Effects of repetitive transcranial magnetic stimulation on individual variability of resting-state functional connectivity in major depressive disorder.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for major depressive disorder (MDD), but substantial heterogeneity in outcomes remains. We examined a potential mechanism of action of rTMS to normalize individual variability in resting-state functional connectivity (rs-fc) before and after a course of treatment. METHODS: Variability in rs-fc was examined in healthy controls (baseline) and individuals with MDD (baseline and after 4-6 weeks of rTMS). Seed-based connectivity was calculated to 4 regions associated with MDD: left dorsolateral prefrontal cortex (DLPFC), right subgenual anterior cingulate cortex (sgACC), bilateral insula, and bilateral precuneus. Individual variability was quantified for each region by calculating the mean correlational distance of connectivity maps relative to the healthy controls; a higher variability score indicated a more atypical/idiosyncratic connectivity pattern. RESULTS: We included data from 66 healthy controls and 252 individuals with MDD in our analyses. Patients with MDD did not show significant differences in baseline variability of rs-fc compared with controls. Treatment with rTMS increased rs-fc variability from the right sgACC and precuneus, but the increased variability was not associated with clinical outcomes. Interestingly, higher baseline variability of the right sgACC was significantly associated with less clinical improvement (p = 0.037, uncorrected; did not survive false discovery rate correction).Limitations: The linear model was constructed separately for each region of interest. CONCLUSION: This was, to our knowledge, the first study to examine individual variability of rs-fc related to rTMS in individuals with MDD. In contrast to our hypotheses, we found that rTMS increased the individual variability of rs-fc. Our results suggest that individual variability of the right sgACC and bilateral precuneus connectivity may be a potential mechanism of rTMS.

Effect of prior pharmacotherapy on remission with sequential bilateral theta-burst versus standard bilateral repetitive transcranial magnetic stimulation in treatment-resistant late-life depression.

Repetitive transcranial magnetic stimulation (rTMS) is used for treatment of late-life depression. In the FOUR-D study, sequential bilateral theta-burst stimulation (TBS) had comparable remission rates to standard bilateral rTMS. Data were analysed from the FOUR-D trial to compare remission rates between two types of rTMS based on the number and class of prior medication trials. The remission rate was higher in participants with ≤1 previous trial (43.9%) than in participants with 2 previous trials (26.5%) or ≥3 previous trials (24.6%; χ² = 6.36, d.f. = 2, P = 0.04). Utilising rTMS earlier in late-life depression may lead to better outcomes.

Deep brain stimulation of the nucleus accumbens in the treatment of severe alcohol use disorder: a phase I pilot trial.

Alcohol use disorder (AUD) is a highly prevalent, often refractory, medical illness. The symptoms of AUD are driven by dysfunction in several neurocircuits centered on the nucleus accumbens (NAc). Case reports and animal studies suggest NAc-DBS may be an effective harm-reduction treatment in severe AUD. Six patients with severe, refractory AUD underwent NAc-DBS. Safety metrics and clinical outcomes were recorded. Positron emission tomography (FDG-PET) was used to measure glucose metabolism in the NAc at baseline and 6 months. Functional magnetic resonance imaging (fMRI) was used to characterize postoperative changes in NAc functional connectivity to the rest of the brain, as well as NAc and dorsal striatal reactivity to alcoholic visual cues. This study was registered with ClinicalTrials.gov, NCT03660124. All patients experienced a reduction in craving. There was a significant reduction in alcohol consumption, alcohol-related compulsivity, and anxiety at 12 months. There was no significant change in depression. FDG-PET analysis demonstrated reduced NAc metabolism by 6 months, which correlated with improvements in compulsive drinking behaviors. Clinical improvement correlated with reduced functional connectivity between the NAc and the visual association cortex. Active DBS was associated with reduced activation of the dorsal striatum during passive viewing of alcohol-containing pictures. NAc-DBS is feasible and safe in patients with severe, otherwise refractory AUD. It is associated with a reduction in cravings and addictive behavior. A potential mechanism underlying this process is a down-regulation of the NAc, a disruption of its functional connectivity to the visual association cortex, and interference of cue-elicited dorsal striatum reactivity. Trial Registration NCT03660124 ( www.clinicaltrials.gov ).

