Enhanced amygdala-cingulate connectivity associates with better mood in both healthy and depressive individuals after sleep deprivation.

Sleep loss robustly disrupts mood and emotion regulation in healthy individuals but can have a transient antidepressant effect in a subset of patients with depression. The neural mechanisms underlying this paradoxical effect remain unclear. Previous studies suggest that the amygdala and dorsal nexus (DN) play key roles in depressive mood regulation. Here, we used functional MRI to examine associations between amygdala- and DN-related resting-state connectivity alterations and mood changes after one night of total sleep deprivation (TSD) in both healthy adults and patients with major depressive disorder using strictly controlled in-laboratory studies. Behavioral data showed that TSD increased negative mood in healthy participants but reduced depressive symptoms in 43% of patients. Imaging data showed that TSD enhanced both amygdala- and DN-related connectivity in healthy participants. Moreover, enhanced amygdala connectivity to the anterior cingulate cortex (ACC) after TSD associated with better mood in healthy participants and antidepressant effects in depressed patients. These findings support the key role of the amygdala-cingulate circuit in mood regulation in both healthy and depressed populations and suggest that rapid antidepressant treatment may target the enhancement of amygdala-ACC connectivity.

Structural brain measures linked to clinical phenotypes in major depression replicate across clinical centres.

Abnormalities in brain structural measures, such as cortical thickness and subcortical volumes, are observed in patients with major depressive disorder (MDD) who also often show heterogeneous clinical features. This study seeks to identify the multivariate associations between structural phenotypes and specific clinical symptoms, a novel area of investigation. T1-weighted magnetic resonance imaging measures were obtained using 3 T scanners for 178 unmedicated depressed patients at four academic medical centres. Cortical thickness and subcortical volumes were determined for the depressed patients and patients' clinical presentation was characterized by 213 item-level clinical measures, which were grouped into several large, homogeneous categories by K-means clustering. The multivariate correlations between structural and cluster-level clinical-feature measures were examined using canonical correlation analysis (CCA) and confirmed with both 5-fold and leave-one-site-out cross-validation. Four broad types of clinical measures were detected based on clustering: an anxious misery composite (composed of item-level depression, anxiety, anhedonia, neuroticism and suicidality scores); positive personality traits (extraversion, openness, agreeableness and conscientiousness); reported history of physical/emotional trauma; and a reported history of sexual abuse. Responses on the item-level anxious misery measures were negatively associated with cortical thickness/subcortical volumes in the limbic system and frontal lobe; reported childhood history of physical/emotional trauma and sexual abuse measures were negatively correlated with entorhinal thickness and left hippocampal volume, respectively. In contrast, the positive traits measures were positively associated with hippocampal and amygdala volumes and cortical thickness of the highly-connected precuneus and cingulate cortex. Our findings suggest that structural brain measures may reflect neurobiological mechanisms underlying MDD features.

Childhood trauma history is linked to abnormal brain connectivity in major depression.

Patients with major depressive disorder (MDD) present with heterogeneous symptom profiles, while neurobiological mechanisms are still largely unknown. Brain network studies consistently report disruptions of resting-state networks (RSNs) in patients with MDD, including hypoconnectivity in the frontoparietal network (FPN), hyperconnectivity in the default mode network (DMN), and increased connection between the DMN and FPN. Using a large, multisite fMRI dataset (n = 189 patients with MDD, n = 39 controls), we investigated network connectivity differences within and between RSNs in patients with MDD and healthy controls. We found that MDD could be characterized by a network model with the following abnormalities relative to controls: (i) lower within-network connectivity in three task-positive RSNs [FPN, dorsal attention network (DAN), and cingulo-opercular network (CON)], (ii) higher within-network connectivity in two intrinsic networks [DMN and salience network (SAN)], and (iii) higher within-network connectivity in two sensory networks [sensorimotor network (SMN) and visual network (VIS)]. Furthermore, we found significant alterations in connectivity between a number of these networks. Among patients with MDD, a history of childhood trauma and current symptoms quantified by clinical assessments were associated with a multivariate pattern of seven different within- and between-network connectivities involving the DAN, FPN, CON, subcortical regions, ventral attention network (VAN), auditory network (AUD), VIS, and SMN. Overall, our study showed that traumatic childhood experiences and dimensional symptoms are linked to abnormal network architecture in MDD. Our results suggest that RSN connectivity may explain underlying neurobiological mechanisms of MDD symptoms and has the potential to serve as an effective diagnostic biomarker.

