Abnormal functional connectivity within resting-state networks is related to rTMS-based therapy effects of treatment resistant depression: A pilot study

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.

Toward a neurocircuit-based sequential transcranial magnetic stimulation treatment of pediatric bipolar II disorder

BACKGROUND

Abnormalities in large-scale neuronal networks-the frontoparietal central executive network (CEN)-are consistent findings in bipolar disorder and potential therapeutic targets for transcranial magnetic stimulation (TMS).

OBJECTIVE

The present study aimed to assess the effects of CEN neurocircuit-based sequential TMS on the clinical symptoms and cognitive functions of adolescents with bipolar II disorder.

METHODS

The study was a single-blinded, randomized, placebo-control trial. Participants with DSM-5-defined bipolar disorder II were recruited and randomized to receive either a sham treatment (n = 20) or an active TMS treatment (n = 22). The active group patients were taking medication, with intermittent theta burst stimulation (iTBS) treatment provided as adjunctive treatment targeting the left DLPFC, the left ITG, and the left PPC nodes consecutively. Patients completed the measurements of HAMD and the Das-Naglieri Cognition Assessment System at baseline and 3 weeks after the intervention.

RESULTS

A significant group-by-time interaction was observed in the HAMD, total cognition, and planning. Post-hoc analysis revealed that patients in the active group significantly improved HAMD scores following neurostimulation. Moreover, within-subject analysis indicated that the active group significantly improved in scores of total cognition and planning, while the sham group did not. No significant differences were seen in the other cognitive measures.

CONCLUSION

The neurocircuit-based sequential TMS protocol targeting three CEN nodes, in conjunction with medication, safely and effectively improved depressive symptoms and cognitive function in adolescents with bipolar II disorder.

Distinguishable neural circuit mechanisms associated with the clinical efficacy of rTMS in aMCI patients

Repetitive transcranial magnetic stimulation is used in early-stage Alzheimer's disease to slow progression, but heterogeneity in response results in different treatment outcomes. The mechanisms underlying this heterogeneity are unclear. This study used resting-state neuroimaging to investigate the variability in episodic memory improvement from angular gyrus repetitive transcranial magnetic stimulation and tracked the neural circuits involved. Thirty-four amnestic mild cognitive impairment patients underwent angular gyrus repetitive transcranial magnetic stimulation (4 weeks, 20 Hz, 100% resting motor threshold) and were divided into high-response and low-response groups based on minimal clinically important differences in auditory verbal learning test scores. Baseline and pre/post-treatment neural circuit activities were compared. Results indicated that the orbital middle frontal gyrus in the orbitofrontal cortex network and the precuneus in the default mode network had higher local activity in the low-response group. After treatment, changes in local and remote connectivity within brain regions of the orbitofrontal cortex, default mode network, visual network, and sensorimotor network showed opposite trends and were related to treatment effects. This suggests that the activity states of brain regions within the orbitofrontal cortex and default mode network could serve as imaging markers for early cognitive compensation in amnestic mild cognitive impairment patients and predict the aftereffects of repetitive transcranial magnetic stimulation response.

Neurophysiological and neuroimaging markers of repetitive transcranial magnetic stimulation treatment response in major depressive disorder: A systematic review and meta-analysis of predictive modeling studies

Predicting repetitive transcranial magnetic stimulation (rTMS) treatment outcomes in major depressive disorder (MDD) could reduce the financial and psychological risks of treatment failure. We systematically reviewed and meta-analyzed studies that leveraged neurophysiological and neuroimaging markers to predict rTMS response in MDD. Five databases were searched from inception to May 25, 2023. The primary meta-analytic outcome was predictive accuracy pooled from classification models. Regression models were summarized qualitatively. A promising marker was identified if it showed a sensitivity and specificity of 80% or higher in at least two independent studies. Searching yielded 36 studies. Twenty-two classification modeling studies produced an estimated area under the summary receiver operating characteristic curve of 0.87 (95% CI = 0.83-0.92), with 86.8% sensitivity (95% CI = 80.6-91.2%) and 81.9% specificity (95% CI = 76.1-86.4%). Frontal theta cordance measured by electroencephalography is closest to proof of concept. Predicting rTMS response using neurophysiological and neuroimaging markers is promising for clinical decision-making. However, replications by different research groups are needed to establish rigorous markers.

Altered functional brain activity in first-episode major depressive disorder treated with electro-acupuncture: A resting-state functional magnetic resonance imaging study

Background

Previous studies have found electroacupuncture could improve the clinical symptoms of first-episode major depressive disorder (MDD), but the exact neural mechanism of action needs to be further elucidated.

Methods

Twenty-eight first-episode MDD patients were randomly divided into 14 electro-acupuncture stimulation (EAS) groups and 14 sham-acupuncture stimulation (SAS) groups, and clinical symptoms were assessed and functional magnetic resonance imaging (fMRI) scans were done in both groups. Amplitude of low-frequency fluctuations (ALFF) was used to observe the changes between the pre-treatment and post-treatment in the two groups, and the altered brain areas were selected as region of interest (ROI) to observe the FC changes. Meanwhile, the correlation between the altered clinical symptoms and the altered ALFF and FC of brain regions in the two groups was analyzed.

Results

The EAS significantly decreased the HAMD-24 and HAMA-14 scores of MDD than SAS group. The imaging results revealed that both groups were able to increase the ALFF of the left middle temporal gyrus and the left cerebellar posterior lobe. When using the left middle temporal gyrus and the left posterior cerebellar lobe as ROIs, EAS group increased the FC between the left middle temporal gyrus with the left superior frontal gyrus, the left middle frontal gyrus, and the left hippocampus, and decreased the FC between the left posterior cerebellar lobe and the left calcarine gyrus, while SAS group only increased the FC between the left middle temporal gyrus with the left superior frontal gyrus. The alternations in clinical symptoms after EAS treatment were positively correlated with the altered ALFF values in the left middle temporal gyrus and the altered FC values in the left middle temporal gyrus and the left middle frontal gyrus.

Conclusion

EA demonstrates modulation of functional activity in the default mode network (DMN), sensorimotor network (SMN), cognitive control network (CCN), limbic system, and visual network (VN) for the treatment of the first-episode MDD. Our findings contribute to the neuroimaging evidence for the efficacy of EAS.

