Integration of valence and conflict processing through cellular-field interactions in human subgenual cingulate during emotional face processing in treatment-resistant depression.

The subgenual anterior cingulate cortex (sgACC) has been identified as a key brain area involved in various cognitive and emotional processes. While the sgACC has been implicated in both emotional valuation and emotional conflict monitoring, it is still unclear how this area integrates multiple functions. We characterized both single neuron and local field oscillatory activity in 14 patients undergoing sgACC deep brain stimulation for treatment-resistant depression. During recording, patients were presented with a modified Stroop task containing emotional face images that varied in valence and congruence. We further analyzed spike-field interactions to understand how network dynamics influence single neuron activity in this area. Most single neurons responded to both valence and congruence, revealing that sgACC neuronal activity can encode multiple processes within the same task, indicative of multifunctionality. During peak neuronal response, we observed increased spectral power in low frequency oscillations, including theta-band synchronization (4-8 Hz), as well as desynchronization in beta-band frequencies (13-30 Hz). Theta activity was modulated by current trial congruency with greater increases in spectral power following non-congruent stimuli, while beta desynchronizations occurred regardless of emotional valence. Spike-field interactions revealed that local sgACC spiking was phase-locked most prominently to the beta band, whereas phase-locking to the theta band occurred in fewer neurons overall but was modulated more strongly for neurons that were responsive to task. Our findings provide the first direct evidence of spike-field interactions relating to emotional cognitive processing in the human sgACC. Furthermore, we directly related theta oscillatory dynamics in human sgACC to current trial congruency, demonstrating it as an important regulator during conflict detection. Our data endorse the sgACC as an integrative hub for cognitive emotional processing through modulation of beta and theta network activity.

Functional brain network features specify DBS outcome for patients with treatment resistant depression.

Deep brain stimulation (DBS) has shown therapeutic benefits for treatment resistant depression (TRD). Stimulation of the subcallosal cingulate gyrus (SCG) aims to alter dysregulation between subcortical and cortex. However, the 50% response rates for SCG-DBS indicates that selection of appropriate patients is challenging. Since stimulation influences large-scale network function, we hypothesized that network features can be used as biomarkers to inform outcome. In this pilot project, we used resting-state EEG recorded longitudinally from 10 TRD patients with SCG-DBS (11 at baseline). EEGs were recorded before DBS-surgery, 1-3 months, and 6 months post surgery. We used graph theoretical analysis to calculate clustering coefficient, global efficiency, eigenvector centrality, energy, and entropy of source-localized EEG networks to determine their topological/dynamical features. Patients were classified as responders based on achieving a 50% or greater reduction in Hamilton Depression (HAM-D) scores from baseline to 12 months post surgery. In the delta band, false discovery rate analysis revealed that global brain network features (segregation, integration, synchronization, and complexity) were significantly lower and centrality of subgenual anterior cingulate cortex (ACC) was higher in responders than in non-responders. Accordingly, longitudinal analysis showed SCG-DBS increased global network features and decreased centrality of subgenual ACC. Similarly, a clustering method separated two groups by network features and significant correlations were identified longitudinally between network changes and depression symptoms. Despite recent speculation that certain subtypes of TRD are more likely to respond to DBS, in the SCG it seems that underlying brain network features are associated with ability to respond to DBS. SCG-DBS increased segregation, integration, and synchronizability of brain networks, suggesting that information processing became faster and more efficient, in those patients in whom it was lower at baseline. Centrality results suggest these changes may occur via altered connectivity in specific brain regions especially ACC. We highlight potential mechanisms of therapeutic effect for SCG-DBS.

Accelerated sequential bilateral theta-burst stimulation in major depression: an open trial.

