Changes in brain connectivity during a sham-controlled, transcranial magnetic stimulation trial for depression

Effectiveness of non-invasive brain stimulation on depressive symptoms targeting prefrontal cortex in functional magnetic resonance imaging studies: a combined systematic review and meta-analysis

The prefrontal cortex (PFC) is a critical non-invasive brain stimulation (NIBS) target for treating depression. However, the alterations of brain activations post-intervention remain inconsistent and the clinical moderators that could improve symptomatic effectiveness are unclear. The study aim was to systematically review the effectiveness of NIBS on depressive symptoms targeting PFC in functional magnetic resonance imaging (fMRI) studies. In our study, we delivered a combined activation likelihood estimation (ALE) meta-analysis and meta-regression. Until November 2020, three databases (PubMed, Web of Science, EMBASE) were searched and 14 studies with a total sample size of 584 were included in the ALE meta-analysis; after NIBS, four clusters in left cerebrum revealed significant activation while two clusters in right cerebrum revealed significant deactivation (P < 0.001, cluster size >150 mm3). Eleven studies were statistically reanalyzed for depressive symptoms pre-post active-NIBS and the pooled effect size was very large [(d = 1.82, 95%CI (1.23, 2.40)]; significant moderators causing substantial heterogeneity (Chi squared = 75.25, P < 0.01; I 2 = 87%) were detected through subgroup analysis and univariate meta-regression. Multivariate meta-regression was then conducted accordingly and the model suggested good fitness (Q = 42.32, P < 0.01). In all, NIBS targeting PFC balanced three core depressive-related neurocognitive networks (the salience network, the default mode network, and the central executive network); the striatum played a central role and might serve as a candidate treatment biomarker; gender difference, treatment-resistant condition, comorbidity, treatment duration, and localization all contributed to moderating depressive symptoms during NIBS. More high-quality, multi-center randomized controlled trails delivering personalized NIBS are needed for clinical practice in the future.

The effect of repetitive transcranial magnetic stimulation on the Hamilton Depression Rating Scale-17 criterion in patients with major depressive disorder without psychotic features: a systematic review and meta-analysis of intervention studies

AIM

In line with the publication of clinical information related to the therapeutic process of repetitive transcranial magnetic stimulation (rTMS) and the updating of relevant treatment guidelines, the present meta-analysis study was designed and conducted to determine the effect of repetitive transcranial magnetic stimulation (rTMS) on the Hamilton Depression Rating Scale-17 (HDRS-17) criterion in patients with major depressive disorder (MDD) without psychotic features.

METHODS

In this study, a systematic search was conducted in electronic databases such as PubMed [Medline], Scopus, Web of Science, Embase, Ovid, Cochrane Library, and ClinicalTrials. gov using relevant keywords. The search period in this study was from January 2000 to January 2022, which was updated until May 2023. Randomized controlled trials (RCTs) that determined the effect of repetitive transcranial magnetic stimulation (rTMS) on the Hamilton Depression Rating Scale-17 (HDRS-17) criterion in patients with major depressive disorder (MDD) without psychotic features were included in the analysis. The quality of the included RCTs was assessed using the Cochrane Risk of Bias checklist. Statistical analyses were performed using STATA (Version 16) and RevMan (Version 5).

RESULTS

Following the combination of results from 16 clinical trial studies in the present meta-analysis, it was found that the mean Hamilton Depression Rating Scale-17 (HDRS-17) in patients with major depressive disorder (MDD) decreases by an average of 1.46 units (SMD: -1.46; % 95 CI: -1.65, -1.27, I square: 45.74%; P heterogeneity: 0.56). Subgroup analysis results indicated that the standardized mean difference of Hamilton Depression Rating Scale-17 (HDRS-17) varied based on the number of treatment sessions: patients receiving 10 or fewer repetitive transcranial magnetic stimulation (rTMS) sessions showed a mean Hamilton Depression Rating Scale-17 (HDRS-17) reduction of 2.60 units (SMD: -2.60; % 95 CI: -2.86, -2.33, I square: 55.12%; P heterogeneity: 0.55), while those receiving 11 to 20 sessions showed a mean Hamilton Depression Rating Scale-17 (HDRS-17) reduction of 0.28 units (SMD: -0.28; % 95 CI: -0.65, -0.09, I square: 39.91%; P heterogeneity: 0.89).

CONCLUSION

In conclusion, our meta-analysis demonstrates the efficacy of repetitive transcranial magnetic stimulation (rTMS) in reducing depressive symptoms in major depressive disorder (MDD) patients. The complex results of subgroup analysis revealed insight on the possible benefits of a more focused strategy with fewer sessions, as well as the impact of treatment session frequency. These findings add to our understanding of repetitive transcranial magnetic stimulation (rTMS) as a therapeutic intervention for the treatment of major depressive illnesses.

Applications of Functional Magnetic Resonance Imaging to the Study of Functional Connectivity and Activation in Neurological Disease: A Scoping Review of the Literature

BACKGROUND

Functional magnetic resonance imaging (fMRI) has transformed our understanding of brain's functional architecture, providing critical insights into neurological diseases. This scoping review synthesizes the current landscape of fMRI applications across various neurological domains, elucidating the evolving role of both task-based and resting-state fMRI in different settings.

METHODS

We conducted a comprehensive scoping review following the Preferred Reporting Items for Systematic Review and Meta-Analyses Extension for Scoping Reviews guidelines. Extensive searches in Medline/PubMed, Embase, and Web of Science were performed, focusing on studies published between 2003 and 2023 that utilized fMRI to explore functional connectivity and regional activation in adult patients with neurological conditions. Studies were selected based on predefined inclusion and exclusion criteria, with data extracted.

RESULTS

We identified 211 studies, covering a broad spectrum of neurological disorders including mental health, movement disorders, epilepsy, neurodegeneration, traumatic brain injury, cerebrovascular accidents, vascular abnormalities, neurorehabilitation, neuro-critical care, and brain tumors. The majority of studies utilized resting-state fMRI, underscoring its prominence in identifying disease-specific connectivity patterns. Results highlight the potential of fMRI to reveal the underlying pathophysiological mechanisms of various neurological conditions, facilitate diagnostic processes, and potentially guide therapeutic interventions.

CONCLUSIONS

fMRI serves as a powerful tool for elucidating complex neural dynamics and pathologies associated with neurological diseases. Despite the breadth of applications, further research is required to standardize fMRI protocols, improve interpretative methodologies, and enhance the translation of imaging findings to clinical practice. Advances in fMRI technology and analytics hold promise for improving the precision of neurological assessments and interventions.

Magnetic resonance imaging connectivity features associated with response to transcranial magnetic stimulation in major depressive disorder

Transcranial magnetic stimulation (TMS) is an FDA-approved neuromodulation treatment for major depressive disorder (MDD), thought to work by altering dysfunctional brain connectivity pathways, or by indirectly modulating the activity of subcortical brain regions. Clinical response to TMS remains highly variable, highlighting the need for baseline predictors of response and for understanding brain changes associated with response. This systematic review examined brain connectivity features, and changes in connectivity features, associated with clinical improvement following TMS in MDD. Forty-one studies met inclusion criteria, including 1097 people with MDD. Most studies delivered one of two types of TMS to left dorsolateral prefrontal cortex and measured connectivity using resting-state functional MRI. The subgenual anterior cingulate cortex was the most well-studied brain region, particularly its connectivity with the TMS target or with the "executive control network" of brain regions. There was marked heterogeneity in findings. There is a need for greater understanding of how cortical TMS modulates connectivity with, and the activity of, subcortical regions, and how these effects change within and across treatment sessions.

A cognitive neural circuit biotype of depression showing functional and behavioral improvement after transcranial magnetic stimulation in the B-SMART-fMRI trial

We previously identified a cognitive biotype of depression characterized by treatment resistance, impaired cognitive control behavioral performance and dysfunction in the cognitive control circuit, comprising the dorsolateral prefrontal cortex (dLPFC) and dorsal anterior cingulate cortex (dACC). Therapeutic transcranial magnetic stimulation (TMS) to the left dLPFC is a promising option for individuals whose depression does not respond to pharmacotherapy. Here, 43 veterans with treatment-resistant depression were assessed before TMS, after early TMS and post-TMS using functional magnetic resonance imaging during a Go-NoGo paradigm, behavioral cognitive control tests and symptom questionnaires. Stratifying veterans at baseline based on task-evoked dLPFC-dACC connectivity, we demonstrate that TMS-related improvement in cognitive control circuit connectivity and behavioral performance is specific to individuals with reduced connectivity at baseline (cognitive biotype +), whereas individuals with intact connectivity at baseline (cognitive biotype -) did not demonstrate significant changes. Our findings show that dLPFC-dACC connectivity during cognitive control is both a promising diagnostic biomarker for a cognitive biotype of depression and a response biomarker for cognitive improvement after TMS applied to the dLPFC.

Transcranial Magnetic Stimulation and Transcranial Direct Current Stimulation Across Mental Disorders: A Systematic Review and Dose-Response Meta-Analysis

Importance

Noninvasive brain stimulation (NIBS) interventions have been shown to be efficacious in several mental disorders, but the optimal dose stimulation parameters for each disorder are unknown.

Objective

To define NIBS dose stimulation parameters associated with the greatest efficacy in symptom improvement across mental disorders.

Data Sources

Studies were drawn from an updated (to April 30, 2023) previous systematic review based on a search of PubMed, OVID, and Web of Knowledge.