Cortical glutamate, Glx, and total N-acetylaspartate: potential biomarkers of repetitive transcranial magnetic stimulation treatment response and outcomes in major depression

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for individuals with major depressive disorder (MDD) who have not improved with standard therapies. However, only 30-45% of patients respond to rTMS. Predicting response to rTMS will benefit both patients and providers in terms of prescribing and targeting treatment for maximum efficacy and directing resources, as individuals with lower likelihood of response could be redirected to more suitable treatment alternatives. In this exploratory study, our goal was to use proton magnetic resonance spectroscopy to examine how glutamate (Glu), Glx, and total N-acetylaspartate (tNAA) predict post-rTMS changes in overall MDD severity and symptoms, and treatment response. Metabolites were measured in a right dorsal anterior cingulate cortex voxel prior to a standard course of 10 Hz rTMS to the left DLPFC in 25 individuals with MDD. MDD severity and symptoms were evaluated via the Inventory of Depression Symptomatology Self-Report (IDS-SR). rTMS response was defined as ≥50% change in full-scale IDS-SR scores post treatment. Percent change in IDS-SR symptom domains were evaluated using principal component analysis and established subscales. Generalized linear and logistic regression models were used to evaluate the relationship between baseline Glu, Glx, and tNAA and outcomes while controlling for age and sex. Participants with baseline Glu and Glx levels in the lower range had greater percent change in full scale IDS-SR scores post-treatment (p < 0.001), as did tNAA (p = 0.007). Low glutamatergic metabolite levels also predicted greater percent change in mood/cognition symptoms (p ≤ 0.001). Low-range Glu, Glx, and tNAA were associated with greater improvement on the immuno-metabolic subscale (p ≤ 0.003). Baseline Glu predicted rTMS responder status (p = 0.025) and had an area under the receiving operating characteristic curve of 0.81 (p = 0.009), demonstrating excellent discriminative ability. Baseline Glu, Glx, and tNAA significantly predicted MDD improvement after rTMS; preliminary evidence also demonstrates metabolite association with symptom subdomain improvement post-rTMS. This work provides feasibility for a personalized medicine approach to rTMS treatment selection, with individuals with Glu levels in the lower range potentially being the best candidates.

Individual resting-state network functional connectivity predicts treatment improvement of repetitive transcranial magnetic stimulation in major depressive disorder: A pilot study

The current pilot study aimed to exploratively investigate whether individual functional connectivity (FC) of the rTMS stimulation site with resting-state networks could predict the individual efficacy of rTMS treatment. We found that rTMS induced an increase of the FC between the stimulation site and the limbic network (LN) in healthy participants, and that this individualized FC was negatively correlated with the rTMS treatment improvement in MDD patients. Moreover, the LN successfully guided the personalized rTMS therapy. These findings highlighted the crucial role of the LN in understanding the mechanisms underlying rTMS treatment improvement, and the personalized therapy in MDD patients.

Whole brain network effects of subcallosal cingulate deep brain stimulation for treatment-resistant depression

Ongoing experimental studies of subcallosal cingulate deep brain stimulation (SCC DBS) for treatment-resistant depression (TRD) show a differential timeline of behavioral effects with rapid changes after initial stimulation, and both early and delayed changes over the course of ongoing chronic stimulation. This study examined the longitudinal resting-state regional cerebral blood flow (rCBF) changes in intrinsic connectivity networks (ICNs) with SCC DBS for TRD over 6 months and repeated the same analysis by glucose metabolite changes in a new cohort. A total of twenty-two patients with TRD, 17 [15 O]-water and 5 [18 F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) patients, received SCC DBS and were followed weekly for 7 months. PET scans were collected at 4-time points: baseline, 1-month after surgery, and 1 and 6 months of chronic stimulation. A linear mixed model was conducted to examine the differential trajectory of rCBF changes over time. Post-hoc tests were also examined to assess postoperative, early, and late ICN changes and response-specific effects. SCC DBS had significant time-specific effects in the salience network (SN) and the default mode network (DMN). The rCBF in SN and DMN was decreased after surgery, but responder and non-responders diverged thereafter, with a net increase in DMN activity in responders with chronic stimulation. Additionally, the rCBF in the DMN uniquely correlated with depression severity. The glucose metabolic changes in a second cohort show the same DMN changes. The trajectory of PET changes with SCC DBS is not linear, consistent with the chronology of therapeutic effects. These data provide novel evidence of both an acute reset and ongoing plastic effects in the DMN that may provide future biomarkers to track clinical improvement with ongoing treatment.

Hippocampal and parahippocampal volume and function predict antidepressant response in patients with major depression: A multimodal neuroimaging study

BACKGROUND

For many patients with major depressive disorder (MDD) adequate treatment remains elusive. Neuroimaging techniques received attention for their potential use in guiding and predicting response, but were rarely investigated in real-world psychiatric settings.

AIMS

To identify structural and functional Magnetic Resonance Imaging (MRI) biomarkers associated with antidepressant response in a real-world clinical sample.

METHODS

We studied 100 MDD inpatients admitted to our psychiatric ward, treated with various antidepressants upon clinical need. Hamilton Depression Rating Scale percentage decrease from admission to discharge was used as a measure of response. All patients underwent 3.0 T MRI scanning. Grey matter (GM) volumes were investigated both in a voxel-based morphometry (VBM), and in a regions of interest (ROI) analysis. In a subsample of patients, functional resting-state connectivity patterns were also explored.

RESULTS

In the VBM analysis, worse response was associated to lower GM volumes in two clusters, encompassing the left hippocampus and parahippocampal gyrus, and the right superior and middle temporal gyrus. Investigating ROIs, lower bilateral hippocampi and amygdalae volumes predicted worse treatment outcomes. Functional connectivity in the right temporal and parahippocampal gyrus was also associated to response.

CONCLUSION

Our results expand existing literature on the relationship between the structure and function of several brain regions and treatment response in MDD. While we are still far from routine use of MRI biomarkers in clinical practice, we confirm a possible role of these techniques in guiding treatment choices and predicting their efficacy.

Network-level dynamics underlying a combined rTMS and psychotherapy treatment for major depressive disorder: An exploratory network analysis

Background

Despite the growing use of repetitive transcranial magnetic stimulation (rTMS) as a treatment for depression, there is a limited understanding of the mechanisms of action and how potential treatment-related brain changes help to characterize treatment response. To address this gap in understanding we investigated the effects of an approach combining rTMS with simultaneous psychotherapy on global functional connectivity.

Method

We compared task-related functional connectomes based on an idiographic goal priming task tied to emotional regulation acquired before and after simultaneous rTMS/psychotherapy treatment for patients with major depressive disorders and compared these changes to normative connectivity patterns from a set of healthy volunteers (HV) performing the same task.

