found ECT to have increased the connectivity of the left CEN with the left angular gyrus and left middle frontal gyrus as well as its within-network connectivity. Both the right CEN and the SCN showed increased connectivity with the precuneus and the anterior DMN with the left amygdala. Finally, improvement of psychomotor retardation was positively correlated with an increase of within-posterior DMN connectivity.

LIMITATIONS

The limitations of our study include its small sample size and the lack of a control dataset to confirm our findings.

CONCLUSION

Our voxelwise data demonstrate that ECT induces a significant increase of connectivity across the whole brain and at the within-network level. Furthermore, we provide the first evidence on the association between an increase of within-posterior DMN connectivity and an improvement of psychomotor retardation, a core symptom of depression.

A multimetric systematic review of fMRI findings in patients with MDD receiving ECT

BACKGROUND

Electroconvulsive therapy (ECT) is considered the most effective treatment for major depressive disorder (MDD). In recent years, the pursuit of the neurobiological mechanisms of ECT action has generated a significant amount of functional magnetic resonance imaging (fMRI) research.

OBJECTIVE

In this systematic review, we integrated all fMRI research in patients with MDD receiving ECT and, importantly, evaluated the level of convergence and replicability across multiple fMRI metrics.

RESULTS

While according to most studies changes in patients with MDD after ECT appear to be widely distributed across the brain, our multimetric review revealed specific changes involving functional connectivity increases in the superior and middle frontal gyri as the most replicated and across-modality convergent findings. Although this modulation of prefrontal connectivity was associated to ECT outcome, we also identified fMRI measurements of the subgenual anterior cingulate cortex as the fMRI signals most significantly linked to clinical response.

CONCLUSION

We identified specific prefrontal and cingulate territories which activity and connectivity with other brain regions is modulated by ECT, critically accounting for its mechanism of action.

Resting-state electroencephalographic functional network alterations in major depressive disorder following magnetic seizure therapy

Magnetic seizure therapy (MST) is emerging as a safe and well-tolerated experimental intervention for major depressive disorder (MDD), with very minimal cognitive side-effects. However, the underlying mechanism of action of MST remains uncertain. Here, we used resting-state electroencephalography (RS-EEG) to characterise the physiological effects of MST for treatment resistant MDD. We recorded RS-EEG in 21 patients before and after an open label trial of MST applied over the prefrontal cortex using a bilateral twin coil. RS-EEG was analysed for changes in functional connectivity, network topology, and spectral power. We also ran further baseline comparisons between the MDD patients and a cohort of healthy controls (n = 22). Network-based connectivity analysis revealed a functional subnetwork of significantly increased theta connectivity spanning frontal and parieto-occipital channels following MST. The change in theta connectivity was further found to predict clinical response to treatment. An additional widespread subnetwork of reduced beta connectivity was also elucidated. Graph-based topological analyses showed an increase in functional network segregation and reduction in integration in the theta band, with a decline in segregation in the beta band. Finally, delta and theta power were significantly elevated following treatment, while gamma power declined. No baseline differences between MDD patients and healthy subjects were observed. These results highlight widespread changes in resting-state brain dynamics following a course of MST in MDD patients, with changes in theta connectivity providing a potential physiological marker of treatment response. Future prospective studies are required to confirm these initial findings.

Enhanced cerebro-cerebellar functional connectivity reverses cognitive impairment following electroconvulsive therapy in major depressive disorder

Electroconvulsive therapy (ECT), a rapidly acting and effective treatment for major depressive disorder (MDD), is frequently accompanied by cognitive impairment. Recent studies have documented that ECT reorganizes dysregulated inter/intra- connected cerebral networks, including the affective network, the cognitive control network(CCN) and default mode network (DMN).Moreover, cerebellum is thought to play an important role in emotion regulation and cognitive processing. However, little is known about the relationship between cerebro-cerebellar connectivity alterations following ECT and antidepressant effects or cognitive impairment. We performed seed-based resting-state functional connectivity (RSFC) analyses in 28 MDD patients receiving ECT and 20 healthy controls to identify cerebro-cerebellar connectivity differences related to MDD and changes induced by ECT. Six seed regions (three per hemisphere) in the cerebrum were selected for RSFC, corresponding to the affective network, CCN and DMN, to establish cerebro-cerebellar functional connectivity with cerebellum. MDD patients showed increased RSFC between left sgACC and left cerebellar lobule VI after ECT. Ggranger causality analyses (GCA) identified the causal interaction is from left cerebellar lobule VI to left sgACC. Furthermore, increased effective connectivity from left cerebellar lobule VI to left sgACC exhibited positively correlated with the change in verbal fluency test (VFT) score following ECT (r = 0.433, p = 0.039). Our findings indicate that the enhanced cerebro-cerebellar functional connectivity from left lobule VI to left sgACC may ameliorate cognitive impairment induced by ECT. This study identifies a potential neural pathway for mitigation of cognitive impairment following ECT.

Altered Dynamic Amplitude of Low-Frequency Fluctuations in Patients With Migraine Without Aura

Migraine is a chronic and idiopathic disorder leading to cognitive and affective problems. However, the neural basis of migraine without aura is still unclear. In this study, dynamic amplitude of low-frequency fluctuations (dALFF) analyses were performed in 21 patients with migraine without aura and 21 gender- and age-matched healthy controls to identify the voxel-level abnormal functional dynamics. Significantly decreased dALFF in the bilateral anterior insula, bilateral lateral orbitofrontal cortex, bilateral medial prefrontal cortex, bilateral anterior cingulate cortex, and left middle frontal cortex were found in patients with migraine without aura. The dALFF values in the anterior cingulate cortex were negatively correlated with pain intensity, i.e., visual analog scale. Finally, support vector machine was used to classify patients with migraine without aura from healthy controls and achieved an accuracy of 83.33%, sensitivity of 90.48%, and specificity of 76.19%. Our findings provide the evidence that migraine influences the brain functional activity dynamics and reveal the neural basis for migraine, which could facilitate understanding the neuropathology of migraine and future treatment.

