Dataset Information

Selective modulation of brain network dynamics by seizure therapy in treatment-resistant depression.

ABSTRACT:

Background

Electroconvulsive therapy (ECT) is highly effective for treatment-resistant depression, yet its mechanism of action is still unclear. Understanding the mechanism of action of ECT can advance the optimization of magnetic seizure therapy (MST) towards higher efficacy and less cognitive impairment. Given the neuroimaging evidence for disrupted resting-state network dynamics in depression, we investigated whether seizure therapy (ECT and MST) selectively modifies brain network dynamics for therapeutic efficacy.

Methods

EEG microstate analysis was used to evaluate resting-state network dynamics in patients at baseline and following seizure therapy, and in healthy controls. Microstate analysis defined four classes of brain states (labelled A, B, C, D). Source localization identified the brain regions associated with these states.

Results

An increase in duration and decrease in frequency of microstates was specific to responders of seizure therapy. Significant changes in the dynamics of States A, C and D were observed and predicted seizure therapy outcome (specifically ECT). Relative change in the duration of States C and D was shown to be a strong predictor of ECT response. Source localization partly associated C and D to the salience and frontoparietal networks, argued to be impaired in depression. An increase in duration and decrease in frequency of microstates was also observed following MST, however it was not specific to responders.

Conclusion

This study presents the first evidence for the modulation of global brain network dynamics by seizure therapy. Successful seizure therapy was shown to selectively modulate network dynamics for therapeutic efficacy.

SUBMITTER: Atluri S

PROVIDER: S-EPMC6214861 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Selective modulation of brain network dynamics by seizure therapy in treatment-resistant depression.

Atluri Sravya S Wong Willy W Moreno Sylvain S Blumberger Daniel M DM Daskalakis Zafiris J ZJ Farzan Faranak F

NeuroImage. Clinical 20181017

<h4>Background</h4>Electroconvulsive therapy (ECT) is highly effective for treatment-resistant depression, yet its mechanism of action is still unclear. Understanding the mechanism of action of ECT can advance the optimization of magnetic seizure therapy (MST) towards higher efficacy and less cognitive impairment. Given the neuroimaging evidence for disrupted resting-state network dynamics in depression, we investigated whether seizure therapy (ECT and MST) selectively modifies brain network dyn ...[more]

PMID: 30388600

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Project description:ImportanceThere is an unmet need for effective treatments for suicidality in mental disorders. Magnetic seizure therapy (MST) has been investigated as an alternative to electroconvulsive therapy, a known effective treatment for suicidality, in the management of treatment-resistant major depressive disorder, with promising findings. Yet, there are very limited data on the association of MST with suicidality directly. It is important to explore the potential of MST as a viable treatment alternative to electroconvulsive therapy for suicidality.ObjectiveTo determine the association of MST with suicidality in patients with treatment-resistant major depressive disorder.Design, setting, and participantsThis nonrandomized controlled trial took place at a single tertiary care psychiatric facility in Canada. It followed an open-label study design with consecutive treatment cohorts. Consecutive groupings of 67 patients with treatment-resistant major depressive disorder and with baseline suicidality present were treated for up to 24 treatments. The study was run from February 2012 through June 2019. Patients were followed up for 6 months at the end of the treatment period. This post hoc secondary analysis of the trial was performed from January to November 2019.InterventionsMST was delivered at 100% stimulator output over the prefrontal cortex with low (25 Hz), moderate (50 or 60 Hz), or high (100 Hz) frequency, for a maximum of 24 sessions.Main outcomes and measuresRemission from suicidality was measured as an end point score of 0 on the Beck Scale for Suicidal Ideation. A linear mixed model was used to assess the trajectory of Beck Scale for Suicidal Ideation scores.ResultsA total of 67 patients (mean [SD] age, 46.3 [13.6] years; 40 women [60.0%]) received a mean (SD) of 19.5 (5.1) MST treatments. The overall number of patients achieving remission was 32 (47.8%). Sixteen patients (55.2%) receiving low-frequency MST achieved remission, as well as 12 patients (54.5%) in the moderate-frequency group, and 4 patients (25.0%) in the high-frequency group. The linear mixed model revealed an association of time with Beck Scale for Suicidal Ideation scores (F8,293.95 = 5.73; P < .001).Conclusions and relevanceThese findings suggest that MST may be an effective treatment for suicidality, and sensitivity analysis shows this may be particularly so at low and moderate frequencies. Future studies should directly compare MST with electroconvulsive therapy for treating suicidality and should evaluate MST as a treatment for suicidality across mental disorders.Trial registrationClinicalTrials.gov Identifier: NCT01596608.