Study Selection

Randomized clinical trials were selected that tested transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS) for any mental disorder in adults aged 18 years or older.

Data Extraction and Synthesis

Two authors independently extracted the data. A 1-stage dose-response meta-analysis using a random-effects model was performed. Sensitivity analyses were conducted to test robustness of the findings. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline.

Main Outcomes and Measures

The main outcome was the near-maximal effective doses of total pulses received for TMS and total current dose in coulombs for tDCS.

Results

A total of 110 studies with 4820 participants (2659 men [61.4%]; mean [SD] age, 42.3 [8.8] years) were included. The following significant dose-response associations emerged with bell-shaped curves: (1) in schizophrenia, high-frequency (HF) TMS on the left dorsolateral prefrontal cortex (LDLPFC) for negative symptoms (χ2 = 9.35; df = 2; P = .009) and TMS on the left temporoparietal junction for resistant hallucinations (χ2 = 36.52; df = 2; P < .001); (2) in depression, HF-DLPFC TMS (χ2 = 14.49; df = 2; P < .001); (3) in treatment-resistant depression, LDLPFC tDCS (χ2 = 14.56; df = 2; P < .001); and (4) in substance use disorder, LDLPFC tDCS (χ2 = 33.63; df = 2; P < .001). The following significant dose-response associations emerged with plateaued or ascending curves: (1) in depression, low-frequency (LF) TMS on the right DLPFC (RDLPFC) with ascending curve (χ2 = 25.67; df = 2; P = .001); (2) for treatment-resistant depression, LF TMS on the bilateral DLPFC with ascending curve (χ2 = 5.86; df = 2; P = .004); (3) in obsessive-compulsive disorder, LF-RDLPFC TMS with ascending curve (χ2 = 20.65; df = 2; P < .001) and LF TMS on the orbitofrontal cortex with a plateaued curve (χ2 = 15.19; df = 2; P < .001); and (4) in posttraumatic stress disorder, LF-RDLPFC TMS with ascending curve (χ2 = 54.15; df = 2; P < .001). Sensitivity analyses confirmed the main findings.

Conclusions and Relevance

The study findings suggest that NIBS yields specific outcomes based on dose parameters across various mental disorders and brain regions. Clinicians should consider these dose parameters when prescribing NIBS. Additional research is needed to prospectively validate the findings in randomized, sham-controlled trials and explore how other parameters contribute to the observed dose-response association.

Repetitive Transcranial Magnetic Stimulation-Induced Neuroplasticity and the Treatment of Psychiatric Disorders: State of the Evidence and Future Opportunities

Neuroplasticity, or activity-dependent neuronal change, is a crucial mechanism underlying the mechanisms of effect of many therapies for neuropsychiatric disorders, one of which is repetitive transcranial magnetic stimulation (rTMS). Understanding the neuroplastic effects of rTMS at different biological scales and on different timescales and how the effects at different scales interact with each other can help us understand the effects of rTMS in clinical populations and offers the potential to improve treatment outcomes. Several decades of research in the fields of neuroimaging and blood biomarkers is increasingly showing its clinical relevance, allowing measurement of the synaptic, functional, and structural changes involved in neuroplasticity in humans. In this narrative review, we describe the evidence for rTMS-induced neuroplasticity at multiple levels of the nervous system, with a focus on the treatment of psychiatric disorders. We also describe the relationship between neuroplasticity and clinical effects, discuss methods to optimize neuroplasticity, and identify future research opportunities in this area.

The future of brain circuit-targeted therapeutics

The principle of targeting brain circuits has drawn increasing attention with the growth of brain stimulation treatments such as transcranial magnetic stimulation (TMS), deep brain stimulation (DBS), and focused ultrasound (FUS). Each of these techniques can effectively treat different neuropsychiatric disorders, but treating any given disorder depends on choosing the right treatment target. Here, we propose a three-phase framework for identifying and modulating these targets. There are multiple approaches to identifying a target, including correlative neuroimaging, retrospective optimization based on existing stimulation sites, and lesion localization. These techniques can then be optimized using personalized neuroimaging, physiological monitoring, and engagement of a specific brain state using pharmacological or psychological interventions. Finally, a specific stimulation modality or combination of modalities can be chosen after considering the advantages and tradeoffs of each. While there is preliminary literature to support different components of this framework, there are still many unanswered questions. This presents an opportunity for the future growth of research and clinical care in brain circuit therapeutics.

Functional connectomics in depression: insights into therapies

Depression is a common mental disorder characterized by heterogeneous cognitive and behavioral symptoms. The emerging research paradigm of functional connectomics has provided a quantitative theoretical framework and analytic tools for parsing variations in the organization and function of brain networks in depression. In this review, we first discuss recent progress in depression-associated functional connectome variations. We then discuss treatment-specific brain network outcomes in depression and propose a hypothetical model highlighting the advantages and uniqueness of each treatment in relation to the modulation of specific brain network connectivity and symptoms of depression. Finally, we look to the future promise of combining multiple treatment types in clinical practice, using multisite datasets and multimodal neuroimaging approaches, and identifying biological depression subtypes.

Robotic transcranial magnetic stimulation in the treatment of depression: a pilot study

There has been an increasing demand for robotic coil positioning during repetitive transcranial magnetic stimulation (rTMS) treatment. Accurate coil positioning is crucial because rTMS generally targets specific brain regions for both research and clinical application with other reasons such as safety, consistency and reliability and individual variablity. Some previous studies have employed industrial robots or co-robots and showed they can more precisely stimulate the target cortical regions than traditional manual methods. In this study, we not only developed a custom-TMS robot for better TMS coil placement but also analyzed the therapeutic effects on depression. Treatment effects were evaluated by measuring regional cerebral blood flow (rCBF) using single-photon emission computed tomography and depression severity before and after rTMS for the two positioning methods. The rTMS preparation time with our robotic coil placement was reduced by 53% compared with that of the manual method. The position and orientation errors were also significantly reduced from 11.17 mm and 4.06° to 0.94 mm and 0.11°, respectively, confirming the superiority of robotic positioning. The results from clinical and neuroimaging assessments indicated comparable improvements in depression severity and rCBF in the left dorsolateral prefrontal cortex between the robotic and manual rTMS groups. A questionnaire was used to determine the patients' feelings about the robotic system, including the safety and preparation time. A high safety score indicated good acceptability of robotic rTMS at the clinical site.

Efficacy of repetitive transcranial magnetic stimulation (rTMS) adjunctive therapy for major depressive disorder (MDD) after two antidepressant treatment failures: meta-analysis of randomized sham-controlled trials

BACKGROUND

Several meta-analyses demonstrated the efficacy of unilateral High-Frequency Left-sided (HFL) repetitive Transcranial Magnetic Stimulation (rTMS) for individuals with Major Depressive Disorder (MDD); however, results are contradictory due to heterogeneity of the included studies.

METHODS

A systematic literature review (SLR) of English language articles published since 2000 was performed in March 2022 on PubMed and Scopus databases. Empirical evidence on the relative efficacy of rTMS treatment compared with standard pharmacotherapy in Treatment-Resistant Depression (TRD) were extracted. Random effects models were used to assess the effects of rTMS on response and remission rates.

RESULTS

19 randomized double-blinded sham-controlled studies were included for quantitative analysis for response (n = 854 patients) and 9 studies for remission (n = 551 patients). The risk ratio (RR) for response and remission are 2.25 and 2.78, respectively for patients after two treatment failures using rTMS as add-on treatment compared to standard pharmacotherapy. Cochrane's Q test showed no significant heterogeneity. No publication bias was detected.

CONCLUSIONS

rTMS is significantly more effective than sham rTMS in TRD in response and remission outcomes and may be beneficial as an adjunctive treatment in patients with MDD after two treatment failures. This finding is consistent with previous meta-analyses; however, the effect size was smaller than in the formerly published literature.

Network effects of Stanford Neuromodulation Therapy (SNT) in treatment-resistant major depressive disorder: a randomized, controlled trial

Here, we investigated the brain functional connectivity (FC) changes following a novel accelerated theta burst stimulation protocol known as Stanford Neuromodulation Therapy (SNT) which demonstrated significant antidepressant efficacy in treatment-resistant depression (TRD). In a sample of 24 patients (12 active and 12 sham), active stimulation was associated with significant pre- and post-treatment modulation of three FC pairs, involving the default mode network (DMN), amygdala, salience network (SN) and striatum. The most robust finding was the SNT effect on amygdala-DMN FC (group*time interaction F(1,22) = 14.89, p < 0.001). This FC change correlated with improvement in depressive symptoms (rho (Spearman) = -0.45, df = 22, p = 0.026). The post-treatment FC pattern showed a change in the direction of the healthy control group and was sustained at the one-month follow-up. These results are consistent with amygdala-DMN connectivity dysfunction as an underlying mechanism of TRD and bring us closer to the goal of developing imaging biomarkers for TMS treatment optimization.Trial registration: ClinicalTrials.gov NCT03068715.

Brain connectivity in major depressive disorder: a precision component of treatment modalities?