Therapeutic effects of classic serotonergic psychedelics: A systematic review of modern-era clinical studies

OBJECTIVE

To conduct a systematic review of modern-era (post-millennium) clinical studies assessing the therapeutic effects of serotonergic psychedelics drugs for mental health conditions. Although the main focus was on efficacy and safety, study characteristics, duration of antidepressants effects across studies, and the role of the subjective drug experiences were also reviewed and presented.

METHOD

A systematic literature search (1 Jan 2000 to 1 May 2020) was conducted in PubMed and PsychINFO for studies of patients undergoing treatment with a serotonergic psychedelic.

RESULTS

Data from 16 papers, representing 10 independent psychedelic-assisted therapy trials (psilocybin = 7, ayahuasca = 2, LSD = 1), were extracted, presented in figures and tables, and narratively synthesized and discussed. Across these studies, a total of 188 patients suffering either cancer- or illness-related anxiety and depression disorders (C/I-RADD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD) or substance use disorder (SUD) were included. The reviewed studies established feasibility and evidence of safety, alongside promising early data of efficacy in the treatment of depression, anxiety, OCD, and tobacco and alcohol use disorders. For a majority of patients, the therapeutic effects appeared to be long-lasting (weeks-months) after only 1 to 3 treatment session(s). All studies were conducted in line with guidelines for the safe conduct of psychedelic therapy, and no severe adverse events were reported.

CONCLUSION

The resurrection of clinical psychedelic research provides early evidence for treatment efficacy and safety for a range of psychiatric conditions, and constitutes an exciting new treatment avenue in a health area with major unmet needs.

Resting State Functional Connectivity of Brain With Electroconvulsive Therapy in Depression: Meta-Analysis to Understand Its Mechanisms

Introduction: Electroconvulsive therapy (ECT) is a commonly used brain stimulation treatment for treatment-resistant or severe depression. This study was planned to find the effects of ECT on brain connectivity by conducting a systematic review and coordinate-based meta-analysis of the studies performing resting state fMRI (rsfMRI) in patients with depression receiving ECT. Methods: We systematically searched the databases published up to July 31, 2020, for studies in patients having depression that compared resting-state functional connectivity (rsFC) before and after a course of pulse wave ECT. Meta-analysis was performed using the activation likelihood estimation method after extracting details about coordinates, voxel size, and method for correction of multiple comparisons corresponding to the significant clusters and the respective rsFC analysis measure with its method of extraction. Results: Among 41 articles selected for full-text review, 31 articles were included in the systematic review. Among them, 13 articles were included in the meta-analysis, and a total of 73 foci of 21 experiments were examined using activation likelihood estimation in 10 sets. Using the cluster-level interference method, one voxel-wise analysis with the measure of amplitude of low frequency fluctuations and one seed-voxel analysis with the right hippocampus showed a significant reduction (p < 0.0001) in the left cingulate gyrus (dorsal anterior cingulate cortex) and a significant increase (p < 0.0001) in the right hippocampus with the right parahippocampal gyrus, respectively. Another analysis with the studies implementing network-wise (posterior default mode network: dorsomedial prefrontal cortex) resting state functional connectivity showed a significant increase (p < 0.001) in bilateral posterior cingulate cortex. There was considerable variability as well as a few key deficits in the preprocessing and analysis of the neuroimages and the reporting of results in the included studies. Due to lesser studies, we could not do further analysis to address the neuroimaging variability and subject-related differences. Conclusion: The brain regions noted in this meta-analysis are reasonably specific and distinguished, and they had significant changes in resting state functional connectivity after a course of ECT for depression. More studies with better neuroimaging standards should be conducted in the future to confirm these results in different subgroups of depression and with varied aspects of ECT.

Inflammation, Hippocampal Volume, and Therapeutic Outcome following Electroconvulsive Therapy in Depressive Patients: A Pilot Study

INTRODUCTION

Electroconvulsive therapy (ECT) influences the concentration of peripheral inflammatory markers, such as interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α). In which way this immune effect contributes to the impact of ECT on the central nervous system in depression remains unknown.

OBJECTIVE

The aim of this study was to examine whether the hippocampal volumetric increase in depressed patients treated with ECT is related to changes in peripheral IL-6 and TNF-α levels.

METHODS

IL-6 and TNF-α plasma levels were measured in 62 patients 1 week before and after an acute course of ECT. Hippocampal volumes were analyzed in a magnetic resonance imaging (MRI) subsample of 13 patients at the same time points.

RESULTS

A significant decrease in IL-6 levels was observed in the total sample and a significant increase in hippocampal volume in the MRI subsample. The reduction of peripheral IL-6 correlated with an increase in total hippocampal volume. A more limited decrease of TNF-α correlated with a more limited increase of both the total and left hippocampus volumes.

CONCLUSION

This pilot study is the first to highlight the link between peripheral immune changes and hippocampal volume increase following ECT. Further research is required to conclude whether ECT indeed exerts its central effect on the brain via changes of peripheral inflammatory markers.

