Electric field causes volumetric changes in the human brain

Electroconvulsive Therapy Modulates Loudness Dependence of Auditory Evoked Potentials: A Pilot MEG Study

Electroconvulsive therapy (ECT) remains a critical intervention for treatment-resistant depression (MDD), yet its neurobiological underpinnings are not fully understood. This pilot study utilizes high-resolution magnetoencephalography (MEG) in nine depressed patients receiving right unilateral ECT, to investigate the changes in loudness dependence of auditory evoked potentials (LDAEP), a proposed biomarker of serotonergic activity, following ECT. We hypothesized that ECT would reduce the LDAEP slope, reflecting enhanced serotonergic neurotransmission. Contrary to this, our findings indicated a significant increase in LDAEP post-ECT ( t 8 = 3.17, p = .013). The increase in LDAEP was not associated with changes in depression severity or cognitive performance, as assessed by the Hamilton Depression Rating Scale (HAMD-24) and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). We discussed potential mechanisms for the observed increase, including ECT's impact on serotonergic, dopaminergic, glutamatergic, and GABAergic receptor activity, neuroplasticity involving brain-derived neurotrophic factor (BDNF), and inflammation modulators such as TNF- alpha . Our results suggest a complex interaction between ECT and these neurobiological systems, rather than a direct reflection of serotonergic neurotransmission.

Exploring New Electroencephalogram Parameters in Electroconvulsive Therapy

OBJECTIVE

This pilot study aims to evaluate a novel metric based on the power spectrum of the EEG recordings from ECT-induced seizures-its association to volume changes in the hippocampus after ECT and improvement in depression rating scores.

METHODS

Depressed patients treated with ECT underwent brain magnetic resonance imaging before and after treatment and the EEG from each seizure was recorded (N = 29). Hippocampal volume changes and EEG parameters were recorded in addition to clinician-rated and self-reported measures of depressive symptoms. The slope of the power law in the power spectral density of the EEG was calculated. Multivariate linear models relating seizure parameters to volume change or clinical outcome were systematically and successively simplified. The best models were selected according to Akaike information criterion.

RESULTS

The slope of the power law was steeper in the right than the left hemisphere (P < 0.001). Electroencephalogram measures were included in the best models of volume change for both hippocampi as well as in the models explaining clinical outcome ( P = 0.014, P = 0.004).

CONCLUSIONS

In this pilot study, novel EEG measures were explored and contributed in models explaining the variation in volume change in the hippocampus and in clinical outcome after ECT.

Amplitude-determined seizure-threshold, electric field modeling, and electroconvulsive therapy antidepressant and cognitive outcomes

Electroconvulsive therapy (ECT) pulse amplitude, which dictates the induced electric field (E-field) magnitude in the brain, is presently fixed at 800 or 900 milliamperes (mA) without clinical or scientific rationale. We have previously demonstrated that increased E-field strength improves ECT's antidepressant effect but worsens cognitive outcomes. Amplitude-determined seizure titration may reduce the E-field variability relative to fixed amplitude ECT. In this investigation, we assessed the relationships among amplitude-determined seizure-threshold (STa), E-field magnitude, and clinical outcomes in older adults (age range 50 to 80 years) with depression. Subjects received brain imaging, depression assessment, and neuropsychological assessment pre-, mid-, and post-ECT. STa was determined during the first treatment with a Soterix Medical 4×1 High Definition ECT Multi-channel Stimulation Interface (Investigation Device Exemption: G200123). Subsequent treatments were completed with right unilateral electrode placement (RUL) and 800 mA. We calculated Ebrain defined as the 90th percentile of E-field magnitude in the whole brain for RUL electrode placement. Twenty-nine subjects were included in the final analyses. Ebrain per unit electrode current, Ebrain/I, was associated with STa. STa was associated with antidepressant outcomes at the mid-ECT assessment and bitemporal electrode placement switch. Ebrain/I was associated with changes in category fluency with a large effect size. The relationship between STa and Ebrain/I extends work from preclinical models and provides a validation step for ECT E-field modeling. ECT with individualized amplitude based on E-field modeling or STa has the potential to enhance neuroscience-based ECT parameter selection and improve clinical outcomes.

Effects of electroconvulsive therapy on cortical thickness in depression: a systematic review

OBJECTIVE

Electroconvulsive therapy (ECT) is one of the most studied and validated available treatments for severe or treatment-resistant depression. However, little is known about the neural mechanisms underlying ECT. This systematic review aims to critically review all structural magnetic resonance imaging studies investigating longitudinal cortical thickness (CT) changes after ECT in patients with unipolar or bipolar depression.

METHODS

We performed a search on PubMed, Medline, and Embase to identify all available studies published before April 20, 2023. A total of 10 studies were included.

RESULTS

The investigations showed widespread increases in CT after ECT in depressed patients, involving mainly the temporal, insular, and frontal regions. In five studies, CT increases in a non-overlapping set of brain areas correlated with the clinical efficacy of ECT. The small sample size, heterogeneity in terms of populations, comorbidities, and ECT protocols, and the lack of a control group in some investigations limit the generalisability of the results.

CONCLUSIONS

Our findings support the idea that ECT can increase CT in patients with unipolar and bipolar depression. It remains unclear whether these changes are related to the clinical response. Future larger studies with longer follow-up are warranted to thoroughly address the potential role of CT as a biomarker of clinical response after ECT.

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression

Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this causal depression network (CDN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis Principal Component Analysis (PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CDN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CDN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes (t = -2.35, p = 0.019). This evidence further supports that treatment interventions converge on a CDN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.

How electroconvulsive therapy works in the treatment of depression: is it the seizure, the electricity, or both?

We have known for nearly a century that triggering seizures can treat serious mental illness, but what we do not know is why. Electroconvulsive Therapy (ECT) works faster and better than conventional pharmacological interventions; however, those benefits come with a burden of side effects, most notably memory loss. Disentangling the mechanisms by which ECT exerts rapid therapeutic benefit from the mechanisms driving adverse effects could enable the development of the next generation of seizure therapies that lack the downside of ECT. The latest research suggests that this goal may be attainable because modifications of ECT technique have already yielded improvements in cognitive outcomes without sacrificing efficacy. These modifications involve changes in how the electricity is administered (both where in the brain, and how much), which in turn impacts the characteristics of the resulting seizure. What we do not completely understand is whether it is the changes in the applied electricity, or in the resulting seizure, or both, that are responsible for improved safety. Answering this question may be key to developing the next generation of seizure therapies that lack these adverse side effects, and ushering in novel interventions that are better, faster, and safer than ECT.

Structural Changes in Depressed Patients Directly After Treatment With Electroconvulsive Therapy and 3 Months Later

OBJECTIVES

It is assumed that neuroplasticity plays a central role in the effect of electroconvulsive therapy (ECT) on patients with major depressive disorder. We carried out an explorative study to map out the extent in which gray matter volume changes could be found directly after ECT treatment and after follow-up.

METHODS

Initially, 12 patients with treatment-resistant depression were recruited from the Radboud Medical Center. Magnetic resonance imaging scans were conducted at the following 3 time points: before ECT (n = 12), after ECT (n = 10), and at 3-month follow-up (n = 8). Subcortical volume, hippocampal subfield volume, and cortical thickness were analyzed using FreeSurfer.

RESULTS

The extensive, generalized changes in gray matter volume are largely transient after treatment with ECT, with the noted exceptions being a sustained increase in volume of the right amygdala and a part of the left cornu ammonis. Post hoc testing revealed no significant correlation with clinical response.

DISCUSSION

Our results suggest that the neuroplastic effects of ECT may not be mediators of clinical response and could be transient epiphenomena.

Transcranial magnetic stimulation mapping of the motor cortex: comparison of five estimation algorithms

Background

There are currently five different kinds of transcranial magnetic stimulation (TMS) motor mapping algorithms available, from ordinary point-based algorithms to advanced field-based algorithms. However, there have been only a limited number of comparison studies conducted, and they have not yet examined all of the currently available algorithms. This deficiency impedes the judicious selection of algorithms for application in both clinical and basic neuroscience, and hinders the potential promotion of a potential superior algorithm. Considering the influence of algorithm complexity, further investigation is needed to examine the differences between fMRI peaks and TMS cortical hotspots that were identified previously.