Theta burst stimulation (TBS) is approved and widely used in the treatment of treatment resistant-major depression. More recently, accelerated protocols delivering multiple treatments per day have been shown to be efficacious and potentially enhance outcomes compared to once daily protocols. Meanwhile, bilateral treatment protocols have also been increasingly tested to enhance outcomes. Here, we examined the efficacy and safety of accelerated bilateral TBS in major depressive disorder (MDD). In this open label pilot study, 25 patients with MDD (60%: women; mean age (SD): 45.24 (12.22)) resistant to at least one antidepressant, received bilateral TBS, consisting of 5 sequential bilateral intermittent TBS (iTBS) (600 pulses) and continuous TBS (cTBS) (600 pulses) treatments delivered to the left and right dorsolateral prefrontal cortex (DLPFC), respectively, daily for 5 days at 120% resting motor threshold. Outcome measures were post-treat treatment changes at day 5 and 2-weeks in Hamilton Depression Rating Scale (HDRS-17) scores and response (≥ 50% reduction from the baseline scores) and remission (≤ 7) rates. There was a significant reduction in HDRS scores at day 5 (p < 0.001) and 2-weeks post treatment (p < 0.001). The response rates increased from 20% at day 5 to 32% at 2-weeks post treatment suggesting delayed clinical effects. However, reduction in symptom scores between two post treatment endpoints was non-significant. 60% of patients could not tolerate the high intensity stimulation. No major adverse events occurred. Open label uncontrolled study with small sample size. These preliminary findings suggest that accelerated bilateral TBS may be clinically effective and safe for treatment resistant depression. Randomized sham-controlled trials are needed to establish the therapeutic role of accelerated bilateral TBS in depression.Trial registration: ClinicalTrials.gov, NCT10001858.

Competencies for Repetitive Transcranial Magnetic Stimulation in Postgraduate Medical Education: Expert Consensus Using a Modified Delphi Process.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is recommended in Canadian guidelines as a first-line treatment for major depressive disorder. With the shift towards competency-based medical education, it remains unclear how to determine when a resident is considered competent in applying knowledge of rTMS to patient care. Given inconsistencies between postgraduate training programmes with regards to training requirements, defining competencies will improve the standard of care in rTMS delivery. OBJECTIVE: The goal of this study was to develop competencies for rTMS that can be implemented into a competency-based training curriculum in postgraduate training programmes. METHODS: A working group drafted competencies for postgraduate psychiatry trainees. Fourteen rTMS experts from across Canada were invited to participate in the modified Delphi process. RESULTS: Ten experts participated in all three rounds of the modified Delphi process. A total of 20 items reached a consensus. There was improvement in the Cronbach's alpha over the rounds of modified Delphi process (Cronbach's alpha increased from 0.554 to 0.824) suggesting improvement in internal consistency. The intraclass correlation coefficient (ICC) increased from 0.543 to 0.805 suggesting improved interrater agreement. CONCLUSIONS: This modified Delphi process resulted in expert consensus on competencies to be acquired during postgraduate medical education programmes where a learner is training to become competent as a consultant and/or practitioner in rTMS treatment. This is a field that still requires development, and it is expected that as more evidence emerges the competencies will be further refined. These results will help the development of other curricula in interventional psychiatry.

High-resolution virtual brain modeling personalizes deep brain stimulation for treatment-resistant depression: Spatiotemporal response characteristics following stimulation of neural fiber pathways.

Over the past 15 years, deep brain stimulation (DBS) has been actively investigated as a groundbreaking therapy for patients with treatment-resistant depression (TRD); nevertheless, outcomes have varied from patient to patient, with an average response rate of ∼50%. The engagement of specific fiber tracts at the stimulation site has been hypothesized to be an important factor in determining outcomes, however, the resulting individual network effects at the whole-brain scale remain largely unknown. Here we provide a computational framework that can explore each individual's brain response characteristics elicited by selective stimulation of fiber tracts. We use a novel personalized in-silico approach, the Virtual Big Brain, which makes use of high-resolution virtual brain models at a mm-scale and explicitly reconstructs more than 100,000 fiber tracts for each individual. Each fiber tract is active and can be selectively stimulated. Simulation results demonstrate distinct stimulus-induced event-related potentials as a function of stimulation location, parametrized by the contact positions of the electrodes implanted in each patient, even though validation against empirical patient data reveals some limitations (i.e., the need for individual parameter adjustment, and differential accuracy across stimulation locations). This study provides evidence for the capacity of personalized high-resolution virtual brain models to investigate individual network effects in DBS for patients with TRD and opens up novel avenues in the personalized optimization of brain stimulation.

