Neural Circuitry and Therapeutic Targeting of Depressive Symptoms in Schizophrenia Spectrum Disorders.

OBJECTIVE: Conceptual similarities between depressive and negative symptoms complicate biomarker and intervention development. This study employed a data-driven approach to delineate the neural circuitry underlying depressive and negative symptoms in schizophrenia spectrum disorders (SSDs). METHODS: Data from three studies were analyzed (157 participants with SSDs) to assess brain-behavior relationships: two neuroimaging studies and a randomized trial of repetitive transcranial magnetic stimulation (rTMS). Partial least squares correlation (PLSC) was used to investigate associations between resting-state functional connectivity and depressive and negative symptoms. Secondary analyses of rTMS trial data (active, N=37; sham, N=33) were used to assess relationships between PLSC-derived symptom profiles and treatment outcomes. RESULTS: PLSC identified three latent variables (LVs) relating functional brain circuitry with symptom profiles. LV1 related a general depressive symptom factor with positive associations between and within the default mode network (DMN), the frontoparietal network (FPN), and the cingulo-opercular network (CON). LV2 related negative symptoms (no depressive symptoms) via negative associations, especially between the FPN and the CON, but also between the DMN and the FPN and the CON. LV3 related a guilt and early wakening depression factor via negative rather than positive associations with the DMN, FPN, and CON. The secondary visual network had a positive association with general depressive symptoms and negative associations with guilt and negative symptoms. Active (but not sham) rTMS applied bilaterally to the dorsolateral prefrontal cortex (DLPFC) reduced general depressive but not guilt-related or negative symptoms. CONCLUSIONS: The results clearly differentiate the neural circuitry underlying depressive and negative symptoms, and segregated across the two-factor structure of depression in SSDs. These findings support divergent neurobiological pathways of depressive symptoms and negative symptoms in people with SSDs. As treatment options are currently limited, bilateral rTMS to the DLPFC is worth exploring further for general depressive symptoms in people with SSDs.

Repetitive Transcranial Magnetic Stimulation (rTMS) Treatment Reduces Variability in Brain Function in Schizophrenia: Data From a Double-Blind, Randomized, Sham-Controlled Trial.

BACKGROUND/HYPOTHESIS: There is increasing awareness of interindividual variability in brain function, with potentially major implications for repetitive transcranial magnetic stimulation (rTMS) efficacy. We perform a secondary analysis using data from a double-blind randomized controlled 4-week trial of 20 Hz active versus sham rTMS to dorsolateral prefrontal cortex (DLPFC) during a working memory task in participants with schizophrenia. We hypothesized that rTMS would change local functional activity and variability in the active group compared with sham. STUDY DESIGN: 83 participants were randomized in the original trial, and offered neuroimaging pre- and post-treatment. Of those who successfully completed both scans (n = 57), rigorous quality control left n = 42 (active/sham: n = 19/23), who were included in this analysis. Working memory-evoked activity during an N-Back (3-Back vs 1-Back) task was contrasted. Changes in local brain activity were examined from an 8 mm ROI around the rTMS coordinates. Individual variability was examined as the mean correlational distance (MCD) in brain activity pattern from each participant to others within the same group. RESULTS: We observed an increase in task-evoked left DLPFC activity in the active group compared with sham (F1,36 = 5.83, False Discovery Rate (FDR))-corrected P = .04). Although whole-brain activation patterns were similar in both groups, active rTMS reduced the MCD in activation pattern compared with sham (F1,36 = 32.57, P < .0001). Reduction in MCD was associated with improvements in attention performance (F1,16 = 14.82, P = .0014, uncorrected). CONCLUSIONS: Active rTMS to DLPFC reduces individual variability of brain function in people with schizophrenia. Given that individual variability is typically higher in schizophrenia patients compared with controls, such reduction may "normalize" brain function during higher-order cognitive processing.

Cognitive Dysfunction in the Addictions (CDiA): A Neuron to Neighbourhood Collaborative Research Program on Executive Dysfunction and Functional Outcomes in Outpatients Seeking Treatment for Addiction.