Temporoparietal Connectivity Within Default Mode Network Associates With Clinical Improvements in Schizophrenia Following Modified Electroconvulsive Therapy

Although modified electroconvulsive therapy (ECT) has been reported to be effective for the treatment of schizophrenia (SCZ), its action mechanism is unclear. To elucidate the underlying ECT mechanisms of SCZ, this study used a longitudinal cohort including 21 SCZ patients receiving only antipsychotics (DSZ group) and 21 SCZ patients receiving a regular course of ECT combining with antipsychotics (MSZ group) for 4 weeks. All patients underwent magnetic resonance imaging (MRI) scans at baseline (t1) and follow-up (t2) time points. A matched healthy control (HC) group included 23 individuals who were only scanned at baseline. Functional connectivity (FC) within the default mode network (DMN) was evaluated before and after ECT. Significant interaction of the group over time was found in FC between angular gyrus (AG) and middle temporal gyrus (MTG). Post-hoc analysis showed a significantly enhanced FC of left AG(AG.L) and right MTG (MTG.R) in the MSZ group relative to the DSZ group. In addition, the right AG (AG.R) showed significantly enhanced FC between MTG.R and left MTG (MTG.L) after ECT in the MSZ group, but no in the DSZ group. In particular, the FCs change in AG.L-MTG.R and AG.R-MTG.R were positively correlated with the Positive and Negative Syndrome Scale (PANSS) negative score reduction. Furthermore, the FC change in AG.L-MTG.R was also positively correlated with the PANSS general psychopathology score reduction. These findings confirmed a potential relationship between ECT inducing hyperconnectivity within DMN and improvements in symptomatology of SCZ, suggesting that ECT controls mental symptoms by regulating the temporoparietal connectivity within DMN.

Resting State Functional Connectivity Biomarkers of Treatment Response in Mood Disorders: A Review

There are currently no validated treatment biomarkers in psychiatry. Resting State Functional Connectivity (RSFC) is a popular method for investigating the neural correlates of mood disorders, but the breadth of the field makes it difficult to assess progress toward treatment response biomarkers. In this review, we followed general PRISMA guidelines to evaluate the evidence base for mood disorder treatment biomarkers across diagnoses, brain network models, and treatment modalities. We hypothesized that no treatment biomarker would be validated across these domains or with independent datasets. Results are organized, interpreted, and discussed in the context of four popular analytic techniques: (1) reference region (seed-based) analysis, (2) independent component analysis, (3) graph theory analysis, and (4) other methods. Cortico-limbic connectivity is implicated across studies, but there is no single biomarker that spans analyses or that has been replicated in multiple independent datasets. We discuss RSFC limitations and future directions in biomarker development.

Neural Correlates of Cognitive Dysfunctions in Cervical Spondylotic Myelopathy Patients: A Resting-State fMRI Study

Cervical spondylotic myelopathy (CSM) is a common disease of the elderly that is characterized by gait instability, sensorimotor deficits, etc. Recurrent symptoms including memory loss, poor attention, etc. have also been reported in recent studies. However, these have been rarely investigated in CSM patients. To investigate the cognitive deficits and their correlation with brain functional alterations, we conducted resting-state fMRI (rs-fMRI) signal variability. This is a novel indicator in the neuroimaging field for assessing the regional neural activity in CSM patients. Further, to explore the network changes in patients, functional connectivity (FC) and graph theory analyses were performed. Compared with the controls, the signal variabilities were significantly lower in the widespread brain regions especially at the default mode network (DMN), visual network, and somatosensory network. The altered inferior parietal lobule signal variability positively correlated with the cognitive function level. Moreover, the FC and the global efficiency of DMN increased in patients with CSM and positively correlated with the cognitive function level. According to the study results, (1) the cervical spondylotic myelopathy patients exhibited regional neural impairments, which correlated with the severity of cognitive deficits in the DMN brain regions, and (2) the increased FC and global efficiency of DMN can compensate for the regional impairment.

Habenula and left angular gyrus circuit contributes to response of electroconvulsive therapy in major depressive disorder

The habenula (Hb), one of the hottest structures in depression, has been widely demonstrated to be involved in the neurobiology of depression. Although the structural and functional abnormalities of Hb have been reported in major depressive disorders (MDD) patients, the role of Hb in treatment response in MDD remains unclear. In this study, resting-state functional connectivity (RSFC) and Granger causality analysis (GCA) were performed to investigate the intrinsic and causal changes of Hb in MDD after ECT. Moreover, support vector classification was applied to find out whether the changed functional and causal connections of Hb can effectively distinguish the MDD patients from healthy controls. The RSFC and GCA identified increased RSFC strength between bilateral Hb and left angular gyrus (AG), decreased causal connectivity strength from left AG to left Hb, from right Hb to left AG, and bidirectional interactions between left and right Hb in MDD patients after ECT. The changed causal connectivities from left AG to left Hb, and from right Hb to left AG were correlated with the changed depression symptoms and impaired delay memory recall performances. Furthermore, the functional and causal connectivities between left AG and bilateral Hb could serve as a biomarker to differentiate MDD from HCs. These results provided new evidence for the importance of Hb in depression and revealed that the interactions between Hb and left AG contribute to ECT response in MDD. Our findings will facilitate the future treatment of depression with the target of Hb in MDD and other brain disorders.

