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.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

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.

Electric field distribution predicts efficacy of accelerated intermittent theta burst stimulation for late-life depression

Introduction

Repetitive transcranial magnetic stimulation (rTMS) is a promising intervention for late-life depression (LLD) but may have lower rates of response and remission owing to age-related brain changes. In particular, rTMS induced electric field strength may be attenuated by cortical atrophy in the prefrontal cortex. To identify clinical characteristics and treatment parameters associated with response, we undertook a pilot study of accelerated fMRI-guided intermittent theta burst stimulation (iTBS) to the right dorsolateral prefrontal cortex in 25 adults aged 50 or greater diagnosed with LLD and qualifying to receive clinical rTMS.

Methods

Participants underwent baseline behavioral assessment, cognitive testing, and structural and functional MRI to generate individualized targets and perform electric field modeling. Forty-five sessions of iTBS were delivered over 9 days (1800 pulses per session, 50-min inter-session interval). Assessments and testing were repeated after 15 sessions (Visit 2) and 45 sessions (Visit 3). Primary outcome measure was the change in depressive symptoms on the Inventory of Depressive Symptomatology-30-Clinician (IDS-C-30) from Visit 1 to Visit 3.

Results

Overall there was a significant improvement in IDS score with the treatment (Visit 1: 38.6; Visit 2: 31.0; Visit 3: 21.3; mean improvement 45.5%) with 13/25 (52%) achieving response and 5/25 (20%) achieving remission (IDS-C-30 < 12). Electric field strength and antidepressant effect were positively correlated in a subregion of the ventrolateral prefrontal cortex (VLPFC) (Brodmann area 47) and negatively correlated in the posterior dorsolateral prefrontal cortex (DLPFC).

Conclusion

Response and remission rates were lower than in recently published trials of accelerated fMRI-guided iTBS to the left DLPFC. These results suggest that sufficient electric field strength in VLPFC may be a contributor to effective rTMS, and that modeling to optimize electric field strength in this area may improve response and remission rates. Further studies are needed to clarify the relationship of induced electric field strength with antidepressant effects of rTMS for LLD.

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

BACKGROUND

Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depressive disorders. A recent multi-center study found no consistent changes in correlation-based (undirected) resting-state connectivity after ECT. Effective (directed) connectivity may provide more insight into the working mechanism of ECT.

OBJECTIVE

We investigated whether there are consistent changes in effective resting-state connectivity.

METHODS

This multi-center study included data from 189 patients suffering from severe unipolar depression and 59 healthy control participants. Longitudinal data were available for 81 patients and 24 healthy controls. We used dynamic causal modeling for resting-state functional magnetic resonance imaging to determine effective connectivity in the default mode, salience and central executive networks before and after a course of ECT. Bayesian general linear models were used to examine differences in baseline and longitudinal effective connectivity effects associated with ECT and its effectiveness.

RESULTS

Compared to controls, depressed patients showed many differences in effective connectivity at baseline, which varied according to the presence of psychotic features and later treatment outcome. Additionally, effective connectivity changed after ECT, which was related to ECT effectiveness. Notably, treatment effectiveness was associated with decreasing and increasing effective connectivity from the posterior default mode network to the left and right insula, respectively. No effects were found using correlation-based (undirected) connectivity.

CONCLUSIONS

A beneficial response to ECT may depend on how brain regions influence each other in networks important for emotion and cognition. These findings further elucidate the working mechanisms of ECT and may provide directions for future non-invasive brain stimulation research.

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.

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.

Sex-specifics of ECT outcome

OBJECTIVE

Electroconvulsive therapy (ECT) is the most effective treatment for patients with severe major depressive disorder (MDD). Given the known sex differences in MDD, improved knowledge may provide more sex-specific recommendations in clinical guidelines and improve outcome. In the present study we examine sex differences in ECT outcome and its predictors.

METHODS

Clinical data from 20 independent sites participating in the Global ECT-MRI Research Collaboration (GEMRIC) were obtained for analysis, totaling 500 patients with MDD (58.6 % women) with a mean age of 54.8 years. Severity of depression before and after ECT was assessed with validated depression scales. Remission was defined as a HAM-D score of 7 points or below after ECT. Variables associated with remission were selected based on literature (i.e. depression severity at baseline, age, duration of index episode, and presence of psychotic symptoms).

RESULTS

Remission rates of ECT were independent of sex, 48.0 % in women and 45.7 % in men (X²(1) = 0.2, p = 0.70). In the logistic regression analyses, a shorter index duration was identified as a sex-specific predictor for ECT outcome in women (X²(1) = 7.05, p = 0.01). The corresponding predictive margins did show overlapping confidence intervals for men and women.

CONCLUSION

The evidence provided by our study suggests that ECT as a biological treatment for MDD is equally effective in women and men. A shorter duration of index episode was an additional sex- specific predictor for remission in women. Future research should establish whether the confidence intervals for the corresponding predictive margins are overlapping, as we find, or not.

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.