Convergence, preliminary findings and future directions across the four human connectome projects investigating mood and anxiety disorders.

In this paper we provide an overview of the rationale, methods, and preliminary results of the four Connectome Studies Related to Human Disease investigating mood and anxiety disorders. The first study, "Dimensional connectomics of anxious misery" (HCP-DAM), characterizes brain-symptom relations of a transdiagnostic sample of anxious misery disorders. The second study, "Human connectome Project for disordered emotional states" (HCP-DES), tests a hypothesis-driven model of brain circuit dysfunction in a sample of untreated young adults with symptoms of depression and anxiety. The third study, "Perturbation of the treatment resistant depression connectome by fast-acting therapies" (HCP-MDD), quantifies alterations of the structural and functional connectome as a result of three fast-acting interventions: electroconvulsive therapy, serial ketamine therapy, and total sleep deprivation. Finally, the fourth study, "Connectomes related to anxiety and depression in adolescents" (HCP-ADA), investigates developmental trajectories of subtypes of anxiety and depression in adolescence. The four projects use comparable and standardized Human Connectome Project magnetic resonance imaging (MRI) protocols, including structural MRI, diffusion-weighted MRI, and both task and resting state functional MRI. All four projects also conducted comprehensive and convergent clinical and neuropsychological assessments, including (but not limited to) demographic information, clinical diagnoses, symptoms of mood and anxiety disorders, negative and positive affect, cognitive function, and exposure to early life stress. The first round of analyses conducted in the four projects offered novel methods to investigate relations between functional connectomes and self-reports in large datasets, identified new functional correlates of symptoms of mood and anxiety disorders, characterized the trajectory of connectome-symptom profiles over time, and quantified the impact of novel treatments on aberrant connectivity. Taken together, the data obtained and reported by the four Connectome Studies Related to Human Disease investigating mood and anxiety disorders describe a rich constellation of convergent biological, clinical, and behavioral phenotypes that span the peak ages for the onset of emotional disorders. These data are being prepared for open sharing with the scientific community following screens for quality by the Connectome Coordinating Facility (CCF). The CCF also plans to release data from all projects that have been pre-processed using identical state-of-the-art pipelines. The resultant dataset will give researchers the opportunity to pool complementary data across the four projects to study circuit dysfunctions that may underlie mood and anxiety disorders, to map cohesive relations among circuits and symptoms, and to probe how these relations change as a function of age and acute interventions. This large and combined dataset may also be ideal for using data-driven analytic approaches to inform neurobiological targets for future clinical trials and interventions focused on clinical or behavioral outcomes.

Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data.

While aggregation of neuroimaging datasets from multiple sites and scanners can yield increased statistical power, it also presents challenges due to systematic scanner effects. This unwanted technical variability can introduce noise and bias into estimation of biological variability of interest. We propose a method for harmonizing longitudinal multi-scanner imaging data based on ComBat, a method originally developed for genomics and later adapted to cross-sectional neuroimaging data. Using longitudinal cortical thickness measurements from 663 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, we demonstrate the presence of additive and multiplicative scanner effects in various brain regions. We compare estimates of the association between diagnosis and change in cortical thickness over time using three versions of the ADNI data: unharmonized data, data harmonized using cross-sectional ComBat, and data harmonized using longitudinal ComBat. In simulation studies, we show that longitudinal ComBat is more powerful for detecting longitudinal change than cross-sectional ComBat and controls the type I error rate better than unharmonized data with scanner included as a covariate. The proposed method would be useful for other types of longitudinal data requiring harmonization, such as genomic data, or neuroimaging studies of neurodevelopment, psychiatric disorders, or other neurological diseases.

A Trial of Sertraline or Cognitive Behavior Therapy for Depression in Epilepsy.