Electroconvulsive therapy modulates functional interactions between submodules of the emotion regulation network in major depressive disorder

An increasing number of neuroimaging studies have consistently revealed that disrupted functional interactions within the cognitive emotion regulation network (ERN) contribute to the onset of major depressive disorders (MDD). To disentangle the functional reorganization of ERN after electroconvulsive therapy (ECT) in MDD is curial for understanding its neuropathology. Resting-state functional magnetic resonance imaging data was collected from 23 MDD patients before and after ECT, as well as 25 healthy controls. Network modularity analysis was used to identify the submodules and functional connectivity (FC) was used to investigate the functional reorganization of ERN in the MDD patients after ECT. Four submodules of ERN were identified, including emotion response module (ERM), emotion integration module (EIM), emotion generation module (EGM), and emotion execution module (EEM). The increased intra-modular FC of EEM and inter-modular FCs of EEM with EIM\ERM were found in MDD patients after ECT. Modular transition analysis revealed that left ventrolateral prefrontal cortex, supplementary motor area, posterior cingulate cortex, right angular gyrus, and right precentral gyrus were transferred across different submodules across the three groups. Further analyses showed correlations between changed FC and clinical symptoms in the MDD patients after ECT. Finally, we also identified 11 increased connections between nodes belonging to different submodules of ERN in MDD patients after ECT. These results showed that ECT could induce functional reorganization of intra- and inter-modules within the ERN, and the functional changes were related to therapeutic efficacy or memory impairments of ECT in MDD patients.

Ketamine plus propofol-electroconvulsive therapy (ECT) transiently improves the antidepressant effects and the associated brain functional alterations in patients with propofol-ECT-resistant depression

New methods for using ketamine in patients with propofol-electroconvulsive therapy-resistant depression (ECT-RD) are needed in the clinic. This study aimed to investigate the therapeutic efficacy of ketamine plus ECT in ECT-RD patients, along with the treatment-induced brain alterations. A total of 28 ECT-RD patients were intravenously injected with ketamine six times and treated with propofol-ECT six times alternately within two weeks. The Hamilton Depression Scale was used to assess the treatment effect. Global functional connectivity density (gFCD) and functional connectivity strength (FCS) were used to evaluate functional brain alterations. As compared with the propofol-ECT treatment group, the addition of ketamine could improve the therapeutic outcomes in patients with ECT-RD. The treatment increased gFCD in the left temporal and subgenual anterior cingulated cortex. Simultaneously, the treatment decreased FCS within the default mode network. Although increased functional connectivity could be sustained for 10 days, the clinical effect was only sustained 7 days, indicating that the clinical effect and functional brain alterations were disjointed. Ketamine plus propofol-ECT can obviously improve the effects of propofol-ECT in ECT-RD patients. However, the effect is limited in 7 days, suggesting the benefit is short-term.

Structural changes induced by electroconvulsive therapy are associated with clinical outcome

BACKGROUND

Electroconvulsive therapy (ECT) is the most effective treatment option for major depressive disorder, so understanding whether its clinical effect relates to structural brain changes is vital for current and future antidepressant research.

OBJECTIVE

To determine whether clinical response to ECT is related to structural volumetric changes in the brain as measured by structural magnetic resonance imaging (MRI) and, if so, which regions are related to this clinical effect. We also determine whether a similar model can be used to identify regions associated with electrode placement (unilateral versus bilateral ECT).

METHODS

Longitudinal MRI and clinical data (Hamilton Depression Rating Scale) was collected from 10 sites as part of the Global ECT-MRI research collaboration (GEMRIC). From 192 subjects, relative changes in 80 (sub)cortical areas were used as potential features for classifying treatment response. We used recursive feature elimination to extract relevant features, which were subsequently used to train a linear classifier. As a validation, the same was done for electrode placement. We report accuracy as well as the structural coefficients of regions included in the discriminative spatial patterns obtained.

RESULTS

A pattern of structural changes in cortical midline, striatal and lateral prefrontal areas discriminates responders from non-responders (75% accuracy, p < 0.001) while left-sided mediotemporal changes discriminate unilateral from bilateral electrode placement (81% accuracy, p < 0.001).

CONCLUSIONS

The identification of a multivariate discriminative pattern shows that structural change is relevant for clinical response to ECT, but this pattern does not include mediotemporal regions that have been the focus of electroconvulsive therapy research so far.

Grey Matter changes in treatment-resistant depression during electroconvulsive therapy

INTRODUCTION

20-30% of depressed patients experience Treatment Resistant Depression (TRD). Electroconvulsive Therapy (ECT) remains the treatment of choice for TRD. However, the exact mechanism of ECT remains unclear. We aim to assess grey matter changes in patients with TRD undergoing bilateral ECT treatment at different points during and after treatment.

METHODS

Patients are recruited at the University Hospital of Toulouse. Eligibility criteria include a diagnosis of TRD and an age between 50 and 70 years old. Patients received clinical assessments (Hamilton Depression Rating Scale) and structural scans (MRI) at three points: baseline (within 48 h before the first ECT); V2 (after the first ECT considered effective); and V3 (within 1 week of completing ECT).

RESULTS

At baseline, controls had significantly higher cortical thickness than patients in the fusiform gyrus, the inferior, middle and superior temporal gyrus, the parahippocampal gyrus and the transverse temporal gyrus (respectively: t(35)=2.7, p = 0.02; t(35)=2.89, p = 0.017; t(35)=3.1, p = 0.015; t(35)=3.6, p = 0.009; t(35)=2.37, p = 0.031; t(35)=2.46, p = 0.03). This difference was no longer significant after ECT. We showed an increase in cortical thickness in superior temporal gyrus between (i) baseline and V3 (t(62)=-3.43 p = 0.009) and (ii) V2 and V3 (t(62)=-3.42 p = 0.009). We showed an increase in hippocampal volume between (i) baseline and V3 (t(62)=-5.23 p < 0.001) and (ii) V2 and V3 (t(62)=-5.3 p < 0.001).

CONCLUSION

We highlight that there are grey matter changes during ECT treatment in a population with TRD compared to a healthy control population. These changes seem to occur after several rounds of ECT.

