Negative cognitive schema modification as mediator of symptom improvement after electroconvulsive therapy in major depressive disorder

Background: Electroconvulsive therapy (ECT) is a potent option for treatment-resistant major depressive disorder (MDD). Cognitive models of depression posit that negative cognitions and underlying all-or-nothing negative schemas contribute to and perpetuate depressed mood. This study investigates whether ECT can modify negative schemas, potentially via memory reactivation, and whether such changes are related to MDD symptom improvement. Method: Seventy-two patients were randomized to either an emotional memory reactivation electroconvulsive therapy (EMR-ECT) or control memory reactivation electroconvulsive therapy (CMR-ECT) intervention prior to ECT-sessions in a randomized controlled trail. Emotional memories associated with patients' depression were reactivated before ECT-sessions. At baseline and after the ECT-course, negative schemas and depression severity were assessed using the Dysfunctional Attitude Scale (DAS) and Hamilton Depression Rating Scale HDRS. Mediation analyses were used to examine whether the effects of ECT on HDRS-scores were mediated by changes in DAS-scores or vice versa. Results: Post-ECT DAS-scores were significantly lower compared to baseline. Post-ECT, the mean HDRS-score of the whole sample (15.10 ± 8.65 [SD]; n = 59) was lower compared to baseline (24.83 ± 5.91 [SD]). Multiple regression analysis showed no significant influence of memory reactivation on schema improvement. Path analysis showed that depression improvement was mediated by improvement of negative cognitive schemas. Conclusion: ECT is associated with improvement of negative schemas, which appears to mediate the improvement of depressive symptoms. An emotional memory intervention aimed to modify negative schemas showed no additional effect

Effectiveness of Emotional Memory Reactivation vs Control Memory Reactivation Before Electroconvulsive Therapy in Adult Patients With Depressive Disorder A Randomized Clinical Trial:A Randomized Clinical Trial

Importance: Although electroconvulsive therapy (ECT) is often effective, approximately half of patients with depression undergoing ECT do not benefit sufficiently, and relapse rates are high. ECT sessions have been shown to weaken reactivated memories. The effect of emotional memory retrieval on cognitive schemas remains unknown. Objective: To assess whether emotional memory retrieval just before patients receive ECT sessions weakens underlying cognitive schemas, improves ECT effectiveness, increases ECT response, and reduces relapse rates. Design, Setting, and Participants: In this multicenter randomized clinical trial conducted from 2014 to 2018 in the departments of psychiatry in 3 hospitals in the Netherlands, 72 participants were randomized 1:1 to 2 parallel groups to receive either emotional memory reactivation (EMR-ECT) or control memory reactivation (CMR-ECT) interventions before ECT sessions. The Hamilton Depression Rating Scale (HDRS [total score range: 0-52, with 0-7 indicating no depression and ≥24 indicating severe depression]) was used to measure symptoms of depression during and after ECT, with a 6-month follow-up period. Participants were between ages 18 and 70 years with a primary diagnosis of unipolar major depressive disorder (MDD) according to the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) and in whom ECT was indicated. Data analysis was performed from July to November 2019. Interventions: EMR-ECT or CMR-ECT interventions prior to ECT sessions. Main Outcomes and Measures: Depression scores and relapse rates within 6 months were assessed with the HDRS and analyzed using logistic and linear multiple regression analyses. Results: A total of 66 patients (mean [SD] age, 49.3 [12.3] years; 39 [59.1%] women) were randomized to the EMR-ECT group (n = 32) or the CMR-ECT group (n = 34). Regardless of the memory intervention, 42.4% (28 of 66) of patients responded (≥50% decrease of symptom severity on the HDRS). Of patients who responded, 39.3% (11 of 28) relapsed within 6 months. Remission rates (CMR-ECT group, 29.4% [10 of 34] vs EMR-ECT group, 25.0% [8 of 32]; P = .58), mean (SD) HDRS scores after the ECT course (CMR-ECT group, 14.6 [8.6] vs EMR-ECT group, 14.9 [8.8]; P = .88), total mean (SD) number of required ECT sessions for response (CMR-ECT group, 14.9 [7.9] vs EMR-ECT group, 15.6 [7.3]; P = .39), and relapse rates (CMR-ECT group, 46.7% [7 of 15] vs EMR-ECT group, 30.8% [4 of 13]; P = .33) were not significantly altered by the intervention. Conclusions and Relevance: Study findings suggest that the EMR-ECT intervention just before patient receipt of ECT for depression did not improve effectiveness, increase speed of response, or reduce relapse rates after the ECT course compared with patients receiving CMR-ECT. Trial Registration: Trialregister.nl Identifier: NL4289

Effective resting-state connectivity in severe unipolar depression before and after electroconvulsive therapy