Ictal Theta Power as an Electroconvulsive Therapy Safety Biomarker: A Pilot Study

OBJECTIVE

Electroconvulsive therapy (ECT) remains the benchmark for treatment resistant depression, yet its cognitive adverse effects have a negative impact on treatment. A predictive safety biomarker early in ECT treatment is needed to identify patients at cognitive risk to maximize therapeutic outcomes and minimize adverse effects. We used ictal electroencephalography frequency analysis from suprathreshold treatments to assess the relationships between ECT dose, ictal power across different frequency domains, and cognitive outcomes.

METHODS

Seventeen subjects with treatment resistant depression received right unilateral ECT. Structural magnetic resonance imaging was obtained pre-ECT for electric field modeling to assess ECT dose. Serial assessments with 24-lead electroencephalography captured ictal activity. Clinical and cognitive assessments were performed before and after ECT. The primary cognitive outcome was the change in Delis Kaplan Executive Function Verbal Fluency Letter Fluency.

RESULTS

Ictal theta (4-8 Hz) power in the Fp1/Fp2 channels was associated with both whole-brain electric field strength (t(2,12) = 19.5, P = 0.007)/(t(2,10) = 21.85, P = 0.02) and Delis Kaplan Executive Function Verbal Fluency Letter Fluency scores (t(2,12) = -2.05, P = 0.05)/(t(2,10) = -2.20, P = 0.01). Other frequency bands (beta, alpha, delta, and gamma) did not demonstrate this relationship.

CONCLUSIONS

This pilot data identify ictal theta power as a potential safety biomarker in ECT and is related to the strength of the ECT dose. Ictal theta power could prove to be a convenient and powerful tool for clinicians to identify those patients most susceptible to cognitive impairment early in the treatment series. Additional studies are needed to assess the role of longitudinal changes in ictal theta power throughout the ECT series.

Crossing State Lines: Ethical and Clinical Considerations in Treating a Child With Catatonia

Catatonia is a complex constellation of symptoms presenting with abnormalities in movement and behavior and arises from multiple medical, neurologic, and psychiatric conditions. In recent years, there has been a call to move catatonia from a classifier to a diagnosis of its own in the DSM-5.^1,2 Catatonia is often underdiagnosed in the hospital and carries with it substantial morbidity and mortality.³ Malignant catatonia, characterized by autonomic instability, hyperactivity, mutism, and stuporous exhaustion, is a medical emergency requiring intensive care.⁴ Early diagnosis and treatment are imperative, as untreated malignant catatonia may be fatal in up to 10% to 20% of cases, sometimes only days from onset.⁵ The combination of lorazepam and electroconvulsive therapy (ECT) is a safe and effective treatment for catatonia in both adults and children, although the body of literature pertaining to children remains limited.^6,7 In addition, there are multiple case reports of improvement in catatonia with ECT regardless of etiology.⁸ However, laws in some US states prohibit ECT's use despite evidence of its effectiveness and safety in children and adolescents.⁹ Here, we describe a case presentation that was both prolonged and complicated by state laws pertaining to the use of ECT in children and adolescents.

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.

Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder

Background: Major depressive disorder (MDD) is a severe mental illness marked by a continuous sense of sadness and a loss of interest. The default mode network (DMN) is a group of brain areas that are more active during rest and deactivate when engaged in task-oriented activities. The DMN of MDD has been found to have aberrant static functional network connectivity (FNC) in recent studies. In this work, we extend previous findings by evaluating dynamic functional network connectivity (dFNC) within the DMN subnodes in MDD. Methods: We analyzed resting-state functional magnetic resonance imaging data of 262 patients with MDD and 277 healthy controls (HCs). We estimated dFNCs for seven subnodes of the DMN, including the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and precuneus (PCu), using a sliding window approach, and then clustered the dFNCs into five brain states. Classification of MDD and HC subjects based on state-specific FC was performed using a logistic regression classifier. Transition probabilities between dFNC states were used to identify relationships between symptom severity and dFNC data in MDD patients. Results: By comparing state-specific FNC between HC and MDD, a disrupted connectivity pattern was observed within the DMN. In more detail, we found that the connectivity of ACC is stronger, and the connectivity between PCu and PCC is weaker in individuals with MDD than in those of HC subjects. In addition, MDD showed a higher probability of transitioning from a state with weaker ACC connectivity to a state with stronger ACC connectivity, and this abnormality is associated with symptom severity. This is the first research to look at the dFC of the DMN in MDD with a large sample size. It provides novel evidence of abnormal time-varying DMN configuration in MDD and offers links to symptom severity in MDD subjects. Impact Statement This study is the first attempt that explored the temporal change on default mode network (DMN) connectivity in a relatively large cohort of patients with major depressive disorder (MDD). We also introduced a new hypothesis that explains the inconsistency in DMN functional network connectivity (FNC) comparison between MDD and healthy control based on static FNC in the previous literature. Additionally, our findings suggest that within anterior cingulate cortex connectivity and the connectivity between the precuneus and posterior cingulate cortex are the potential biomarkers for the future intervention of MDD.

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.