Methods

Twelve healthy participants underwent TMS motor mapping and a finger-tapping task during fMRI. The motor cortex TMS mapping results were estimated by five algorithms, and fMRI activation results were obtained. For each algorithm, the prediction error was defined as the distance between the measured scalp hotspot and optimized coil position, which was determined by the maximum electric field strength in the estimated motor cortex. Additionally, the study identified the minimum number of stimuli required for stable mapping. Finally, the location difference between the TMS mapping cortical hotspot and the fMRI activation peak was analyzed.

Results

The projection yielded the lowest prediction error (5.27 ± 4.24 mm) among the point-based algorithms and the association algorithm yielded the lowest (6.66 ± 3.48 mm) among field-based estimation algorithms. The projection algorithm required fewer stimuli, possibly resulting from its suitability for the grid-based mapping data collection method. The TMS cortical hotspots from all algorithms consistently deviated from the fMRI activation peak (20.52 ± 8.46 mm for five algorithms).

Conclusion

The association algorithm might be a superior choice for clinical applications and basic neuroscience research, due to its lower prediction error and higher estimation sensitivity in the deep cortical structure, especially for the sulcus. It also has potential applicability in various other TMS domains, including language area mapping and more. Otherwise, our results provide further evidence that TMS motor mapping intrinsically differs from fMRI motor mapping.

What Can We Tell About the Effect of Electroconvulsive Therapy on the Human Hippocampus?

Electroconvulsive therapy (ECT) is the most effective antidepressant treatment, although its mechanisms of action remain unclear. Since 2010, several structural magnetic resonance imaging studies based on a neuroplastic hypothesis have consistently reported increases in the hippocampal volume following ECT. Moreover, volume increases in the human dentate gyrus, where neurogenesis occurs, have also been reported. These results are in line with the preclinical findings of ECT-induced neuroplastic changes, including neurogenesis, gliogenesis, synaptogenesis, and angiogenesis, in rodents and nonhuman primates. Despite this robust evidence of an effect of ECT on hippocampal plasticity, the clinical relevance of these human hippocampal changes continues to be questioned. This narrative review summarizes recent findings regarding ECT-induced hippocampal volume changes. Furthermore, this review also discusses methodological considerations and future directions in this field.

Neurobiological mechanisms of ECT and TMS treatment in depression: study protocol of a multimodal magnetic resonance investigation

BACKGROUND

Noninvasive neurostimulation treatments are increasingly being used to treat major depression, which is a common cause of disability worldwide. While electroconvulsive therapy (ECT) and transcranial magnetic stimulation (TMS) are both effective in treating depressive episodes, their mechanisms of action are, however, not completely understood. ECT is given under general anesthesia, where an electrical pulse is administered through electrodes placed on the patient's head to trigger a seizure. ECT is used for the most severe cases of depression and is usually not prescribed before other options have failed. With TMS, brain stimulation is achieved through rapidly changing magnetic fields that induce electric currents underneath a ferromagnetic coil. Its efficacy in depressive episodes has been well documented. This project aims to identify the neurobiological underpinnings of both the effects and side effects of the neurostimulation techniques ECT and TMS.

METHODS

The study will utilize a pre-post case control longitudinal design. The sample will consist of 150 subjects: 100 patients (bipolar and major depressive disorder) who are treated with either ECT (N = 50) or TMS (N = 50) and matched healthy controls (N = 50) not receiving any treatment. All participants will undergo multimodal magnetic resonance imaging (MRI) as well as neuropsychological and clinical assessments at multiple time points before, during and after treatment. Arterial spin labeling MRI at baseline will be used to test whether brain perfusion can predict outcomes. Signs of brain disruption, potentiation and rewiring will be explored with resting-state functional MRI, magnetic resonance spectroscopy and multishell diffusion weighted imaging (DWI). Clinical outcome will be measured by clinician assessed and patient reported outcome measures. Memory-related side effects will be investigated, and specific tests of spatial navigation to test hippocampal function will be administered both before and after treatment. Blood samples will be stored in a biobank for future analyses. The observation time is 6 months. Data will be explored in light of the recently proposed disrupt, potentiate and rewire (DPR) hypothesis.

DISCUSSION

The study will contribute data and novel analyses important for our understanding of neurostimulation as well as for the development of enhanced and more personalized treatment.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05135897.

The Fifth Bioelectronic Medicine Summit: today's tools, tomorrow's therapies

The emerging field of bioelectronic medicine (BEM) is poised to make a significant impact on the treatment of several neurological and inflammatory disorders. With several BEM therapies being recently approved for clinical use and others in late-phase clinical trials, the 2022 BEM summit was a timely scientific meeting convening a wide range of experts to discuss the latest developments in the field. The BEM Summit was held over two days in New York with more than thirty-five invited speakers and panelists comprised of researchers and experts from both academia and industry. The goal of the meeting was to bring international leaders together to discuss advances and cultivate collaborations in this emerging field that incorporates aspects of neuroscience, physiology, molecular medicine, engineering, and technology. This Meeting Report recaps the latest findings discussed at the Meeting and summarizes the main developments in this rapidly advancing interdisciplinary field. Our hope is that this Meeting Report will encourage researchers from academia and industry to push the field forward and generate new multidisciplinary collaborations that will form the basis of new discoveries that we can discuss at the next BEM Summit.

Baseline levels of miR-223-3p correlate with the effectiveness of electroconvulsive therapy in patients with major depression

There is a strong medical need to develop suitable biomarkers to improve the diagnosis and treatment of depression, particularly in predicting response to certain therapeutic approaches such as electroconvulsive therapy (ECT). MicroRNAs are small non-coding RNAs that have the ability to influence the transcriptome as well as proteostasis at the systems level. Here, we investigate the role of circulating microRNAs in depression and response prediction towards ECT. Of the 64 patients with treatment-resistant major depression (MDD) who received ECT treatment, 62.5% showed a response, defined as a reduction of ≥50% in the MADRS total score from baseline. We performed smallRNA sequencing in blood samples that were taken before the first ECT, after the first and the last ECT. The microRNAome was compared between responders and non-responders. Co-expression network analysis identified three significant microRNA modules with reverse correlation between ECT- responders and non-responders, that were amongst other biological processes linked to inflammation. A candidate microRNA, namely miR-223-3p was down-regulated in ECT responders when compared to non-responders at baseline. In line with data suggesting a role of miR-223-3p in inflammatory processes we observed higher expression levels of proinflammatory factors Il-6, Il-1b, Nlrp3 and Tnf-α in ECT responders at baseline when compared to non-responders. ROC analysis of confirmed the diagnostic power of miR-223-3p demarcating ECT-responders from non-responder subjects (AUC = 0.76, p = 0.0031). Our data suggest that miR-223-3p expression and related cytokine levels could serve as predictors of response to ECT in individuals with treatment-resistant depressive disorders.

Electric Field, Ictal Theta Power, and Clinical Outcomes in Electroconvulsive Therapy

BACKGROUND

Electroconvulsive therapy (ECT) is efficacious for treatment-resistant depression. Treatment-induced cognitive impairment can adversely impact functional outcomes. Our pilot study linked the electric field to ictal theta power from a single suprathreshold treatment and linked ictal theta power to changes in phonemic fluency. In this study, we set out to replicate our findings and expand upon the utility of ictal theta power as a potential cognitive biomarker.

METHODS

Twenty-seven participants (18 female and 9 male) received right unilateral ECT for treatment-resistant depression. Pre-ECT magnetic resonance imaging and finite element modeling determined the 90th percentile maximum electric field in the brain. Two-lead electroencephalographs were digitally captured across the ECT course, with the earliest suprathreshold treatment used to determine power spectral density. Clinical and cognitive outcomes were assessed pre-, mid-, and post-ECT. We assessed the relationship between the electric field in the brain, ictal theta power, clinical outcome (Inventory of Depressive Symptomatology), and cognitive outcomes (phonemic and semantic fluency) with linear models.