Major depressive disorder (MDD) is a very prevalent mental disorder that imposes an enormous burden on individuals, society, and health care systems. Most patients benefit from commonly used treatment methods such as pharmacotherapy, psychotherapy, electroconvulsive therapy (ECT), and repetitive transcranial magnetic stimulation (rTMS). However, the clinical decision on which treatment method to use remains generally informed and the individual clinical response is difficult to predict. Most likely, a combination of neural variability and heterogeneity in MDD still impedes a full understanding of the disorder, as well as influences treatment success in many cases. With the help of neuroimaging methods like functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), the brain can be understood as a modular set of functional and structural networks. In recent years, many studies have investigated baseline connectivity biomarkers of treatment response and the connectivity changes after successful treatment. Here, we systematically review the literature and summarize findings from longitudinal interventional studies investigating the functional and structural connectivity in MDD. By compiling and discussing these findings, we recommend the scientific and clinical community to deepen the systematization of findings to pave the way for future systems neuroscience roadmaps that include brain connectivity parameters as a possible precision component of the clinical evaluation and therapeutic decision.

Association between daily dose and efficacy of rTMS over the left dorsolateral prefrontal cortex in depression: A meta-analysis

Repetitive transcranial magnetic stimulation (rTMS) is a well-established, safe, and effective brain stimulation technique for depression; however, uniform parameters have not been used in clinical practice. The aim of this study was to identify the parameters that affect rTMS effectiveness and ascertain the range in which that parameter has optimal efficacy. A meta-analysis of sham-controlled trials using rTMS delivered over the left dorsolateral prefrontal cortex (DLPFC) in depression was conducted. In the meta-regression and subgroup analyses, all rTMS stimulation parameters were extracted and their association with efficacy was investigated. Of the 17,800 references, 52 sham-controlled trials were included. Compared to sham controls, our results demonstrated a significant improvement in depressive symptoms at the end of treatment. According to the results of meta-regression, the number of pulses and sessions per day correlated with rTMS efficacy; however, the positioning method, stimulation intensity, frequency, number of treatment days, and total pulses did not. Furthermore, subgroup analysis revealed that the efficacy was correspondingly better in the group with higher daily pulses. In clinical practice, increasing the number of daily pulses and sessions may improve the effectiveness of rTMS.

Functional connectivity analysis of the depression connectome provides potential markers and targets for transcranial magnetic stimulation

BACKGROUND

Despite efforts to improve targeting accuracy of the dorsolateral prefrontal cortex (DLPFC) as a repetitive transcranial magnetic stimulation (rTMS) target for Major Depressive Disorder (MDD), the heterogeneity in clinical response remains unexplained.

OBJECTIVE

We sought to compare the patterns of functional connectivity from the DLPFC treatment site in patients with MDD who were TMS responders to those who were TMS non-responders.

METHODS

Baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI, and diffusion weighted imaging scans were obtained from 37 participants before they underwent a course of rTMS to left Brodmann area 46. A novel machine learning method was utilized to identify brain regions associated with each item of the Beck's Depression Inventory II (BDI-II), and for 26 participants who underwent rTMS treatment over the left Brodmann area 46, identify regions differentiating rTMS responders and non-responders.

RESULTS

Nine parcels of the Human Connectome Project Multimodal Parcellation Atlas matched to at least three items of the Beck's Depression Inventory II (BDI-II) as predictors of response to rTMS, with many in the temporal, parietal and cingulate cortices. Additionally, pre-treatment mapping for 17 items of the BDI-II demonstrated significant variability in symptom to parcel mapping. When parcels associated with symptom presence and symptom resolution were compared, 15 parcels were uniquely associated with resolution (potential targets), and 12 parcels were associated with both symptom presence and resolution (blockers or biomarkers).

CONCLUSIONS

Machine learning approaches show promise for the development of pathoanatomical diagnosis and treatment algorithms for MDD. Prospective studies are required to facilitate clinical translation.

Network-specific metabolic and haemodynamic effects elicited by non-invasive brain stimulation

Repetitive transcranial magnetic stimulation (TMS), when applied to the dorsolateral prefrontal cortex (dlPFC), treats depression. Therapeutic effects are hypothesized to arise from propagation of local dlPFC stimulation effects across distributed networks; however, the mechanisms of this remain unresolved. dlPFC contains representations of different networks. As such, dlPFC TMS may exert different effects depending on the network being stimulated. Here, to test this, we applied high-frequency TMS to two nearby dlPFC targets functionally embedded in distinct anti-correlated networks-the default and salience networks- in the same individuals in separate sessions. Local and distributed TMS effects were measured with combined 18fluorodeoxyglucose positron emission tomography and functional magnetic resonance imaging. Identical TMS patterns caused opposing effects on local glucose metabolism: metabolism increased at the salience target following salience TMS but decreased at the default target following default TMS. At the distributed level, both conditions increased functional connectivity between the default and salience networks, with this effect being dramatically larger following default TMS. Metabolic and haemodynamic effects were also linked: across subjects, the magnitude of local metabolic changes correlated with the degree of functional connectivity changes. These results suggest that TMS effects upon dlPFC are network specific. They also invoke putative antidepressant mechanisms of TMS: network de-coupling.

Effects of bilateral sequential theta-burst stimulation on functional connectivity in treatment-resistant depression: First results

BACKGROUND

Previous studies suggest that transcranial magnetic stimulation exerts antidepressant effects by altering functional connectivity (FC). However, knowledge about this mechanism is still limited. Here, we aimed to investigate the effect of bilateral sequential theta-burst stimulation (TBS) on FC in treatment-resistant depression (TRD) in a sham-controlled longitudinal study.

METHODS

TRD patients (n = 20) underwent a three-week treatment of intermittent TBS of the left and continuous TBS of the right dorsolateral prefrontal cortex (DLPFC). Upon this trial's premature termination, 15 patients had received active TBS and five patients sham stimulation. Resting-state functional magnetic resonance imaging was performed at baseline and after treatment. FC (left and right DLPFC) was estimated for each participant, followed by group statistics (t-tests). Furthermore, depression scores were analyzed (linear mixed models analysis) and tested for correlation with FC.

RESULTS

Both groups exhibited reductions of depression scores, however, there was no significant main effect of group, or group and time. Anticorrelations between DLPFC and the subgenual cingulate cortex (sgACC) were observed for baseline FC, corresponding to changes in depression severity. Treatment did not significantly change DLPFC-sgACC connectivity, but significantly reduced FC between the left stimulation target and bilateral anterior insula.

CONCLUSIONS

Our data is compatible with previous reports on the relevance of anticorrelation between DLPFC and sgACC for treatment success. Furthermore, FC changes between left DLPFC and bilateral anterior insula highlight the effect of TBS on the salience network.

LIMITATIONS

Due to the limited sample size, results should be interpreted with caution and are of exploratory nature.

Distinct patterns of functional brain network integration between treatment-resistant depression and non treatment-resistant depression: A resting-state functional magnetic resonance imaging study

BACKGROUND

Previous neuroimaging has paid little attention to the differences in brain network integration between patients with treatment-resistant depression(TRD) and non-TRD (nTRD), and the relationship between their impaired brain network integration and clinical symptoms has not been elucidated.

METHOD

Eighty one major depressive disorder (MDD) patients (40 in TRD, 41 in nTRD) and 40 healthy controls (HCs) were enrolled for the functional magnetic resonance imaging (fMRI) scans. A seed-based functional connectivity (FC) method was used to investigate the brain network abnormalities of default mode network (DMN), affective network (AN), salience network (SN) and cognitive control network (CCN) for the MDD. Finally, the correlation was analyzed between the abnormal FCs and 17-item Hamilton Rating Scale for Depression scale (HAMD-17) scores.

RESULTS

Compared with the HC group, the FCs in DMN, AN, SN, CCN were altered in both the TRD and nTRD groups. Compared with the nTRD group, FC alterations in the AN and CCN were more abnormal in the TRD group, and the FC alterations were generally decreased at the SN in the TRD group. In addition, the FC values of right dorsolateral prefrontal cortices and left caudate nucleus in the TRD group and the FC values of right subgenual anterior cingulate cortex and left middle temporal gyrus in the nTRD group were positively correlated with HAMD-17 scale scores.

CONCLUSIONS

Abnormal FCs are present in four brain networks (DMN, AN, SN, CCN) in both the TRD and nTRD groups. Except of DMN, FCs in AN, SN and CCN maybe underlay the neurobiological mechanism in differentiating TRD from nTRD.

The Association Between Sample and Treatment Characteristics and the Efficacy of Repetitive Transcranial Magnetic Stimulation in Depression: A Meta-analysis and Meta-regression of Sham-controlled Trials

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) is a form of non-invasive neuromodulation that is increasingly used to treat major depressive disorder (MDD). However, treatment with rTMS could be optimized by identifying optimal treatment parameters or characteristics of patients that are most likely to benefit. This meta-analysis and meta-regression aims to identify sample and treatment characteristics that are associated with change in depressive symptom level, treatment response and remission.

METHODS

The databases PubMed, Embase, Web of Science and Cochrane library were searched for randomized controlled trials (RCTs) reporting on the therapeutic efficacy of high-frequent, low-frequent, or bilateral rTMS for MDD compared to sham. Study and sample characteristics as well as rTMS parameters and outcome variables were extracted. Effect sizes were calculated for change in depression score and risk ratios for response and remission.

RESULTS

Sixty-five RCTs with a total of 2982 subjects were included in this meta-analysis. Active rTMS resulted in a larger depressive symptom reduction than sham protocol (Hedges' g = -0.791 95% CI -0.977; -0.605). Risk ratios for response and remission were 2.378 (95% CI 1.882; 3.005) and 2.450 (95% CI 1.779; 3.375), respectively. We found no significant association between sample and treatment parameters and rTMS efficacy.