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

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

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

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

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

Electroconvulsive Therapy Pulse Amplitude and Clinical Outcomes

INTRODUCTION

Electroconvulsive therapy (ECT) pulse amplitude, which determines the induced electric field magnitude in the brain, is currently set at 800-900 milliamperes (mA) on modern ECT devices without any clinical or scientific rationale. The present study assessed differences in depression and cognitive outcomes for three different pulse amplitudes during an acute ECT series. We hypothesized that the lower amplitudes would maintain the antidepressant efficacy of the standard treatment and reduce the risk of neurocognitive impairment.

METHODS

This double-blind investigation randomized subjects to three treatment arms: 600, 700, and 800 mA (active comparator). Clinical, cognitive, and imaging assessments were conducted pre-, mid- and post-ECT. Subjects had a diagnosis of major depressive disorder, age range between 50 and 80 years, and met clinical indication for ECT.

RESULTS

The 700 and 800 mA arms had improvement in depression outcomes relative to the 600 mA arm. The amplitude groups showed no differences in the primary cognitive outcome variable, the Hopkins Verbal Learning Test-Revised (HVLT-R) retention raw score. However, secondary cognitive outcomes such as the Delis Kaplan Executive Function System Letter and Category Fluency measures demonstrated cognitive impairment in the 800 mA arm.

DISCUSSION

The results demonstrated a dissociation of depression (higher amplitudes better) and cognitive (lower amplitudes better) related outcomes. Future work is warranted to elucidate the relationship between amplitude, electric field, neuroplasticity, and clinical outcomes.

Magnetic Resonance Spectroscopy in Depressed Subjects Treated With Electroconvulsive Therapy-A Systematic Review of Literature

Electroconvulsive therapy (ECT) is considered to be the most effective acute treatment for otherwise treatment resistant major depressive episodes, and has been used for over 80 years. Still, the underlying mechanism of action is largely unknow. Several studies suggest that ECT affects the cerebral neurotransmitters, such as gamma-aminobutyric acid (GABA) and glutamate. Magnetic resonance spectroscopy (MRS) allows investigators to study neurotransmitters in vivo, and has been used to study neurochemical changes in the brain of patients treated with ECT. Several investigations have been performed on ECT-patients; however, no systematic review has yet summarized these findings. A systematic literature search based on the Prisma guidelines was performed. PubMed (Medline) was used in order to find investigations studying patients that had been treated with ECT and had undergone an MRS examination. A search in the databases Embase, PsycInfo, and Web of Science was also performed, leading to no additional records. A total of 30 records were identified and screened which resulted in 16 original investigations for review. The total number of patients that was included in these studies, ignoring potential overlap of samples in some investigations, was 325. The metabolites reported were N-acetyl aspartate, Choline, Myoinositol, Glutamate and Glutamine, GABA and Creatine. The strongest evidence for neurochemical change related to ECT, was found for N-acetyl aspartate (reduction), which is a marker of neuronal integrity. Increased choline and glutamate following treatment was also commonly reported.

Anterior cingulate gamma-aminobutyric acid concentrations and electroconvulsive therapy

OBJECTIVE

The anticonvulsant hypothesis posits that ECT's mechanism of action is related to enhancement of endogenous anticonvulsant brain mechanisms. Results of prior studies investigating the role of the inhibitory neurotransmitter gamma-aminobutyric acid ("GABA+", GABA and coedited macromolecules) in the pathophysiology and treatment of depression remain inconclusive. The aim of our study was to investigate treatment-responsive changes of GABA+ in subjects with a depressive episode receiving electroconvulsive therapy (ECT).

METHODS

In total, 41 depressed subjects (DEP) and 35 healthy controls (HC) were recruited at two independent sites in Norway and the USA. MEGA-PRESS was used for investigation of GABA+ in the anterior cingulate cortex. We assessed longitudinal and cross-sectional differences between DEP and HC, as well as the relationship between GABA+ change and change in depression severity and number of ECTs. We also assessed longitudinal differences in cognitive performance and GABA+ levels.

RESULTS

Depressive episode did not show a difference in GABA+ relative to HC (t₇₁  = -0.36, p = .72) or in longitudinal analysis (t₃₆  = 0.97, p = .34). Remitters and nonremitters did not show longitudinal (t₃₆  = 1.12, p = .27) or cross-sectional differences in GABA+. GABA+ levels were not related to changes in antidepressant response (t₃₅  = 1.12, p = .27) or treatment number (t₃₆  = 0.05, p = .96). An association between cognitive performance and GABA+ levels was found in DEP that completed cognitive effortful testing (t₁₈  = 2.4, p = .03).

CONCLUSION

Our results failed to support GABA as a marker for depression and abnormal mood state and provide no support for the anticonvulsant hypothesis of ECT. ECT-induced change in GABA concentrations may be related to change in cognitive function.