Results

At baseline, compared to HVs, patients demonstrated hyperconnectivity of the DMN, cerebellum and limbic system, and hypoconnectivity of the fronto-parietal dorsal-attention network and visual cortex. Simultaneous rTMS/psychotherapy helped to normalize these differences, which were reduced after treatment. This finding suggests that the rTMS/therapy treatment regularizes connectivity patterns in both hyperactive and hypoactive brain networks.

Conclusions

These results help to link treatment to a comprehensive model of the neurocircuitry underlying depression and pave the way for future studies using network-guided principles to significantly improve rTMS efficacy for depression.

Transcutaneous electrical cranial-auricular acupoint stimulation versus escitalopram for modulating the brain activity in mild to moderate major depressive disorder: An fMRI study

Transcutaneous electrical cranial-auricular acupoint stimulation (TECAS) is an innovative, non-invasive therapy for major depressive disorder (MDD). However, its effectiveness and underlying neural mechanisms remain not fully understood. This study aimed to investigate the treatment response and neurological effects of TECAS compared to escitalopram, a commonly used depression medication, using resting-state functional magnetic resonance imaging (rs-fMRI). Fifty-one patients with mild-to-moderate MDD (34 in the TECAS group and 17 in the Escitalopram group) and 51 healthy controls (HCs) participated in the study. We employed the low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) methods to explore brain abnormalities in MDD patients and HCs. Additionally, seed-based functional connectivity (FC) analysis was conducted to examine altered brain networks before and after treatment.Compared to the HCs group, the MDD group exhibited lower ReHo and ALFF values in the right medial superior frontal gyrus (mSFG_R), indicating altered neural activity in this region. Furthermore, mSFG-based FC analysis revealed abnormal FC values in the right inferior occipital gyrus (IOG_R) and middle temporal gyrus (MTG) between after and before treatment in MDD patients. Interestingly, TECAS treatment was found to normalize these abnormal FC brain regions, suggesting its potential role in restoring neural connectivity in MDD patients. Notably, both TECAS and escitalopram demonstrated equivalent antidepressant efficacy, with both treatments showing modulatory effects on connectivity within the default mode network (DMN). The observed normalization of abnormal FC regions, including mSFG_R, IOG_R, and MTG, all belong to the DMN. In conclusion, this study sheds light on the neurological effects and treatment response of TECAS in MDD, highlighting its potential as a non-invasive therapeutic option for depressed patients.

Irremediability in psychiatric euthanasia: examining the objective standard

BACKGROUND

Irremediability is a key requirement for euthanasia and assisted suicide for psychiatric disorders (psychiatric EAS). Countries like the Netherlands and Belgium ask clinicians to assess irremediability in light of the patient's diagnosis and prognosis and 'according to current medical understanding'. Clarifying the relevance of a default objective standard for irremediability when applied to psychiatric EAS is crucial for solid policymaking. Yet so far, a thorough examination of this standard is lacking.

METHODS

Using treatment-resistant depression (TRD) as a test case, through a scoping review in PubMed, we analyzed the state-of-the-art evidence for whether clinicians can accurately predict individual long-term outcome and single out irremediable cases, by examining the following questions: (1) What is the definition of TRD; (2) What are group-level long-term outcomes of TRD; and (3) Can clinicians make accurate individual outcome predictions in TRD?

RESULTS

A uniform definition of TRD is lacking, with over 150 existing definitions, mostly focused on psychopharmacological research. Available yet limited studies about long-term outcomes indicate that a majority of patients with long-term TRD show significant improvement over time. Finally, evidence about individual predictions in TRD using precision medicine is growing, but methodological shortcomings and varying predictive accuracies pose important challenges for its implementation in clinical practice.

CONCLUSION

Our findings support the claim that, as per available evidence, clinicians cannot accurately predict long-term chances of recovery in a particular patient with TRD. This means that the objective standard for irremediability cannot be met, with implications for policy and practice of psychiatric EAS.

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.

Whole Brain Network effects of subcallosal cingulate deep brain stimulation for treatment-resistant depression

Ongoing experimental studies of subcallosal cingulate deep brain stimulation (SCC DBS) for treatment-resistant depression (TRD) show a differential timeline of behavioral effects with rapid changes after initial stimulation, and both early and delayed changes over the course of ongoing chronic stimulation. This study examined the longitudinal resting-state regional cerebral blood ow (rCBF) changes in intrinsic connectivity networks (ICNs) with SCC DBS for TRD over 6 months and repeated the same analysis by glucose metabolite changes in a new cohort. A total of twenty-two patients with TRD, 17 [15O]-water and 5 [18]-Fluorodeoxyglucose (FDG) positron emission tomography (PET) patients, received SCC DBS and were followed weekly for 7 months. PET scans were collected at 4-time points: baseline, 1-month after surgery, and 1 and 6 months of chronic stimulation. A linear mixed model was conducted to examine the differential trajectory of rCBF changes over time. Post-hoc tests were also examined to assess postoperative, early, and late ICN changes and response-specific effects. SCC DBS had significant time-specific effects in the salience network (SN) and the default mode network (DMN). The rCBF in SN and DMN was decreased after surgery, but responder and non-responders diverged thereafter, with a net increase in DMN activity in responders with chronic stimulation. Additionally, the rCBF in the DMN uniquely correlated with depression severity. The glucose metabolic changes in a second cohort show the same DMN changes. The trajectory of PET changes with SCC DBS is not linear, consistent with the chronology of therapeutic effects. These data provide novel evidence of both an acute reset and ongoing plastic effects in the DMN that may provide future biomarkers to track clinical improvement with ongoing treatment.

Functional MRI markers for treatment-resistant depression: Insights and challenges

Imaging studies of treatment-resistant depression (TRD) have examined brain activity, structure, and metabolite concentrations to identify critical areas of investigation in TRD as well as potential targets for treatment interventions. This chapter provides an overview of the main findings of studies using three imaging modalities: structural magnetic resonance imaging (MRI), functional MRI (fMRI), and magnetic resonance spectroscopy (MRS). Decreased connectivity and metabolite concentrations in frontal brain areas appear to characterize TRD, although results are not consistent across studies. Treatment interventions, including rapid-acting antidepressants and transcranial magnetic stimulation (TMS), have shown some efficacy in reversing these changes while alleviating depressive symptoms. However, comparatively few TRD imaging studies have been conducted, and these studies often have relatively small sample sizes or employ different methods to examine a variety of brain areas, making it difficult to draw firm conclusions from imaging studies about the pathophysiology of TRD. Larger studies with more unified hypotheses, as well as data sharing, could help TRD research and spur better characterization of the illness, providing critical new targets for treatment intervention.