Background: Substance use disorders (SUDs) are pressing global public health problems. Executive functions (EFs) are prominently featured in mechanistic models of addiction. However, there remain significant gaps in our understanding of EFs in SUDs, including the dimensional relationships of EFs to underlying neural circuits, molecular biomarkers, disorder heterogeneity, and functional ability. To improve health outcomes for people with SUDs, interdisciplinary clinical, preclinical and health services research is needed to inform policies and interventions aligned with biopsychosocial models of addiction. Here, we introduce Cognitive Dysfunction in the Addictions (CDiA), an integrative team-science and translational research program, which aims to fill these knowledge gaps and facilitate research discoveries to enhance treatments for people living with SUDs. Methods: The CDiA Program comprises seven complementary interdisciplinary projects that aim to progress understanding of EF in SUDs and investigate new biological treatment approaches. The projects draw on a diverse sample of adults aged 18-60 (target N=400) seeking treatment for addiction, who are followed prospectively over one year to identify EF domains crucial to recovery. Projects 1-3 investigate SUD symptoms, brain circuits, and blood biomarkers and their associations with both EF domains (inhibition, working memory, and set-shifting) and functional outcomes (disability, quality of life). Projects 4 and 5 evaluate interventions for addiction and their impacts on EF: a clinical trial of repetitive transcranial magnetic stimulation and a preclinical study of potential new pharmacological treatments in rodents. Project 6 links EF to healthcare utilization and is supplemented with a qualitative investigation of EF-related barriers to treatment engagement for those with substance use concerns. Project 7 uses innovative whole-person modeling to integrate the multi-modal data generated across projects, applying clustering and deep learning methods to identify patient subtypes and drive future cross-disciplinary initiatives. Discussion: The CDiA program has promise to bring scientific domains together to uncover the diverse ways in which EFs are linked to SUD severity and functional recovery. These findings, supported by emerging clinical, preclinical, health service, and whole-person modeling investigations, will facilitate future discoveries about cognitive dysfunction in addiction and could enhance the future clinical care of individuals seeking treatment for SUDs.

Transcranial magnetic stimulation for the rehabilitation of patients with addiction: current status and future prospects.

INTRODUCTION: Substance use disorders (SUDs) are severe conditions that remain extremely challenging to treat in clinical practice. With high rates of non-response to current treatment options and several SUDs with no approved interventions, novel therapies are needed. Repetitive transcranial magnetic stimulation (rTMS) can non-invasively modulate the neurocircuitry of brain-based disorders, and investigation into its therapeutic potential for SUDs is growing rapidly. AREAS COVERED: In this review, we summarize the clinical research to date evaluating its safety and efficacy for various SUDs. We highlight the investigations comparing different stimulation parameters to present our current understanding on optimal stimulation parameters. Additionally, we cover key research avenues in the use of neuroimaging to guide treatment, cue-induction paradigms, and adjunctive or combination treatments that may optimize outcomes. EXPERT OPINION: Evidence of rTMS as an effective treatment for certain SUDs has emerged and is preliminary for others. There are a growing number of studies showing benefit and meta-analyses suggesting that rTMS can significantly reduce substance craving and consumption. However, the optimal approach has not been determined, and there is a great deal of heterogeneity in rTMS protocols and mixed outcomes. Further research into strategies for enhancing precision will be crucial in moving the field forward.

Frontostriatal salience network expansion in individuals in depression.

Decades of neuroimaging studies have shown modest differences in brain structure and connectivity in depression, hindering mechanistic insights or the identification of risk factors for disease onset1. Furthermore, whereas depression is episodic, few longitudinal neuroimaging studies exist, limiting understanding of mechanisms that drive mood-state transitions. The emerging field of precision functional mapping has used densely sampled longitudinal neuroimaging data to show behaviourally meaningful differences in brain network topography and connectivity between and in healthy individuals2-4, but this approach has not been applied in depression. Here, using precision functional mapping and several samples of deeply sampled individuals, we found that the frontostriatal salience network is expanded nearly twofold in the cortex of most individuals with depression. This effect was replicable in several samples and caused primarily by network border shifts, with three distinct modes of encroachment occurring in different individuals. Salience network expansion was stable over time, unaffected by mood state and detectable in children before the onset of depression later in adolescence. Longitudinal analyses of individuals scanned up to 62 times over 1.5 years identified connectivity changes in frontostriatal circuits that tracked fluctuations in specific symptoms and predicted future anhedonia symptoms. Together, these findings identify a trait-like brain network topology that may confer risk for depression and mood-state-dependent connectivity changes in frontostriatal circuits that predict the emergence and remission of depressive symptoms over time.

Poor Sleep is Common in Treatment-Resistant Late-life Depression and Associated With Poorer Antidepressant Response: Findings From the OPTIMUM Clinical Trial.