RESULTS

Ictal theta power in the Fp1 and Fp2 channels was associated with the electric field, antidepressant outcome, and phonemic and semantic fluency. The relationship between ictal theta power and phonemic fluency was strengthened in the longitudinal analysis. The electric field in the brain was directly associated with phonemic and semantic fluency but not with antidepressant outcome.

CONCLUSIONS

Ictal theta power is a potential cognitive biomarker early on in the ECT course to help guide parameter changes. Larger studies are needed to further assess ictal theta power's role in predicting mood outcome and changes with ECT parameters.

Electroconvulsive therapy triggers a reversible decrease in brain N-acetylaspartate

Introduction

Based on previous research on electroconvulsive therapy (ECT) we have proposed a model where disruption, potentiation, and rewiring of brain networks occur in sequence and serve as the underlying therapeutic mechanism of ECT. This model implies that a temporary disturbance of neuronal networks (disruption) is followed by a trophic effect (potentiation), which enables the rewiring of neuronal circuits to a more euthymic functioning brain. We hypothesized that disruption of neuronal networks could trigger biochemical alterations leading to a temporary decrease in N-acetylaspartate (tNAA, considered a marker of neuronal integrity), while choline (a membrane component), myo-Inositol (mI, astroglia marker), and glutamate/glutamine (Glx, excitatory neurotransmitter) were postulated to increase. Previous magnetic resonance spectroscopy studies, reporting diverse findings, have used two different referencing methods - creatine ratios and tissue corrected values referenced to water - for the quantification of brain metabolites. Changes in creatine during ECT have also been reported, which may confound estimates adopting this as an internal reference.

Methods

Using MR spectroscopy, we investigated 31 moderately to severely depressed patients and 19 healthy controls before, during, and after ECT or at similar time points (for controls). We tested whether biochemical alterations in tNAA, choline, mI, and Glx lend support to the disrupt, potentiate, and rewire hypothesis. We used both creatine ratios and water-scaled values for the quantification of brain metabolites to validate the results across referencing methods.

Results

Levels of tNAA in the anterior cingulate cortex decreased after an ECT treatment series (average 10.6 sessions) by 6% (p = 0.007, creatine ratio) and 3% (p = 0.02, water referenced) but returned to baseline 6 months after ECT. Compared to after treatment series tNAA levels at 6-month follow-up had increased in both creatine ratio (+6%, p < 0.001) and water referenced data (+7%, p < 0.001). Findings for other brain metabolites varied and could not be validated across referencing methods.

Discussion

Our findings suggest that prior research must be interpreted with care, as several referencing and processing methods have been used in the past. Yet, the results for tNAA were robust across quantification methods and concur with relevant parts of the disrupt, potentiate, and rewire model.

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression

Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this common causal network (CCN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis (Principal Component Analysis, PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CCN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CCN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes. This evidence further supports that treatment interventions converge on a CCN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.

Impact of modeled field of view in electroconvulsive therapy current flow simulations

Background

The field of view (FOV) considered in MRI-guided forward models of electroconvulsive therapy (ECT) are, as expected, limited to the MRI volume collected. Therefore, there is variation in model extent considered across simulation efforts. This study examines the impact of FOV on the induced electric field (E-field) due to two common electrode placements: right unilateral (RUL) and bilateral (BL).

Methods

A full-body dataset was obtained and processed for modeling relevant to ECT physics. Multiple extents were derived by truncating from the head down to four levels: upper head (whole-brain), full head, neck, and torso. All relevant stimulation and focality metrics were determined. The differences in the 99th percentile peak of stimulation strength in the brain between each extent to the full-body (reference) model were considered as the relative error (RE). We also determine the FOV beyond which the difference to a full-body model would be negligible.

Results

The 2D and 3D spatial plots revealed anticipated results in line with prior efforts. The RE for BL upper head was ~50% reducing to ~2% for the neck FOV. The RE for RUL upper head was ~5% reducing to subpercentage (0.28%) for the full-head FOV. As shown previously, BL was found to stimulate a larger brain volume-but restricted to the upper head and for amplitude up to ~480 mA. To some extent, RUL stimulated a larger volume. The RUL-induced volume was larger even when considering the neural activation threshold corresponding to brief pulse BL if ECT amplitude was >270 mA. This finding is explained by the BL-induced current loss through the inferior regions as more FOV is considered. Our result is a departure from prior efforts and raises questions about the focality metric as defined and/or inter-individual differences.

Conclusion

Our findings highlight that BL is impacted more than RUL with respect to FOV. It is imperative to collect full-head data at a minimum for any BL simulation and possibly more. Clinical practice resorts to using BL ECT when RUL is unsuccessful. However, the notion that BL is more efficacious on the premise of stimulating more brain volume needs to be revisited.

Commonalities and differences in ECT-induced gray matter volume change between depression and schizophrenia

BACKGROUND

Electroconvulsive therapy (ECT) is one of the most effective treatments for depression and schizophrenia, particularly in urgent or treatment-resistant cases. After ECT, regional gray matter volume (GMV) increases have been repeatedly reported both in depression and schizophrenia. However, the interpretation of these findings remains entangled because GMV changes do not necessarily correlate with treatment effects and may be influenced by the intervention itself. We hypothesized that the comparison of longitudinal magnetic resonance imaging data between the two diagnostic groups will provide clues to distinguish diagnosis-specific and transdiagnostic changes.

METHOD

Twenty-nine Japanese participants, including 18 inpatients with major depressive disorder and 11 with schizophrenia, underwent longitudinal voxel-based morphometry before and after ECT. We investigated GMV changes common to both diagnostic groups and those specific to each group. Moreover, we also evaluated potential associations between GMV changes and clinical improvement for each group.

RESULTS

In both diagnostic groups, GMV increased in widespread areas after ECT, sharing common regions including: anterior temporal cortex; medial frontal and anterior cingulate cortex; insula; and caudate nucleus. In addition, we found a schizophrenia-specific GMV increase in a region including the left pregenual anterior cingulate cortex, with volume increase significantly correlating with clinical improvement.

CONCLUSIONS

Transdiagnostic volume changes may represent the effects of the intervention itself and pathophysiological changes common to both groups. Conversely, diagnosis-specific volume changes are associated with treatment effects and may represent pathophysiology-specific impacts of ECT.

Electroconvulsive Therapy: Mechanisms of Action, Clinical Considerations, and Future Directions

LEARNING OBJECTIVES

• Outline and discuss the fundamental physiologic, cellular, and molecular mechanisms of ECT to devise strategies to optimize therapeutic outcomes• Summarize the overview of ECT, its efficacy in treating depression, the known effects on cognition, evidence of mechanisms, and future directions.

ABSTRACT

Electroconvulsive therapy (ECT) is the most effective treatment for a variety of psychiatric illnesses, including treatment-resistant depression, bipolar depression, mania, catatonia, and clozapine-resistant schizophrenia. ECT is a medical and psychiatric procedure whereby electrical current is delivered to the brain under general anesthesia to induce a generalized seizure. ECT has evolved a great deal since the 1930s. Though it has been optimized for safety and to reduce adverse effects on cognition, issues persist. There is a need to understand fundamental physiologic, cellular, and molecular mechanisms of ECT to devise strategies to optimize therapeutic outcomes. Clinical trials that set out to adjust parameters, electrode placement, adjunctive medications, and patient selection are critical steps towards the goal of improving outcomes with ECT. This narrative review provides an overview of ECT, its efficacy in treating depression, its known effects on cognition, evidence of its mechanisms, and future directions.

Clinical Improvement in Depression and Cognitive Deficit Following Electroconvulsive Therapy

Electroconvulsive therapy (ECT) is a long-standing treatment choice for disorders such as depression when pharmacological treatments have failed. However, a major drawback of ECT is its cognitive side effects. While numerous studies have investigated the therapeutic effects of ECT and its mechanism, much less research has been conducted regarding the mechanism behind the cognitive side effects of ECT. As both clinical remission and cognitive deficits occur after ECT, it is possible that both may share a common mechanism. This review highlights studies related to ECT as well as those investigating the mechanism of its outcomes. The process underlying these effects may lie within BDNF and NMDA signaling. Edema in the astrocytes may also be responsible for the adverse cognitive effects and is mediated by metabotropic glutamate receptor 5 and the protein Homer1a.