Background Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depressive disorders. A recent multi-center study found no consistent changes in correlation-based (undirected) resting-state connectivity after ECT. Effective (directed) connectivity may provide more insight into the working mechanism of ECT. Objective We investigated whether there are consistent changes in effective resting-state connectivity. Methods This multi-center study included data from 189 patients suffering from severe unipolar depression and 59 healthy control participants. Longitudinal data were available for 81 patients and 24 healthy controls. We used dynamic causal modeling for resting-state functional magnetic resonance imaging to determine effective connectivity in the default mode, salience and central executive networks before and after a course of ECT. Bayesian general linear models were used to examine differences in baseline and longitudinal effective connectivity effects associated with ECT and its effectiveness. Results Compared to controls, depressed patients showed many differences in effective connectivity at baseline, which varied according to the presence of psychotic features and later treatment outcome. Additionally, effective connectivity changed after ECT, which was related to ECT effectiveness. Notably, treatment effectiveness was associated with decreasing and increasing effective connectivity from the posterior default mode network to the left and right insula, respectively. No effects were found using correlation-based (undirected) connectivity. Conclusions A beneficial response to ECT may depend on how brain regions influence each other in networks important for emotion and cognition. These findings further elucidate the working mechanisms of ECT and may provide directions for future non-invasive brain stimulation research.publishedVersio

Effective resting-state connectivity in severe unipolar depression before and after electroconvulsive therapy

BACKGROUND: Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depressive disorders. A recent multi-center study found no consistent changes in correlation-based (undirected) resting-state connectivity after ECT. Effective (directed) connectivity may provide more insight into the working mechanism of ECT. OBJECTIVE: We investigated whether there are consistent changes in effective resting-state connectivity. METHODS: This multi-center study included data from 189 patients suffering from severe unipolar depression and 59 healthy control participants. Longitudinal data were available for 81 patients and 24 healthy controls. We used dynamic causal modeling for resting-state functional magnetic resonance imaging to determine effective connectivity in the default mode, salience and central executive networks before and after a course of ECT. Bayesian general linear models were used to examine differences in baseline and longitudinal effective connectivity effects associated with ECT and its effectiveness. RESULTS: Compared to controls, depressed patients showed many differences in effective connectivity at baseline, which varied according to the presence of psychotic features and later treatment outcome. Additionally, effective connectivity changed after ECT, which was related to ECT effectiveness. Notably, treatment effectiveness was associated with decreasing and increasing effective connectivity from the posterior default mode network to the left and right insula, respectively. No effects were found using correlation-based (undirected) connectivity. CONCLUSIONS: A beneficial response to ECT may depend on how brain regions influence each other in networks important for emotion and cognition. These findings further elucidate the working mechanisms of ECT and may provide directions for future non-invasive brain stimulation research

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.publishedVersio

The Longitudinal Effects of Electroconvulsive Therapy on Ictal Interhemispheric Coherence and Its Associations With Treatment Outcome : A Naturalistic Cohort Study

Objectives. Electroconvulsive therapy (ECT) is an effective treatment for severe depression. Electroencephalogram (EEG) measures between ECT sessions seem to be related to the antidepressant efficacy of ECT. In this naturalistic cohort study, we examine longitudinal effects of ECT on interhemispheric EEG coherence measures during seizure activity and its relation to the antidepressant efficacy. Methods. This study included 65 patients diagnosed with severe depressive disorder. Depressive symptoms were rated according to the Montgomery-Åsberg Depression Rating Scale before and after the course of ECT. Frequency-specific ictal interhemispheric (fp1-fp2) EEG coherence measures were established during the first and each consecutive sixth treatment session. Linear mixed-effect models were used to determine longitudinal changes in ictal coherence measures during the course of ECT and its relation to treatment efficacy. Results. Ictal interhemispheric coherence in the theta and alpha frequency bands increased over the course of treatment, whereas no significant change was found for the delta and beta frequency bands. A main effect of treatment efficacy on the interhemispheric coherence in the delta and theta band was revealed. However, the longitudinal effects of ECT were not associated with treatment efficacy. Conclusion. The current study suggests that interhemispheric coherence during ECT-induced seizures increases over the course of treatment. Furthermore, these longitudinal effects seem to be unrelated to the antidepressant efficacy of ECT. These findings contribute to the understanding of the mechanism of action of ECT

The Longitudinal Effects of Electroconvulsive Therapy on Ictal Interhemispheric Coherence and Its Associations With Treatment Outcome:A Naturalistic Cohort Study

Objectives. Electroconvulsive therapy (ECT) is an effective treatment for severe depression. Electroencephalogram (EEG) measures between ECT sessions seem to be related to the antidepressant efficacy of ECT. In this naturalistic cohort study, we examine longitudinal effects of ECT on interhemispheric EEG coherence measures during seizure activity and its relation to the antidepressant efficacy. Methods. This study included 65 patients diagnosed with severe depressive disorder. Depressive symptoms were rated according to the Montgomery-Åsberg Depression Rating Scale before and after the course of ECT. Frequency-specific ictal interhemispheric (fp1-fp2) EEG coherence measures were established during the first and each consecutive sixth treatment session. Linear mixed-effect models were used to determine longitudinal changes in ictal coherence measures during the course of ECT and its relation to treatment efficacy. Results. Ictal interhemispheric coherence in the theta and alpha frequency bands increased over the course of treatment, whereas no significant change was found for the delta and beta frequency bands. A main effect of treatment efficacy on the interhemispheric coherence in the delta and theta band was revealed. However, the longitudinal effects of ECT were not associated with treatment efficacy. Conclusion. The current study suggests that interhemispheric coherence during ECT-induced seizures increases over the course of treatment. Furthermore, these longitudinal effects seem to be unrelated to the antidepressant efficacy of ECT. These findings contribute to the understanding of the mechanism of action of ECT