Combined Atlas and Convolutional Neural Network-Based Segmentation of the Hippocampus from MRI According to the ADNI Harmonized Protocol.

Hippocampus atrophy is an early structural feature that can be measured from magnetic resonance imaging (MRI) to improve the diagnosis of neurological diseases. An accurate and robust standardized hippocampus segmentation method is required for reliable atrophy assessment. The aim of this work was to develop and evaluate an automatic segmentation tool (DeepHarp) for hippocampus delineation according to the ADNI harmonized hippocampal protocol (HarP). DeepHarp utilizes a two-step process. First, the approximate location of the hippocampus is identified in T1-weighted MRI datasets using an atlas-based approach, which is used to crop the images to a region-of-interest (ROI) containing the hippocampus. In the second step, a convolutional neural network trained using datasets with corresponding manual hippocampus annotations is used to segment the hippocampus from the cropped ROI. The proposed method was developed and validated using 107 datasets with manually segmented hippocampi according to the ADNI-HarP standard as well as 114 multi-center datasets of patients with Alzheimer's disease, mild cognitive impairment, cerebrovascular disease, and healthy controls. Twenty-three independent datasets manually segmented according to the ADNI-HarP protocol were used for testing to assess the accuracy, while an independent test-retest dataset was used to assess precision. The proposed DeepHarp method achieved a mean Dice similarity score of 0.88, which was significantly better than four other established hippocampus segmentation methods used for comparison. At the same time, the proposed method also achieved a high test-retest precision (mean Dice score: 0.95). In conclusion, DeepHarp can automatically segment the hippocampus from T1-weighted MRI datasets according to the ADNI-HarP protocol with high accuracy and robustness, which can aid atrophy measurements in a variety of pathologies.

Hippocampal segmentation for brains with extensive atrophy using three-dimensional convolutional neural networks.

Hippocampal volumetry is a critical biomarker of aging and dementia, and it is widely used as a predictor of cognitive performance; however, automated hippocampal segmentation methods are limited because the algorithms are (a) not publicly available, (b) subject to error with significant brain atrophy, cerebrovascular disease and lesions, and/or (c) computationally expensive or require parameter tuning. In this study, we trained a 3D convolutional neural network using 259 bilateral manually delineated segmentations collected from three studies, acquired at multiple sites on different scanners with variable protocols. Our training dataset consisted of elderly cases difficult to segment due to extensive atrophy, vascular disease, and lesions. Our algorithm, (HippMapp3r), was validated against four other publicly available state-of-the-art techniques (HippoDeep, FreeSurfer, SBHV, volBrain, and FIRST). HippMapp3r outperformed the other techniques on all three metrics, generating an average Dice of 0.89 and a correlation coefficient of 0.95. It was two orders of magnitude faster than some of the tested techniques. Further validation was performed on 200 subjects from two other disease populations (frontotemporal dementia and vascular cognitive impairment), highlighting our method's low outlier rate. We finally tested the methods on real and simulated "clinical adversarial" cases to study their robustness to corrupt, low-quality scans. The pipeline and models are available at: https://hippmapp3r.readthedocs.ioto facilitate the study of the hippocampus in large multisite studies.

APOE-ε4 associates with hippocampal volume, learning, and memory across the spectrum of Alzheimer's disease and dementia with Lewy bodies.

INTRODUCTION: Although the apolipoprotein E ε4-allele (APOE-ε4) is a susceptibility factor for Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), its relationship with imaging and cognitive measures across the AD/DLB spectrum remains unexplored. METHODS: We studied 298 patients (AD = 250, DLB = 48; 38 autopsy-confirmed; NCT01800214) using neuropsychological testing, volumetric magnetic resonance imaging, and APOE genotyping to investigate the association of APOE-ε4 with hippocampal volume and learning/memory phenotypes, irrespective of diagnosis. RESULTS: Across the AD/DLB spectrum: (1) hippocampal volumes were smaller with increasing APOE-ε4 dosage (no genotype × diagnosis interaction observed), (2) learning performance as assessed by total recall scores was associated with hippocampal volumes only among APOE-ε4 carriers, and (3) APOE-ε4 carriers performed worse on long-delay free word recall. DISCUSSION: These findings provide evidence that APOE-ε4 is linked to hippocampal atrophy and learning/memory phenotypes across the AD/DLB spectrum, which could be useful as biomarkers of disease progression in therapeutic trials of mixed disease.