OBJECTIVE: Limited evidence is available to guide treatment of depression for persons with epilepsy. We evaluated the comparative effectiveness of sertraline and cognitive behavior therapy (CBT) for depression, quality of life, seizures, and adverse treatment effects. METHODS: We randomly assigned 140 adult outpatients with epilepsy and current major depressive disorder to sertraline or weekly CBT for 16 weeks. The primary outcome was remission from depression based on the Mini International Neuropsychiatric Interview (MINI). Secondary outcomes included the Quality of Life in Epilepsy Inventory-89 (QOLIE-89) seizure rates, the Adverse Events Profile (AEP), the Beck Depression Inventory, and MINI Suicide Risk Module. RESULTS: In the intention-to-treat analysis, 38 (52.8%; 95% confidence interval [CI] = ±12) of the 72 subjects assigned to sertraline and 41 (60.3%; 95% CI = ±11.6) of the 68 subjects in the CBT group achieved remission; the lower bound of efficacy for both groups was greater than our historical placebo control group upper bound of 33.7%. Difference in time to remission between groups was 2.8 days (95% CI = ±0.43; p = 0.79). The percent improvement of mean QOLIE-89 scores was significant for both the CBT (25.7%; p < 0.001) and sertraline (28.3%; p < 0.001) groups. The difference in occurrence of generalized tonic-clonic seizures between groups was 0.3% (95% CI = ±8.6; p = 0.95). Suicide risk at final assessment was associated with persistent depression (p < 0.0001) but not seizures or sertraline. INTERPRETATION: Depression remitted in just over one-half of subjects following sertraline or CBT. Despite the complex psychosocial disability associated with epilepsy, improving depression benefits quality of life. Serotonin reuptake inhibition does not appear to increase seizures or suicidality in persons with epilepsy. ANN NEUROL 2019;86:552-560.

Network changes associated with transdiagnostic depressive symptom improvement following cognitive behavioral therapy in MDD and PTSD.

Despite widespread use of cognitive behavioral therapy (CBT) in clinical practice, its mechanisms with respect to brain networks remain sparsely described. In this study, we applied tools from graph theory and network science to better understand the transdiagnostic neural mechanisms of this treatment for depression. A sample of 64 subjects was included in a study of network dynamics: 33 patients (15 MDD, 18 PTSD) received longitudinal fMRI resting state scans before and after 12 weeks of CBT. Depression severity was rated on the Montgomery-Asberg Depression Rating Scale (MADRS). Thirty-one healthy controls were included to determine baseline network roles. Univariate and multivariate regression analyses were conducted on the normalized change scores of within- and between-system connectivity and normalized change score of the MADRS. Penalized regression was used to select a sparse set of predictors in a data-driven manner. Univariate analyses showed greater symptom reduction was associated with an increased functional role of the Ventral Attention (VA) system as an incohesive provincial system (decreased between- and decreased within-system connectivity). Multivariate analyses selected between-system connectivity of the VA system as the most prominent feature associated with depression improvement. Observed VA system changes are interesting in light of brain controllability descriptions: attentional control systems, including the VA system, fall on the boundary between-network communities, and facilitate integration or segregation of diverse cognitive systems. Thus, increasing segregation of the VA system following CBT (decreased between-network connectivity) may result in less contribution of emotional attention to cognitive processes, thereby potentially improving cognitive control.

Advanced Research Institute (ARI): An Effective Model for Career Development and Transition to Independence.

The vitality of geriatric mental health research requires an ongoing infusion of new investigators into the career pipeline. This report examines outcomes of the NIMH-funded, Advanced Research Institute (ARI) in Geriatric Mental Health, a national mentoring program supporting the transition of early career researchers to independent investigators. Outcome data for 119 ARI Scholars were obtained from the NIH Reporter database, CVs, and PubMed: 95.0% continue in research, 80.7% had obtained federal grants, and 45.4% had achieved an NIH R01. Among all NIMH mentored K awardees initially funded 2002-2014 (n=901), 60.4% (32/53) of ARI participants vs. 42.0% (356/848) of nonparticipants obtained an R01. Controlling for funding year, ARI participants were 1.9 times more likely to achieve R01 funding than nonparticipants. These data suggest that ARI has helped new generations of researchers to achieve independent funding, become scientific leaders, and conduct high impact research contributing to public health and patient care.