CONCLUSIONS

rTMS is an efficacious treatment for MDD. No associations between sample or treatment characteristics and efficacy were found, for which we caution that publication bias, heterogeneity and lack of consistency in the definition of remission might bias these latter null findings. Our results are clinically relevant and support the use of rTMS as a non-invasive and effective treatment option for depression.

Use of machine learning in predicting the efficacy of repetitive transcranial magnetic stimulation on treating depression based on functional and structural thalamo-prefrontal connectivity: A pilot study

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive, safe, and efficacious treatment for major depressive disorder (MDD). However, the antidepressant efficacy of rTMS greatly varies across individual patients. Thus, markers that can be used to predict the outcome of rTMS treatment at the individual level must be identified. Thalamo-cortical connectivity was abnormal in patients with MDD, and was normalized after rTMS treatment. In the current study, we investigated whether the resting-state functional and structural thalamo-cortical connectivity could be utilized to predict the rTMS treatment efficacy by employing support vector machine regression analysis. Results showed that the Hamilton Depression Scale scores of patients with MDD decreased after rTMS treatment. The functional connectivity of mediodorsal nucleus with prefrontal cortex predicted the rTMS treatment improvement, whereas the functional connectivity of other thalamic nuclei with cerebral cortex did not predict the treatment efficacy. The brain areas that contributed the most to the prediction were dorsal lateral prefrontal cortex, ventral lateral, and orbital and medial prefrontal areas. The improvement in the outcome of rTMS treatment could also be predicted by the thalamo-prefrontal structural connectivity. No statistically significantly difference in thalamo-cortical connectivity was observed between early improvers and early non-improvers. These results suggested that the thalamo-prefrontal connectivity can predict the rTMS treatment improvement. This study highlighted the crucial role of the thalamo-prefrontal connectivity as a neuroimaging marker in the treatment of depression via rTMS.

Safety of transcranial magnetic stimulation in unipolar depression: A systematic review and meta-analysis of randomized-controlled trials

BACKGROUND

To study the safety and patients' tolerance of transcranial magnetic stimulation (TMS), we conducted a systematic review and meta-analysis of the major depressive disorder population.

METHODS

Our study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched the literature published before April 30th, 2021 and performed a random-effects meta-analyses which included drop-out due to adverse events, serious adverse events and other non-serious adverse events as primary and secondary outcomes.

RESULTS

A total of 53 randomized sham-controlled trials with 3,273 participants were included. There was no increased risk of drop-out due to an adverse event (active TMS intervention group=3.3%, sham TMS intervention group=2.3%, odds ratio = 1.30, 95% CI= 0.78-2.16, P = 0.31) or a serious adverse event (active TMS intervention group=0.9%, sham TMS intervention group=1.5%, odds ratio = 0.67, 95% CI= 0.29-1.55, P = 0.35). Our findings suggest that TMS intervention may significantly increase the risk of non-serious adverse events including: headaches (active TMS intervention group=22.6%, sham TMS intervention group=16.2%, odds ratio = 1.48, 95% CI= 1.15-1.91, P = 0.002), discomfort (active TMS intervention group=10.9%, sham TMS intervention group=5.0%, odds ratio 1.98, 95% CI= 1.22-3.21, P = 0.006) and pain (active TMS intervention group=23.8%, sham TMS intervention group=5.2%, odds ratio= 8.09, 95% CI= 4.71-13.90, P < 0.001) at the stimulation site, but these non-serious events were mostly mild and transient after TMS treatment.

CONCLUSIONS

These findings provide evidence for the safety and patients' tolerance of transcranial magnetic stimulation technique as an alternative monotherapy or as an add-on treatment for major depressive disorder.

Mechanisms of Repetitive Transcranial Magnetic Stimulation on Post-stroke Depression: A Resting-State Functional Magnetic Resonance Imaging Study

We aimed to identify neural mechanisms underlying clinical response to repetitive transcranial magnetic stimulation (rTMS) in post-stroke depression (PSD) by the Resting-state functional magnetic resonance imaging (rs-fMRI). Thirty-two depressed patients after ischemic stroke were randomized in a 1:1 ratio to receive 20 min of 5 Hz rTMS or sham over left dorsolateral prefrontal cortex (DLPFC) in addition to routine supportive treatments. The clinical outcome was measured by the 17-item Hamilton Depression Rating Scale (HDRS-17), while the imaging results were acquired from rs-fMRI, including regional homogeneity (ReHo), fractional amplitude of low-frequency fluctuation (fALFF) and seed-based dynamic functional connection (dFC). HRSD-17 scores were improved in the two groups after treatment (P < 0.01), while greater mood improvement was observed in the rTMS group (P < 0.05). Compared with the sham group, the rTMS group demonstrated regions with higher ReHo and fALFF values locating mainly in the left hemisphere and highly consistent with the default mode network (DMN) (p < 0.05). Using the medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) as seeds, significant difference between the two groups in dFC within the DMN was found after treatment, including 10 connections with increased connectivity strength and 2 connections with reduced connectivity strength. The ReHo, fALFF and dFC values within DMN in the rTMS group were negatively correlated with the HDRS scores after treatment (P < 0.05). Our results indicated reductions in depressive symptoms following rTMS in PSD are associated with functional alterations of different depression-related areas within the DMN.

Childhood Threat Is Associated With Lower Resting-State Connectivity Within a Central Visceral Network

Childhood adversity is associated with altered or dysregulated stress reactivity; these altered patterns of physiological functioning persist into adulthood. Evidence from both preclinical animal models and human neuroimaging studies indicates that early life experience differentially influences stressor-evoked activity within central visceral neural circuits proximally involved in the control of stress responses, including the subgenual anterior cingulate cortex (sgACC), paraventricular nucleus of the hypothalamus (PVN), bed nucleus of the stria terminalis (BNST) and amygdala. However, the relationship between childhood adversity and the resting-state connectivity of this central visceral network remains unclear. To this end, we examined relationships between childhood threat and childhood socioeconomic deprivation, the resting-state connectivity between our regions of interest (ROIs), and affective symptom severity and diagnoses. We recruited a transdiagnostic sample of young adult males and females (n = 100; mean age = 27.28, SD = 3.99; 59 females) with a full distribution of maltreatment history and symptom severity across multiple affective disorders. Resting-state data were acquired using a 7.2-min functional magnetic resonance imaging (fMRI) sequence; noted ROIs were applied as masks to determine ROI-to-ROI connectivity. Threat was determined by measures of childhood traumatic events and abuse. Socioeconomic deprivation (SED) was determined by a measure of childhood socioeconomic status (parental education level). Covarying for age, race and sex, greater childhood threat was significantly associated with lower BNST-PVN, amygdala-sgACC and PVN-sgACC connectivity. No significant relationships were found between SED and resting-state connectivity. BNST-PVN connectivity was associated with the number of lifetime affective diagnoses. Exposure to threat during early development may entrain altered patterns of resting-state connectivity between these stress-related ROIs in ways that contribute to dysregulated neural and physiological responses to stress and subsequent affective psychopathology.

Decreased salience network fMRI functional connectivity following a course of rTMS for treatment-resistant depression

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) is a treatment shown to be effective in treating major depressive disorder (MDD). However, the effect of rTMS therapy on functional connectivity within the brains of patients being treated for MDD remains poorly understood. Few studies have investigated the effects of a course of rTMS on resting-state network activity.

METHODS

In an open-label naturalistic study, resting-state fMRI was collected prior to and following a four-week course of rTMS in 24 participants with MDD and 2 with bipolar disorder. Montgomery-Asberg depression rating scale scores showed a response rate of 42%.

RESULTS

Clinical response to rTMS was correlated with reduced functional connectivity from baseline to post-rTMS within the salience network (SN). This indicates SN connectivity may be functionally relevant to how rTMS produces antidepressant effects. In an exploratory inter-network analysis, connectivity between the SN and posterior default mode network (pDMN) was higher following treatment. However this difference was not correlated with the antidepressant response. Local BOLD activity within these networks was also assessed using the fractional amplitude of low-frequency fluctuations (fALFF) technique. Local activity increased in both the SN and pDMN following rTMS. However this increase was also not correlated with antidepressant response.

LIMITATIONS

The sample population was heterogeneous, continuing current use of medications, and the study lacked a healthy control or sham stimulation comparison group.

CONCLUSIONS

Together, these results provide evidence for the involvement of the SN in the antidepressant response to rTMS treatment.

Insight Into the Effects of Clinical Repetitive Transcranial Magnetic Stimulation on the Brain From Positron Emission Tomography and Magnetic Resonance Imaging Studies: A Narrative Review

Repetitive transcranial magnetic stimulation (rTMS) has been proposed as a therapeutic tool to alleviate symptoms for neurological and psychiatric diseases such as chronic pain, stroke, Parkinson’s disease, major depressive disorder, and others. Although the therapeutic potential of rTMS has been widely explored, the neurological basis of its effects is still not fully understood. Fortunately, the continuous development of imaging techniques has advanced our understanding of rTMS neurobiological underpinnings on the healthy and diseased brain. The objective of the current work is to summarize relevant findings from positron emission tomography (PET) and magnetic resonance imaging (MRI) techniques evaluating rTMS effects. We included studies that investigated the modulation of neurotransmission (evaluated with PET and magnetic resonance spectroscopy), brain activity (evaluated with PET), resting-state connectivity (evaluated with resting-state functional MRI), and microstructure (diffusion tensor imaging). Overall, results from imaging studies suggest that the effects of rTMS are complex and involve multiple neurotransmission systems, regions, and networks. The effects of stimulation seem to not only be dependent in the frequency used, but also in the participants characteristics such as disease progression. In patient populations, pre-stimulation evaluation was reported to predict responsiveness to stimulation, while post-stimulation neuroimaging measurements showed to be correlated with symptomatic improvement. These studies demonstrate the complexity of rTMS effects and highlight the relevance of imaging techniques.