Cerebro-cerebellar functional neuroplasticity mediates the effect of electric field on electroconvulsive therapy outcomes

Electroconvulsive therapy (ECT) is the most effective treatment for severe depression and works by applying an electric current through the brain. The applied current generates an electric field (E-field) and seizure activity, changing the brain's functional organization. The E-field, which is determined by electrode placement (right unilateral or bitemporal) and pulse amplitude (600, 700, or 800 milliamperes), is associated with the ECT response. However, the neural mechanisms underlying the relationship between E-field, functional brain changes, and clinical outcomes of ECT are not well understood. Here, we investigated the relationships between whole-brain E-field (Ebrain, the 90th percentile of E-field magnitude in the brain), cerebro-cerebellar functional network connectivity (FNC), and clinical outcomes (cognitive performance and depression severity). A fully automated independent component analysis framework determined the FNC between the cerebro-cerebellar networks. We found a linear relationship between Ebrain and cognitive outcomes. The mediation analysis showed that the cerebellum to middle occipital gyrus (MOG)/posterior cingulate cortex (PCC) FNC mediated the effects of Ebrain on cognitive performance. In addition, there is a mediation effect through the cerebellum to parietal lobule FNC between Ebrain and antidepressant outcomes. The pair-wise t-tests further demonstrated that a larger Ebrain was associated with increased FNC between cerebellum and MOG and decreased FNC between cerebellum and PCC, which were linked with decreased cognitive performance. This study implies that an optimal E-field balancing the antidepressant and cognitive outcomes should be considered in relation to cerebro-cerebellar functional neuroplasticity.

Predictive signature of static and dynamic functional connectivity for ECT clinical outcomes

Introduction: Electroconvulsive therapy (ECT) remains one of the most effective approaches for treatment-resistant depressive episodes, despite the potential cognitive impairment associated with this treatment. As a potent stimulator of neuroplasticity, ECT might normalize aberrant depression-related brain function via the brain's reconstruction by forming new neural connections. Multiple lines of evidence have demonstrated that functional connectivity (FC) changes are reliable indicators of antidepressant efficacy and cognitive changes from static and dynamic perspectives. However, no previous studies have directly ascertained whether and how different aspects of FC provide complementary information in terms of neuroimaging-based prediction of clinical outcomes. Methods: In this study, we implemented a fully automated independent component analysis framework to an ECT dataset with subjects (n = 50, age = 65.54 ± 8.92) randomized to three treatment amplitudes (600, 700, or 800 milliamperes [mA]). We extracted the static functional network connectivity (sFNC) and dynamic FNC (dFNC) features and employed a partial least square regression to build predictive models for antidepressant outcomes and cognitive changes. Results: We found that both antidepressant outcomes and memory changes can be robustly predicted by the changes in sFNC (permutation test p < 5.0 × 10^-3). More interestingly, by adding dFNC information, the model achieved higher accuracy for predicting changes in the Hamilton Depression Rating Scale 24-item (HDRS₂₄, t = 9.6434, p = 1.5 × 10^-21). The predictive maps of clinical outcomes show a weakly negative correlation, indicating that the ECT-induced antidepressant outcomes and cognitive changes might be associated with different functional brain neuroplasticity. Discussion: The overall results reveal that dynamic FC is not redundant but reflects mechanisms of ECT that cannot be captured by its static counterpart, especially for the prediction of antidepressant efficacy. Tracking the predictive signatures of static and dynamic FC will help maximize antidepressant outcomes and cognitive safety with individualized ECT dosing.

Links between electroconvulsive therapy responsive and cognitive impairment multimodal brain networks in late-life major depressive disorder

BACKGROUND

Although electroconvulsive therapy (ECT) is an effective treatment for depression, ECT cognitive impairment remains a major concern. The neurobiological underpinnings and mechanisms underlying ECT antidepressant and cognitive impairment effects remain unknown. This investigation aims to identify ECT antidepressant-response and cognitive-impairment multimodal brain networks and assesses whether they are associated with the ECT-induced electric field (E-field) with an optimal pulse amplitude estimation.

METHODS

A single site clinical trial focused on amplitude (600, 700, and 800 mA) included longitudinal multimodal imaging and clinical and cognitive assessments completed before and immediately after the ECT series (n = 54) for late-life depression. Another two independent validation cohorts (n = 84, n = 260) were included. Symptom and cognition were used as references to supervise fMRI and sMRI fusion to identify ECT antidepressant-response and cognitive-impairment multimodal brain networks. Correlations between ECT-induced E-field within these two networks and clinical and cognitive outcomes were calculated. An optimal pulse amplitude was estimated based on E-field within antidepressant-response and cognitive-impairment networks.

RESULTS

Decreased function in the superior orbitofrontal cortex and caudate accompanied with increased volume in medial temporal cortex showed covarying functional and structural alterations in both antidepressant-response and cognitive-impairment networks. Volume increases in the hippocampal complex and thalamus were antidepressant-response specific, and functional decreases in the amygdala and hippocampal complex were cognitive-impairment specific, which were validated in two independent datasets. The E-field within these two networks showed an inverse relationship with HDRS reduction and cognitive impairment. The optimal E-filed range as [92.7-113.9] V/m was estimated to maximize antidepressant outcomes without compromising cognitive safety.

CONCLUSIONS

The large degree of overlap between antidepressant-response and cognitive-impairment networks challenges parameter development focused on precise E-field dosing with new electrode placements. The determination of the optimal individualized ECT amplitude within the antidepressant and cognitive networks may improve the treatment benefit-risk ratio.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02999269.

Neurocapillary-Modulation

OBJECTIVES

We consider two consequences of brain capillary ultrastructure in neuromodulation. First, blood-brain barrier (BBB) polarization as a consequence of current crossing between interstitial space and the blood. Second, interstitial current flow distortion around capillaries impacting neuronal stimulation.

MATERIALS AND METHODS

We developed computational models of BBB ultrastructure morphologies to first assess electric field amplification at the BBB (principle 1) and neuron polarization amplification by the presence of capillaries (principle 2). We adapt neuron cable theory to develop an analytical solution for maximum BBB polarization sensitivity.

RESULTS

Electrical current crosses between the brain parenchyma (interstitial space) and capillaries, producing BBB electric fields (EBBB) that are >400x of the average parenchyma electric field (ĒBRAIN), which in turn modulates transport across the BBB. Specifically, for a BBB space constant (λBBB) and wall thickness (dth-BBB), the analytical solution for maximal BBB electric field (EABBB) is given as: (ĒBRAIN × λBBB)/dth-BBB. Electrical current in the brain parenchyma is distorted around brain capillaries, amplifying neuronal polarization. Specifically, capillary ultrastructure produces ∼50% modulation of the ĒBRAIN over the ∼40 μm inter-capillary distance. The divergence of EBRAIN (Activating function) is thus ∼100 kV/m2 per unit ĒBRAIN.

CONCLUSIONS

BBB stimulation by principle 1 suggests novel therapeutic strategies such as boosting metabolic capacity or interstitial fluid clearance. Whereas the spatial profile of EBRAIN is traditionally assumed to depend only on macroscopic anatomy, principle 2 suggests a central role for local capillary ultrastructure-which impact forms of neuromodulation including deep brain stimulation (DBS), spinal cord stimulation (SCS), transcranial magnetic stimulation (TMS), electroconvulsive therapy (ECT), and transcranial electrical stimulation (tES)/transcranial direct current stimulation (tDCS).

Cerebral perfusion is related to antidepressant effect and cognitive side effects of Electroconvulsive Therapy

BACKGROUND

The mechanisms underlying the antidepressant effect and cognitive side effects of Electroconvulsive Therapy (ECT) remain elusive. The measurement of cerebral perfusion provides an insight into brain physiology.

OBJECTIVE

We investigated ECT-related perfusion changes in depressed patients and tested whether these changes correlate with clinical effects.