Small vessel disease is linked to disrupted structural network covariance in Alzheimer's disease.

INTRODUCTION: Cerebral small vessel disease (SVD) is thought to contribute to Alzheimer's disease (AD) through abnormalities in white matter networks. Gray matter (GM) hub covariance networks share only partial overlap with white matter connectivity, and their relationship with SVD has not been examined in AD. METHODS: We developed a multivariate analytical pipeline to elucidate the cortical GM thickness systems that covary with major network hubs and assessed whether SVD and neurodegenerative pathologic markers were associated with attenuated covariance network integrity in mild AD and normal elderly control subjects. RESULTS: SVD burden was associated with reduced posterior cingulate corticocortical GM network integrity and subneocorticocortical hub network integrity in AD. DISCUSSION: These findings provide evidence that SVD is linked to the selective disruption of cortical hub GM networks in AD brains and point to the need to consider GM hub covariance networks when assessing network disruption in mixed disease.

Treatment expectations and clinical outcomes following repetitive transcranial magnetic stimulation for treatment-resistant depression.

BACKGROUND: Patient expectations, including both positive (placebo) and negative (nocebo) effects, influence treatment outcomes, yet their impact on acute repetitive transcranial magnetic stimulation (rTMS) for treatment-resistant depression (TRD) is unclear. METHODS: In this single-center retrospective chart review, 208 TRD patients completed the Stanford Expectation of Treatment Scale (SETS) before starting open-label rTMS treatment. Patients were offered two excitatory rTMS protocols (deep TMS or intermittent theta-burst stimulation), which stimulated the left dorsolateral prefrontal cortex. A minimum of 20 once daily treatments were provided, delivered over 4-6 weeks. Primary outcomes were 1) remission, measured by a post-treatment score of <8 on the Hamilton Depression Rating Scale (HAMD-17), and 2) premature discontinuation. The change in HAMD-17 scores over time was used as a secondary outcome. Physicians were blinded to SETS scores. Logistic and linear regression, adjusting for covariates, assessed SETS and HAMD-17 relationships. RESULTS: Of 208 patients, 177 had baseline and covariate data available. The mean positivity bias score (positive expectancy minus negative expectancy subscale averages) was 0.48 ± 2.21, indicating the cohort was neutral regarding the expectations of their treatment on average. Higher positive expectancy scores were significantly associated with greater odds of remission (OR = 1.90, p = 0.003) and greater reduction in HAMD-17 scores (ß = 1.30, p = 0.005) at the end of acute treatment, after adjusting for covariates. Negative expectancy was not associated with decreased odds of remission (p = 0.2) or treatment discontinuation (p = 0.8). CONCLUSIONS: Higher pre-treatment positive expectations were associated with greater remission rates with open-label rTMS in a naturalistic cohort of patients with TRD.

Insertional effect following electrode implantation: an underreported but important phenomenon.

Deep brain stimulation has revolutionized the treatment of movement disorders and is gaining momentum in the treatment of several other neuropsychiatric disorders. In almost all applications of this therapy, the insertion of electrodes into the target has been shown to induce some degree of clinical improvement prior to stimulation onset. Disregarding this phenomenon, commonly referred to as 'insertional effect', can lead to biased results in clinical trials, as patients receiving sham stimulation may still experience some degree of symptom amelioration. Similar to the clinical scenario, an improvement in behavioural performance following electrode implantation has also been reported in preclinical models. From a neurohistopathologic perspective, the insertion of electrodes into the brain causes an initial trauma and inflammatory response, the activation of astrocytes, a focal release of gliotransmitters, the hyperexcitability of neurons in the vicinity of the implants, as well as neuroplastic and circuitry changes at a distance from the target. Taken together, it would appear that electrode insertion is not an inert process, but rather triggers a cascade of biological processes, and, as such, should be considered alongside the active delivery of stimulation as an active part of the deep brain stimulation therapy.