Protocol for a prospective open-label clinical trial to investigate the utility of concurrent TBS/fNIRS for antidepressant treatment optimisation

INTRODUCTION

Repetitive transcranial magnetic stimulation (rTMS) with theta burst stimulation (i.e. TBS) of the dorsolateral prefrontal cortex (DLPFC) is an innovative treatment for major depressive disorder (MDD). However, fewer than 50% of patients show sufficient response to this treatment; markers for response prediction are urgently needed. Research shows considerable individual variability in the brain responses to rTMS. However, whether differences in individual DLPFC modulation by rTMS can be used as a predictive marker for treatment response remains to be investigated. Here, we present a research programme that will exploit the combination of functional near-infrared spectroscopy (fNIRS) with brain stimulation. Concurrent TBS/fNIRS will allow us to systematically investigate TBS-induced modulation of blood oxygenation as a proxy for induced brain activity changes. The findings from this study will (1) elucidate the immediate effects of excitatory and inhibitory TBS on prefrontal activity in TBS treatment-naïve patients with MDD and (2) validate the potential utility of TBS-induced brain modulation at baseline for the prediction of antidepressant response to 4 weeks of daily TBS treatment.

METHODS AND ANALYSIS

Open-label, parallel-group experiment consisting of two parts. In part 1, 70 patients and 37 healthy controls will be subjected to concurrent TBS/fNIRS. Intermittent TBS (iTBS) and continuous TBS (cTBS) will be applied on the left and right DLPFC, respectively. fNIRS data will be acquired before, during and several minutes after stimulation. In part 2, patients who participated in part 1 will receive a 4 week iTBS treatment of the left DLPFC, performed daily for 5 days per week. Psychometric evaluation will be performed periodically and at 1 month treatment follow-up. Statistical analysis will include a conventional, as well as a machine learning approach.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the Institutional Review Board. Findings will be disseminated through scientific journals, conferences and university courses.

TRIAL REGISTRATION NUMBER

NCT04526002.

Using Brain Imaging to Improve Spatial Targeting of Transcranial Magnetic Stimulation for Depression

Transcranial magnetic stimulation (TMS) is an effective treatment for depression but is limited in that the optimal therapeutic target remains unknown. Early TMS trials lacked a focal target and thus positioned the TMS coil over the prefrontal cortex using scalp measurements. Over time, it became clear that this method leads to variation in the stimulation site and that this could contribute to heterogeneity in antidepressant response. Newer methods allow for precise positioning of the TMS coil over a specific brain location, but leveraging these precise methods requires a more precise therapeutic target. We review how neuroimaging is being used to identify a more focal therapeutic target for depression. We highlight recent studies showing that more effective TMS targets in the frontal cortex are functionally connected to deep limbic regions such as the subgenual cingulate cortex. We review how connectivity might be used to identify an optimal TMS target for use in all patients and potentially even a personalized target for each individual patient. We address the clinical implications of this emerging field and highlight critical questions for future research.

Connectivity changes in major depressive disorder after rTMS: a review of functional and structural connectivity data

Aims

In the search for effective therapeutic strategies for depression, repetitive transcranial magnetic stimulation (rTMS) emerged as a non-invasive, promising treatment. This is because the antidepressant effect of rTMS might be related to neuronal plasticity mechanisms possibly reverting connectivity alterations often observed in depression. Therefore, in this review, we aimed at providing an overview of the findings reported by studies investigating functional and structural connectivity changes after rTMS in depression.

Methods

A bibliographic search was conducted on PubMed, including studies that used unilateral, excitatory (⩾10 Hz) rTMS treatment targeted on the left dorsolateral prefrontal cortex (DLPFC) in unipolar depressed patients.

Results

The majority of the results showed significant TMS-induced changes in functional connectivity (FC) between areas important for emotion regulation, including the DLPFC and the subgenual anterior cingulate cortex, and among regions that are part of the major resting-state networks, such as the Default Mode Network, the Salience Networks and the Central Executive Network. Finally, in diffusion tensor imaging studies, it has been reported that rTMS appeared to increase fractional anisotropy in the frontal lobe.

Limitations

The small sample size, the heterogeneity of the rTMS stimulation parameters, the concomitant use of psychotropic drugs might have limited the generalisability of the results.

Conclusions

Overall, rTMS treatment induces structural and FC changes in brain regions and networks implicated in the pathogenesis of unipolar depression. However, whether these changes underlie the antidepressant effect of rTMS still needs to be clarified.

Novel method for identification of individualized resonant frequencies for treatment of Major Depressive Disorder (MDD) using repetitive Transcranial Magnetic Stimulation (rTMS): A proof-of-concept study

BACKGROUND

Repetitive Transcranial Magnetic Stimulation (rTMS) is an effective treatment for Major Depressive Disorder (MDD), but therapeutic benefit is highly variable. Clinical improvement is related to changes in brain circuits, which have preferred resonant frequencies (RFs) and vary across individuals.

OBJECTIVE

We developed a novel rTMS-electroencephalography (rTMS-EEG) interrogation paradigm to identify RFs using the association of power/connectivity measures with symptom severity and treatment outcome.

METHODS

35 subjects underwent rTMS interrogation at 71 frequencies ranging from 3 to 17 Hz administered to left dorsolateral prefrontal cortex (DLPFC). rTMS-EEG was used to assess resonance in oscillatory power/connectivity changes (phase coherence [PC], envelope correlation [EC], and spectral correlation coefficient [SCC]) after each frequency. Multiple regression was used to detect relationships between 10 Hz resonance and baseline symptoms as well as clinical improvement after 10 sessions of 10 Hz rTMS treatment.

RESULTS

Baseline symptom severity was significantly associated with SCC resonance in left sensorimotor (SM; p < 0.0004), PC resonance in fronto-parietal (p = 0.001), and EC resonance in centro-posterior channels (p = 0.002). Subjects significantly improved with 10 sessions of rTMS treatment. Only decreased SCC SM resonance was significantly associated with clinical improvement (r = 0.35, p = 0.04). Subjects for whom 10 Hz SM SCC was highly ranked as an RF among all stimulation frequencies had better outcomes from 10 Hz treatment.

CONCLUSIONS

Resonance of 10 Hz stimulation measured using SCC correlated with both symptom severity and improvement with 10 Hz rTMS treatment. Research should determine whether this interrogation paradigm can identify individualized rTMS treatment frequencies.

Recent Advances and Future Directions in Brain MR Imaging Studies in Schizophrenia: Toward Elucidating Brain Pathology and Developing Clinical Tools

Schizophrenia is a common severe psychiatric disorder that affects approximately 1% of general population through the life course. Historically, in Kraepelin's time, schizophrenia was a disease unit conceptualized as dementia praecox; however, since then, the disease concept has changed. Recent MRI studies had shown that the neuropathology of the brain in this disorder was characterized by mild progression before and after the onset of the disease, and that the brain alterations were relatively smaller than assumed. Although genetic factors contribute to the brain alterations in schizophrenia, which are thought to be trait differences, other changes include factors that are common in psychiatric diseases. Furthermore, it has been shown that the brain differences specific to schizophrenia were relatively small compared to other changes, such as those caused by brain development, aging, and gender. In addition, compared to the disease and participant factors, machine and imaging protocol differences could affect MRI signals, which should be addressed in multi-site studies. Recent advances in MRI modalities, such as multi-shell diffusion-weighted imaging, magnetic resonance spectroscopy, and multimodal brain imaging analysis, may be candidates to sharpen the characterization of schizophrenia-specific factors and provide new insights. The Brain/MINDS Beyond Human Brain MRI (BMB-HBM) project has been launched considering the differences and noises irrespective of the disease pathologies and includes the future perspectives of MRI studies for various psychiatric and neurological disorders. The sites use restricted MRI machines and harmonized multi-modal protocols, standardized image preprocessing, and traveling subject harmonization. Data sharing to the public will be planned in FY 2024. In the future, we believe that combining a high-quality human MRI dataset with genetic data, randomized controlled trials, and MRI for non-human primates and animal models will enable us to understand schizophrenia, elucidate its neural bases and therapeutic targets, and provide tools for clinical application at bedside.

Importance of test-retest reliability for promoting fMRI based screening and interventions in major depressive disorder

Proponents of personalized medicine have promoted neuroimaging in three areas of clinical application for major depression: clinical prediction, outcome evaluation, and treatment, via neurofeedback. Whereas psychometric considerations such as test-retest reliability are basic precursors to clinical adoption for most clinical instruments, we show, in this article, that basic psychometrics have not been regularly attended to in fMRI of depression. For instance, no fMRI neurofeedback study has included measures of test-retest reliability, despite the implicit assumption that brain signals are stable enough to train. We consider several factors that could be useful to aid clinical translation, including (1) attending to how the BOLD response is parameterized, (2) identifying and promoting regions or voxels with stronger psychometric properties, (3) accounting for within-individual changes (e.g., in symptomatology) across time, and (4) focusing on tasks and clinical populations that are relevant for the intended clinical application. We apply these principles to published prognostic and neurofeedback data sets. The broad implication of this work is that attention to psychometrics is important for clinical adoption of mechanistic assessment, is feasible, and may improve the underlying science.