Transdiagnostic modulation of brain networks by electroconvulsive therapy in schizophrenia and major depression

Major depressive disorder (MDD) and schizophrenia (SCZ) share neurobiological and clinical commonalities. Altered functional connectivity of large-scale brain networks has been associated with both disorders. Electroconvulsive therapy (ECT) has proven to be an effective treatment in severe forms of MDD and SCZ. However, the role of ECT on the modulation of the dynamics of brain networks is still unknown. In this study, we used resting state functional magnetic resonance imaging (rs-fMRI) to investigate functional connectivity in 16 pharmacoresistant patients with SCZ or MDD and a matched group of normal controls. Patients were scanned before and after right-sided unilateral ECT. Group spatial independent component analysis was carried out with a multiple analysis of covariance (MANCOVA) approach to estimate the effects of ECT treatment on intrinsic components (INs). Functional network connectivity (FNC) was calculated between pairs of INs. Patients had reduced connectivity within a striato-thalamic network in the thalamus as well as increased low frequency oscillations in a striatal network. ECT reduced low frequency oscillations (LFOs) on a striatal network along with increasing functional connectivity in the medial prefrontal cortex within the DMN. Following ECT treatment, the FNC of the executive network was reduced with the DMN and increased with the salience network, respectively. Our findings suggest transnosological effects of ECT on the connectivity of large-scale networks as well as at the level of their interplay. Furthermore, they support a transnosological approach for the investigation not only of the neural correlates of the disease but also of the brain mechanism of treatment of mental disorders.

Classic psychedelics: the special role of the visual system

Here, we briefly overview the various aspects of classic serotonergic hallucinogens reported by a number of studies. One of the key hypotheses of our paper is that the visual effects of psychedelics might play a key role in resetting fears. Namely, we especially focus on visual processes because they are among the most prominent features of hallucinogen-induced hallucinations. We hypothesize that our brain has an ancient visual-based (preverbal) intrinsic cognitive process that, during the transient inhibition of top-down convergent and abstract thinking (mediated by the prefrontal cortex) by psychedelics, can neutralize emotional fears of unconscious and conscious life experiences from the past. In these processes, the decreased functional integrity of the self-referencing processes of the default mode network, the modified multisensory integration (linked to bodily self-consciousness and self-awareness), and the modified amygdala activity may also play key roles. Moreover, the emotional reset (elimination of stress-related emotions) by psychedelics may induce psychological changes and overwrite the stress-related neuroepigenetic information of past unconscious and conscious emotional fears.

The Principles of Electroconvulsive Therapy Based on Correlations of Schizophrenia and Epilepsy: A View From Brain Networks

Electroconvulsive therapy (ECT) was established based on Meduna's hypothesis that there is an antagonism between schizophrenia and epilepsy, and that the induction of a seizure could alleviate the symptoms of schizophrenia. However, subsequent investigations of the mechanisms of ECT have largely ignored this originally established relationship between these two disorders. With the development of functional magnetic resonance imaging (fMRI), brain-network studies have demonstrated that schizophrenia and epilepsy share common dysfunctions in the default-mode network (DMN), saliency network (SN), dorsal-attention network (DAN), and central-executive network (CEN). Additionally, fMRI-defined brain networks have also been shown to be useful in the evaluation of the treatment efficacy of ECT. Here, we compared the ECT-induced changes in the pathological conditions between schizophrenia and epilepsy in order to offer further insight as to whether the mechanisms of ECT are truly based on antagonistic and/or affinitive relationships between these two disorders.

Indices of Change, Expectations, and Popularity of Biological Treatments for Major Depressive Disorder between 1988 and 2017: A Scientometric Analysis

BACKGROUND

Major Depressive Disorder (MDD) is the most common psychiatric disorder with high prevalence and disease burden. Biological treatments of MDD over the last several decades include a wide range of antidepressants and neurostimulation therapies. While recent meta-analyses have explored the efficacy and tolerability of antidepressants, the changing trends of biological treatments have not been evaluated. Our study measured the indices of change, expectations, and popularity of biological treatments of MDD between 1988 and 2017.

METHODS

We performed a scientometric analysis to identify all relevant publications related to biological treatments of MDD from 1988 to 2017. We searched the Web of Science websites for publications from 1 January 1988 to 31 December 2017. We included publications of fluoxetine, paroxetine, citalopram, sertraline, amitriptyline, fluvoxamine, escitalopram, venlafaxine, duloxetine, milnacipran, desvenlafaxine, levomilnacipran, clomipramine, nortriptyline, bupropion, trazodone, nefazodone, mirtazapine, agomelatine, vortioxetine, vilazodone, electroconvulsive therapy (ECT), repetitive transcranial magnetic stimulation (rTMS), vagus nerve stimulation (VNS), deep brain stimulation (DBS), and transcranial direct current stimulation (tDCS). We excluded grey literature, conference proceedings, books/book chapters, and publications with low quality as well as publications not related to medicine or human health. The primary outcomes assessed were indices of change, expectations, and popularity.

RESULTS

Of 489,496 publications identified, we included 355,116 publications in this scientometric analysis. For the index of change, fluoxetine, sertraline and ECT demonstrated a positive index of change in 6 consecutive periods. Other neurostimulation therapies including rTMS, VNS, DBS and tDCS had shown a positive index of change since 1998. We calculated the index of change of popularity index (PI), which indicates that from 2013 to 2017, the number of publications on tricyclic antidepressants (TCAs) and monoamine oxidase inhibitors (MAOIs) were reduced by 85.0% and 81.3% respectively, as compared with the period 2008-2012. For the index of expectation, fluoxetine and ECT showed the highest index of expectations in six consecutive periods and remained the highest in 2013-2017. For popularity, the three antidepressants with highest PI were fluoxetine (4.01), paroxetine (2.09), and sertraline (1.66); the three antidepressants with lowest PI were desvenlafaxine (0.08), vilazodone (0.04) and levomilnacipran (0.03). Among neurostimulation therapies, ECT has the highest PI (2.55), and tDCS the lowest PI (0.14). The PI of SSRI remained the highest among all biological treatments of MDD in 2013-2017. In contrast, the PI of ECT was reduced by approximately 50% during the period 2008 to2012 than that in the period 2013 to 2017.