Aberrant Functional Network Connectivity Transition Probability in Major Depressive Disorder

Major depressive disorder (MDD) is a common and serious mental disorder characterized by a persistent negative feeling and tremendous sadness. In recent decades, several studies used functional network connectivity (FNC), estimated from resting state functional magnetic resonance imaging (fMRI), to investigate the biological signature of MDD. However, the majority of them have ignored the temporal change of brain interaction by focusing on static FNC (sFNC). Dynamic functional network connectivity (dFNC) that explores temporal patterns of functional connectivity (FC) might provide additional information to its static counterpart. In the current study, by applying k-means clustering on dFNC of MDD and healthy subjects (HCs), we estimated 5 different states. Next, we use the hidden Markov model as a potential biomarker to differentiate the dFNC pattern of MDD patients from HCs. Comparing MDD and HC subjects' hidden Markov model (HMM) features, we have highlighted the role of transition probabilities between states as potential biomarkers and identified that transition probability from a lightly- connected state to highly connected one reduces as symptom severity increases in MDD subjects.Index Terms- Major depressive disorder, Dynamic functional network connectivity, Machine learning, Resting- state functional magnetic resonance imaging, Hidden Markov model.

Structural changes induced by electroconvulsive therapy are associated with clinical outcome

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data

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The negative FC networks achieve predictive accuracy of 76.23% for ECT response.

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The consensus FCs represent predominately frontal, temporal and subcortical regions.

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FCs that changed significantly were concentrated in frontal and limbic networks.

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Longitudinal change overlapped with two FCs compared with FC with predictive power.

Electroconvulsive therapy (ECT) works rapidly and has been widely used to treat depressive disorders (DEP). However, identifying biomarkers predictive of response to ECT remains a priority to individually tailor treatment and understand treatment mechanisms. This study used a connectome-based predictive modeling (CPM) approach in 122 patients with DEP to determine if pre-ECT whole-brain functional connectivity (FC) predicts depressive rating changes and remission status after ECT (47 of 122 total subjects or 38.5% of sample), and whether pre-ECT and longitudinal changes (pre/post-ECT) in regional brain network biomarkers are associated with treatment-related changes in depression ratings. Results show the networks with the best predictive performance of ECT response were negative (anti-correlated) FC networks, which predict the post-ECT depression severity (continuous measure) with a 76.23% accuracy for remission prediction. FC networks with the greatest predictive power were concentrated in the prefrontal and temporal cortices and subcortical nuclei, and include the inferior frontal (IFG), superior frontal (SFG), superior temporal (STG), inferior temporal gyri (ITG), basal ganglia (BG), and thalamus (Tha). Several of these brain regions were also identified as nodes in the FC networks that show significant change pre-/post-ECT, but these networks were not related to treatment response. This study design has limitations regarding the longitudinal design and the absence of a control group that limit the causal inference regarding mechanism of post-treatment status. Though predictive biomarkers remained below the threshold of those recommended for potential translation, the analysis methods and results demonstrate the promise and generalizability of biomarkers for advancing personalized treatment strategies.

Electroconvulsive therapy electrode placement for bipolar state-related targeted engagement

Background

Electroconvulsive therapy (ECT) is an effective treatment for all bipolar states. However, ECT remains underutilized, likely stemming from stigma and the risk of neurocognitive impairment. Neuroimaging research has identified state-specific areas of aberrant brain activity that may serve as targets for therapeutic brain stimulation. Electrode placement determines the geometry of the electric field and can be either non-focal (bitemporal) or more focal (right unilateral or bifrontal). Previous research has shown that electrode placement can impact clinical and cognitive outcomes independent of seizure activity. This review critically examines the evidence that focal (unilateral or bifrontal) electrode placements target specific aberrant circuitry in specific bipolar states to optimize clinical outcomes. We hypothesize that optimal target engagement for a bipolar state will be associated with equivalent efficacy relative to bitemporal non-focal stimulation with less neurocognitive impairment.

Methods

We performed a literature search in the PubMed database. Inclusion criteria included prospective, longitudinal investigations during the ECT series with specific electrode placements within a bipolar state from 2000 to 2018.

Results

We identified investigations that met our inclusion criteria with bipolar mania (n = 6), depression (n = 6), mixed (n = 3) and catatonia (n = 1) states. These studies included clinical outcomes and several included cognitive outcomes, which were discussed separately.

Conclusions

While the heterogeneity of the studies makes comparisons difficult, important patterns included the reduced cognitive side effects, faster rate of response, and equivalent efficacy rates of the focal electrode placements (right unilateral and bifrontal) when compared to non-focal (bitemporal) placement. Further avenues for research include more robust cognitive assessments to separate procedure-related and state-related impairment. In addition, future studies could investigate novel electrode configurations with more specific target engagement for different bipolar states.