BACKGROUND: Adults with treatment-resistant late-life depression (TRLLD) have high rates of sleep problems; however, little is known about the occurrence and change in sleep during pharmacotherapy of TRLLD. This analysis examined: (1) the occurrence of insufficient sleep among adults with TRLLD; (2) how sleep changed during pharmacotherapy; and (3) whether treatment outcomes differed among participants with persistent insufficient sleep, worsened sleep, improved sleep, or persistent sufficient sleep. METHODS: Secondary analysis of data from 634 participants age 60+ years in the OPTIMUM clinical trial for TRLLD. Sleep was assessed using the sleep item from the Montgomery-Asberg Depression Rating Scale at the beginning (week-0) and end (week-10) of treatment. The analyses examined whether treatment outcomes differed among participants with persistent insufficient sleep, worsened sleep, improved sleep, or persistent sufficient sleep during depression treatment. RESULTS: About half (51%, n = 323) of participants reported insufficient sleep at baseline. Both persistent insufficient sleep (25%, n = 158) and worsened sleep (10%, n = 62) during treatment were associated with antidepressant nonresponse. Participants who maintained sufficient sleep (26%, n = 164) or who improved their sleep (n = 25%, n = 158) were three times more likely to experience a depression response than those with persistent insufficient sleep or worsened sleep. CONCLUSION: Insufficient sleep is common in TRLLD and it is associated with poorer treatment response to antidepressants.

Influence of Large-Scale Brain State Dynamics on the Evoked Response to Brain Stimulation.

Understanding how spontaneous brain activity influences the response to neurostimulation is crucial for the development of neurotherapeutics and brain-computer interfaces. Localized brain activity is suggested to influence the response to neurostimulation, but whether fast-fluctuating (i.e., tens of milliseconds) large-scale brain dynamics also have any such influence is unknown. By stimulating the prefrontal cortex using combined transcranial magnetic stimulation (TMS) and electroencephalography, we examined how dynamic global brain state patterns, as defined by microstates, influence the magnitude of the evoked brain response. TMS applied during what resembled the canonical Microstate C was found to induce a greater evoked response for up to 80 ms compared with other microstates. This effect was found in a repeated experimental session, was absent during sham stimulation, and was replicated in an independent dataset. Ultimately, ongoing and fast-fluctuating global brain states, as probed by microstates, may be associated with intrinsic fluctuations in connectivity and excitation-inhibition balance and influence the neurostimulation outcome. We suggest that the fast-fluctuating global brain states be considered when developing any related paradigms.

Cognitive Profiles in Treatment-Resistant Late-Life Depression and Their Impact on Treatment Outcomes.

BACKGROUND: Late-life depression (LLD) is associated with cognitive impairment, but substantial heterogeneity exists among patients. Data on the extent of cognitive impairments are inconclusive, particularly in patients with treatment-resistant depression (TRD). We investigated the cognitive profiles of patients with treatment-resistant versus nonresistant LLD and aimed to identify distinct cognitive subgroups. We also examined whether cognitive subgroups responded differentially to treatment with bilateral repetitive transcranial magnetic stimulation (rTMS). METHODS: A total of 165 patients with LLD were divided into treatment-resistant and nonresistant groups and compared with healthy control participants on measures of executive function, information processing speed, verbal learning, and memory. Cluster analysis identified subgroups based on cognitive scores. Demographic and clinical variables, as well as outcomes with bilateral rTMS, were compared between cognitive subgroups. RESULTS: Patients with LLD, particularly TRD, exhibited significantly worse cognitive performance than healthy controls. A 3-cluster solution was found, including cognitively intact (n = 89), cognitively diminished (n = 29), and impaired memory (n = 47) subgroups. Both the cognitively diminished and impaired memory subgroups had more anxiety symptoms and a higher proportion of patients with TRD than the cognitively intact group, although the latter difference did not survive multiple comparison correction. No significant differences were observed in outcomes to rTMS treatment. CONCLUSIONS: Patients with LLD exhibited impairments across cognitive domains, which were more pronounced in TRD. Three cognitive subgroups responded similarly to rTMS treatment, indicating its effectiveness across cognitive profiles, especially when medications are not tolerated. Future research should examine the relationships among cognitive subgroups, cognitive decline, and neurodegeneration.

N100 as a response prediction biomarker for accelerated 1 Hz right DLPFC-rTMS in major depression.