Neural predictors of cognitive-behavior therapy outcome in anxiety-related disorders: a meta-analysis of task-based fMRI studies

BACKGROUND

Cognitive-behavior therapy (CBT) is a well-established first-line intervention for anxiety-related disorders, including specific phobia, social anxiety disorder, panic disorder/agoraphobia, generalized anxiety disorder, obsessive-compulsive disorder, and posttraumatic stress disorder. Several neural predictors of CBT outcome for anxiety-related disorders have been proposed, but previous results are inconsistent.

METHODS

We conducted a systematic review and meta-analysis of task-based functional magnetic resonance imaging (fMRI) studies investigating whole-brain predictors of CBT outcome in anxiety-related disorders (17 studies, n = 442).

RESULTS

Across different tasks, we observed that brain response in a network of regions involved in salience and interoception processing, encompassing fronto-insular (the right inferior frontal gyrus-anterior insular cortex) and fronto-limbic (the dorsomedial prefrontal cortex-dorsal anterior cingulate cortex) cortices was strongly associated with a positive CBT outcome.

CONCLUSIONS

Our results suggest that there are robust neural predictors of CBT outcome in anxiety-related disorders that may eventually lead (probably in combination with other data) to develop personalized approaches for the treatment of these mental disorders.

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.

Effects of bilateral sequential theta-burst stimulation on 5-HT1A receptors in the dorsolateral prefrontal cortex in treatment-resistant depression: a proof-of-concept trial

Theta-burst stimulation (TBS) represents a brain stimulation technique effective for treatment-resistant depression (TRD) as underlined by meta-analyses. While the methodology undergoes constant refinement, bilateral stimulation of the dorsolateral prefrontal cortex (DLPFC) appears promising to restore left DLPFC hypoactivity and right hyperactivity found in depression. The post-synaptic inhibitory serotonin-1A (5-HT1A) receptor, also occurring in the DLPFC, might be involved in this mechanism of action. To test this hypothesis, we performed PET-imaging using the tracer [carbonyl-11C]WAY-100635 including arterial blood sampling before and after a three-week treatment with TBS in 11 TRD patients compared to sham stimulation (n = 8 and n = 3, respectively). Treatment groups were randomly assigned, and TBS protocol consisted of excitatory intermittent TBS to the left and inhibitory continuous TBS to the right DLPFC. A linear mixed model including group, hemisphere, time, and Hamilton Rating Scale for Depression (HAMD) score revealed a 3-way interaction effect of group, time, and HAMD on specific distribution volume (VS) of 5-HT1A receptor. While post-hoc comparisons showed no significant changes of 5-HT1A receptor VS in either group, higher 5-HT1A receptor VS after treatment correlated with greater difference in HAMD (r = -0.62). The results of this proof-of-concept trial hint towards potential effects of TBS on the distribution of the 5-HT1A receptor. Due to the small sample size, all results must, however, be regarded with caution.

Parietal-hippocampal rTMS improves cognitive function in Alzheimer's disease and increases dynamic functional connectivity of default mode network

Parietal-hippocampal repetitive transcranial magnetic stimulation (rTMS) improves cognitive function in Alzheimer's disease (AD), however, the underlying therapeutic mechanism has not been elucidated. A double-blind, randomized, sham-controlled parietal-hippocampal rTMS trial (five sessions/week for a total of 10 sessions) of mild-to-moderate AD patients was conducted in the study. High-frequency rTMS was applied to a subject-specific left lateral parietal region with the highest functional connectivity with the hippocampus based on resting-state fMRI. A multimodal MRI scan and a complete neuropsychological battery of tests were conducted at baseline, immediately after the intervention and 12-week follow-up after the rTMS treatment. Compared to sham treatment (n = 27), patients undergoing active rTMS treatment (n = 29) showed higher Mini Mental State Examination (MMSE) score and dynamic functional connectivity (dFC) magnitude of the default mode network (DMN) after two weeks of rTMS treatment, but not at 12-week follow-up. A significant positive correlation was observed between changes in MMSE and changes in the dFC magnitude of DMN in patients who underwent active-rTMS treatment, but not in those who received sham-rTMS treatment. The findings of the current study indicate that fMRI-guided rTMS treatment improves cognitive function of AD patients in the short term, and DMN functional connectivity contributes to therapeutic effectiveness of rTMS.

The Impact of Theta-Burst Stimulation on Cortical GABA and Glutamate in Treatment-Resistant Depression: A Surface-Based MRSI Analysis Approach

Background: Theta burst stimulation (TBS) belongs to one of the biological antidepressant treatment options. When applied bilaterally, excitatory intermittent TBS (iTBS) is commonly targeted to the left and inhibitory continuous TBS (cTBS) to the right dorsolateral prefrontal cortex. TBS was shown to influence neurotransmitter systems, while iTBS is thought to interfere with glutamatergic circuits and cTBS to mediate GABAergic neurotransmission.

Objectives: We aimed to expand insights into the therapeutic effects of TBS on the GABAergic and glutamatergic system utilizing 3D-multivoxel magnetic resonance spectroscopy imaging (MRSI) in combination with a novel surface-based MRSI analysis approach to investigate changes of cortical neurotransmitter levels in patients with treatment-resistant depression (TRD).

Methods: Twelve TRD patients (five females, mean age ± SD = 35 ± 11 years) completed paired MRSI measurements, using a GABA-edited 3D-multivoxel MEGA-LASER sequence, before and after 3 weeks of bilateral TBS treatment. Changes in cortical distributions of GABA+/tNAA (GABA+macromolecules relative to total N-acetylaspartate) and Glx/tNAA (Glx = mixed signal of glutamate and glutamine), were investigated in a surface-based region-of-interest (ROI) analysis approach.

Results: ANCOVAs revealed a significant increase in Glx/tNAA ratios in the left caudal middle frontal area (p_corr. = 0.046, F = 13.292), an area targeted by iTBS treatment. Whereas, contralateral treatment with cTBS evoked no alterations in glutamate or GABA concentrations.

Conclusion: This study demonstrates surface-based adaptions in the stimulation area to the glutamate metabolism after excitatory iTBS but not after cTBS, using a novel surface-based analysis of 3D-MRSI data. The reported impact of facilitatory iTBS on glutamatergic neurotransmission provides further insight into the neurobiological effects of TBS in TRD.

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

OBJECTIVE

The study objective was to investigate the predictive value of functional connectivity changes induced by acute repetitive transcranial magnetic stimulation (rTMS) for clinical response in treatment-resistant depression.