Harmonization of cortical thickness measurements across scanners and sites.

With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as "scanner effects", can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements across a total of 11 scanners. We propose a set of tools for visualizing and identifying scanner effects that are generalizable to other modalities. We then propose to use ComBat, a technique adopted from the genomics literature and recently applied to diffusion tensor imaging data, to combine and harmonize cortical thickness values across scanners. We show that ComBat removes unwanted sources of scan variability while simultaneously increasing the power and reproducibility of subsequent statistical analyses. We also show that ComBat is useful for combining imaging data with the goal of studying life-span trajectories in the brain.

Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data.

Acquiring resting-state functional magnetic resonance imaging (fMRI) datasets at multiple MRI scanners and clinical sites can improve statistical power and generalizability of results. However, multi-site neuroimaging studies have reported considerable nonbiological variability in fMRI measurements due to different scanner manufacturers and acquisition protocols. These undesirable sources of variability may limit power to detect effects of interest and may even result in erroneous findings. Until now, there has not been an approach that removes unwanted site effects. In this study, using a relatively large multi-site (4 sites) fMRI dataset, we investigated the impact of site effects on functional connectivity and network measures estimated by widely used connectivity metrics and brain parcellations. The protocols and image acquisition of the dataset used in this study had been homogenized using identical MRI phantom acquisitions from each of the neuroimaging sites; however, intersite acquisition effects were not completely eliminated. Indeed, in this study, we found that the magnitude of site effects depended on the choice of connectivity metric and brain atlas. Therefore, to further remove site effects, we applied ComBat, a harmonization technique previously shown to eliminate site effects in multi-site diffusion tensor imaging (DTI) and cortical thickness studies. In the current work, ComBat successfully removed site effects identified in connectivity and network measures and increased the power to detect age associations when using optimal combinations of connectivity metrics and brain atlases. Our proposed ComBat harmonization approach for fMRI-derived connectivity measures facilitates reliable and efficient analysis of retrospective and prospective multi-site fMRI neuroimaging studies.

Neural Correlates of Trait Rumination During an Emotion Interference Task in Women With PTSD.

Rumination, defined as repetitive, negative, self-focused thinking, is hypothesized to be a transdiagnostic factor that is associated with depression, anxiety, and posttraumatic stress disorder (PTSD). Theory has suggested that in individuals with PTSD, rumination serves as a cognitive avoidance factor that contributes to the maintenance of symptoms by inhibiting the cognitive and emotional processing of the traumatic event, subsequently interfering with treatment engagement and outcome. Little is known about the neural correlates of rumination in women with PTSD. The current study utilized functional magnetic resonance imaging (fMRI) to examine neural correlates during an emotion interference task of self-reported rumination in women with PTSD. Women with PTSD (39 participants) were recruited at a university-based trauma clinic and completed a clinical evaluation that included measures of PTSD symptoms, rumination, and depressive symptoms, as well as a neuroimaging session in which the participants were administered an emotion interference task. There was a significant relationship between self-reported rumination and activity in the right orbital frontal cortex, BA 11; t(37) = 5.62, p = .004, k = 46 during the task. This finding suggested that women with PTSD, who had higher levels of rumination, may experience greater difficulty inhibiting negative emotional stimuli compared to women with lower levels of rumination.

Comparison of brain structural variables, neuropsychological factors, and treatment outcome in early-onset versus late-onset late-life depression.

OBJECTIVE: To compare differences in gray matter volumes, white matter and subcortical gray matter hyperintensities, neuropsychological factors, and treatment outcome between early- and late-onset late-life depressed (LLD) subjects. METHODS: We conducted a prospective, nonrandomized, controlled trial at the outpatient clinics at Washington University and Duke University on 126 subjects, aged 60 years or older, who met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for major depression, scored 20 or more on the Montgomery-Asberg Depression Rating Scale (MADRS), and received neuropsychological testing and magnetic resonance imaging. Subjects were excluded for cognitive impairment or severe medical disorders. After 12 weeks of sertraline treatment, subjects' MADRS scores over time and neuropsychological factors were studied. RESULTS: Left anterior cingulate thickness was significantly smaller in the late-onset depressed group than in the early-onset LLD subjects. The late-onset group also had more hyperintensities than the early-onset LLD subjects. No differences were found in neuropsychological factor scores or treatment outcome between early-onset and late-onset LLD subjects. CONCLUSION: Age at onset of depressive symptoms in LLD subjects are associated with differences in cortical thickness and white matter and subcortical gray matter hyperintensities, but age at onset did not affect neuropsychological factors or treatment outcome.