BACKGROUND AND OBJECTIVE: Repetitive transcranial magnetic stimulation (rTMS) is a safe and effective treatment for major depressive disorder (MDD); however, this treatment currently lacks reliable biomarkers of treatment response. TMS-evoked potentials (TEPs), measured using TMS-electroencephalography (TMS-EEG), have been suggested as potential biomarker candidates, with the N100 peak being one of the most promising. This study investigated the association between baseline N100 amplitude and 1 Hz right dorsolateral prefrontal cortex (R-DLPFC) accelerated rTMS (arTMS) treatment in MDD. METHODS: Baseline TMS-EEG sessions were performed for 23 MDD patients. All patients then underwent 40 sessions of 1 Hz R-DLPFC (F4) arTMS over 5 days and a follow-up TMS-EEG session one week after the end of theses arTMS sessions. RESULTS: Baseline N100 amplitude at F4 showed a strong positive association (p < .001) with treatment outcome. The association between the change in N100 amplitude (baseline to follow-up) and treatment outcome did not remain significant after Bonferroni correction (p = .06, corrected; p = .03, uncorrected). Furthermore, treatment responders had a significantly larger mean baseline F4 TEP amplitude during the N100 time frame compared to non-responders (p < .001). Topographically, after Bonferroni correction, F4 is the only electrode at which its baseline N100 amplitude showed a significant positive association (p < .001) with treatment outcome. LIMITATIONS: Lack of control group and auditory masking. CONCLUSION: Baseline N100 amplitude showed a strong association with treatment outcome and thus demonstrated great potential to be utilized as a cost-effective and widely adoptable biomarker of rTMS treatment in MDD.

Relationship between Patient Health Questionnaire (PHQ-9) and Montgomery-Asberg Depression Rating Scale (MADRS) total scores in older adults with major depressive disorder: An analysis of the OPTIMUM clinical trial.

BACKGROUND: The Patient Health Questionnaire (PHQ-9) and Montgomery-Asberg Depression Rating Scale (MADRS) are commonly used scales to measure depression severity in older adults. METHODS: We utilized data from the Optimizing Outcomes of Treatment-Resistant Depression in Older Adults (OPTIMUM) clinical trial to produce conversion tables relating PHQ-9 and MADRS total scores. We split the sample into training (N = 555) and validation samples (N = 187). Equipercentile linking was performed on the training sample to produce conversion tables for PHQ-9 and MADRS. We compared the original and estimated scores in the validation sample with Bland-Altman analysis. We compared the depression severity level using the original and estimated scores with Chi-square tests. RESULTS: The Bland-Altman analysis confirmed that differences between the original and estimated scores for at least 95 % of the sample fit within 1.96 standard deviations of the mean difference. Chi-square tests showed a significant difference in the proportion of participants at each depression severity category determined using the original and estimated scores. LIMITATIONS: The conversion tables should be used with caution when comparing depression severity at the individual level. CONCLUSIONS: Our conversion tables relating PHQ-9 and MADRS scores can be used to compare treatment outcomes using aggregate data in studies that only used one of these scales.

Neurophysiological and other features of working memory in older adults at risk for dementia.

Theta-gamma coupling (TGC) is a neurophysiological process that supports working memory. Working memory is associated with other clinical and biological features. The extent to which TGC is associated with these other features and whether it contributes to working memory beyond these features is unknown. Two-hundred-and-three older participants at risk for Alzheimer's dementia-98 with mild cognitive impairment (MCI), 39 with major depressive disorder (MDD) in remission, and 66 with MCI and MDD (MCI + MDD)-completed a clinical assessment, N-back-EEG, and brain MRI. Among them, 190 completed genetic testing, and 121 completed [11C] Pittsburgh Compound B ([11C] PIB) PET imaging. Hierarchical linear regressions were used to assess whether TGC is associated with demographic and clinical variables; Alzheimer's disease-related features (APOE ε4 carrier status and ß-amyloid load); and structural features related to working memory. Then, linear regressions were used to assess whether TGC is associated with 2-back performance after accounting for these features. Other than age, TGC was not associated with any non-neurophysiological features. In contrast, TGC (ß = 0.27; p = 0.006), age (ß = - 0.29; p = 0.012), and parietal cortical thickness (ß = 0.24; p = 0.020) were associated with 2-back performance. We also examined two other EEG features that are linked to working memory-theta event-related synchronization and alpha event-related desynchronization-and found them not to be associated with any feature or performance after accounting for TGC. Our findings suggest that TGC is a process that is independent of other clinical, genetic, neurochemical, and structural variables, and supports working memory in older adults at risk for dementia. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-023-09938-y.