Alterations in resting-state functional connectivity in substance use disorders and treatment implications

Substance use disorders (SUD) are diseases of the brain, characterized by aberrant functioning in the neural circuitry of the brain. Resting state functional connectivity (rsFC) can illuminate these functional changes by measuring the temporal coherence of low-frequency fluctuations of the blood oxygenation level-dependent magnetic resonance imaging signal in contiguous or non-contiguous regions of the brain. Because this data is easy to obtain and analyze, and therefore fairly inexpensive, it holds promise for defining biological treatment targets in SUD, which could help maximize the efficacy of existing clinical interventions and develop new ones. In an effort to identify the most likely "treatment targets" obtainable with rsFC we summarize existing research in SUD focused on 1) the relationships between rsFC and functionality within important psychological domains which are believed to underlie relapse vulnerability 2) changes in rsFC from satiety to deprived or abstinent states 3) baseline rsFC correlates of treatment outcome and 4) changes in rsFC induced by treatment interventions which improve clinical outcomes and reduce relapse risk. Converging evidence indicates that likely "treatment target" candidates, emerging consistently in all four sections, are reduced connectivity within executive control network (ECN) and between ECN and salience network (SN). Other potential treatment targets also show promise, but the literature is sparse and more research is needed. Future research directions include data-driven prediction analyses and rsFC analyses with longitudinal datasets that incorporate time since last use into analysis to account for drug withdrawal. Once the most reliable biological markers are identified, they can be used for treatment matching, during preliminary testing of new pharmacological compounds to establish clinical potential ("target engagement") prior to carrying out costly clinical trials, and for generating hypotheses for medication repurposing.

A Critical Review and Synthesis of Clinical and Neurocognitive Effects of Noninvasive Neuromodulation Antidepressant Therapies

There is a plethora of current and emerging antidepressant therapies in the psychiatric armamentarium for the treatment of major depressive disorder. Noninvasive neuromodulation therapies are one such therapeutic category; they typically involve the transcranial application of electrical or magnetic stimulation to modulate cortical and subcortical brain activity. Although electroconvulsive therapy (ECT) has been used since the 1930s, with the prevalence of major depressive disorder and treatment-resistant depression (TRD), the past three decades have seen a proliferation of noninvasive neuromodulation antidepressant therapeutic development. The purpose of this critical review was to synthesize information regarding the clinical effects, neurocognitive effects, and possible mechanisms of action of noninvasive neuromodulation therapies, including ECT, transcranial magnetic stimulation, magnetic seizure therapy, and transcranial direct current stimulation. Considerable research has provided substantial information regarding their antidepressant and neurocognitive effects, but their mechanisms of action remain unknown. Although the four therapies vary in how they modulate neurocircuitry and their resultant antidepressant and neurocognitive effects, they are nonetheless useful for patients with acute and chronic major depressive disorder and TRD. Continued research is warranted to inform dosimetry, algorithm for administration, and integration among the noninvasive neuromodulation therapies and with other antidepressant strategies to continue to maximize their safety and antidepressant benefit.

Increased Excitability Induced in the Primary Motor Cortex by Transcranial Ultrasound Stimulation

Background: Transcranial Ultrasound Stimulation (tUS) is an emerging technique that uses ultrasonic waves to noninvasively modulate brain activity. As with other forms of non-invasive brain stimulation (NIBS), tUS may be useful for altering cortical excitability and neuroplasticity for a variety of research and clinical applications. The effects of tUS on cortical excitability are still unclear, and further complications arise from the wide parameter space offered by various types of devices, transducer arrangements, and stimulation protocols. Diagnostic ultrasound imaging devices are safe, commonly available systems that may be useful for tUS. However, the feasibility of modifying brain activity with diagnostic tUS is currently unknown. Objective: We aimed to examine the effects of a commercial diagnostic tUS device using an imaging protocol on cortical excitability. We hypothesized that imaging tUS applied to motor cortex could induce changes in cortical excitability as measured using a transcranial magnetic stimulation (TMS) motor evoked potential (MEP) paradigm. Methods: Forty-three subjects were assigned to receive either verum (n = 21) or sham (n = 22) diagnostic tUS in a single-blind design. Baseline motor cortex excitability was measured using MEPs elicited by TMS. Diagnostic tUS was subsequently administered to the same cortical area for 2 min, immediately followed by repeated post-stimulation MEPs recorded up to 16 min post-stimulation. Results: Verum tUS increased excitability in the motor cortex (from baseline) by 33.7% immediately following tUS (p = 0.009), and 32.4% (p = 0.047) 6 min later, with excitability no longer significantly different from baseline by 11 min post-stimulation. By contrast, subjects receiving sham tUS showed no significant changes in MEP amplitude. Conclusion: These findings demonstrate that tUS delivered via a commercially available diagnostic imaging ultrasound system transiently increases excitability in the motor cortex as measured by MEPs. Diagnostic tUS devices are currently used for internal imaging in many health care settings, and the present results suggest that these same devices may also offer a promising tool for noninvasively modulating activity in the central nervous system. Further studies exploring the use of diagnostic imaging devices for neuromodulation are warranted.