Adverse Effects of Deep Brain Stimulation for Treatment-Resistant Depression: A Scoping Review.

Deep brain stimulation (DBS) is an emerging therapy for treatment-resistant depression (TRD). Although adverse effects have been reported in early-phase and a few randomized clinical trials, little is known about its overall safety profile, which has been assumed to be similar to that of DBS for movement disorders. The objective of this study was to pool existing safety data on DBS for TRD. Following PRISMA guidelines, PubMed was searched for English articles describing adverse outcomes after DBS for TRD. Studies were included if they reported at least 5 patients with a minimal follow-up of 6 months. After abstract (n = 607) and full-article review (n = 127), 28 articles reporting on 353 patients met criteria for final inclusion. Follow-up of the studies retrieved ranged from 12 to 96 months. Hemorrhages occurred in 0.8% of patients and infections in 10.2%. The rate of completed suicide was 2.5%. Development or worsening of depressive symptoms, anxiety, and mania occurred in 18.4%, 9.1%, and 5.1%, respectively. There were some differences between targets, but between-study heterogeneity precluded statistical comparisons. In conclusion, DBS for TRD is associated with surgical and psychiatric adverse events. Hemorrhage and infection occur at rates within an accepted range for other DBS applications. The risk of suicide after DBS for TRD is 2.5% but may not represent a significant deviation from the natural history of TRD. Finally, risks of worsening depression, anxiety, and the incidence of mania should be acknowledged when considering DBS for TRD.

Predictors of remission after repetitive transcranial magnetic stimulation for the treatment of late-life depression.

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment in patients with depression, yet treatment response remains variable. While previous work has identified predictors of remission in younger adults, relatively little data exists in late-life depression (LLD). To address this gap, data from 164 participants with LLD from a randomized non-inferiority treatment trial comparing standard bilateral rTMS to bilateral theta burst stimulation (TBS) (ClinicalTrials.gov identifier: NCT02998580) were analyzed using binary logistic regression and conditional inference tree (CIT) modeling. Lower baseline depression symptom severity, fewer prior antidepressant treatment failures, and higher global cognition predicted remission following rTMS treatment. The CIT predicted a higher likelihood of achieving remission for patients with a total score of 19 or lower on the Montgomery-Åsberg Depression Rating Scale, 1 or fewer prior antidepressant treatment failures, and a total score of 23 or higher on the Montreal Cognitive Assessment. Our results indicate that older adults with lower severity of depression, fewer antidepressant treatment failures, and higher global cognition benefit more from current forms of rTMS. The results suggest that there is potentially higher value in using rTMS earlier in the treatment pathway for depression in older adults.

Engaging Mood Brain Circuits with Psilocybin (EMBRACE): a study protocol for a randomized, placebo-controlled and delayed-start, neuroimaging trial in depression.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide across domains of health and cognition, affecting overall quality of life. Approximately one third of individuals with depression do not fully respond to treatments (e.g., conventional antidepressants, psychotherapy) and alternative strategies are needed. Recent early phase trials suggest psilocybin may be a safe and efficacious intervention with rapid-acting antidepressant properties. Psilocybin is thought to exert therapeutic benefits by altering brain network connectivity and inducing neuroplastic changes that endure for weeks post-treatment. Although early clinical results are encouraging, psilocybin's acute neurobiological effects on neuroplasticity have not been fully investigated. We aim to examine for the first time how psilocybin acutely (intraday) and subacutely (weeks) alters functional brain networks implicated in depression. METHODS: Fifty participants diagnosed with MDD or persistent depressive disorder (PDD) will be recruited from a tertiary mood disorders clinic and undergo 1:1 randomization into either an experimental or control arm. Participants will be given either 25 mg psilocybin or 25 mg microcrystalline cellulose (MCC) placebo for the first treatment. Three weeks later, those in the control arm will transition to receiving 25 mg psilocybin. We will investigate whether treatments are associated with changes in arterial spin labelling and blood oxygenation level-dependent contrast neuroimaging assessments at acute and subacute timepoints. Primary outcomes include testing whether psilocybin demonstrates acute changes in (1) cerebral blood flow and (2) functional brain activity in networks associated with mood regulation and depression when compared to placebo, along with changes in MADRS score over time compared to placebo. Secondary outcomes include changes across complementary clinical psychiatric, cognitive, and functional scales from baseline to final follow-up. Serum peripheral neurotrophic and inflammatory biomarkers will be collected at baseline and follow-up to examine relationships with clinical response, and neuroimaging measures. DISCUSSION: This study will investigate the acute and additive subacute neuroplastic effects of psilocybin on brain networks affected by depression using advanced serial neuroimaging methods. Results will improve our understanding of psilocybin's antidepressant mechanisms versus placebo response and whether biological measures of brain function can provide early predictors of treatment response. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT06072898. Registered on 6 October 2023.