Elevated senescence-associated secretory phenotype index in late-life bipolar disorder.

BACKGROUND: The senescence-associated secretory phenotype (SASP) is a biomarker index based on the profile of 22 blood proteins associated with cellular senescence. The SASP index has not been assessed in older patients with bipolar disorder (BD). We hypothesized that older adults with BD will have elevated cellular senescence burden as measured by the SASP index. METHODS: We measured the 22 SASP proteins to calculate the SASP index in 38 older patients with BD and 34 non-psychiatric comparison individuals (HC). RESULTS: The SASP index scores were significantly higher in BD than HC after controlling for age, sex, psychopathology, and physical health (F(1,8) = 5.37, p = 0.024, η2 = 0.08). SASP index scores were also associated with higher age, more severe depressive symptoms, and physical illness burden (p < 0.05) in the whole sample. LIMITATION: Cross-sectional study and small sample size. CONCLUSION: This is the first report of increased SASP index scores in older adults with BD. Our results suggest that dysregulation of age-related biological processes may contribute to more severe depressive symptoms and worse physical health in older adults with BD.

Canadian Network for Mood and Anxiety Treatments (CANMAT) 2023 Update on Clinical Guidelines for Management of Major Depressive Disorder in Adults: Réseau canadien pour les traitements de l'humeur et de l'anxiété (CANMAT) 2023 : Mise à jour des lignes directrices cliniques pour la prise en charge du trouble dépressif majeur chez les adultes.

BACKGROUND: The Canadian Network for Mood and Anxiety Treatments (CANMAT) last published clinical guidelines for the management of major depressive disorder (MDD) in 2016. Owing to advances in the field, an update was needed to incorporate new evidence and provide new and revised recommendations for the assessment and management of MDD in adults. METHODS: CANMAT convened a guidelines editorial group comprised of academic clinicians and patient partners. A systematic literature review was conducted, focusing on systematic reviews and meta-analyses published since the 2016 guidelines. Recommendations were organized by lines of treatment, which were informed by CANMAT-defined levels of evidence and supplemented by clinical support (consisting of expert consensus on safety, tolerability, and feasibility). Drafts were revised based on review by patient partners, expert peer review, and a defined expert consensus process. RESULTS: The updated guidelines comprise eight primary topics, in a question-and-answer format, that map a patient care journey from assessment to selection of evidence-based treatments, prevention of recurrence, and strategies for inadequate response. The guidelines adopt a personalized care approach that emphasizes shared decision-making that reflects the values, preferences, and treatment history of the patient with MDD. Tables provide new and updated recommendations for psychological, pharmacological, lifestyle, complementary and alternative medicine, digital health, and neuromodulation treatments. Caveats and limitations of the evidence are highlighted. CONCLUSIONS: The CANMAT 2023 updated guidelines provide evidence-informed recommendations for the management of MDD, in a clinician-friendly format. These updated guidelines emphasize a collaborative, personalized, and systematic management approach that will help optimize outcomes for adults with MDD.

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.

Depressive symptom trajectories with prolonged rTMS treatment.

BACKGROUND: A prolonged repetitive transcranial magnetic stimulation (rTMS) treatment course could be beneficial for some patients experiencing major depressive episodes (MDE). We identified trajectories of rTMS response in depressive patients who received an extended rTMS treatment course and sought to determine which trajectories achieved the greatest benefit with a prolonged treatment course. METHOD: We applied group-based trajectory modeling to a naturalistic dataset of depressive patients receiving a prolonged course of sequential bilateral rTMS (up to 51 treatment sessions) to the dorsolateral prefrontal cortex. Trajectories of the PHQ-9 with extended treatment courses were characterized, and we explored the association between baseline clinical characteristics and group membership using multinomial logistic regression. RESULTS: Among the 324 study participants, four trajectories were identified: "linear response, extended course" (N = 73; 22.5 %); "nonresponse" (N = 23; 7.1 %); "slowed response" (N = 159; 49.1 %); "rapid response, standard treatment length" (N = 69; 21.3 %). Only the "linear response, extended course" group showed considerable clinical improvement after receiving additional rTMS treatments. Greater baseline depressive symptoms were associated with linear response and non-response. CONCLUSION: Our results confirmed the distinctive response trajectories in depressive patients receiving rTMS and further highlighted that prolonged rTMS treatment courses may be beneficial for a subset of patients with higher initial symptom levels and linear early treatment response.