METHODS

A sample of 22 in-patients was examined at three time points: 1) within two days before, 2) within one week after, and 3) six months after an ECT series. Cerebral perfusion was quantified using arterial spin labeling magnetic resonance imaging. The primary regions of interest were the bilateral dorsolateral prefrontal cortices (DL-PFC) and hippocampi. The depression severity was assessed by the six-item Hamilton Depression Rating Scale, and cognitive performance by the Screen for Cognitive Impairment in Psychiatry. A linear mixed model and partial correlation were used for statistical analyses.

RESULTS

Following an ECT series, perfusion decreased in the right (-6.0%, p = .01) and left DL-PFC (-5.6%, p = .001). Perfusion increased in the left hippocampus (4.8%, p = .03), while on the right side the increase was insignificant (2.3%, p = .23). A larger perfusion reduction in the right DL-PFC correlated with a better antidepressant effect, and a larger perfusion increase in the right hippocampus with worse cognitive impairment.

CONCLUSION

ECT-induced attenuation of prefrontal activity may be related to clinical improvement, whereas a hippocampal process triggered by the treatment is likely associated with cognitive side effects.

Fronto-medial electrode placement for electroconvulsive treatment of depression

Electroconvulsive therapy (ECT) is the most effective treatment for severe treatment-resistant depression but concern about cognitive side-effects, particularly memory loss, limits its use. Recent observational studies on large groups of patients who have received ECT report that cognitive side-effects were associated with electric field (EF) induced increases in hippocampal volume, whereas therapeutic efficacy was associated with EF induced increases in sagittal brain structures. The aim in the present study was to determine whether a novel fronto-medial (FM) ECT electrode placement would minimize electric fields in bilateral hippocampi (HIP) whilst maximizing electric fields in dorsal sagittal cortical regions. An anatomically detailed computational head model was used with finite element analysis, to calculate ECT-induced electric fields in specific brain regions identified by translational neuroimaging studies of treatment-resistant depressive illness, for a range of electrode placements. As hypothesized, compared to traditional bitemporal (BT) electrode placement, a specific FM electrode placement reduced bilateral hippocampal electric fields two-to-three-fold, whilst the electric fields in the dorsal anterior cingulate (dAC) were increased by approximately the same amount. We highlight the clinical relevance of this specific FM electrode placement for ECT, which may significantly reduce cognitive and non-cognitive side-effects and suggest a clinical trial is indicated.

Parsing the Network Mechanisms of Electroconvulsive Therapy

Electroconvulsive therapy (ECT) is one of the oldest and most effective forms of neurostimulation, wherein electrical current is used to elicit brief, generalized seizures under general anesthesia. When electrodes are positioned to target frontotemporal cortex, ECT is arguably the most effective treatment for severe major depression, with response rates and times superior to other available antidepressant therapies. Neuroimaging research has been pivotal in improving the field's mechanistic understanding of ECT, with a growing number of magnetic resonance imaging studies demonstrating hippocampal plasticity after ECT, in line with evidence of upregulated neurotrophic processes in the hippocampus in animal models. However, the precise roles of the hippocampus and other brain regions in antidepressant response to ECT remain unclear. Seizure physiology may also play a role in antidepressant response to ECT, as indicated by early positron emission tomography, single-photon emission computed tomography, and electroencephalography research and corroborated by recent magnetic resonance imaging studies. In this review, we discuss the evidence supporting neuroplasticity in the hippocampus and other brain regions during and after ECT, and their associations with antidepressant response. We also offer a mechanistic, circuit-level model that proposes that core mechanisms of antidepressant response to ECT involve thalamocortical and cerebellar networks that are active during seizure generalization and termination over repeated ECT sessions, and their interactions with corticolimbic circuits that are dysfunctional prior to treatment and targeted with the electrical stimulus.

Applications of open-source software ROAST in clinical studies: A review

Background:

Transcranial electrical stimulation (TES) is broadly investigated as a therapeutic technique for a wide range of neurological disorders. The electric fields induced by TES in the brain can be estimated by computational models. A realistic and volumetric approach to simulate TES (ROAST) has been recently released as an open-source software package and has been widely used in TES research and its clinical applications. Rigor and reproducibility of TES studies have recently become a concern, especially in the context of computational modeling.

Methods:

Here we reviewed 94 clinical TES studies that leveraged ROAST for computational modeling. When reviewing each study, we pay attention to details related to the rigor and reproducibility as defined by the locations of stimulation electrodes and the dose of stimulating current. Specifically, we compared across studies the electrode montages, stimulated brain areas, achieved electric field strength, and the relations between modeled electric field and clinical outcomes.

Results:

We found that over 1800 individual heads have been modeled by ROAST for more than 30 different clinical applications. Similar electric field intensities were found to be reproducible by ROAST across different studies at the same brain area under same or similar stimulation montages.

Conclusion:

This article reviews the use cases of ROAST and provides an overview of how ROAST has been leveraged to enhance the rigor and reproducibility of TES research and its applications.

Improved Safety of Hybrid Electroconvulsive Therapy Compared With Standard Electroconvulsive Therapy in Patients With Major Depressive Disorder: A Randomized, Double-Blind, Parallel-Group Pilot Trial

Objectives

ECT is a rapid and effective treatment for depression. While efficacy is often remarkable over the initial 3-4 sessions, the efficacy of later sessions is less rapid, and the side-effects, especially cognitive impairment limit its use. To preliminarily compare the efficacy and acceptability of a novel hybrid-ECT (HECT) protocol for patients with major depressive disorder (MDD) with standard ECT, we conducted this pilot trial.

Methods

Thirty patients were randomly assigned to ECT or HECT. Both arms received three ECT sessions (phase 1) but, in phase 2, the HECT arm received low-charge electrotherapy instead of ECT. The primary outcome was the change in 24-item Hamilton depression rating scale (HAMD-24) scores between baseline and the end of treatment. Cognitive function was assessed by repeatable battery for the assessment of neuropsychological status (RBANS), Stroop color word, and orientation recovery tests (ORT). Safety was measured by the drop-out rate and adverse events (AEs). Four visits were conducted at baseline, post-phase 1, post-phase 2, and at 1-month follow-up. Trial registration: Chinese Clinical Trial Registry (http://www.chictr.org.cn/), identifier: ChiCTR1900027701.

Results

Patients in both arms showed significant within-group improvements in HAMD-24, but the between-group differences were non-significant. Participants in the HECT arm outperformed ECT patients for most cognitive tests at the end of treatment or at follow-up. There was a significantly lower AE rate and shorter ORT in phase 2 of the HECT ar.

Conclusion

In this pilot trial, HECT was associated with fewer AEs and better cognitive function including executive and memory function, but its possible similar antidepressive efficacy needs to be further investigated in future.

The Neurobiological Effects of Electroconvulsive Therapy Studied Through Magnetic Resonance: What Have We Learned, and Where Do We Go?

Electroconvulsive therapy (ECT) is an established treatment choice for severe, treatment-resistant depression, yet its mechanisms of action remain elusive. Magnetic resonance imaging (MRI) of the human brain before and after treatment has been crucial to aid our comprehension of the ECT neurobiological effects. However, to date, a majority of MRI studies have been underpowered and have used heterogeneous patient samples as well as different methodological approaches, altogether causing mixed results and poor clinical translation. Hence, an association between MRI markers and therapeutic response remains to be established. Recently, the availability of large datasets through a global collaboration has provided the statistical power needed to characterize whole-brain structural and functional brain changes after ECT. In addition, MRI technological developments allow new aspects of brain function and structure to be investigated. Finally, more recent studies have also investigated immediate and long-term effects of ECT, which may aid in the separation of the therapeutically relevant effects from epiphenomena. The goal of this review is to outline MRI studies (T1, diffusion-weighted imaging, proton magnetic resonance spectroscopy) of ECT in depression to advance our understanding of the ECT neurobiological effects. Based on the reviewed literature, we suggest a model whereby the neurobiological effects can be understood within a framework of disruption, neuroplasticity, and rewiring of neural circuits. An improved characterization of the neurobiological effects of ECT may increase our understanding of ECT's therapeutic effects, ultimately leading to improved patient care.