A direct morphometric comparison of five labeling protocols for multi-atlas driven automatic segmentation of the hippocampus in Alzheimer's disease.

Hippocampal volumetry derived from structural MRI is increasingly used to delineate regions of interest for functional measurements, assess efficacy in therapeutic trials of Alzheimer's disease (AD) and has been endorsed by the new AD diagnostic guidelines as a radiological marker of disease progression. Unfortunately, morphological heterogeneity in AD can prevent accurate demarcation of the hippocampus. Recent developments in automated volumetry commonly use multi-template fusion driven by expert manual labels, enabling highly accurate and reproducible segmentation in disease and healthy subjects. However, there are several protocols to define the hippocampus anatomically in vivo, and the method used to generate atlases may impact automatic accuracy and sensitivity - particularly in pathologically heterogeneous samples. Here we report a fully automated segmentation technique that provides a robust platform to directly evaluate both technical and biomarker performance in AD among anatomically unique labeling protocols. For the first time we test head-to-head the performance of five common hippocampal labeling protocols for multi-atlas based segmentation, using both the Sunnybrook Longitudinal Dementia Study and the entire Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) baseline and 24-month dataset. We based these atlas libraries on the protocols of (Haller et al., 1997; Killiany et al., 1993; Malykhin et al., 2007; Pantel et al., 2000; Pruessner et al., 2000), and a single operator performed all manual tracings to generate de facto "ground truth" labels. All methods distinguished between normal elders, mild cognitive impairment (MCI), and AD in the expected directions, and showed comparable correlations with measures of episodic memory performance. Only more inclusive protocols distinguished between stable MCI and MCI-to-AD converters, and had slightly better associations with episodic memory. Moreover, we demonstrate that protocols including more posterior anatomy and dorsal white matter compartments furnish the best voxel-overlap accuracies (Dice Similarity Coefficient=0.87-0.89), compared to expert manual tracings, and achieve the smallest sample sizes required to power clinical trials in MCI and AD. The greatest distribution of errors was localized to the caudal hippocampus and the alveus-fimbria compartment when these regions were excluded. The definition of the medial body did not significantly alter accuracy among more comprehensive protocols. Voxel-overlap accuracies between automatic and manual labels were lower for the more pathologically heterogeneous Sunnybrook study in comparison to the ADNI-1 sample. Finally, accuracy among protocols appears to significantly differ the most in AD subjects compared to MCI and normal elders. Together, these results suggest that selection of a candidate protocol for fully automatic multi-template based segmentation in AD can influence both segmentation accuracy when compared to expert manual labels and performance as a biomarker in MCI and AD.

Mapping the future of interventional psychiatry for the obsessive-compulsive related disorders: A scoping review.