Brain stimulation and brain lesions converge on common causal circuits in neuropsychiatric disease

Damage to specific brain circuits can cause specific neuropsychiatric symptoms. Therapeutic stimulation to these same circuits may modulate these symptoms. To determine if these circuits converge, we studied depression severity after brain lesions (n=461, five datasets), transcranial magnetic stimulation (TMS) (n=151, four datasets), and deep brain stimulation (DBS) (n=101, five datasets). Lesions and stimulation sites most associated with depression severity were connected to a similar brain circuit across all 14 datasets (p<0.001). Circuits derived from lesions, DBS, and TMS were similar (p<0.0005), as were circuits derived from patients with major depression versus other diagnoses (p<0.001). Connectivity to this circuit predicted out-of-sample antidepressant efficacy of TMS and DBS sites (p<0.0001). In an independent analysis, 29 lesions and 95 stimulation sites converged on a distinct circuit for motor symptoms of Parkinson’s disease (p<0.05). We conclude that lesions, TMS, and DBS converge on common brain circuitry that may represent improved neurostimulation targets for depression and other disorders.

Repetitive Transcranial Magnetic Stimulation for People With Treatment-Resistant Depression: A Health Technology Assessment

BACKGROUND

Major depression is one of the most diagnosed mental illnesses in Canada. Generally, people are treated successfully with antidepressants or psychotherapy, but some people do not respond to these treatments (called treatment-resistant depression [TRD]). Repetitive transcranial magnetic stimulation (rTMS) delivers magnetic pulses to stimulate the areas of the brain associated with mood regulation. Several modalities of rTMS exist (e.g., high frequency rTMS, intermittent theta burst stimulation [iTBS], deep transcranial magnetic stimulation). We conducted a health technology assessment of rTMS for people with TRD, which included an evaluation of effectiveness, safety, cost-effectiveness, the budget impact of publicly funding rTMS, and patient preferences and values.

METHODS

We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Risk of Bias in Systematic Reviews (ROBIS) tool and Cochrane Risk of Bias for Randomized Controlled Trials and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We performed a systematic economic literature search and conducted a cost-utility analysis with a 3-year horizon from a public payer perspective. We also analyzed the 5-year budget impact of publicly funding rTMS for people with TRD in Ontario. To assess the potential value of rTMS, we spoke with people who have TRD. Seven rTMS modalities were considered: low-frequency (1 Hz) stimulation, high-frequency (10-20 Hz) stimulation, unilateral stimulation, bilateral stimulation, iTBS, continuous theta burst stimulation, and deep transcranial magnetic stimulation.

RESULTS

We included 58 primary studies, 9 systematic reviews, and 1 network meta-analysis in the clinical evidence review. Most rTMS modalities were more effective than sham treatment for all outcomes (GRADE: Moderate to High). All rTMS modalities were similar to one another in response and remission rates (GRADE: not reported) and were similar to electroconvulsive therapy (ECT) in response and remission rates (GRADE: Moderate). Moreover, in both the reference case and scenario analyses, two rTMS modalities (rTMS or iTBS), followed by ECT when patients did not respond to initial treatment, were less expensive and more effective than ECT alone. They were cost-effective compared with pharmacotherapy alone at a willingness-to-pay amount of $50,000 per quality-adjusted life-year (QALY). The annual budget impact of publicly funding rTMS would range from $9.3 million in year 1 to $15.76 million in year 5, for a total of $63.2 million over the next 5 years. People with TRD we spoke with reported that their experiences were generally favourable, and their attitudes toward rTMS were positive. Similarly, psychiatrists had positive attitudes toward and acceptance of rTMS. Our quantitative literature review on preferences revealed some gaps in psychiatrists' knowledge of rTMS, which could have been influenced by their level of training on rTMS.

CONCLUSIONS

Most rTMS modalities are likely more effective than sham rTMS on all outcomes. All rTMS modalities are similar to ECT and to one another in response and remission rates. Compared with ECT alone, two rTMS modalities (high-frequency rTMS and iTBS), followed by ECT when necessary in a stepped care pathway, were less costly and more effective for managing adults with TRD. These types of rTMS (high-frequency rTMS and iTBS) were cost-effective compared with pharmacotherapy alone at a willingness-to-pay amount of $50,000 per QALY. Publicly funding rTMS (high-frequency rTMS and iTBS) for the treatment of adults with TRD in Ontario over the next 5 years would add $63.2 million in total costs. People with TRD had positive experiences and attitudes toward rTMS.

Effects of rTMS on the brain: is there value in variability?

The ability of repetitive transcranial magnetic stimulation (rTMS) to non-invasively induce neuroplasticity in the human cortex has opened exciting possibilities for its application in both basic and clinical research. Changes in the amplitude of motor evoked potentials (MEPs) elicited by single-pulse transcranial magnetic stimulation has so far provided a convenient model for exploring the neurophysiology of rTMS effects on the brain, influencing the ways in which these stimulation protocols have been applied therapeutically. However, a growing number of studies have reported large inter-individual variability in the mean MEP response to rTMS, raising legitimate questions about the usefulness of this model for guiding therapy. Although the increasing application of different neuroimaging approaches has made it possible to probe rTMS-induced neuroplasticity outside the motor cortex to measure changes in neural activity that impact other aspects of human behaviour, the high variability of rTMS effects on these measurements remains an important issue for the field to address. In this review, we seek to move away from the conventional facilitation/inhibition dichotomy that permeates much of the rTMS literature, presenting a non-standard approach for measuring rTMS-induced neuroplasticity. We consider the evidence that rTMS is able to modulate an individual's moment-to-moment variability of neural activity, and whether this could have implications for guiding the therapeutic application of rTMS.

Personalized connectivity-guided DLPFC-TMS for depression: Advancing computational feasibility, precision and reproducibility

Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) is an established treatment for refractory depression, however, therapeutic outcomes vary. Mounting evidence suggests that clinical response relates to functional connectivity with the subgenual cingulate cortex (SGC) at the precise DLPFC stimulation site. Critically, SGC-related network architecture shows considerable interindividual variation across the spatial extent of the DLPFC, indicating that connectivity-based target personalization could potentially be necessary to improve treatment outcomes. However, to date accurate personalization has not appeared feasible, with recent work indicating that the intraindividual reproducibility of optimal targets is limited to 3.5 cm. Here we developed reliable and accurate methodologies to compute individualized connectivity-guided stimulation targets. In resting-state functional MRI scans acquired across 1,000 healthy adults, we demonstrate that, using this approach, personalized targets can be reliably and robustly pinpointed, with a median accuracy of ~2 mm between scans repeated across separate days. These targets remained highly stable, even after 1 year, with a median intraindividual distance between coordinates of only 2.7 mm. Interindividual spatial variation in personalized targets exceeded intraindividual variation by a factor of up to 6.85, suggesting that personalized targets did not trivially converge to a group-average site. Moreover, personalized targets were heritable, suggesting that connectivity-guided rTMS personalization is stable over time and under genetic control. This computational framework provides capacity for personalized connectivity-guided TMS targets to be robustly computed with high precision and has the flexibly to advance research in other basic research and clinical applications.

Association between tDCS computational modeling and clinical outcomes in depression: data from the ELECT-TDCS trial

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation intervention investigated for the treatment of depression. Clinical results have been heterogeneous, partly due to the variability of electric field (EF) strength in the brain owing to interindividual differences in head anatomy. Therefore, we investigated whether EF strength was correlated with behavioral changes in 16 depressed patients using simulated electric fields in real patient data from a controlled clinical trial. We hypothesized that EF strength in the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC), brain regions implicated in depression pathophysiology, would be associated with changes in depression, mood and anxiety scores. SimNIBS were used to simulate individual electric fields based on the MRI structural T1-weighted brain scans of depressed subjects. Linear regression models showed, at the end of the acute treatment phase, that simulated EF strength was inversely associated with negative affect in the bilateral ACC (left: β = - 160.463, CI [- 291.541, - 29.385], p = 0.021; right: β = - 189.194, CI [- 289.479, - 88.910], p = 0.001) and DLPFC (left: β = - 93.210, CI [- 154.960, - 31.461], p = 0.006; right: β = - 82.564, CI [- 142.867, - 22.262], p = 0.011) and with depression scores in the left ACC (β = - 156.91, CI [- 298.51, - 15.30], p = 0.033). No association between positive affect or anxiety scores, and simulated EF strength in the investigated brain regions was found. To conclude, our findings show preliminary evidence that EF strength simulations might be associated with further behavioral changes in depressed patients, unveiling a potential mechanism of action for tDCS. Further studies should investigate whether individualization of EF strength in key brain regions impact clinical response.

Identifying response and predictive biomarkers for Transcranial magnetic stimulation outcomes: protocol and rationale for a mechanistic study of functional neuroimaging and behavioral biomarkers in veterans with Pharmacoresistant depression

BACKGROUND

Although repetitive transcranial magnetic stimulation ('TMS') is becoming a gold standard treatment for pharmacoresistant depression, we lack neural target biomarkers for identifying who is most likely to respond to TMS and why. To address this gap in knowledge we evaluate neural targets defined by activation and functional connectivity of the dorsolateral prefrontal cortex-anchored cognitive control circuit, regions of the default mode network and attention circuit, and interactions with the subgenual anterior cingulate. We evaluate whether these targets and interactions between them change in a dose-dependent manner, whether changes in these neural targets correspond to changes in cognitive behavioral performance, and whether baseline and early change in neural target and cognitive behavioral performance predict subsequent symptom severity, suicidality, and quality of life outcomes. This study is designed as a pragmatic, mechanistic trial partnering with the National Clinical TMS Program of the Veteran's Health Administration.