METHODS

Cross-sectional changes in functional connectivity induced by a single concurrent rTMS-fMRI session were assessed in 38 outpatients with treatment-resistant depression (26 of them female; mean age, 41.87 years) who subsequently underwent a 4-week course of rTMS. rTMS was delivered at 1 Hz over the right dorsolateral prefrontal cortex. Acute rTMS-induced functional connectivity changes were computed and subjected to connectome-based predictive modeling to test their association with changes in score on the Montgomery-Åsberg Depression Rating Scale (MADRS) after rTMS treatment.

RESULTS

TMS-fMRI induced widespread, acute, and transient alterations in functional connectivity. The rTMS-induced connectivity changes predicted about 30% of the variance of improvement in the MADRS score. The most robust predictive associations involved connections between prefrontal regions and motor, parietal, and insular cortices and between bilateral regions of the thalamus.

CONCLUSIONS

Acute rTMS-induced connectivity changes in patients with treatment-resistant depression may index macro-level neuroplasticity, relevant to interindividual variability in rTMS treatment response. Large-scale network phenomena occurring during rTMS might be used to inform prospective clinical trials.

Modulation of dorsolateral prefrontal cortex functional connectivity after intermittent theta-burst stimulation in depression: Combining findings from fNIRS and fMRI

BACKGROUND

Resting-state functional magnetic resonance imaging (fMRI) can assess modulation of functional connectivity networks following repetitive transcranial magnetic stimulation (rTMS) in the treatment of depression. Functional near-infrared spectroscopy (fNIRS) is well suited for the concurrent application during rTMS treatment sessions to capture immediate blood oxygenation (oxy-Hb) effects, however limited in spatial resolution.

OBJECTIVE

To understand the network effects behind such a prefrontal fNIRS response during rTMS, and to test whether the fNIRS signal may be predictive of treatment response, we linked data from fNIRS and fMRI within a clinical intervention study.

METHODS

42 patients with ongoing depression were recruited and randomized to receive active or sham intermittent theta-burst stimulation (iTBS) over the dorsomedial prefrontal cortex (dmPFC) twice daily for ten days at target intensity. Oxy-Hb was recorded with fNIRS during the first, fifth, and final day of iTBS, with the probe holders located laterally to the TMS coil over regions corresponding to the left and right dorsolateral prefrontal cortex (dlPFC). Resting-state fMRI scanning was performed before and after the whole iTBS treatment course. Functional connectivity analyses were then performed using dlPFC seeds from parcels of a brain atlas showing most overlap with the fNIRS probe locations during treatment.

RESULTS

After active iTBS, left dlPFC-connectivity to the right insula/operculum was reduced compared to sham. The left insula showed a connectivity reduction to the left dlPFC that correlated with an improvement in symptoms. In addition, the posterior parietal cortex showed a connectivity reduction to the left dlPFC that correlated with the fNIRS signal following active iTBS. Finally, the fNIRS oxy-Hb signal from the left dlPFC-seed during the first treatment day was predictive of dlPFC-connectivity change to precentral and temporal cortex regions.

CONCLUSION

By linking findings from these two different methods, this study suggests that changes within both the salience network and the central executive network affect the fNIRS response to iTBS.

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

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

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.

Structural covariance pattern abnormalities of insula in major depressive disorder: A CAN-BIND study report

BACKGROUND AND METHODS

Investigation of the insula may inform understanding of the etiopathogenesis of major depressive disorder (MDD). In the present study, we introduced a novel gray matter volume (GMV) based structural covariance technique, and applied it to a multi-centre study of insular subregions of 157 patients with MDD and 93 healthy controls from the Canadian Biomarker Integration Network in Depression (CAN-BIND, https://www.canbind.ca/). Specifically, we divided the unilateral insula into three subregions, and investigated their coupling with whole-brain GMV-based structural brain networks (SBNs). We compared between-group difference of the structural coupling patterns between the insular subregions and SBNs.

RESULTS

The insula was divided into three subregions, including an anterior one, a superior-posterior one and an inferior-posterior one. In the comparison between MDD patients and controls we found that patients' right anterior insula showed increased inter-network coupling with the default mode network, and it showed decreased inter-network coupling with the central executive network; whereas patients' right ventral-posterior insula showed decreased inter-network coupling with the default mode network, and it showed increased inter-network coupling with the central executive network. We also demonstrated that patients' loading parameters of the right ventral-posterior insular structural covariance negatively correlated with their suicidal ideation scores; and controls' loading parameters of the right ventral-posterior insular structural covariance positively correlated with their motor and psychomotor speed scores, whereas these phenomena were not found in patients. Additionally, we did not find significant inter-network coupling between the whole-brain SBNs, including salience network, default mode network, and central executive network.

CONCLUSIONS

Our work proposed a novel technique to investigate the structural covariance coupling between large-scale structural covariance networks, and provided further evidence that MDD is a system-level disorder that shows disrupted structural coupling between brain networks.

Predicting treatment selections for individuals with major depressive disorder according to functional connectivity subgroups

BACKGROUND

Major depressive disorder (MDD) is a highly prevalent and disabling disease. Currently, patients' treatment choices depend on their clinical symptoms observed by clinicians, which are subjective. Rich evidence suggests that different functional networks' dysfunctions correspond to different intervention preferences. Here, we aimed to develop a prediction model based on data-driven subgroups to provide treatment recommendations.

METHODS

All 630 participants enrolled from four sites underwent functional magnetic resonances imaging at baseline. In the discovery dataset (n=228), we firstly identified MDD subgroups by the hierarchical clustering method using the canonical variates of resting-state functional connectivity (FC) through canonical correlation analyses. The demographic, symptom improvement and FC were compared among subgroups. The preference intervention for each subgroup was also determined. Next, we predicted the individual treatment strategy. Specifically, a patient was assigned into predefined subgroups based on FC similarities and then his/her treatment strategy was determined by the subgroups' preferred interventions.

RESULTS

Three subgroups with specific treatment recommendations were emerged including: (1) a selective serotonin reuptake inhibitors-oriented subgroup with early improvements in working and activities. (2) a stimulation-oriented subgroup with more alleviation in suicide. (3) a selective serotonin noradrenaline reuptake inhibitors-oriented subgroup with more alleviation in hypochondriasis. Through cross-dataset testing respectively conducted on three testing datasets, results showed an overall accuracy of 72.83%.