Severe hippocampal atrophy is not associated with depression in temporal lobe epilepsy.

Depression in temporal lobe epilepsy (TLE) is common, is a strong predictor of subjective disability, and may have unique pathophysiological characteristics. Previous studies showed that reduced hippocampal volume is associated with significant depressive symptoms in patients with TLE. We utilized regions of interest analysis of high-resolution brain MRI and a reliable and valid measure of depressive symptoms to evaluate 28 consecutive adult subjects with video-EEG-confirmed TLE. Regions of interest were based on prior human and animal studies of mood and behavioral dysfunction. Forty-three percent of the entire group had significant symptoms of depression, defined by a Beck Depression Inventory (BDI) score of greater than 15. Total hippocampal volumes were significantly smaller in the group with BDI<15, (p<0.007). None of the subjects in the quartile with the smallest left hippocampal volume had a BDI score greater than 15 compared with 57% of the subjects in the upper three quartiles (p<0.008). No other limbic brain structures (amygdala, subcallosal gyrus, subgenual gyrus, gyrus rectus), or total cerebral volume were associated with depressive symptoms. Adequate hippocampal integrity may be necessary to maintain depression symptoms in mesial temporal lobe epilepsy. This finding also supports the possibility of a unique mechanism for depression in mesial temporal lobe epilepsy, such as hyperexcitable neuronal influence on the limbic network.

Serotonin signaling is associated with lower amyloid-ß levels and plaques in transgenic mice and humans.

Aggregation of amyloid-ß (Aß) as toxic oligomers and amyloid plaques within the brain appears to be the pathogenic event that initiates Alzheimer's disease (AD) lesions. One therapeutic strategy has been to reduce Aß levels to limit its accumulation. Activation of certain neurotransmitter receptors can regulate Aß metabolism. We assessed the ability of serotonin signaling to alter brain Aß levels and plaques in a mouse model of AD and in humans. In mice, brain interstitial fluid (ISF) Aß levels were decreased by 25% following administration of several selective serotonin reuptake inhibitor (SSRI) antidepressant drugs. Similarly, direct infusion of serotonin into the hippocampus reduced ISF Aß levels. Serotonin-dependent reductions in Aß were reversed if mice were pretreated with inhibitors of the extracellular regulated kinase (ERK) signaling cascade. Chronic treatment with an SSRI, citalopram, caused a 50% reduction in brain plaque load in mice. To test whether serotonin signaling could impact Aß plaques in humans, we retrospectively compared brain amyloid load in cognitively normal elderly participants who were exposed to antidepressant drugs within the past 5 y to participants who were not. Antidepressant-treated participants had significantly less amyloid load as quantified by positron emission tomography (PET) imaging with Pittsburgh Compound B (PIB). Cumulative time of antidepressant use within the 5-y period preceding the scan correlated with less plaque load. These data suggest that serotonin signaling was associated with less Aß accumulation in cognitively normal individuals.

Intermittent theta-burst stimulation to the right dorsolateral prefrontal cortex may increase potentiated startle in healthy individuals.