Electroconvulsive therapy, electric field, neuroplasticity, and clinical outcomes

Electroconvulsive therapy (ECT) remains the gold-standard treatment for patients with depressive episodes, but the underlying mechanisms for antidepressant response and procedure-induced cognitive side effects have yet to be elucidated. Such mechanisms may be complex and involve certain ECT parameters and brain regions. Regarding parameters, the electrode placement (right unilateral or bitemporal) determines the geometric shape of the electric field (E-field), and amplitude determines the E-field magnitude in select brain regions (e.g., hippocampus). Here, we aim to determine the relationships between hippocampal E-field strength, hippocampal neuroplasticity, and antidepressant and cognitive outcomes. We used hippocampal E-fields and volumes generated from a randomized clinical trial that compared right unilateral electrode placement with different pulse amplitudes (600, 700, and 800 mA). Hippocampal E-field strength was variable but increased with each amplitude arm. We demonstrated a linear relationship between right hippocampal E-field and right hippocampal neuroplasticity. Right hippocampal neuroplasticity mediated right hippocampal E-field and antidepressant outcomes. In contrast, right hippocampal E-field was directly related to cognitive outcomes as measured by phonemic fluency. We used receiver operating characteristic curves to determine that the maximal right hippocampal E-field associated with cognitive safety was 112.5 V/m. Right hippocampal E-field strength was related to the whole-brain ratio of E-field strength per unit of stimulation current, but this whole-brain ratio was unrelated to antidepressant or cognitive outcomes. We discuss the implications of optimal hippocampal E-field dosing to maximize antidepressant outcomes and cognitive safety with individualized amplitudes.

High-resolution computational modeling of the current flow in the outer ear during transcutaneous auricular Vagus Nerve Stimulation (taVNS)

BACKGROUND

Transcutaneous auricular Vagus Nerve Stimulation (taVNS) applies low-intensity electrical current to the ear with the intention of activating the auricular branch of the Vagus nerve. The sensitivity and selectivity of stimulation applied to the ear depends on current flow pattern produced by a given electrode montage (size and placement).

OBJECTIVE

We compare different electrodes designs for taVNS considering both the predicted peak electric fields (sensitivity) and their spatial distribution (selectivity).

METHODS

Based on optimized high-resolution (0.47 mm) T1 and T2 weighted MRI, we developed an anatomical model of the left ear and the surrounding head tissues including brain, CSF/meninges, skull, muscle, blood vessels, fat, cartilage, and skin. The ear was further segmented into 6 regions of interest (ROI) based on various nerve densities: cavum concha, cymba concha, crus of helix, tragus, antitragus, and earlobe. A range of taVNS electrode montages were reproduced spanning varied electrodes sizes and placements over the tragus, cymba concha, earlobe, cavum concha, and crus of helix. Electric field across the ear (from superficial skin to cartilage) for each montage at 1 mA or 2 mA taVNS, assuming an activation threshold of 6.15 V/m, 12.3 V/m or 24.6 V/m was predicted using a Finite element method (FEM). Finally, considering every ROI, we calculated the sensitivity and selectivity of each montage.

RESULTS

Current flow patterns through the ear were highly specific to the electrode montage. Electric field was maximal at the ear regions directly under the electrodes, and for a given total current, increases with decreasing electrode size. Depending on the applied current and nerves threshold, activation may also occur in the regions between multiple anterior surface electrodes. Each considered montage was selective for one or two regions of interest. For example, electrodes across the tragus restricted significant electric field to the tragus. Stimulation across the earlobe restricted significant electric field to the earlobe and the antitragus. Because of this relative selectivity, use of control ear montages in experimental studies, support testing of targeting. Relative targeting was robust across assumptions of activation threshold and tissue properties.

DISCUSSION

Computational models provide additional insight on how details in electrode shape and placement impact sensitivity (how much current is needed) and selectivity (spatial distribution), thereby supporting analysis of existing approaches and optimization of new devices. Our result suggest taVNS current patterns and relative target are robust across individuals, though (variance in) axon morphology was not represented.

ECT-induced cognitive side effects are associated with hippocampal enlargement

Electroconvulsive therapy (ECT) is of the most effective treatments available for treatment-resistant depression, yet it is underutilized in part due to its reputation of causing cognitive side effects in a significant number of patients. Despite intensive neuroimaging research on ECT in the past two decades, the underlying neurobiological correlates of cognitive side effects remain elusive. Because the primary ECT-related cognitive deficit is memory impairment, it has been suggested that the hippocampus may play a crucial role. In the current study, we investigated 29 subjects with longitudinal MRI and detailed neuropsychological testing in two independent cohorts (N = 15/14) to test if volume changes were associated with cognitive side effects. The two cohorts underwent somewhat different ECT study protocols reflected in electrode placements and the number of treatments. We used longitudinal freesurfer algorithms (6.0) to obtain a bias-free estimate of volume changes in the hippocampus and tested its relationship with neurocognitive score changes. As an exploratory analysis and to evaluate how specific the effects were to the hippocampus, we also calculated this relationship in 41 other areas. In addition, we also analyzed cognitive data from a group of healthy volunteers (N = 29) to assess practice effects. Our results supported the hypothesis that hippocampus enlargement was associated with worse cognitive outcomes, and this result was generalizable across two independent cohorts with different diagnoses, different electrode placements, and a different number of ECT sessions. We found, in both cohorts, that treatment robustly increased the volume size of the hippocampus (Cohort 1: t = 5.07, Cohort 2: t = 4.82; p < 0.001), and the volume increase correlated with the neurocognitive T-score change. (Cohort 1: r = -0.68, p = 0.005; Cohort 2: r = -0.58; p = 0.04). Overall, our research indicates that novel treatment methods serving to avoid hippocampal volume increase may result in a better side effect profile.

Neural Substrates of Psychotic Depression: Findings From the Global ECT-MRI Research Collaboration

Psychotic major depression (PMD) is hypothesized to be a distinct clinical entity from nonpsychotic major depression (NPMD). However, neurobiological evidence supporting this notion is scarce. The aim of this study is to identify gray matter volume (GMV) differences between PMD and NPMD and their longitudinal change following electroconvulsive therapy (ECT). Structural magnetic resonance imaging (MRI) data from 8 independent sites in the Global ECT-MRI Research Collaboration (GEMRIC) database (n = 108; 56 PMD and 52 NPMD; mean age 71.7 in PMD and 70.2 in NPMD) were analyzed. All participants underwent MRI before and after ECT. First, cross-sectional whole-brain voxel-wise GMV comparisons between PMD and NPMD were conducted at both time points. Second, in a flexible factorial model, a main effect of time and a group-by-time interaction were examined to identify longitudinal effects of ECT on GMV and longitudinal differential effects of ECT between PMD and NPMD, respectively. Compared with NPMD, PMD showed lower GMV in the prefrontal, temporal and parietal cortex before ECT; PMD showed lower GMV in the medial prefrontal cortex (MPFC) after ECT. Although there was a significant main effect of time on GMV in several brain regions in both PMD and NPMD, there was no significant group-by-time interaction. Lower GMV in the MPFC was consistently identified in PMD, suggesting this may be a trait-like neural substrate of PMD. Longitudinal effect of ECT on GMV may not explain superior ECT response in PMD, and further investigation is needed.

Short and long-term effects of single and multiple sessions of electroconvulsive therapy on brain gray matter volumes

BACKGROUND

Electroconvulsive therapy (ECT) has been shown to induce broadly distributed cortical and subcortical volume increases, more prominently in the amygdala and the hippocampus. Structural changes after one ECT session and in the long-term have been understudied.

OBJECTIVE

The aim of this study was to describe short-term and long-term volume changes induced in cortical and subcortical regions by ECT.

METHODS

Structural brain data were acquired from depressed patients before and 2 h after their first ECT session, 7-14 days after the end of the ECT series and at 6 months follow up (N = 34). Healthy, age and gender matched volunteers were scanned according to the same schedule (N = 18) and patients affected by atrial fibrillation were scanned 1-2 h before and after undergoing electrical cardioversion (N = 16). Images were parcelled using FreeSurfer and estimates of cortical gray matter volume and subcortical volume changes were obtained using Quarc.

RESULTS

Volume increase was observable in most of gray matter regions after 2 h from the first ECT session, with significant results in brain stem, bilateral hippocampi, right putamen and left thalamus, temporal and occipital regions in the right hemisphere. At the end of treatment series, widespread significant volume changes were observed. After six months, the right amygdala volume was still significantly increased. No significant changes were observed in the comparison groups.