CONCLUSIONS

Our works revealed the correspondences between subgroups and their treatment preferences and predicted individual treatment strategy based on such correspondences. Our model has the potential to support psychiatrists in early clinical decision making for better treatment outcomes.

Handedness and depression: A meta-analysis across 87 studies

Alterations in functional brain lateralization, often indicated by an increased prevalence of left- and/or mixed-handedness, have been demonstrated in several psychiatric and neurodevelopmental disorders like schizophrenia or autism spectrum disorder. For depression, however, this relationship is largely unclear. While a few studies found evidence that handedness and depression are associated, both the effect size and the direction of this association remain elusive. Here, we collected data from 87 studies totaling 35,501 individuals to provide a precise estimate of differences in left-, mixed- and non-right-handedness between depressed and healthy samples and computed odds ratios (ORs) between these groups. Here, an OR > 1 signifies higher rates of atypical handedness in depressed compared to healthy samples. We found no differences in left- (OR = 1.04, 95% CI = [0.95, 1.15], p = .384), mixed- (OR = 1.64, 95% CI = [0.98, 2.74], p = .060) or non-right-handedness (OR = 1.05, 95% CI = [0.96, 1.15], p = .309) between the two groups. We could thus find no link between handedness and depression on the meta-analytical level.

Treating cocaine and opioid use disorder with transcranial magnetic stimulation: A path forward

Developing new, effective treatments for substance use disorders (SUDs), especially cocaine and opioid use disorders (CUD and OUD), are of immense importance. These are chronic, relapsing brain diseases characterized by dysregulated circuits manifesting from neuroplastic change brought on by repeated exposure to substances of abuse. A potential treatment is therapeutically inducing neuroplastic change in targeted dysregulated circuits. One such intervention, repetitive transcranial magnetic stimulation (rTMS) has gained traction over the past two decades as a method of noninvasively stimulating cortical structures in order to induce subcortical neuroplastic change. By doing so, rTMS ameliorates symptoms that are consequent of dysregulations in disease-related circuits, such as craving, and reduces drug use. Although rTMS has been successfully applied as a treatment for other clinical disorders, progress toward treatment applications for SUDs has been stymied by what we dub "known unknowns". These are fundamental lines of research within the rTMS-SUD field that have yet to be systematically understood which could help to optimize TMS as an intervention for SUDs. Because progress in treatment for CUD and OUD is imperative given the widespread severity of OUD and the lack of treatment for CUD, it is necessary to critically reflect on the ways in which rTMS research for these disorders can most effectively move forward to help patients. We articulate six "known unknowns" and outline a direction of research to address each. Briefly, the "known unknowns" in the field are: 1) Cortical target selection, 2) subcortical circuit engagement, 3) optimizing rTMS sequences, 4) rTMS as an adjuvant to existing interventions, 5) manipulating brain state, and 6) selecting outcome measures. We also outline research design approaches to address these "known unknowns" in the rTMS-SUDs field. Unification of efforts across research laboratories is necessary to develop empirically validated treatments that will benefit patients in a timely fashion.

Repetitive Transcranial Magnetic Stimulation Target Location Methods for Depression

Major depressive disorder (MDD) is a substantial global public health problem in need of novel and effective treatment strategies. Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive and promising treatment for depression that has been approved by the U.S. Food and Drug Administration (FDA). However, the methodological weaknesses of existing work impairs the universal clinical use of rTMS. The variation of stimulated targets across the dorsolateral prefrontal cortex may account for most of the heterogeneity in the efficacy of rTMS. Many rTMS target location methods for MDD have been developed in recent decades. This review was conducted to assess this emerging field and to improve treatment outcomes in clinical practice.

Transcranial Magnetic and Direct Current Stimulation in the Treatment of Depression: Basic Mechanisms and Challenges of Two Commonly Used Brain Stimulation Methods in Interventional Psychiatry

Noninvasive neuromodulation, including repetitive trans-cranial magnetic stimulation (rTMS) and direct current stimulation (tDCS), provides researchers and health care professionals with the ability to gain unique insights into brain functions and treat several neurological and psychiatric conditions. Undeniably, the number of published research and clinical papers on this topic is increasing exponentially. In parallel, several methodological and scientific caveats have emerged in the transcranial stimulation field; these include less robust and reliable effects as well as contradictory clinical findings. These inconsistencies are maybe due to the fact that research exploring the relationship between the methodological aspects and clinical efficacy of rTMS and tDCS is far from conclusive. Hence, additional work is needed to understand the mechanisms underlying the effects of magnetic stimulation and low-intensity transcranial electrical stimulation (TES) in order to optimize dosing, methodological designs, and safety aspects.

Repetitive Transcranial Magnetic Stimulation for Adolescent Major Depressive Disorder: A Focus on Neurodevelopment

Adolescent depression is a potentially lethal condition and a leading cause of disability for this age group. There is an urgent need for novel efficacious treatments since half of adolescents with depression fail to respond to current therapies and up to 70% of those who respond will relapse within 5 years. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising treatment for major depressive disorder (MDD) in adults who do not respond to pharmacological or behavioral interventions. In contrast, rTMS has not demonstrated the same degree of efficacy in adolescent MDD. We argue that this is due, in part, to conceptual and methodological shortcomings in the existing literature. In our review, we first provide a neurodevelopmentally focused overview of adolescent depression. We then summarize the rTMS literature in adult and adolescent MDD focusing on both the putative mechanisms of action and neurodevelopmental factors that may influence efficacy in adolescents. We then identify limitations in the existing adolescent MDD rTMS literature and propose specific parameters and approaches that may be used to optimize efficacy in this uniquely vulnerable age group. Specifically, we suggest ways in which future studies reduce clinical and neural heterogeneity, optimize neuronavigation by drawing from functional brain imaging, apply current knowledge of rTMS parameters and neurodevelopment, and employ an experimental therapeutics platform to identify neural targets and biomarkers for response. We conclude that rTMS is worthy of further investigation. Furthermore, we suggest that following these recommendations in future studies will offer a more rigorous test of rTMS as an effective treatment for adolescent depression.