Personality changes with subcallosal cingulate deep brain stimulation in patients with treatment-resistant depression.

BACKGROUND: Deep brain stimulation (DBS) is a promising investigational approach for treatment-resistant depression. However, reports suggesting changes in personality with DBS for movement disorders have raised clinical and ethical concerns. We prospectively examined changes in personality dimensions and antidepressant response to subcallosal cingulate (SCC)-DBS for treatment-resistant depression. METHODS: Twenty-two patients with treatment-resistant depression underwent SCC-DBS. We used the NEO Five-Factor Inventory for personality assessment at baseline and every 3 months until 15 months post-DBS. We assessed depression severity monthly using the Hamilton Depression Rating Scale. RESULTS: We found a significant decrease in neuroticism (p = 0.002) and an increase in extraversion (p = 0.001) over time, showing a change toward normative data. Improvement on the Hamilton Depression Rating Scale was correlated with decreases in neuroticism at 6 months (p = 0.001) and 12 months (p < 0.001), and with an increase in extraversion at 12 months (p = 0.01). Changes on the Hamilton Depression Rating Scale over time had a significant covariate effect on neuroticism (p < 0.001) and extraversion (p = 0.001). Baseline openness and agreeableness predicted response to DBS at 6 (p = 0.006) and 12 months (p = 0.004), respectively. LIMITATIONS: Limitations included a small sample size, a lack of sham control and the use of subjective personality evaluation. CONCLUSION: We observed positive personality changes following SCC-DBS, with reduced neuroticism and increased extraversion related to clinical improvement in depression, suggesting a state effect. As well, pretreatment levels of openness and agreeableness may have predicted subsequent response to DBS. The NEO Five-Factor Inventory assessment may have a role in clinical decision-making and prognostic evaluation in patients with treatment-resistant depression who undergo SCC-DBS.

Treatment-resistant major depressive disorder: Canadian expert consensus on definition and assessment.

BACKGROUND: Treatment-resistant depression (TRD) is a debilitating chronic mental illness that confers increased morbidity and mortality, decreases the quality of life, impairs occupational, social, and offspring development, and translates into increased costs on the healthcare system. The goal of this study is to reach an agreement on the concept, definition, staging model, and assessment of TRD. METHODS: This study involved a review of the literature and a modified Delphi process for consensus agreement. The Appraisal of Guidelines for Research & Evaluation II guidelines were followed for the literature appraisal. Literature was assessed for quality and strength of evidence using the grading, assessment, development, and evaluations system. Canadian national experts in depression were invited for the modified Delphi process based on their prior clinical and research expertize. Survey items were considered to have reached a consensus if 80% or more of the experts supported the statement. RESULTS: Fourteen Canadian experts were recruited for three rounds of surveys to reach a consensus on a total of 27 items. Experts agreed that a dimensional definition for treatment resistance was a useful concept to describe the heterogeneity of this illness. The use of staging models and clinical scales was recommended in evaluating depression. Risk factors and comorbidities were identified as potential predictors for treatment resistance. CONCLUSIONS: TRD is a meaningful concept both for clinical practice and research. An operational definition for TRD will allow for opportunities to improve the validity of predictors and therapeutic options for these patients.

Quality of Life Impacts of Bright Light Treatment, Fluoxetine, and the Combination in Patients with Nonseasonal Major Depressive Disorder: A Randomized Clinical Trial.