Project description:Therapeutic seizures may work for treatment-resistant depression (TRD) by producing neuroplasticity. We evaluated whether magnetic seizure therapy (MST) produces changes in suicidal ideation and neuroplasticity as indexed through transcranial magnetic stimulation and electroencephalography (TMS-EEG) of the dorsolateral prefrontal cortex (DLPFC). Twenty-three patients with TRD were treated with MST. Changes in suicidal ideation was assessed through the Scale for Suicidal Ideation (SSI). Before and after the treatment course, neuroplasticity in excitatory and inhibitory circuits was assessed with TMS-EEG measures of cortical-evoked activity (CEA) and long-interval cortical inhibition (LICI) from the left DLPFC, and the left motor cortex as a control condition. As in our previous report, the relationship between TMS-EEG measures and suicidal ideation was examined with the SSI. Results show that 44.4% of patients experienced resolution of suicidal ideation. Based on DLPFC assessment, MST produced significant CEA increase over the frontal central electrodes (cluster p < 0.05), but did not change LICI on a group level. MST also reduced the SSI scores (p < 0.005) and the amount of reduction correlated with the decrease in LICI over the right frontal central electrodes (cluster p < 0.05; rho = 0.73 for Cz). LICI change identified patients who were resolved of suicidal ideation with 90% sensitivity and 88% specificity (AUC = 0.9, p = 0.004). There was no significant finding with motor cortex assessment. Overall, MST produced significant rates of resolution of suicidal ideation. MST also produced neuroplasticity in the frontal cortex, likely through long-term potentiation (LTP)-like mechanisms. The largest reduction in suicidal ideation was demonstrated in patients showing concomitant decreases in cortical inhibition-a mechanism linked to enhanced LTP-like plasticity. These findings provide insights into the mechanisms through which patients experience resolution of suicidal ideation following seizure treatments in depression.

Project description:Dynamic functional brain connectivity facilitates adaptive cognition and behaviour. Abnormal alterations within such connectivity could result in disrupted functions observed across various neurological conditions. As one of the most common neurological disorders, epilepsy is defined by the seemingly random occurrence of spontaneous seizures. A central but unresolved question concerns the mechanisms by which extraordinarily diverse propagation dynamics of seizures emerge. Here, we applied a graph-theoretical approach to assess dynamic reconfigurations in the functional brain connectivity before, during and after seizures that display heterogeneous propagation patterns despite sharing similar cortical onsets. We computed time-varying functional brain connectivity networks from human intracranial recordings of 67 seizures (across 14 patients) that had a focal origin-49 of these focal seizures remained focal and 18 underwent a bilateral spread (focal to bilateral tonic-clonic seizures). We utilized functional connectivity networks estimated from interictal periods across patients as control. Our results characterize network features that quantify the underlying functional dynamics associated with the observed heterogeneity of seizure propagation across these two types of focal seizures. Decoding these network features demonstrate that bilateral propagation of seizure activity is an outcome of the imbalance of global integration and segregation in the brain prior to seizure onset. We show that there exist intrinsic network signatures preceding seizure onset that are associated with the extent to which an impending seizure will propagate throughout the brain (i.e. staying within one hemisphere versus spreading transcallosally). Additionally, these features characterize an increase in segregation and a decrease in excitability within the brain network (i.e. high modularity and low spectral radius). Importantly, seizure-type-specific differences in these features emerge several minutes prior to seizure onset, suggesting the potential utility of such measures in intervention strategies. Finally, our results reveal network characteristics after the onset that are unique to the propagation mechanisms of two most common focal seizure subtypes, indicative of distinct reconfiguration processes that may assist termination of each seizure type. Together, our findings provide insights into the relationship between the temporal evolution of seizure activity and the underlying functional connectivity dynamics. These results offer exciting avenues where graph-theoretical measures could potentially guide personalized clinical interventions for epilepsy and other neurological disorders in which extensive heterogeneity is observed across subtypes as well as across and within individual patients.

Dataset Information

Selective modulation of brain network dynamics by seizure therapy in treatment-resistant depression.

Background

Methods

Results

Conclusion

Publications

Selective modulation of brain network dynamics by seizure therapy in treatment-resistant depression.

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