The consequences of the new European reclassification of non-invasive brain stimulation devices and the medical device regulations pose an existential threat to research and treatment: An invited opinion paper.

A significant amount of European basic and clinical neuroscience research includes the use of transcranial magnetic stimulation (TMS) and low intensity transcranial electrical stimulation (tES), mainly transcranial direct current stimulation (tDCS). Two recent changes in the EU regulations, the introduction of the Medical Device Regulation (MDR) (2017/745) and the Annex XVI have caused significant problems and confusions in the brain stimulation field. The negative consequences of the MDR for non-invasive brain stimulation (NIBS) have been largely overlooked and until today, have not been consequently addressed by National Competent Authorities, local ethical committees, politicians and by the scientific communities. In addition, a rushed bureaucratic decision led to seemingly wrong classification of NIBS products without an intended medical purpose into the same risk group III as invasive stimulators. Overregulation is detrimental for any research and for future developments, therefore researchers, clinicians, industry, patient representatives and an ethicist were invited to contribute to this document with the aim of starting a constructive dialogue and enacting positive changes in the regulatory environment.

Bayesian Optimization of Neurostimulation (BOONStim).

BACKGROUND: Transcranial magnetic stimulation (TMS) treatment response is influenced by individual variability in brain structure and function. Sophisticated, user-friendly approaches, incorporating both established functional magnetic resonance imaging (fMRI) and TMS simulation tools, to identify TMS targets are needed. OBJECTIVE: The current study presents the development and validation of the Bayesian Optimization of Neuro-Stimulation (BOONStim) pipeline. METHODS: BOONStim uses Bayesian optimization for individualized TMS targeting, automating interoperability between surface-based fMRI analytic tools and TMS electric field modeling. Bayesian optimization performance was evaluated in a sample dataset (N=10) using standard circular and functional connectivity-defined targets, and compared to grid optimization. RESULTS: Bayesian optimization converged to similar levels of total electric field stimulation across targets in under 30 iterations, converging within a 5% error of the maxima detected by grid optimization, and requiring less time. CONCLUSIONS: BOONStim is a scalable and configurable user-friendly pipeline for individualized TMS targeting with quick turnaround.

Neuromodulation for Cannabis Use: A Scoping Review.

This scoping review explores the use of neuromodulation techniques in individuals with cannabis use. Our goal was to determine whether cannabis use alters cortical excitation and inhibition in the context of neuromodulation and to determine whether neuromodulation affects craving and cannabis use patterns. A systematic search was conducted using PubMed, OVID Medline, and PsycINFO from inception to 20 December 2022. Our review identified ten relevant studies, eight of which used Transcranial Magnetic Stimulation (TMS), while two employed Transcranial Direct Current Stimulation (tDCS). Findings from TMS studies suggest that cannabis users exhibit altered cortical inhibition, with decreased short interval intracortical inhibition (SICI) compared to non-users. Single sessions of rTMS did not have any impact on cannabis craving. By contrast, two studies found that multiple sessions of rTMS reduced cannabis use, but these changes did not meet the threshold for statistical significance and both studies were limited by small sample sizes. The two included tDCS studies found contradictory results, with one showing reduced cannabis craving with active treatment and another showing no effect of active treatment on craving compared to sham. Future studies should further explore the effects of multiple treatment sessions and different neuromodulation modalities.

Causal network localization of brain stimulation targets for trait anxiety.

Transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS) can treat some neuropsychiatric disorders, but there is no consensus approach for identifying new targets. We localized causal circuit-based targets for anxiety that converged across multiple natural experiments. Lesions (n=451) and TMS sites (n=111) that modify anxiety mapped to a common normative brain circuit (r=0.68, p=0.01). In an independent dataset (n=300), individualized TMS site connectivity to this circuit predicted anxiety change (p=0.02). Subthalamic DBS sites overlapping the circuit caused more anxiety (n=74, p=0.006), thus demonstrating a network-level effect, as the circuit was derived without any subthalamic sites. The circuit was specific to trait versus state anxiety in datasets that measured both (p=0.003). Broadly, this illustrates a pathway for discovering novel circuit-based targets across neuropsychiatric disorders.