CONCLUSIONS

This scientometric analysis represents comprehensive evidence on the popularity and change in prospects of biological treatments for MDD from 1988 to 2017. The popularity of SSRI peaked between 1998 and 2002, when their efficacy, tolerability and safety profile allowed them to replace the TCAs and MAOIs. While the newer neurostimulation therapies are gaining momentum, the popularity of ECT has sustained.

Leveraging Neuroplasticity to Enhance Adaptive Learning: The Potential for Synergistic Somatic-Behavioral Treatment Combinations to Improve Clinical Outcomes in Depression

Until recently, therapeutic development in psychiatry was targeted solely toward symptom reduction. While this is a worthwhile goal, it has yielded little progress in improved therapeutics in the last several decades in the field of mood disorders. Recent advancements in our understanding of pathophysiology suggests that an impairment of neuroplasticity may be a critical part of the development of neuropsychiatric disorders. Interventions that enhance or modulate neuroplasticity often reduce depressive symptoms when applied as stand-alone treatments. Unfortunately, when treatments are discontinued, the disease state often returns as patients relapse. However, treatments that enhance or modulate plasticity not only reduce symptom burden, but also may provide an opportune window wherein cognitive or behavioral interventions could be introduced to harness a state of enhanced neuroplasticity and lead to improved longer-term clinical outcomes. Here, we review the potential of synergistically combining plasticity-enhancing and behavioral therapies to develop novel translational treatment approaches for depression. After reviewing relevant neuroplasticity deficits in depression, we survey biological treatments that appear to reverse such deficits in humans, including N-methyl-D-aspartate receptor modulators (ketamine, D-cycloserine), electroconvulsive therapy, and transcranial brain stimulation. We then review evidence that either directly or indirectly supports the hypothesis that a robust enhancement of neuroplasticity through these methods might promote the uptake of cognitive and behavioral interventions to enhance longer-term treatment outcomes through a synergistic effect. We identify key missing pieces of evidence and discuss future directions to enhance this emerging line of research.

Structural changes in amygdala nuclei, hippocampal subfields and cortical thickness following electroconvulsive therapy in treatment-resistant depression: longitudinal analysis

BACKGROUND

Electroconvulsive therapy (ECT) is the treatment of choice for severe mental illness including treatment-resistant depression (TRD). Increases in volume of the hippocampus and amygdala following ECT have consistently been reported.AimsTo investigate neuroplastic changes after ECT in specific hippocampal subfields and amygdala nuclei using high-resolution structural magnetic resonance imaging (MRI) (trial registration: clinicaltrials.gov - NCT02379767).

METHOD

MRI scans were carried out in 14 patients (11 women, 46.9 years (s.d. = 8.1)) with unipolar TRD twice before and once after a series of right unilateral ECT in a pre-post study design. Volumes of subcortical structures, including subfields of the hippocampus and amygdala, and cortical thickness were extracted using FreeSurfer. The effect of ECT was tested using repeated-measures ANOVA. Correlations of imaging and clinical parameters were explored.

RESULTS

Increases in volume of the right hippocampus by 139.4 mm3 (s.d. = 34.9), right amygdala by 82.3 mm3 (s.d. = 43.9) and right putamen by 73.9 mm3 (s.d. = 77.0) were observed. These changes were localised in the basal and lateral nuclei, and the corticoamygdaloid transition area of the amygdala, the hippocampal-amygdaloid transition area and the granule cell and molecular layer of the dentate gyrus. Cortical thickness increased in the temporal, parietal and insular cortices of the right hemisphere.

CONCLUSIONS

Following ECT structural changes were observed in hippocampal subfields and amygdala nuclei that are specifically implicated in the pathophysiology of depression and stress-related disorders and retain a high potential for neuroplasticity in adulthood.Declaration of interestS.K. has received grants/research support, consulting fees and/or honoraria within the past 3 years from Angelini, AOP Orphan Pharmaceuticals AG, AstraZeneca, Celegne GmbH, Eli Lilly, Janssen-Cilag Pharma GmbH, KRKA-Pharma, Lundbeck A/S, Neuraxpharm, Pfizer, Pierre Fabre, Schwabe and Servier. R.L. received travel grants and/or conference speaker honoraria from Shire, AstraZeneca, Lundbeck A/S, Dr. Willmar Schwabe GmbH, Orphan Pharmaceuticals AG, Janssen-Cilag Pharma GmbH, and Roche Austria GmbH.

Making Sense of Connectivity

In addition to the assessment of local alterations of specific brain regions, the investigation of entire networks with in vivo neuroimaging techniques has gained increasing attention. In general, connectivity analysis refers to the investigation of links between brain regions, with the aim to characterize their interactions and information transfer. These may represent or relate to different physiological characteristics (structural, functional, or metabolic information) and can be calculated across different levels of granularity (2 regions vs whole brain). In this article, we provide an overview of different connectivity analysis approaches with interpretations and limitations as well as examples in pharmacological imaging and clinical applications. Structural connectivity obtained from diffusion MRI enables the reconstruction of neuronal fiber tracts. These physical links represent major constraints of functional connections, which are in turn defined as correlations between signal time courses. In addition, molecular connectivity approaches based on PET imaging enable the assessment of interregional associations of metabolic demands and neurotransmitter systems. Application of these approaches in clinical investigations has demonstrated novel alterations in various neurological and psychiatric disorders on a network level. Future work should aim for the combined assessment of multiple imaging modalities and to establish robust biomarkers for clinical use. These advancements will further improve the biological interpretation of connectivity metrics and networks of the human brain.