METHODS

Target enrollment consists of 100 veterans with pharmacoresistant Major Depressive Disorder (MDD). All veterans will receive a clinical course of TMS and will be assessed at 'baseline' pre-TMS commencement, 'first week' after initiation of TMS (targeting five sessions) and 'post-treatment' at the completion of TMS (targeting 30 sessions). Veterans will be assessed using functional magnetic resonance imaging (fMRI), a cognitive behavioral performance battery, and established questionnaires. Multivariate linear mixed models will be used to assess whether neural targets change with TMS as a function of dose (Aim 1), whether extent and change of neural target relates to and predicts extent of behavioral performance (Aim 3), and whether extent of neural target change predicts improvement in symptom severity, suicidality, and quality of life (Aim 3). For all three aims, we will also assess the contribution of baseline moderators such as biological sex and age.

DISCUSSION

To our knowledge, our study will be the first pragmatic, mechanistic observational trial to use fMRI imaging and cognitive-behavioral performance as biomarkers of TMS treatment response in pharmacoresistant MDD. The results of this trial will allow providers to select suitable candidates for TMS treatment and better predict treatment response by assessing circuit connectivity and cognitive-behavioral performance at baseline and during early treatment.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04663481 , December 5th, 2020, retrospectively registered. The first veteran was enrolled October 30th, 2020.

Resting State Functional Connectivity Biomarkers of Treatment Response in Mood Disorders: A Review

There are currently no validated treatment biomarkers in psychiatry. Resting State Functional Connectivity (RSFC) is a popular method for investigating the neural correlates of mood disorders, but the breadth of the field makes it difficult to assess progress toward treatment response biomarkers. In this review, we followed general PRISMA guidelines to evaluate the evidence base for mood disorder treatment biomarkers across diagnoses, brain network models, and treatment modalities. We hypothesized that no treatment biomarker would be validated across these domains or with independent datasets. Results are organized, interpreted, and discussed in the context of four popular analytic techniques: (1) reference region (seed-based) analysis, (2) independent component analysis, (3) graph theory analysis, and (4) other methods. Cortico-limbic connectivity is implicated across studies, but there is no single biomarker that spans analyses or that has been replicated in multiple independent datasets. We discuss RSFC limitations and future directions in biomarker development.

Distinct Symptom-Specific Treatment Targets for Circuit-Based Neuromodulation

OBJECTIVE

Treatment of different depression symptoms may require different brain stimulation targets with different underlying brain circuits. The authors sought to identify such targets, which could improve the efficacy of therapeutic brain stimulation and facilitate personalized therapy.

METHODS

The authors retrospectively analyzed two independent cohorts of patients who received left prefrontal transcranial magnetic stimulation (TMS) for treatment of depression (discovery sample, N=30; active replication sample, N=81; sham replication sample, N=87). Each patient's TMS site was mapped to underlying brain circuits using functional connectivity MRI from a large connectome database (N=1,000). Circuits associated with improvement in each depression symptom were identified and then clustered based on similarity. The authors tested for reproducibility across data sets and whether symptom-specific targets derived from one data set could predict symptom improvement in the other independent cohort.

RESULTS

The authors identified two distinct circuit targets effective for two discrete clusters of depressive symptoms. Dysphoric symptoms, such as sadness and anhedonia, responded best to stimulation of one circuit, while anxiety and somatic symptoms responded best to stimulation of a different circuit. These circuit maps were reproducible, predicted symptom improvement in independent patient cohorts, and were specific to active compared with sham stimulation. The maps predicted symptom improvement in an exploratory analysis of stimulation sites from 14 clinical TMS trials.

CONCLUSIONS

Distinct clusters of depressive symptoms responded better to different TMS targets across independent retrospective data sets. These symptom-specific targets can be prospectively tested in a randomized clinical trial. This data-driven approach for identifying symptom-specific targets may prove useful for other disorders and facilitate personalized neuromodulation therapy.

Global connectivity and local excitability changes underlie antidepressant effects of repetitive transcranial magnetic stimulation

Repetitive transcranial magnetic stimulation (rTMS) is a commonly- used treatment for major depressive disorder (MDD). However, our understanding of the mechanism by which TMS exerts its antidepressant effect is minimal. Furthermore, we lack brain signals that can be used to predict and track clinical outcome. Such signals would allow for treatment stratification and optimization. Here, we performed a randomized, sham-controlled clinical trial and measured electrophysiological, neuroimaging, and clinical changes before and after rTMS. Patients (N = 36) were randomized to receive either active or sham rTMS to the left dorsolateral prefrontal cortex (dlPFC) for 20 consecutive weekdays. To capture the rTMS-driven changes in connectivity and causal excitability, resting fMRI and TMS/EEG were performed before and after the treatment. Baseline causal connectivity differences between depressed patients and healthy controls were also evaluated with concurrent TMS/fMRI. We found that active, but not sham rTMS elicited (1) an increase in dlPFC global connectivity, (2) induction of negative dlPFC-amygdala connectivity, and (3) local and distributed changes in TMS/EEG potentials. Global connectivity changes predicted clinical outcome, while both global connectivity and TMS/EEG changes tracked clinical outcome. In patients but not healthy participants, we observed a perturbed inhibitory effect of the dlPFC on the amygdala. Taken together, rTMS induced lasting connectivity and excitability changes from the site of stimulation, such that after active treatment, the dlPFC appeared better able to engage in top-down control of the amygdala. These measures of network functioning both predicted and tracked clinical outcome, potentially opening the door to treatment optimization.

Default mode network alterations after intermittent theta burst stimulation in healthy subjects

Understanding the mechanisms by which intermittent theta burst stimulation (iTBS) protocols exert changes in the default-mode network (DMN) is paramount to develop therapeutically more effective approaches in the future. While a full session (3000 pulses) of 10 Hz repetitive transcranial magnetic stimulation (HF-rTMS) reduces the functional connectivity (FC) of the DMN and the subgenual anterior cingulate cortex, the current understanding of the effects of a single session of iTBS on the DMN in healthy subjects is limited. Here, we use a previously validated target selection approach for an unprecedented investigation into the effects of a single session (1800 pulses) of iTBS over the DMN in healthy controls. Twenty-six healthy subjects participated in a double-blind, crossover, sham-controlled study. After iTBS to the personalized left dorsolateral prefrontal cortex (DLPFC) targets, we investigated the time lapse of effects in the DMN and its relationship to the harm avoidance (HA) personality trait measure (Temperament and Character Inventory/TCI). Approximately 25-30 min after stimulation, we observed reduced FC between the DMN and the rostral and dorsal anterior cingulate cortex (dACC). About 45 min after stimulation the FC of rostral and dACC strongly decreased further, as did the FC of right anterior insula (AI) with the DMN. Also, we report a positive correlation between the FC decrease in the rostral ACC and the HA domain of TCI, indicating that the HA scores can potentially predict iTBS response. Overall, our results show the time lapse by which iTBS at left-DLPFC targets reduces the FC between DMN and the dACC and right AI, regions typically described as nodes of the salience network.

Repetitive Transcranial Magnetic Stimulation Improves Amygdale Functional Connectivity in Major Depressive Disorder

Emotional abnormality in major depressive disorder (MDD) is generally regarded to be associated with functional dysregulation in the affective network (AN). The present study examined the changes in characteristics of AN connectivity of MDD patients before and after repetitive transcranial magnetic stimulation (rTMS) treatment over the left dorsolateral prefrontal cortex, and to further assess how these connectivity changes are linked to clinical characteristics of patients. Functional connectivity (FC) in the AN defined by placing seeds in the bilateral amygdale was calculated in 20 patients with MDD before and after rTMS, and in 20 healthy controls (CN). Furthermore, a linear regression model was used to obtain correlations between FC changes and Hamilton depression scale (HAMD) changes in MDD before and after rTMS. Before rTMS, compared with CN, MDD exhibited significantly lower FC between left insula (INS.L), right superior and inferior frontal gyrus (SFG.R and IFG.R), right inferior parietal lobule (IPL.R), and amygdala, and showed an increment of FC between the bilateral precuneus and amygdala in AN. After rTMS, MDD exhibited a significant increase in FC in the INS.L, IFG.R, SFG.R, IPL.R, and a significant reduction in FC in the precuneus. Interestingly, change in FC between INS.L and left amygdala was positively correlated with change in HAMD scores before and after rTMS treatment. rTMS can enhance affective network connectivity in MDD patients, which is linked to emotional improvement. This study further suggests that the insula may be a potential target region of clinical efficacy for MDD to design rationale strategies for therapeutic trials.