CONCLUSIONS

Volume increases in gray matter areas can be detected 2 h after a single ECT session. Further studies are warranted to explore the underlying molecular mechanisms.

Association of electroconvulsive therapy-induced structural plasticity with clinical remission

BACKGROUND

Electroconvulsive therapy (ECT) is the most effective treatment for severe depression. Recent neuroimaging studies have consistently reported that ECT induces volume increases in widely distributed brain regions. However, it still remains unclear about ECT-induced volume changes associated with clinical improvement.

METHODS

Longitudinal assessments of structural magnetic resonance imaging were conducted in 48 participants. Twenty-seven elderly melancholic depressed individuals (mean 67.5 ± 8.1 years old; 19 female) were scanned before (TP1) and after (TP2) ECT. Twenty-one healthy controls were also scanned twice. Whole-brain gray matter volume (GMV) was analyzed via group (remitters, nonremitters, and controls) by time (TP1 and TP2) analysis of covariance to identify ECT-related GMV changes and GMV changes specific to remitters. Within-subject and between-subjects correlation analyses were conducted to investigate the associations between clinical improvement and GMV changes. Depressive symptoms were evaluated using the 17-item Hamilton Depression Rating Scale (HAM-D), and remission was defined as HAM-D total score ≤ 7.

RESULTS

Bilateral ECT increased GMV in multiple brain regions bilaterally regardless of clinical improvement. Remitters showed a larger GMV increase in the right-lateralized frontolimbic brain regions compared to nonremitters and healthy controls. GMV changes in the right hippocampus/amygdala and right middle frontal gyrus showed correlations with clinical improvement in within-/between-subjects correlation analyses.

CONCLUSIONS

ECT-induced GMV increase in the right frontolimbic regions was associated with clinical remission.

Accounting for symptom heterogeneity can improve neuroimaging models of antidepressant response after electroconvulsive therapy

Depression symptom heterogeneity limits the identifiability of treatment‐response biomarkers. Whether improvement along dimensions of depressive symptoms relates to separable neural networks remains poorly understood. We build on work describing three latent symptom dimensions within the 17‐item Hamilton Depression Rating Scale (HDRS) and use data‐driven methods to relate multivariate patterns of patient clinical, demographic, and brain structural changes over electroconvulsive therapy (ECT) to dimensional changes in depressive symptoms. We included 110 ECT patients from Global ECT‐MRI Research Collaboration (GEMRIC) sites who underwent structural MRI and HDRS assessments before and after treatment. Cross validated random forest regression models predicted change along symptom dimensions. HDRS symptoms clustered into dimensions of somatic disturbances (SoD), core mood and anhedonia (CMA), and insomnia. The coefficient of determination between predicted and actual changes were 22%, 39%, and 39% (all p < .01) for SoD, CMA, and insomnia, respectively. CMA and insomnia change were predicted more accurately than HDRS‐6 and HDRS‐17 changes (p < .05). Pretreatment symptoms, body‐mass index, and age were important predictors. Important imaging predictors included the right transverse temporal gyrus and left frontal pole for the SoD dimension; right transverse temporal gyrus and right rostral middle frontal gyrus for the CMA dimension; and right superior parietal lobule and left accumbens for the insomnia dimension. Our findings support that recovery along depressive symptom dimensions is predicted more accurately than HDRS total scores and are related to unique and overlapping patterns of clinical and demographic data and volumetric changes in brain regions related to depression and near ECT electrodes.

Adaptive current-flow models of ECT: Explaining individual static impedance, dynamic impedance, and brain current density

BACKGROUND

Improvements in electroconvulsive therapy (ECT) outcomes have followed refinement in device electrical output and electrode montage. The physical properties of the ECT stimulus, together with those of the patient's head, determine the impedances measured by the device and govern current delivery to the brain and ECT outcomes.

OBJECTIVE

However, the precise relations among physical properties of the stimulus, patient head anatomy, and patient-specific impedance to the passage of current are long-standing questions in ECT research and practice. To this end, we develop a computational framework based on diverse clinical data sets.

METHODS

We developed anatomical MRI-derived models of transcranial electrical stimulation (tES) that included changes in tissue conductivity due to local electrical current flow. These "adaptive" models simulate ECT both during therapeutic stimulation using high current (∼1 A) and when dynamic impedance is measured, as well as prior to stimulation when low current (∼1 mA) is used to measure static impedance. We modeled two scalp layers: a superficial scalp layer with adaptive conductivity that increases with electric field up to a subject-specific maximum (σ_SS¯), and a deep scalp layer with a subject-specific fixed conductivity (σ_DS).

RESULTS

We demonstrated that variation in these scalp parameters may explain clinical data on subject-specific static impedance and dynamic impedance, their imperfect correlation across subjects, their relationships to seizure threshold, and the role of head anatomy. Adaptive tES models demonstrated that current flow changes local tissue conductivity which in turn shapes current delivery to the brain in a manner not accounted for in fixed tissue conductivity models.

CONCLUSIONS

Our predictions that variation in individual skin properties, rather than other aspects of anatomy, largely govern the relationship between static impedance, dynamic impedance, and ECT current delivery to the brain, themselves depend on assumptions about tissue properties. Broadly, our novel modeling pipeline opens the door to explore how adaptive-scalp conductivity may impact transcutaneous electrical stimulation (tES).

Elevated body weight modulates subcortical volume change and associated clinical response following electroconvulsive therapy

BACKGROUND

Obesity is a frequent somatic comorbidity of major depression, and it has been associated with worse clinical outcomes and brain structural abnormalities. Converging evidence suggests that electroconvulsive therapy (ECT) induces both clinical improvements and increased subcortical grey matter volume in patients with depression. However, it remains unknown whether increased body weight modulates the clinical response and structural neuroplasticity that occur with ECT.

METHODS

To address this question, we conducted a longitudinal investigation of structural MRI data from the Global ECT-MRI Research Collaboration (GEMRIC) in 223 patients who were experiencing a major depressive episode (10 scanning sites). Structural MRI data were acquired before and after ECT, and we assessed change in subcortical grey matter volume using FreeSurfer and Quarc.

RESULTS

Higher body mass index (BMI) was associated with a significantly lower increase in subcortical grey matter volume following ECT. We observed significant negative associations between BMI and change in subcortical grey matter volume, with pronounced effects in the thalamus and putamen, where obese participants showed increases in grey matter volume that were 43.3% and 49.6%, respectively, of the increases found in participants with normal weight. As well, BMI significantly moderated the association between subcortical grey matter volume change and clinical response to ECT. We observed no significant association between BMI and clinical response to ECT.

LIMITATIONS

Because only baseline BMI values were available, we were unable to study BMI changes during ECT and their potential association with clinical and grey matter volume change.

CONCLUSION

Future studies should take into account the relevance of body weight as a modulator of structural neuroplasticity during ECT treatment and aim to further explore the functional relevance of this novel finding.

Biophysical mechanisms of electroconvulsive therapy-induced volume expansion in the medial temporal lobe: A longitudinal in vivo human imaging study

Background:

Electroconvulsive therapy (ECT) applies electric currents to the brain to induce seizures for therapeutic purposes. ECT increases gray matter (GM) volume, predominantly in the medial temporal lobe (MTL). The contribution of induced seizures to this volume change remains unclear.

Methods:

T1-weighted structural MRI was acquired from thirty patients with late-life depression (mean age 72.5 ± 7.9 years, 19 female), before and one week after one course of right unilateral ECT. Whole brain voxel-/deformation-/surface-based morphometry analyses were conducted to identify tissue-specific (GM, white matter: WM), and cerebrospinal fluid (CSF) and cerebral morphometry changes following ECT. Whole-brain voxel-wise electric field (EF) strength was estimated to investigate the association of EF distribution and regional brain volume change. The association between percentage volume change in the right MTL and ECT-related parameters (seizure duration, EF, and number of ECT sessions) was investigated using multiple regression.