Body dysmorphic disorder (BDD), hoarding disorder (HD), skin-picking disorder (SPD), and hair-pulling disorder (HPD) are characterized by compulsive behaviours leading to distress and impairment. Current treatments attain only partial or non-response. Interventional psychiatric approaches may target specific regions of the brain for treatment. This scoping review maps the current literature and synthesizes key findings. Databases were searched up to June 27, 2022 for studies examining interventional psychiatric treatments for BDD, HD, SPD, and HPD, producing 910 results. Twenty were included; 16 were case reports, two were case series, and two were randomized controlled trials. Studies reported on electroconvulsive therapy (ECT) (n=7), deep brain stimulation (DBS) (n=1), and intermittent theta-burst stimulation repetitive transcranial magnetic stimulation (rTMS) (n=1) for BDD; rTMS (n=1) and transcranial direct current stimulation (n=1) for HD; gamma knife capsulotomy (n=1) and rTMS (n=1) for SPD; and rTMS (n=2) and ECT (n=1) for HPD. Four studies reported on DBS for other indications complicated by SPD or HPD. The current literature consists mainly of case reports. Future studies should be randomized, controlled, adequately powered and blinded, examining rTMS localized to the anatomical targets for each disorder. Presently, the mainstay of treatment remains disorder-specific psychotherapy with limited evidence for medications.

Adverse childhood experiences and repetitive transcranial magnetic stimulation outcomes for depression.

BACKGROUND: History of adverse childhood experiences (ACEs) is associated with poorer treatment outcomes in depression. How ACEs affect outcomes from repetitive transcranial magnetic stimulation (rTMS) is not well-defined. The primary aim was to investigate whether ACEs affect depression outcomes in patients receiving high frequency rTMS, either deep TMS (dTMS) or intermittent theta burst stimulation (iTBS), to the left dorsolateral prefrontal cortex. METHODS: The Hamilton Depression Rating Scale (HAMD-17) was collected at baseline and every 2 weeks for 4-6 weeks. Outcomes included improvement in HAMD-17 and remission. The ACE-10 questionnaire was used to quantify categories of ACEs. Data from 99 patients with MDD receiving an acute rTMS course were analyzed. RESULTS: Patients had a mean of 2.4 ACEs (SD 2.5). No significant differences in outcomes were found between dTMS or iTBS so these data were pooled. Using a continuous ACE variable showed no significant impact on outcomes. Using a categorical ACE variable (0, 1, 2, 3, 4 or more) did not reveal significant effects of ACEs on outcomes. Higher ACE was associated with steeper decrease in HAMD-17 only from baseline to week 2 but not at other times. LIMITATIONS: This was an open-label study. The well-validated ACE questionnaire does not measure severity or frequency of adversities. CONCLUSIONS: Patients with depression receiving rTMS reported on average 2.4 ACEs. ACE scores may lead to a steeper early decline in HAMD-17 but did not otherwise impact depression outcomes. Presence of high levels of ACEs should not preclude consideration of rTMS for depression.

Seasonal pattern and depression outcomes from repetitive transcranial magnetic stimulation.

Individuals with major depressive disorder (MDD) may exhibit a seasonal pattern. The impact of a seasonal pattern in depressive symptoms on rTMS outcomes is unexplored. A retrospective analysis was performed on patients with MDD receiving open-label high frequency rTMS to the left dorsolateral prefrontal cortex. Having a seasonal pattern was defined as scoring ≥ 12 on the Personal Inventory for Depression and Seasonal Affective Disorder (PIDS). Primary outcomes included improvement in the Hamilton Depression Rating Scale (HAMD) and remission. Secondary analyses included the use of the self-rated Quick Inventory of Depressive Symptomatology (QIDS) to assess for changes in atypical neurovegetative symptoms. Multiple linear regression, multiple logistic regression, and linear mixed effects analyses were performed. 46 % (58/127) of the sample had a seasonal pattern. Seasonal pattern did not significantly influence improvement in HAMD (PIDS < 12, 7.8, SD 5.9; PIDS ≥ 12, 10.4, SD 4.9 or remission (PIDS < 12, 30 %; PIDS ≥ 12, 34 %). There were equivalent degrees of improvement in atypical neurovegetative symptoms over time as assessed using the QIDS. Depression with seasonal pattern was found to respond to rTMS treatment similarly to depression without seasonal pattern, suggesting that this may be a viable treatment for this group.