SMRI Biomarkers Predict Electroconvulsive Treatment Outcomes: Accuracy with Independent Data Sets

Owing to the rapid and robust clinical effects, electroconvulsive therapy (ECT) represents an optimal model to develop and test treatment predictors for major depressive disorders (MDDs), whereas imaging markers can be informative in identifying MDD patients who will respond to a specific antidepressant treatment or not. Here we aim to predict post-ECT depressive rating changes and remission status using pre-ECT gray matter (GM) in 38 MDD patients and validate in two independent data sets. Six GM regions including the right hippocampus/parahippocampus, right orbitofrontal gyrus, right inferior temporal gyrus (ITG), left postcentral gyrus/precuneus, left supplementary motor area, and left lingual gyrus were identified as predictors of ECT response, achieving accuracy of 89, 90 and 86% for remission prediction in three independent, age-matched data sets, respectively. For MDD patients, GM density increases only in the left supplementary motor cortex and left postcentral gyrus/precuneus after ECT. These results suggest that treatment-predictive and treatment-responsive regions may be anatomically different but functionally related in the context of ECT response. To the best of our knowledge, this is the first attempt to quantitatively identify and validate the ECT treatment biomarkers using multi-site GM data. We address a major clinical challenge and provide potential opportunities for more effective and timely interventions for electroconvulsive treatment.

From Behavioral Facilitation to Inhibition: The Neuronal Correlates of the Orienting and Reorienting of Auditory Attention

Successful adaptive behavior relies on the ability to automatically (bottom-up) orient attention to different locations in the environment. This results in a biphasic pattern in which reaction times (RT) are faster for stimuli that occur in the same spatial location (valid) for the first few hundred milliseconds, which is termed facilitation. This is followed by faster RT for stimuli that appear in novel locations (invalid) after longer delays, termed inhibition of return. The neuronal areas and networks involved in the transition between states of facilitation and inhibition remain poorly understood, especially for auditory stimuli. Functional magnetic resonance imaging (fMRI) data were therefore collected in a large sample of healthy volunteers (N = 52) at four separate auditory stimulus onset asynchronies (SOAs; 200, 400, 600, and 800 ms). Behavioral results indicated that facilitation (valid RT < invalid RT) occurred at the 200 ms SOA, with inhibition of return (valid RT > invalid RT) present at the three longer SOAs. fMRI results showed several brain areas varying their activation as a function of SOA, including bilateral superior temporal gyrus, anterior thalamus, cuneus, dorsal anterior cingulate gyrus, and right ventrolateral prefrontal cortex (VLPFC)/anterior insula. Right VLPFC was active during a behavioral state of facilitation, and its activation (invalid – valid trials) further correlated with behavioral reorienting at the 200 ms delay. These results suggest that right VLPFC plays a critical role when auditory attention must be quickly deployed or redeployed, demanding heightened cognitive and inhibitory control. In contrast to previous work, the ventral and dorsal frontoparietal attention networks were both active during valid and invalid trials across SOAs. These results suggest that the dorsal and ventral networks may not be as specialized during bottom-up auditory orienting as has been previously reported during visual orienting.

DATA-DRIVEN CLUSTER SELECTION FOR SUBCORTICAL SHAPE AND CORTICAL THICKNESS PREDICTS RECOVERY FROM DEPRESSIVE SYMPTOMS

Patients with major depressive disorder (MDD) who do not achieve full symptomatic recovery after antidepressant treatment have a higher risk of relapse. Compared to pharmacotherapies, electroconvulsive therapy (ECT) more rapidly produces a greater extent of response in severely depressed patients. However, prediction of which candidates are most likely to improve after ECT remains challenging. Using structural MRI data from 42 ECT patients scanned prior to ECT treatment, we developed a random forest classifier based on data-driven shape cluster selection and cortical thickness features to predict remission. Right hemisphere hippocampal shape and right inferior temporal cortical thickness was most predictive of remission, with the predicted probability of recovery decreasing when these regions were thicker prior to treatment. Remission was predicted with an average 73% balanced accuracy. Classification of MRI data may help identify treatment-responsive patients and aid in clinical decision-making. Our results show promise for the development of personalized treatment strategies.

Hemodynamic response function abnormalities in schizophrenia during a multisensory detection task

Functional magnetic resonance imaging (fMRI) of the blood oxygen level dependent (BOLD) response has commonly been used to investigate the neuropathology underlying cognitive and sensory deficits in patients with schizophrenia (SP) by examining the positive phase of the BOLD response, assuming a fixed shape for the hemodynamic response function (HRF). However, the individual phases (positive and post-stimulus undershoot (PSU)) of the HRF may be differentially affected by a variety of underlying pathologies. The current experiment used a multisensory detection task with a rapid event-related fMRI paradigm to investigate both the positive and PSU phases of the HRF in SP and healthy controls (HC). Behavioral results indicated no significant group differences during task performance. Analyses that examined the shape of the HRF indicated two distinct group differences. First, SP exhibited a reduced and/or prolonged PSU following normal task-related positive BOLD activation in secondary auditory and visual sensory areas relative to HC. Second, SP did not show task-induced deactivation in the anterior node of the default-mode network (aDMN) relative to HC. In contrast, when performing traditional analyses that focus on the positive phase, there were no group differences. Interestingly, the magnitude of the PSU in secondary auditory and visual areas was positively associated with the magnitude of task-induced deactivation within the aDMN, suggesting a possible common neural mechanism underlying both of these abnormalities (failure in neural inhibition). Results are consistent with recent views that separate neural processes underlie the two phases of the HRF and that they are differentially affected in SP. Hum Brain Mapp 37:745-755, 2016. © 2015 Wiley Periodicals, Inc.