Theta Burst Transcranial Magnetic Stimulation of Fronto-Parietal Networks: Modulation by Mental State

Transcranial magnetic stimulation (TMS) treats neuropsychiatric disorders, but effects of stimulation are highly state-dependent and in most therapeutic applications, mental state is not controlled. This exploratory proposal will test the broad hypothesis that when TMS, specifically intermittent theta burst stimulation (iTBS), is applied during a controlled mental state, network changes will be facilitated, compared to stimulation when mental state is uncontrolled. We will focus on the dorsolateral prefrontal cortex (dlPFC) and the associated fronto-parietal network (FPN), which subserves cognitive control, an important neural and behavioral target of therapeutic TMS. After a baseline functional magnetic resonance imaging (fMRI) session, iTBS will be administered to 40 healthy subjects in three sessions over three days in a within-subjects, cross-over design: (1) dlPFC stimulation by iTBS alone, (2) dlPFC stimulation by iTBS while simultaneously performing a cognitive task, and (3) vertex (control) iTBS stimulation. Immediately after each iTBS session, we will measure blood oxygenation level-dependent (BOLD) activation during a cognitive control task (“n-back” task) and during the resting state, using BOLD connectivity and arterial spin labeling (ASL). We will test hypotheses that persisting neural changes and performance enhancement induced by iTBS to the dlPFC, compared to iTBS to the vertex, will affect the FPN, and these effects will be modulated by whether or not subjects receive iTBS when they are engaged in a cognitive control task. Demonstrating this interaction between iTBS and mental state will lay critical groundwork for future studies to show how controlling mental state during TMS can improve therapeutic effects.

Converging Resting State Networks Unravels Potential Remote Effects of Transcranial Magnetic Stimulation for Major Depression

Despite being a commonly used protocol to treat major depressive disorder (MDD), the underlying mechanism of repetitive transcranial magnetic stimulation (rTMS) on dorsolateral prefrontal cortex (DLPFC) remains unclear. In the current study, we investigated the resting-state fMRI data of 100 healthy subjects by exploring three overlapping functional networks associated with the psychopathologically MDD-related areas (the nucleus accumbens, amygdala, and ventromedial prefrontal cortex). Our results showed that these networks converged at the bilateral DLPFC, which suggested that rTMS over DLPFC might improve MDD by remotely modulating the MDD-related areas synergistically. Additionally, they functionally converged at the DMPFC and bilateral insula which are known to be associated with MDD. These two areas could also be potential targets for rTMS treatment. Dynamic causal modelling (DCM) and Granger causality analysis (GCA) revealed that all pairwise connections among bilateral DLPFC, DMPFC, bilateral insula, and three psychopathologically MDD-related areas contained significant causality. The DCM results also suggested that most of the functional interactions between MDD-related areas and bilateral DLPFC, DMPFC, and bilateral insula can predominantly be explained by the effective connectivity from the psychopathologically MDD-related areas to the rTMS stimulation sites. Finally, we found the conventional functional connectivity to be a more representative measure to obtain connectivity parameters compared to GCA and DCM analysis. Our research helped inspecting the convergence of the functional networks related to a psychiatry disorder. The results identified potential targets for brain stimulation treatment and contributed to the optimization of patient-specific brain stimulation protocols.

Theta-Burst Transcranial Magnetic Stimulation for Posttraumatic Stress Disorder

OBJECTIVE

Posttraumatic stress disorder (PTSD) is a highly prevalent psychiatric disorder associated with disruption in social and occupational function. Transcranial magnetic stimulation (TMS) represents a novel approach to PTSD, and intermittent theta-burst stimulation (iTBS) is a new, more rapid administration protocol with data supporting efficacy in depression. The authors conducted a sham-controlled study of iTBS for PTSD.

METHODS

Fifty veterans with PTSD received 10 days of sham-controlled iTBS (1,800 pulses/day), followed by 10 unblinded sessions. Primary outcome measures included acceptability (retention rates), changes in PTSD symptoms (clinician- and self-rated), quality of life, social and occupational function, and depression, obtained at the end of 2 weeks; analysis of variance was used to compare active with sham stimulation. Secondary outcomes were evaluated 1 month after treatment, using mixed-model analyses. Resting-state functional MRI was acquired at pretreatment baseline on an eligible subset of participants (N=26) to identify response predictors.

RESULTS

Retention was high, side effects were consistent with standard TMS, and blinding was successful. At 2 weeks, active iTBS was significantly associated with improved social and occupational function (Cohen's d=0.39); depression was improved with iTBS compared with the sham treatment (d=-0.45), but the difference fell short of significance, and moderate nonsignificant effect sizes were observed on self-reported PTSD symptoms (d=-0.34). One-month outcomes, which incorporated data from the unblinded phase of the study, indicated superiority of active iTBS on clinician- and self-rated PTSD symptoms (d=-0.74 and -0.63, respectively), depression (d=-0.47), and social and occupational function (d=0.93) (all significant). Neuroimaging indicated that clinical improvement was significantly predicted by stronger (greater positive) connectivity within the default mode network and by anticorrelated (greater negative) cross-network connectivity.

CONCLUSIONS

iTBS appears to be a promising new treatment for PTSD. Most clinical improvements from stimulation occurred early, which suggests a need for further investigation of optimal iTBS time course and duration. Consistent with previous neuroimaging studies of TMS, default mode network connectivity played an important role in response prediction.

Identification of Clinical Features and Biomarkers that may inform a Personalized Approach to rTMS for Depression

Repetitive transcranial magnetic stimulation (rTMS), an established treatment for treatment-resistant depression, may hold promise as a personalized medicine approach for the treatment of major depressive disorder (MDD). Clinical research has begun to identify patient-specific factors that could be used to guide rTMS treatment decisions or individualized treatment approaches. This literature review describes a range of patient factors which have been evaluated as potential biomarkers of rTMS treatment response, including patient- and illness-related characteristics, genetic factors, and biomarkers derived from neuroimaging and EEG. We highlight the need for validation data for imaging and electrophysiological biomarkers associated with rTMS as well as prospective evaluation of clinical predictors. Finally, we consider implications for future efforts to move toward a personalized medicine approach in the treatment of depression with rTMS.

Measuring change in anhedonia using the "Happy Faces" task pre- to post-repetitive transcranial magnetic stimulation (rTMS) treatment to left dorsolateral prefrontal cortex in Major Depressive Disorder (MDD): relation to empathic happiness

We investigated whether repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (DLPFC) would reduce anhedonia in a sample of 19 depressed adults (M_age = 45.21, SD = 11.21, 63% women) randomized to either active or sham rTMS. To track anhedonia, patients completed the Snaith-Hamilton Pleasure Scale (SHAPS)¹ and a novel behavioral task called "Happy Faces," which required patients to interpret neutral versus various intensities of positively valenced human facial expressions. Patients had to indicate dichotomously whether any degree of positive emotion was expressed. We expected that more anhedonic patients would struggle most with low intensity happy faces; often incorrectly calling them neutral. Patients also completed a self-report measure of "empathic happiness"-i.e., vicarious joy. Measures were completed pre- to post-treatment. Results indicate rTMS to DLPFC related to improvement in interpretation of subtle forms of happiness in active rTMS patients relative to sham. Furthermore, empathic happiness and anhedonia score were significantly antagonistic across all patients.

An Integrative Way for Studying Neural Basis of Basic Emotions With fMRI

How emotions are represented in the nervous system is a crucial unsolved problem in the affective neuroscience. Many studies are striving to find the localization of basic emotions in the brain but failed. Thus, many psychologists suspect the specific neural loci for basic emotions, but instead, some proposed that there are specific neural structures for the core affects, such as arousal and hedonic value. The reason for this widespread difference might be that basic emotions used previously can be further divided into more “basic” emotions. Here we review brain imaging data and neuropsychological data, and try to address this question with an integrative model. In this model, we argue that basic emotions are not contrary to the dimensional studies of emotions (core affects). We propose that basic emotion should locate on the axis in the dimensions of emotion, and only represent one typical core affect (arousal or valence). Therefore, we propose four basic emotions: joy-on positive axis of hedonic dimension, sadness-on negative axis of hedonic dimension, fear, and anger-on the top of vertical dimensions. This new model about basic emotions and construction model of emotions is promising to improve and reformulate neurobiological models of basic emotions.

Baseline effective connectivity predicts response to repetitive transcranial magnetic stimulation in patients with treatment-resistant depression

Repetitive transcranial magnetic stimulation (rTMS) has become a popular treatment option for treatment-resistant depression (TRD). However, suboptimal response rates highlight the need for improved efficacy through optimisation of treatment protocol and patient selection. We investigate whether the limbic salience network and its connectivity with prefrontal stimulation sites predict immediate and longer-term responsiveness to rTMS. Twenty-seven patients with TRD were randomly allocated to receive 16 sessions of either conventional rTMS or intermittent theta-burst (iTBS) over 4 weeks; delivered using connectivity profiling and neuronavigation to target person-specific dorsolateral prefrontal cortex (DLPFC). At baseline and 3-month follow-up, patients underwent clinical assessment and scanning session, and 1-month clinical follow-up. Resting-state fMRI data were entered into seed-based functional and effective connectivity analyses between right anterior insula (rAI) and DLPFC target, and independent components analysis to extract resting-state networks. Cerebral blood flow (CBF) was also assessed in the rAI. All brain measures were compared between baseline and follow-up, and related to treatment response at 1- and 3-months. Baseline fronto-insular effective connectivity and salience network connectivity were significantly positively correlated, while baseline rAI CBF was negatively correlated, with early (1-month) response to rTMS treatment but not sustained response (3-months), suggesting persistence of therapeutic response is not associated with baseline features. Connectivity or CBF measures did not change between the two time points. We demonstrate that fronto-insular and salience-network interactions can predict early response to rTMS in TRD, suggesting that these network nodes may be key regions toward developing rTMS response biomarkers.