Suicide Assessment and Prevention in Bipolar Disorder: How Current Evidence Can Inform Clinical Practice.

Bipolar disorder is associated with a considerable risk of suicide, and this fact must be incorporated into management of all patients with the condition. This article highlights the importance of a more nuanced understanding of the factors associated with the increased risk of suicidal behavior in people diagnosed as having bipolar disorder and interventions that could mitigate it. Several sociodemographic, clinical, environmental, and other variables have been associated with suicide attempts or deaths in bipolar disorder. Youths with bipolar disorder are a particularly vulnerable group, and their trajectory of illness could be modified by early interventions. Several medications have been studied regarding their relationship to suicide risk in bipolar disorder, and interventional psychiatry is a newer area of research focus. Finally, community-based approaches can be incorporated into a comprehensive approach to suicide prevention. This article summarizes the current understanding of key variables that can help inform a clinical risk assessment of individuals and interventions that can be employed in suicide prevention in bipolar disorder.

Predictive Value of Acute Neuroplastic Response to rTMS in Treatment Outcome in Depression: A Concurrent TMS-fMRI Trial.

OBJECTIVE: The study objective was to investigate the predictive value of functional connectivity changes induced by acute repetitive transcranial magnetic stimulation (rTMS) for clinical response in treatment-resistant depression. METHODS: Cross-sectional changes in functional connectivity induced by a single concurrent rTMS-fMRI session were assessed in 38 outpatients with treatment-resistant depression (26 of them female; mean age, 41.87 years) who subsequently underwent a 4-week course of rTMS. rTMS was delivered at 1 Hz over the right dorsolateral prefrontal cortex. Acute rTMS-induced functional connectivity changes were computed and subjected to connectome-based predictive modeling to test their association with changes in score on the Montgomery-Åsberg Depression Rating Scale (MADRS) after rTMS treatment. RESULTS: TMS-fMRI induced widespread, acute, and transient alterations in functional connectivity. The rTMS-induced connectivity changes predicted about 30% of the variance of improvement in the MADRS score. The most robust predictive associations involved connections between prefrontal regions and motor, parietal, and insular cortices and between bilateral regions of the thalamus. CONCLUSIONS: Acute rTMS-induced connectivity changes in patients with treatment-resistant depression may index macro-level neuroplasticity, relevant to interindividual variability in rTMS treatment response. Large-scale network phenomena occurring during rTMS might be used to inform prospective clinical trials.

Large-scale structural network change correlates with clinical response to rTMS in depression.

Response to repetitive transcranial magnetic stimulation (rTMS) among individuals with major depressive disorder (MDD) varies widely. The neural mechanisms underlying rTMS are thought to involve changes in large-scale networks. Whether structural network integrity and plasticity are associated with response to rTMS therapy is unclear. Structural MRIs were acquired from a series of 70 adult healthy controls and 268 persons with MDD who participated in two arms of a large randomized, non-inferiority trial, THREE-D, comparing intermittent theta-burst stimulation to high-frequency rTMS of the left dorsolateral prefrontal cortex (DLPFC). Patients were grouped according to percentage improvement on the 17-item Hamilton Depression Rating Score at treatment completion. For the entire sample and then for each treatment arm, multivariate analyses were used to characterize structural covariance networks (SCN) from cortical gray matter thickness, volume, and surface area maps from T1-weighted MRI. The association between SCNs and clinical improvement was assessed. For both study arms, cortical thickness and volume SCNs distinguished healthy controls from MDD (p = 0.005); however, post-hoc analyses did not reveal a significant association between pre-treatment SCN expression and clinical improvement. We also isolated an anticorrelated SCN between the left DLPFC rTMS target site and the subgenual anterior cingulate cortex across cortical measures (p = 0.0004). Post-treatment change in cortical thickness SCN architecture was associated with clinical improvement in treatment responders (p = 0.001), but not in non-responders. Structural network changes may underpin clinical response to rTMS, and SCNs are useful for understanding the pathophysiology of depression and neural mechanisms of plasticity and response to circuit-based treatments.