Catatonia after cerebral hypoxia: do the usual treatments apply?

BACKGROUND

Neurologic deterioration occurring days to weeks after a cerebral hypoxic event accompanied by diffuse white matter demyelination is called delayed posthypoxic leukoencephalopathy (DPHL). Manifestations of DPHL are diverse and include dementia, gait disturbance, incontinence, pyramidal tract signs, parkinsonism, chorea, mood and thought disorders, akinetic mutism, and rarely catatonia.

METHODS

We report a case of malignant catatonia in a patient diagnosed with DPHL that was refractory to electroconvulsive therapy (ECT) and review the literature on catatonia in DPHL.

RESULTS

The patient was a 56-year-old woman with schizoaffective disorder who was admitted with catatonia 2 weeks after hospitalization for drug overdose and respiratory failure. Her catatonic symptoms did not respond to treatment of lorazepam, amantadine, methylphenidate, or 10 sessions of bilateral ECT at maximum energy. Repeat magnetic resonance imaging revealed extensive periventricular white matter lesions not present on admission scans, and she was diagnosed with DPHL.

DISCUSSION

No treatment for DPHL has been proven to be widely effective. Hyperbaric oxygen treatments may reduce the rate of development, and symptom improvement has been reported with stimulants and other psychotropic agents. Review of literature reveals rare success with GABAergic agents for catatonia after cerebral hypoxia and no cases successfully treated with ECT. There are 7 case reports of neurologic decompensation during ECT treatment after a cerebral hypoxic event.

CONCLUSION

Caution is advised when considering ECT for catatonia when delayed sequelae of cerebral hypoxia are on the differential diagnosis, as there is a dearth of evidence to support this treatment approach.

Hippocampal structural and functional changes associated with electroconvulsive therapy response

Previous animal models and structural imaging investigations have linked hippocampal neuroplasticity to electroconvulsive therapy (ECT) response, but the relationship between changes in hippocampal volume and temporal coherence in the context of ECT response is unknown. We hypothesized that ECT response would increase both hippocampal resting-state functional magnetic resonance imaging connectivity and hippocampal volumes. Patients with major depressive disorder (n=19) were scanned before and after the ECT series. Healthy, demographically matched comparisons (n=20) were scanned at one-time interval. Longitudinal changes in functional connectivity of hippocampal regions and volumes of hippocampal subfields were compared with reductions in ratings of depressive symptoms. Right hippocampal connectivity increased (normalized) after the ECT series and correlated with depressive symptom reduction. Similarly, the volumes of the right hippocampal cornu ammonis (CA2/3), dentate gyrus and subiculum regions increased, but the hippocampal subfields were unchanged relative to the comparison group. Connectivity changes were not evident in the left hippocampus, and volume changes were limited to the left CA2/3 subfields. The laterality of the right hippocampal functional connectivity and volume increases may be related to stimulus delivery method, which was predominately right unilateral in this investigation. The findings suggested that increased hippocampal functional connectivity and volumes may be biomarkers for ECT response.

Thalamus and posterior temporal lobe show greater inter-network connectivity at rest and across sensory paradigms in schizophrenia

Although a number of recent studies have examined functional connectivity at rest, few have assessed differences between connectivity both during rest and across active task paradigms. Therefore, the question of whether cortical connectivity patterns remain stable or change with task engagement continues to be unaddressed. We collected multi-scan fMRI data on healthy controls (N=53) and schizophrenia patients (N=42) during rest and across paradigms arranged hierarchically by sensory load. We measured functional network connectivity among 45 non-artifactual distinct brain networks. Then, we applied a novel analysis to assess cross paradigm connectivity patterns applied to healthy controls and patients with schizophrenia. To detect these patterns, we fit a group by task full factorial ANOVA model to the group average functional network connectivity values. Our approach identified both stable (static effects) and state-based differences (dynamic effects) in brain connectivity providing a better understanding of how individuals' reactions to simple sensory stimuli are conditioned by the context within which they are presented. Our findings suggest that not all group differences observed during rest are detectable in other cognitive states. In addition, the stable differences of heightened connectivity between multiple brain areas with thalamus across tasks underscore the importance of the thalamus as a gateway to sensory input and provide new insight into schizophrenia.

A review of longitudinal electroconvulsive therapy: neuroimaging investigations

Electroconvulsive therapy (ECT) is the most effective treatment for a depressive episode but the mechanism of action and neural correlates of response are poorly understood. Different theories have suggested that anticonvulsant properties or neurotrophic effects are related to the unique mechanism of action of ECT. This review assessed longitudinal imaging investigations (both structural and functional) associated with ECT response published from 2002 to August 2013. We identified 26 investigations that used a variety of different imaging modalities and data analysis methods. Despite these methodological differences, we summarized the major findings of each investigation and identified common patterns that exist across multiple investigations. The ECT response is associated with decreased frontal perfusion, metabolism, and functional connectivity and increased volume and neuronal chemical metabolites. The general collective of longitudinal neuroimaging investigations support both the anticonvulsant and the neurotrophic effects of ECT. We propose a conceptual framework that integrates these seemingly contradictory hypotheses.