Increased resting-state global functional connectivity density of default mode network in schizophrenia subjects treated with electroconvulsive therapy

Modified electroconvulsive therapy (MECT) has been widely applied to help treat schizophrenia patients who are treatment-resistant to pharmaceutical therapy. Although the technique is increasingly prevalent, the underlying neural mechanisms have not been well clarified. We conducted a longitudinal study to investigate the alteration of global functional connectivity density (gFCD) in schizophrenia patients undergoing MECT using resting state fMRI (functional magnetic resonance imaging). Two groups of schizophrenia inpatients were recruited. One group received a four-week MECT together with antipsychotic drugs (ECT+Drug, n=21); the other group only received antipsychotic drugs (Drug, n=21). Both groups were compared to a sample of healthy controls (HC, n=23). fMRI scans were obtained from the schizophrenia patients twice at baseline (t₁) and after 4-week treatment (t₂), and from healthy controls at baseline. gFCD was computed using resting state fMRI. Repeated ANCOVA showed a significant interaction effect of group×time in the schizophrenia patients in left precuneus (Pcu), ventral medial prefrontal cortex (vMPFC), and dorsal medial prefrontal cortex (dMPFC) (GRF-corrected P<0.05), which are mainly located within the default mode network (DMN). Post-hoc analysis revealed that compared with baseline (t₁), an increased gFCD was found in the ECT+Drug group in the dMPFC (t=3.87, p=0.00095), vMPFC (t=3.95, p=0.00079) and left Pcu (t=3.33, p=0.0034), but no significant effect was identified in the Drug group. The results suggested that increased global functional connectivity density within the DMN might be one important neural mechanism of MECT in schizophrenia.

How Does Repetitive Transcranial Magnetic Stimulation Influence the Brain in Depressive Disorders?: A Review of Neuroimaging Magnetic Resonance Imaging Studies

OBJECTIVE

Repetitive transcranial magnetic stimulation (rTMS) is a nonpharmacological technique used to stimulate the brain. It is a safe and proven alternative tool to treat resistant major depressive disorders (MDDs). Neuroimaging studies suggest a wide corticolimbic network is involved in MDDs. We researched observable changes in magnetic resonance imaging induced by rTMS to clarify the operational mechanism.

METHODS

A systematic search of the international literature was performed using PubMed and Embase, using papers published up to January 1, 2017. The following MESH terms were used: (depression or major depressive disorder) and (neuroimaging or MRI) and (rTMS or repetitive transcranial magnetic stimulation). We searched the databases using a previously defined strategy to identify potentially eligible studies.

RESULTS

Both structural and functional changes were observed on magnetic resonance imagings performed before and after rTMS. Various areas of the brain were impacted when rTMS was used. Although the results were very heterogeneous, a pattern that involved the anterior cingulate cortex and the prefrontal cortex emerged. These are known to be regions of interest in MDDs. However, the various parameters used in rTMS make any generalization difficult.

CONCLUSIONS

Repetitive transcranial magnetic stimulation helps to treat MDDs with good efficacy. Its effect on the brain, as observed in several neuroimaging studies, seems to impact on the structural and functional features of several networks and structures involved in major depressive disorders.

Abnormal Default Mode Network Homogeneity in Treatment-Naive Patients With First-Episode Depression

Background and Objective: The default mode network (DMN) may be an important component involved in the broad-scale cognitive problems seen in patients with first-episode treatment-naive depression. Nevertheless, information is scarce regarding the changes in network homogeneity (NH) found in the DMN of these patients. Therefore, in this study, we explored the NH of the DMN in patients with first-episode treatment-naive depression. Methods: The study included 66 patients and 74 control participants matched by age, gender, educational level and health status who underwent resting-state functional magnetic resonance imaging (rs-fMRI) and the attentional network test (ANT). To assess data, the study utilizes NH and independent component analysis (ICA). Additionally, Spearman's rank correlation analysis is performed among significantly abnormal NH in depression patients and clinical measurements and executive control reaction time (ECRT). Results: In comparison with the control group, patients with first-episode treatment-naive depression showed lower NH in the bilateral angular gyrus (AG), as well as increased NH in the bilateral precuneus (PCu) and posterior cingulate cortex (PCC). Likewise, patients with first-episode treatment-naive depression had longer ECRT. No significant relation was found between abnormal NH values and the measured clinical variables. Conclusions: Our results suggest patients with first-episode treatment-naive depression have abnormal NH values in the DMN. This highlights the significance of DMN in the pathophysiology of cognitive problems in depression. Our study also found alterations in executive functions in patients with first-episode treatment-naive depression.