Prefrontal resting-state connectivity and antidepressant response: no associations in the ELECT-TDCS trial

Functional and structural MRI of prefrontal cortex (PFC) may provide putative biomarkers for predicting the treatment response to transcranial direct current stimulation (tDCS) in depression. A recent MRI study from ELECT-TDCS (Escitalopram versus Electrical Direct-Current Theror Depression Study) showed that depression improvement after tDCS was associated with gray matter volumes of PFC subregions. Based thereon, we investigated whether antidepressant effects of tDCS are similarly associated with baseline resting-state functional connectivity (rsFC). A subgroup of 51 patients underwent baseline rsFC-MRI. All patients of ELECT-TDCS were randomized to three treatment arms for 10 weeks (anodal-left, cathodal-right PFC tDCS plus placebo medication; escitalopram 10 mg/day for 3 weeks and 20 mg/day thereafter plus sham tDCS; and placebo medication plus sham tDCS). RsFC was calculated for various PFC regions and analyzed in relation to the individual antidepressant response. There was no significant association between baseline PFC connectivity of essential structural regions, nor any other PFC regions (after correction for multiple comparisons) and patients' individual antidepressant response. This study did not reveal an association between antidepressants effects of tDCS and baseline rsFC, unlike the gray matter volume findings. Thus, the antidepressant effects of tDCS may be differentially related to structural and functional MRI measurements.

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.

Changes in Functional Connectivity Predict Outcome of Repetitive Transcranial Magnetic Stimulation Treatment of Major Depressive Disorder

Repetitive transcranial magnetic stimulation (rTMS) treatment of major depressive disorder (MDD) is associated with changes in brain functional connectivity (FC). These changes may be related to the mechanism of action of rTMS and explain the variability in clinical outcome. We examined changes in electroencephalographic FC during the first rTMS treatment in 109 subjects treated with 10 Hz stimulation to left dorsolateral prefrontal cortex. All subjects subsequently received 30 treatments and clinical response was defined as ≥40% improvement in the inventory of depressive symptomatology-30 SR score at treatment 30. Connectivity change was assessed with coherence, envelope correlation, and a novel measure, alpha spectral correlation (αSC). Machine learning was used to develop predictive models of outcome for each connectivity measure, which were compared with prediction based upon early clinical improvement. Significant connectivity changes were associated with clinical outcome (P < 0.001). Machine learning models based on αSC yielded the most accurate prediction (area under the curve, AUC = 0.83), and performance improved when combined with early clinical improvement measures (AUC = 0.91). The initial rTMS treatment session produced robust changes in FC, which were significant predictors of clinical outcome of a full course of treatment for MDD.

Prediction on treatment improvement in depression with resting state connectivity: A coordinate-based meta-analysis

BACKGROUND

Previous neuroimaging studies revealed abnormal resting-state functional connectivity between distributed brain areas in patients with major depressive disorder. Those abnormalities were normalized after treatment. Moreover, the functional connectivity could predict clinical response to those treatments. However, there has currently been no meta-analysis to verify these findings.

METHODS

The current study aimed to investigate how the resting-state connectivity patterns predict antidepressant response to various treatments across depressive studies by using coordinate-based meta-analysis named activation likelihood estimation. The relevant articles were obtained by searching on PubMed and Web of Science.

RESULTS

Following exclusion criteria of inappropriate studies, seventeen papers with 392 individual depressive patients were included. Those articles contained repetitive transcranial magnetic stimulation (rTMS) treatment, pharmacotherapy, cognitive behavioral therapy (CBT), electroconvulsive therapy (ECT) and transcutaneous vagus nerve stimulation in patients with depression. Meta-analysis revealed that clinical response to all treatments could be predicted by baseline default mode network connectivity in patients with depression. The rTMS treatment had larger effect size compared to other treatment strategies. Furthermore, subgroup meta-analysis showed that the baseline connectivity of perigenual anterior cingulate cortex (pgACC) and ventral medial prefrontal cortex could predict symptoms improvement of rTMS treatment.

LIMITATIONS

More resting-state connectivity studies of CBT and ECT treatment are needed.

CONCLUSIONS

This study highlighted crucial role of DMN, especially the pgACC, in understanding the underlying treatment mechanism of depression.

Using resting-state intrinsic network connectivity to identify suicide risk in mood disorders

BACKGROUND

Little is known about the neural substrates of suicide risk in mood disorders. Improving the identification of biomarkers of suicide risk, as indicated by a history of suicide-related behavior (SB), could lead to more targeted treatments to reduce risk.

METHODS

Participants were 18 young adults with a mood disorder with a history of SB (as indicated by endorsing a past suicide attempt), 60 with a mood disorder with a history of suicidal ideation (SI) but not SB, 52 with a mood disorder with no history of SI or SB (MD), and 82 healthy comparison participants (HC). Resting-state functional connectivity within and between intrinsic neural networks, including cognitive control network (CCN), salience and emotion network (SEN), and default mode network (DMN), was compared between groups.

RESULTS

Several fronto-parietal regions (k > 57, p < 0.005) were identified in which individuals with SB demonstrated distinct patterns of connectivity within (in the CCN) and across networks (CCN-SEN and CCN-DMN). Connectivity with some of these same regions also distinguished the SB group when participants were re-scanned after 1-4 months. Extracted data defined SB group membership with good accuracy, sensitivity, and specificity (79-88%).

CONCLUSIONS

These results suggest that individuals with a history of SB in the context of mood disorders may show reliably distinct patterns of intrinsic network connectivity, even when compared to those with mood disorders without SB. Resting-state fMRI is a promising tool for identifying subtypes of patients with mood disorders who may be at risk for suicidal behavior.

Two-week rTMS-induced neuroimaging changes measured with fMRI in depression

OBJECTIVE

To study the neuroimaging mechanisms of repetitive transcranial magnetic stimulation (rTMS) in treating major depressive disorder (MDD).

METHODS

Twenty-seven treatment-naive patients with major depressive disorder (MDD) and 27 controls were enrolled. All of them were scanned with resting-state functional magnetic resonance imaging (fMRI) at baseline, and 15 patients were rescanned after two-week rTMS. The amplitude of low frequency fluctuation (ALFF) and functional connection degree (FCD), based on voxels and 3 brain networks (default mode network [DMN], central executive network [CEN], salience network[SN]),were used as imaging indicators to analyze. The correlations of brain imaging changes after rTMS with clinical efficacy were calculated.

RESULTS

At baseline, patients groups showed increased ALFF in the right orbital frontal cortex (OFC) and decreased ALFF in the left striatal cortex and medial prefrontal cortex (PFC), while increased FCD in the right dorsal anterior cingulate cortex and OFC and decreased FCD in the right inferior parietal lobe and in the CEN. After rTMS, patients showed increased ALFF in the left dorsolateral prefrontal cortex (DLPFC)and superior frontal gyrus, FCD in the right dorsal anterior cingulate cortex, superior temporal gyrus and CEN, as well as decreased FCD in the bilateral lingual gyrus than pre-rTMS . These rTMS induced neuroimaging changes did not significantly correlated with clinical effecacy.