OBJECTIVE: Bright light therapy is increasingly recommended (alone or in combination with antidepressant medication) to treat symptoms of nonseasonal major depressive disorder (MDD). However, little is known about its impacts on quality of life (QoL), a holistic, patient-valued outcome. METHODS: This study utilizes secondary outcome data from an 8-week randomized, controlled, double blind trial comparing light monotherapy (n = 32), fluoxetine monotherapy (n = 30), and the combination of these (n = 27) to placebo (n = 30). QoL was assessed using the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (Q-LES-Q-SF). Treatment-related differences in QoL improvements were assessed using a repeated measures analysis of variance. The influence of potential predictors of QoL (demographic variables and change in depressive symptoms) were investigated via hierarchical linear regression. RESULTS: Q-LES-Q-SF scores significantly improved across all treatment conditions; however, no significant differences were observed between treatment arms. QoL remained poor relative to community norms by the end of the trial period: Across conditions, 70.6% of participants had significantly impaired QoL at the 8-week assessment. Reduction in depressive scores was a significant predictor of improved QoL, with the final model accounting for 54% of variance in QoL change scores. CONCLUSION: The findings of this study emphasize that improvement in QoL and reduction in depressive symptoms in MDD, while related, cannot be taken to be synonymous. Adjunctive therapies may be required to address unmet QoL needs in patients with MDD receiving antidepressant or light therapies. Further research is required to explore additional predictors of QoL in order to better refine treatments for MDD.

Automatic classification of major depression disorder using arterial spin labeling MRI perfusion measurements.

AIM: Neuroimaging-based multivariate pattern-recognition methods have been successfully used to develop diagnostic algorithms to distinguish patients with major depressive disorder (MDD) from healthy controls (HC). We developed and evaluated the accuracy of a multivariate classification method for the differentiation of MDD and HC using cerebral blood flow (CBF) features measured by non-invasive arterial spin labeling (ASL) MRI. METHODS: Twenty-two medication-free patients with the diagnosis of MDD based on DSM-IV criteria and 22 HC underwent pseudo-continuous 3-D-ASL imaging to assess CBF. Using an atlas-based approach, regional CBF was determined in various brain regions and used together with sex and age as classification features. A linear kernel support vector machine was used for feature ranking and selection as well as for the classification of patients with MDD and HC. Permutation testing was used to test for significance of the classification results. RESULTS: The automatic classifier based on CBF features showed a statistically significant accuracy of 77.3% (P = 0.004) with a specificity of 80% and sensitivity of 75% for classification of MDD versus HC. The features that contributed to the classification were sex and regional CBF of the cortical, limbic, and paralimbic regions. CONCLUSION: Machine-learning models based on CBF measurements are capable of differentiating MDD from HC with high accuracy. The use of larger study cohorts and inclusion of other imaging measures may improve the performance of the classifier to achieve the accuracy required for clinical application.

The 5-HTTLPR and BDNF polymorphisms moderate the association between uncinate fasciculus connectivity and antidepressants treatment response in major depression.

Symptom improvement in depression due to antidepressant treatment is highly variable and clinically unpredictable. Linking neuronal connectivity and genetic risk factors in predicting antidepressant response has clinical implications. Our investigation assessed whether indices of white matter integrity, serotonin transporter-linked polymorphism (5-HTTLPR) and brain-derived neurotrophic factor (BDNF) val66met polymorphism predicted magnitude of depression symptom change following antidepressant treatment. Fractional anisotropy (FA) was used as an indicator of white matter integrity and was assessed in the uncinate fasciculus and superior longitudinal fasciculus using tract-based spatial statistics (TBSS) and probabilistic tractography. Forty-six medication-free patients with major depressive disorder participated in a diffusion tensor imaging scan prior to completing an 8-week treatment regime with citalopram or quetiapine XR. Indexed improvements in Hamilton Depression Rating Scale score from baseline to 8-week endpoint were used as an indicator of depression improvement. Carriers of the BDNF met allele exhibited lower FA values in the left uncinate fasciculus relative to val/val individuals [F(1, 40) = 7.314, p = 0.009]. Probabilistic tractography identified that higher FA in the left uncinate fasciculus predicted percent change in depression severity, with BDNF moderating this association [F(3, 30) = 3.923, p = 0.018]. An interaction between FA in the right uncinate fasciculus and 5-HTTLPR also predicted percent change in depression severity [F(5, 25) = 5.315, p = 0.002]. Uncorrected TBSS results revealed significantly higher FA in hippocampal portions of the cingulum bundle in responders compared to non-responders (p = 0.016). The predictive value of prefrontal and amygdala/hippocampal WM connectivity on antidepressant treatment response may be influenced by 5-HTTLPR and BDNF polymorphisms in MDD.