Repetitive transcranial magnetic stimulation (rTMS) treatment protocols targeting the right dlPFC have been effective in reducing anxiety symptoms comorbid with depression. However, the mechanism behind these effects is unclear. Further, it is unclear whether these results generalize to non-depressed individuals. We conducted a series of studies aimed at understanding the link between anxiety potentiated startle and the right dlPFC, following a previous study suggesting that continuous theta burst stimulation (cTBS) to the right dlPFC can make people more anxious. Based on these results we hypothesized that intermittent TBS (iTBS), which is thought to have opposing effects on plasticity, may reduce anxiety when targeted at the same right dlPFC region. In this double-blinded, cross-over design, 28 healthy subjects underwent 12 study visits over a 4-week period. During each of their 2 stimulation weeks, they received four 600 pulse iTBS sessions (2/day), with a post-stimulation testing session occurring 24 h following the final iTBS session. One week they received active stimulation, one week they received sham. Stimulation weeks were separated by a 1-week washout period and the order of active/sham delivery was counterbalanced across subjects. During the testing session, we induced anxiety using the threat of unpredictable shock and measured anxiety potentiated startle. Contrary to our initial hypothesis, subjects showed increased startle reactivity following active compared to sham stimulation. These results replicate work from our two previous trials suggesting that TMS to the right dlPFC increases anxiety potentiated startle, independent of both the pattern of stimulation and the timing of the post stimulation measure. Although these results confirm a mechanistic link between right dlPFC excitability and startle, capitalizing upon this link for the benefit of patients will require future exploration.

Neuromodulatory transcranial magnetic stimulation (TMS) changes functional connectivity proportional to the electric-field induced by the TMS pulse.

OBJECTIVE: Transcranial magnetic stimulation (TMS) can efficiently and robustly modulate synaptic plasticity, but little is known about how TMS affects functional connectivity (rs-fMRI). Accordingly, this project characterized TMS-induced rsFC changes in depressed patients who received 3 days of left prefrontal intermittent theta burst stimulation (iTBS). METHODS: rs-fMRI was collected from 16 subjects before and after iTBS. Correlation matrices were constructed from the cleaned rs-fMRI data. Electric-field models were conducted and used to predict pre-post changes in rs-fMRI. Site by orientation heatmaps were created for vectors centered on the stimulation site and a control site (contralateral motor cortex). RESULTS: For the stimulation site, there was a clear relationship between both site and coil orientation, and connectivity changes. As distance from the stimulation site increased, prediction accuracy decreased. Similarly, as eccentricity from the optimal orientation increased, prediction accuracy decreased. The systematic effects described above were not apparent in the heatmap centered on the control site. CONCLUSIONS: These results suggest that rs-fMRI following iTBS changes systematically as a function of the distribution of electrical energy delivered from the TMS pulse, as represented by the e-field model. SIGNIFICANCE: This finding lays the groundwork for future studies to individualize TMS targeting based on how predicted rs-fMRI changes might impact psychiatric symptoms.

Accelerated Intermittent Theta-Burst Stimulation and Treatment-Refractory Bipolar Depression: A Randomized Clinical Trial.

Importance: Bipolar disorder (BD) is chronic and disabling, with depression accounting for the majority of time with illness. Recent research demonstrated a transformative advance in the clinical efficacy of transcranial magnetic stimulation for treatment-resistant major depressive disorder (MDD) using an accelerated schedule of intermittent theta-burst stimulation (aiTBS), but the effectiveness of this treatment for treatment-refractory BD is unknown. Objective: To evaluate the effectiveness of aiTBS for treatment-refractory BD. Design, Setting, and Participants: This randomized clinical trial, conducted from March 2022 to February 2024, included individuals with treatment-resistant BD with moderate to severe depressive episodes referred from the Penn Bipolar outpatient clinic. Included patients had 2 or more prior failed antidepressant trials by Antidepressant Treatment History Form criteria and no other primary psychiatric diagnosis, were receiving a mood stabilizer for 4 or more weeks, and had a Montgomery-Åsberg Depression Rating Scale (MADRS) score of 20 or higher. Intervention: Prior to treatment, resting-state functional magnetic resonance imaging was used to compute personalized left dorsolateral prefrontal cortex target by connectivity to subgenual anterior cingulate cortex. Patients were randomized 1:1 to 10 sessions per day of imaging-guided active or sham aiTBS for 5 days with 1 session per hour at 90% resting motor threshold for 90 000 pulses total. Main Outcome and Measures: The main outcome was repeated MADRS scores before and after treatment. Results: A total of 24 participants (12 [50%] female; 12 [50%] male; mean [SD] age, 43.3 [16.9] years) were randomized to active (n = 12) or sham (n = 12) aiTBS. All participants completed treatment and 1-month follow-up. MADRS scores were significantly lower in the active group (mean [SD], 30.4 [4.8] at baseline; 10.5 [6.7] after treatment) than in the sham group (28.0 [5.4] at baseline; 25.3 [6.7] after treatment) at treatment end (estimated difference, -14.75; 95% CI, -19.73 to -9.77; P < .001; Cohen d, -2.19). Conclusion and Relevance: In this randomized clinical trial, aiTBS was more effective than sham stimulation for depressive symptom reduction in patients with treatment-resistant BD. Further trials are needed to determine aiTBS durability and to compare with other treatments. Trial Registration: ClinicalTrials.gov Identifier: NCT05228457.

Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus.

To better understand intrinsic brain connections in major depression, we used a neuroimaging technique that measures resting state functional connectivity using functional MRI (fMRI). Three different brain networks--the cognitive control network, default mode network, and affective network--were investigated. Compared with controls, in depressed subjects each of these three networks had increased connectivity to the same bilateral dorsal medial prefrontal cortex region, an area that we term the dorsal nexus. The dorsal nexus demonstrated dramatically increased depression-associated fMRI connectivity with large portions of each of the three networks. The discovery that these regions are linked together through the dorsal nexus provides a potential mechanism to explain how symptoms of major depression thought to arise in distinct networks--decreased ability to focus on cognitive tasks, rumination, excessive self-focus, increased vigilance, and emotional, visceral, and autonomic dysregulation--could occur concurrently and behave synergistically. It suggests that the newly identified dorsal nexus plays a critical role in depressive symptomatology, in effect "hot wiring" networks together; it further suggests that reducing increased connectivity of the dorsal nexus presents a potential therapeutic target.

The role of dlPFC laterality in the expression and regulation of anxiety.

Anxiety disorders are the most common mental health disorder. Therefore, elucidating brain mechanisms implicated in anxiety disorders is important avenue for developing novel treatments and improving care. The dorsolateral prefrontal cortex (dlPFC) is thought to be critically involved in working memory processes (i.e. maintenance, manipulation, suppression, etc.). In addition, there is evidence that this region is involved in anxiety regulation. However, it is unclear how working memory related dlPFC processes contribute to anxiety regulation. Furthermore, we know that laterality plays an important role in working memory related dlPFC processing, however there is no current model of dlPFC mediated anxiety regulation that accounts for potential laterality effects. To address this gap, we propose a potential framework where the dlPFC contributes to emotion regulation via working memory processing. According to this framework, working memory is a fundamental process executed by the dlPFC. However, the domain of content differs across the left and right dlPFC, with the left dlPFC sensitive to primarily verbal content, and the right dlPFC sensitive to primarily non-verbal (affective content). Critically, working memory processes allow for both the retention and suppression of affective information in working memory and the overall net effect of processing on mood will depend on the balance of retention and suppression, the valence of the information being processed (positive vs. negative), and the domain of the information (verbal vs. non-verbal). If accurate, the proposed framework predicts that effects of neuromodulation targeting the dlPFC may be dependent upon the context during which the stimulation is presented. This article is part of the Special Issue on 'Fear, Anxiety and PTSD'.

Role of the intraparietal sulcus (IPS) in anxiety and cognition: Opportunities for intervention for anxiety-related disorders.

Our objective was to review the literature on the parietal cortex and intraparietal sulcus (IPS) in anxiety-related disorders, as well as opportunities for using neuromodulation to target this region and reduce anxiety. We provide an overview of prior research demonstrating: 1) the importance of the IPS in attention, vigilance, and anxious arousal, 2) the potential for neuromodulation of the IPS to reduce unnecessary attention toward threat and anxious arousal as demonstrated in healthy samples; and 3) limited data on the potential for neuromodulation of the IPS to reduce hyper-attention toward threat and anxious arousal among clinical samples with anxiety-related disorders. Future research should evaluate the efficacy of IPS neuromodulation in fully powered clinical trials, as well as the value in augmenting evidence-based treatments for anxiety with IPS neuromodulation.