Results:

ECT induced widespread GM volume expansion with corresponding contraction in adjacent CSF compartments, and limited WM change. The regional EF was strongly correlated with the distance from the electrodes, but not with regional volume change. The largest volume expansion was identified in the right MTL, and this was correlated with the total seizure duration.

Conclusions:

Right unilateral ECT induces widespread, bilateral regional volume expansion and contraction, with the largest change in the right MTL. This dynamic volume change cannot be explained by the effect of electrical stimulation alone and is related to the cumulative effect of ECT-induced seizures.

Magnetic seizure therapy is associated with functional and structural brain changes in MDD: Therapeutic versus side effect correlates

BACKGROUND

Magnetic Seizure therapy (MST) is an effective treatment for major depressive disorder (MDD) but its mechanism of action is not fully understood. The present study sought to characterize neuroimaging correlates of response and side effects of MST in a MDD cohort.

METHODS

Fifteen severe MDD patients underwent a six-day course of MST treatment to the vertex. Before and after treatment, participants received rs-fMRI and structural MRI scans as well as assessments of depressive symptoms and neuropsychological functioning. 10 healthy volunteers received functional and structural MRI scans at similar time intervals.

RESULTS

MST treatment was associated with increased functional connectivity between the subgenual anterior cingulate cortex (sgACC) and the parietal cortex, which positively correlated with clinical improvement. In contrast, greater decrease in functional connectivity between the right anterior hippocampus and the prefrontal cortex was correlated with lesser clinical and cognitive improvements. Changes in gray matter volume were evident in the bilateral parietal cortex, but were not associated with treatment outcomes.

LIMITATIONS

The sample size was small and results warrant replication.

CONCLUSIONS

This is the first quantitative fMRI study to investigate the neural correlates of MST treatment for MDD patients. While preliminary, these findings suggest that the modulation of sgACC activity is integral to the antidepressant mechanisms of MST. In contrast, changes in the hippocampus were not associated with symptom improvement, and appeared to contribute instead to side effects. Future studies in larger samples are warranted and explore the effect of e-electric field and correlates of response.

Hippocampal volume and memory impairment after electroconvulsive therapy in patients with depression

OBJECTIVE

Patients hesitate to consent to electroconvulsive therapy (ECT) because of the fear of memory impairment. The mechanisms underlying this impairment are unclear, but several observations suggest hippocampal alterations may be involved. We investigated whether ECT-induced change in hippocampal volume correlates with memory impairment.

METHODS

Using a 3 T MRI scanner, we acquired brain images and assessed cognitive performance in 22 severely depressed patients at three time points: (1) before ECT series, (2) within one week after the series, and (3) at six-month follow-up. The hippocampus was segmented into subregions using FreeSurfer. The dentate gyri (DG) were the primary regions of interest (ROIs) and major hippocampal subregions secondary ROIs. Cognitive performance was assessed using the Screen for Cognitive Impairment in Psychiatry and verbal memory using the Verbal Learning subtest. The linear mixed model and the repeated-measures correlation were used for statistical analyses.

RESULTS

ECT induced an increase in the right and left DG volume with co-occurring worsening in verbal memory, and these changes were within-patients negatively correlated (right DG, r_rm  = -0.85, df = 18, p = 0.0000002; left DG, r_rm  = -0.58, df = 18, p = 0.008). At a six-month follow-up, the volume of both DG decreased with a co-occurring improvement in verbal memory, and these changes were negatively correlated in the right DG (r_rm  = -0.64, df = 15, p = 0.005). Volume increases in 14 secondary ROIs were also negatively correlated with memory impairment.

CONCLUSION

ECT-related transient increases in the volume of major hippocampal subregions within-patients are associated with memory impairment. Hippocampal alterations following ECT should be the focus in searching for causes of the cognitive side effects.

Volume of hippocampal subregions and clinical improvement following electroconvulsive therapy in patients with depression

It is thought that the hippocampal neurogenesis is an important mediator of the antidepressant effect of electroconvulsive therapy (ECT). However, most previous studies failed to demonstrate the relationship between the increase in the hippocampal volume and the antidepressant effect. We reinvestigated this relationship by looking at distinct hippocampal subregions and applying repeated measures correlation. Using a 3 Tesla MRI-scanner, we scanned 22 severely depressed in-patients at three time points: before the ECT series, after the series, and at six-month follow-up. The depression severity was assessed by the 17-item Hamilton Rating Scale for Depression (HAMD-17). The hippocampus was segmented into subregions using Freesurfer software. The dentate gyrus (DG) was the primary region of interest (ROI), due to the role of this region in neurogenesis. The other major hippocampal subregions were the secondary ROIs (n = 20). The general linear mixed model and the repeated measures correlation were used for statistical analyses. Immediately after the ECT series, a significant volume increase was present in the right DG (Cohen's d = 1.7) and the left DG (Cohen's d = 1.5), as well as 15 out of 20 secondary ROIs. The clinical improvement, i.e., the decrease in HAMD-17 score, was correlated to the increase in the right DG volume (r_rm = -0.77, df = 20, p < .001), and the left DG volume (r_rm = -0.75, df = 20, p < .001). Similar correlations were observed in 14 out of 20 secondary ROIs. Thus, ECT induces an increase not only in the volume of the DG, but also in the volume of other major hippocampal subregions. The volumetric increases may reflect a neurobiological process that may be related to the ECT's antidepressant effect. Further investigation of the relationship between hippocampal subregions and the antidepressant effect is warranted. A statistical approach taking the repeated measurements into account should be preferred in the analyses.

Functional connectivity underpinnings of electroconvulsive therapy-induced memory impairments in patients with depression

Electroconvulsive therapy (ECT) is an effective treatment for severe medication-resistant depression. However, ECT frequently results in episodic memory impairments, causing many patients to discontinue treatment. The objective of this study was to explore the functional connectivity underpinnings of ECT-induced episodic memory impairments. We investigated verbal episodic memory and intrinsic functional connectivity in 24 patients with depression (13F, 11M) before and after ECT, and 1 month after treatment. We used a novel individual-oriented approach to examine functional connectivity, and trained a linear support vector regression model to estimate verbal memory performance based on connectivity. The model identified a set of brain connections that can predict baseline verbal memory performance (r = 0.535, p = 0.026). Importantly, we found a nonoverlapping set of brain connections whose changes after ECT can track patients' verbal memory impairments (r = 0.613, p = 0.008). These connections mainly involve the frontoparietal control, default mode, and hippocampal networks, suggesting that ECT affects broad functional networks that are involved in memory performance. In contrast, functional connectivity defined using traditional group-level analyses was unable to estimate either baseline memory performance or post-ECT verbal memory impairments. A parallel analysis using the same strategy did not identify a connectivity marker for overall mood improvement, suggesting that functional connectivity changes related to depressive symptoms may be highly heterogenous. Our findings shed light on the mechanism through which ECT impairs episodic memory, and additionally underline the importance of accounting for interindividual variability in the investigation of functional brain organization in patients with depression.

Electroconvulsive therapy treatment responsive multimodal brain networks

Electroconvulsive therapy is regarded as the most effective antidepressant treatment for severe and treatment-resistant depressive episodes. Despite the efficacy of electroconvulsive therapy, the neurobiological underpinnings and mechanisms underlying electroconvulsive therapy induced antidepressant effects remain unclear. The objective of this investigation was to identify electroconvulsive therapy treatment responsive multimodal biomarkers with the 17-item Hamilton Depression Rating Scale guided brain structure-function fusion in 118 patients with depressive episodes and 60 healthy controls. Results show that reduced fractional amplitude of low frequency fluctuations in the prefrontal cortex, insula and hippocampus, linked with increased gray matter volume in anterior cingulate, medial temporal cortex, insula, thalamus, caudate and hippocampus represent electroconvulsive therapy responsive covarying functional and structural brain networks. In addition, relative to nonresponders, responder-specific electroconvulsive therapy related brain networks occur in frontal-limbic network and are associated with successful therapeutic outcomes. Finally, electroconvulsive therapy responsive brain networks were unrelated to verbal declarative memory. Using a data-driven, supervised-learning method, we demonstrated that electroconvulsive therapy produces a remodeling of brain functional and structural covariance that was unique to antidepressant symptom response, but not linked to memory impairment.