Psilocybin for treatment-resistant depression: fMRI-measured brain mechanisms

Psilocybin with psychological support is showing promise as a treatment model in psychiatry but its therapeutic mechanisms are poorly understood. Here, cerebral blood flow (CBF) and blood oxygen-level dependent (BOLD) resting-state functional connectivity (RSFC) were measured with functional magnetic resonance imaging (fMRI) before and after treatment with psilocybin (serotonin agonist) for treatment-resistant depression (TRD). Quality pre and post treatment fMRI data were collected from 16 of 19 patients. Decreased depressive symptoms were observed in all 19 patients at 1-week post-treatment and 47% met criteria for response at 5 weeks. Whole-brain analyses revealed post-treatment decreases in CBF in the temporal cortex, including the amygdala. Decreased amygdala CBF correlated with reduced depressive symptoms. Focusing on a priori selected circuitry for RSFC analyses, increased RSFC was observed within the default-mode network (DMN) post-treatment. Increased ventromedial prefrontal cortex-bilateral inferior lateral parietal cortex RSFC was predictive of treatment response at 5-weeks, as was decreased parahippocampal-prefrontal cortex RSFC. These data fill an important knowledge gap regarding the post-treatment brain effects of psilocybin, and are the first in depressed patients. The post-treatment brain changes are different to previously observed acute effects of psilocybin and other 'psychedelics' yet were related to clinical outcomes. A 'reset' therapeutic mechanism is proposed.

Serotonin and brain function: a tale of two receptors

Previous attempts to identify a unified theory of brain serotonin function have largely failed to achieve consensus. In this present synthesis, we integrate previous perspectives with new and older data to create a novel bipartite model centred on the view that serotonin neurotransmission enhances two distinct adaptive responses to adversity, mediated in large part by its two most prevalent and researched brain receptors: the 5-HT1A and 5-HT2A receptors. We propose that passive coping (i.e. tolerating a source of stress) is mediated by postsynaptic 5-HT1AR signalling and characterised by stress moderation. Conversely, we argue that active coping (i.e. actively addressing a source of stress) is mediated by 5-HT2AR signalling and characterised by enhanced plasticity (defined as capacity for change). We propose that 5-HT1AR-mediated stress moderation may be the brain's default response to adversity but that an improved ability to change one's situation and/or relationship to it via 5-HT2AR-mediated plasticity may also be important - and increasingly so as the level of adversity reaches a critical point. We propose that the 5-HT1AR pathway is enhanced by conventional 5-HT reuptake blocking antidepressants such as the selective serotonin reuptake inhibitors (SSRIs), whereas the 5-HT2AR pathway is enhanced by 5-HT2AR-agonist psychedelics. This bipartite model purports to explain how different drugs (SSRIs and psychedelics) that modulate the serotonergic system in different ways, can achieve complementary adaptive and potentially therapeutic outcomes.

Clinical utility of a short resting-state MRI scan in differentiating bipolar from unipolar depression

OBJECTIVE

Depression in bipolar disorder (BipD) requires a therapeutic approach that is from treating unipolar major depressive disorder (UniD), but to date, no reliable methods could separate these two disorders. The aim of this study was to establish the clinical validity and utility of a non-invasive functional MRI-based method to classify BipD from UniD.

METHOD

The degree of connectivity (degree centrality or DC) of every small unit (voxel) with every other unit of the brain was estimated in 22 patients with BipD and 22 age, gender, and depressive severity-matched patients with UniD and 22 healthy controls. Pattern classification analysis was carried out using a support-vector machine (SVM) approach.

RESULTS

Degree centrality pattern from 8-min resting fMRI discriminated BipD from UniD with an accuracy of 86% and diagnostic odds ratio of 9.6. DC was reduced in the left insula and increased in bilateral precuneus in BipD when compared to UniD. In this sample with a high degree of uncertainty (50% prior probability), positive predictive value of the DC test was 79%.

CONCLUSION

Degree centrality maps are potential candidate measures to separate bipolar depression from unipolar depression. Test performance reported here requires further pragmatic evaluation in regular clinical practice.

Resting state brain network function in major depression - Depression symptomatology, antidepressant treatment effects, future research

The alterations of functional connectivity brain networks in major depressive disorder (MDD) have been subject of a large number of studies. Using different methodologies and focusing on diverse aspects of the disease, research shows heterogeneous results lacking integration. Disrupted network connectivity has been found in core MDD networks like the default mode network (DMN), the central executive network (CEN), and the salience network, but also in cerebellar and thalamic circuitries. Here we review literature published on resting state brain network function in MDD focusing on methodology, and clinical characteristics including symptomatology and antidepressant treatment related findings. There are relatively few investigations concerning the qualitative aspects of symptomatology of MDD, whereas most studies associate quantitative aspects with distinct resting state functional connectivity alterations. Such depression severity associated alterations are found in the DMN, frontal, cerebellar and thalamic brain regions as well as the insula and the subgenual anterior cingulate cortex. Similarly, different therapeutical options in MDD and their effects on brain function showed patchy results. Herein, pharmaceutical treatments reveal functional connectivity alterations throughout multiple brain regions notably the DMN, fronto-limbic, and parieto-temporal regions. Psychotherapeutical interventions show significant functional connectivity alterations in fronto-limbic networks, whereas electroconvulsive therapy and repetitive transcranial magnetic stimulation result in alterations of the subgenual anterior cingulate cortex, the DMN, the CEN and the dorsal lateral prefrontal cortex. While it appears clear that functional connectivity alterations are associated with the pathophysiology and treatment of MDD, future research should also generate a common strategy for data acquisition and analysis, as a least common denominator, to set the basis for comparability across studies and implementation of functional connectivity as a scientifically and clinically useful biomarker.

Potential Mechanisms Underlying the Therapeutic Effects of Electroconvulsive Therapy

In spite of the extensive application of electroconvulsive therapy (ECT), how it works remains unclear. So far, researchers have made great efforts in figuring out the mechanisms underlying the effect of ECT treatment via determining the levels of neurotransmitters and cytokines and using genetic and epigenetic tools, as well as structural and functional neuroimaging. To help address this question and provide implications for future research, relevant clinical trials and animal experiments are reviewed.