Differential diagnosis of psychiatric symptoms after deep brain stimulation for movement disorders

OBJECTIVES

The presence of a deep brain stimulator (DBS) in a patient with a movement disorder who develops psychiatric symptoms poses unique diagnostic and therapeutic challenges for the treating clinician. Few sources discuss approaches to diagnosing and treating these symptoms.

MATERIALS AND METHODS

The authors review the literature on psychiatric complications in DBS for movement disorders and propose a heuristic for categorizing symptoms according to their temporal relationship with the DBS implantation process.

RESULTS

Psychiatric symptoms after DBS can be categorized as preimplantation, intra-operative/perioperative, stimulation related, device malfunction, medication related, and chronic stimulation related/long term. Once determined, the specific etiology of a symptom guides the practitioner in treatment.

CONCLUSIONS

A structured approach to psychiatric symptoms in DBS patients allows practitioners to effectively diagnose and treat them when they arise.

Antipsychotic drug effects in schizophrenia: a review of longitudinal FMRI investigations and neural interpretations

The evidence that antipsychotics improve brain function and reduce symptoms in schizophrenia is unmistakable, but how antipsychotics change brain function is poorly understood, especially within neuronal systems. In this review, we investigated the hypothesized normalization of the functional magnetic resonance imaging (fMRI) blood oxygen level dependent signal in the context of antipsychotic treatment. First, we conducted a systematic PubMed search to identify eight fMRI investigations that met the following inclusion criteria: case-control, longitudinal design; pre- and post-treatment contrasts with a healthy comparison group; and antipsychotic-free or antipsychotic-naive patients with schizophrenia at the start of the investigation. We hypothesized that aberrant activation patterns or connectivity between patients with schizophrenia and healthy comparisons at the first imaging assessment would no longer be apparent or "normalize" at the second imaging assessment. The included studies differed by analysis method and fMRI task but demonstrated normalization of fMRI activation or connectivity during the treatment interval. Second, we reviewed putative mechanisms from animal studies that support normalization of the BOLD signal in schizophrenia. We provided several neuronal-based interpretations of these changes of the BOLD signal that may be attributable to long-term antipsychotic administration.

Electroconvulsive therapy response in major depressive disorder: a pilot functional network connectivity resting state FMRI investigation

Major depressive disorder (MDD) is associated with increased functional connectivity in specific neural networks. Electroconvulsive therapy (ECT), the gold-standard treatment for acute, treatment-resistant MDD, but temporal dependencies between networks associated with ECT response have yet to be investigated. In the present longitudinal, case-control investigation, we used independent component analysis to identify distinct networks of brain regions with temporally coherent hemodynamic signal change and functional network connectivity (FNC) to assess component time course correlations across these networks. MDD subjects completed imaging and clinical assessments immediately prior to the ECT series and a minimum of 5 days after the last ECT treatment. We focused our analysis on four networks affected in MDD: the subcallosal cingulate gyrus, default mode, dorsal lateral prefrontal cortex, and dorsal medial prefrontal cortex (DMPFC). In an older sample of ECT subjects (n = 12) with MDD, remission associated with the ECT series reverses the relationship from negative to positive between the posterior default mode (p_DM) and two other networks: the DMPFC and left dorsal lateral prefrontal cortex (l_DLPFC). Relative to demographically healthy subjects (n = 12), the FNC between the p_DM areas and the DMPFC normalizes with ECT response. The FNC changes following treatment did not correlate with symptom improvement; however, a direct comparison between ECT remitters and non-remitters showed the pattern of increased FNC between the p_DM and l_DLPFC following ECT to be specific to those who responded to the treatment. The differences between ECT remitters and non-remitters suggest that this increased FNC between p_DM areas and the left dorsolateral prefrontal cortex is a neural correlate and potential biomarker of recovery from a depressed episode.

Auditory orienting and inhibition of return in schizophrenia: a functional magnetic resonance imaging study

Patients with schizophrenia (SP) exhibit deficits in both attentional reorienting and inhibition of return (IOR) during visual tasks. However, it is currently unknown whether these deficits are supramodal in nature and how these deficits relate to other domains of cognitive dysfunction. In addition, the neuronal correlates of this pathological orienting response have not been investigated in either the visual or auditory modality. Therefore, 30 SP and 30 healthy controls (HC) were evaluated with an extensive clinical protocol and functional magnetic resonance imaging (fMRI) during an auditory cuing paradigm. SP exhibited both increased costs and delayed IOR during auditory orienting, suggesting a prolonged interval for attentional disengagement from cued locations. Moreover, a delay in the development of IOR was associated with cognitive deficits on formal neuropsychological testing in the domains of attention/inhibition and working memory. Event-related fMRI showed the characteristic activation of a frontoparietal network (invalid trials>valid trials), but there were no differences in functional activation between patients and HC during either attentional reorienting or IOR. Current results suggest that orienting deficits are supramodal in nature in SP, and are related to higher-order cognitive deficits that directly interfere with day-to-day functioning.