CONCLUSIONS

This study indicated that rTMS resulted in changes of ALFF and FCD in some brain regions and CEN. But we could not conclude this is the neuroimaging mechanism of rTMS according to the correlation analysis.

Frequency-Specific Changes in the Fractional Amplitude of the Low-Frequency Fluctuations in the Default Mode Network in Medication-Free Patients With Bipolar II Depression: A Longitudinal Functional MRI Study

Objective: This study aimed to examine the treatment-related changes of the fractional amplitude of low-frequency fluctuations (fALFF) in the default mode network (DMN) across different bands after the medication-free patients with bipolar II depression received a 16-week treatment of escitalopram and lithium. Methods: A total of 23 medication-free patients with bipolar II depression and 29 healthy controls (HCs) were recruited. We evaluated the fALFF values of slow 4 (0.027-0.073 Hz) band and slow 5 (0.01-0.027 Hz) band of the patients and compared the results with those of the 29 HCs at baseline. After 16-week treatment of escitalopram with lithium, the slow 4 and slow 5 fALFF values of the patients were assessed and compared with the baselines of patients and HCs. The depressive symptoms of bipolar II depression in patients were assessed with a 17-item Hamilton Depression Rating Scale (HDRS) before and after treatment. Results: Treatment-related effects showed increased slow 5 fALFF in cluster D (bilateral medial superior frontal gyrus, bilateral superior frontal gyrus, right middle frontal gyrus, and bilateral anterior cingulate), cluster E (bilateral precuneus/posterior cingulate, left cuneus), and cluster F (left angular, left middle temporal gyrus, left superior temporal gyrus, and left supramarginal gyrus) in comparison with the baseline of the patients. Moreover, a positive association was found between the increase in slow 5 fALFF values (follow-up value minus the baseline values) in cluster D and the decrease in HDRS scores (baseline HDRS scores minus follow-up HDRS scores) at follow-up, and the same association between the increase in slow 5 fALFF values and the decrease in HDRS scores was found in cluster E. Conclusions: The study reveals that the hypoactivity of slow 5 fALFF in the DMN is related to depression symptoms and might be corrected by the administration of escitalopram with lithium, implying that slow 5 fALFF of the DMN plays a key role in bipolar depression.

Integrating sleep, neuroimaging, and computational approaches for precision psychiatry

In advancing precision psychiatry, we focus on what imaging technology and computational approaches offer for the future of diagnostic subtyping and personalized tailoring of interventions for sleep impairment in mood and anxiety disorders. Current diagnostic criteria for mood and anxiety tend to lump different forms of sleep disturbance together. Parsing the biological features of sleep impairment and brain circuit dysfunction is one approach to identifying subtypes within these disorders that are mechanistically coherent and offer targets for intervention. We focus on two large-scale neural circuits implicated in sleep impairment and in mood and anxiety disorders: the default mode network and negative affective network. Through a synthesis of existing knowledge about these networks, we pose a testable framework for understanding how hyper- versus hypo-engagement of these networks may underlie distinct features of mood and sleep impairment. Within this framework we consider whether poor sleep quality may have an explanatory role in previously observed associations between network dysfunction and mood symptoms. We expand this framework to future directions including the potential for connecting circuit-defined subtypes to more distal features derived from digital phenotyping and wearable technologies, and how new discovery may be advanced through machine learning approaches.

Repetitive Transcranial Magnetic Stimulation Delivered With an H-Coil to the Right Insula Reduces Functional Connectivity Between Insula and Medial Prefrontal Cortex

OBJECTIVE

Insula neurocircuitry alterations are reported in a range of neuropsychiatric disorders holding promise for clinical interventions. We measured, in a pilot study, acute neuroplastic modulations resulting from high- and low-frequency stimulation with repetitive transcranial magnetic stimulation (rTMS) delivered via an H-coil that targeted the right insula and overlying prefrontal cortex.

METHODS

Healthy, nonsmoking, adult participants (N = 28), in a within-participant, sham-controlled experiment, received a single rTMS session on four separate days. Participants received one session each of low- (1 Hz) and high (10 Hz)-frequency stimulation and two sessions of sham stimulation matched to each rTMS frequency. After each rTMS session, participants completed a functional magnetic resonance imaging (fMRI) scan while performing two cognitive tasks and a resting-state scan. The effect of rTMS was examined on task behavior as well as blood oxygenated level-dependent (BOLD) response during task performance and resting state. We expected low- and high-frequency stimulation to decrease and increase, respectively, insula and overlying cortical BOLD signal and network connectivity.

RESULTS/CONCLUSIONS

There was no effect of rTMS, regardless of frequency, on task behavior or task-based BOLD response. There was an effect of rTMS compared to sham on rsFC between insula and medial prefrontal cortex, with connectivity reduced after rTMS compared to sham, regardless of frequency. Implications for using rTMS to the insula as a treatment for neuropsychiatric disorders are discussed in light of insula-medial prefrontal cortex connectivity.

Functional connectivity of the anterior cingulate cortex predicts treatment outcome for rTMS in treatment-resistant depression at 3-month follow-up

BACKGROUND AND OBJECTIVE

Repetitive transcranial magnetic stimulation (rTMS) is a first-line treatment for treatment-resistant depression (TRD). The mechanisms of action of rTMS are not fully understood, and no biomarkers are available to assist in clinical practice to predict response to rTMS. This study aimed to demonstrate that after-rTMS clinical improvement is associated with functional connectivity (FC) changes of the subgenual cingulate cortex (sgACC) and rostral anterior cingulate (rACC), and FC of sgACC and rACC might serve as potential predictors for treatment response.

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected within 1 week before rTMS initiation in 50 TRD patients to predict subsequent response to rTMS on the left dorsolateral prefrontal cortex (DLPFC). Follow-up rs-fMRI was obtained 12 weeks after completion of rTMS and neural correlates of rTMS in sgACC- and rACC-related FC patterns were compared to before rTMS data and with rs-fMRI from healthy participants.

RESULTS

Treatment response was associated with lower FC of sgACC to right DLPFC and higher FC of rACC to left lateral parietal cortex (IPL) measured at baseline. Using sgACC-DLPFC and rACC-IPL connectivity as features, responder-nonresponder classification accuracies of 84% and 76% (end-of-treatment), 88% and 81% (3-month follow-up), respectively were achieved. Longitudinal rs-fMRI data analyses revealed that the hyperconnectivity between sgACC and visual cortex was normalized to a level which was comparable to that of healthy participants.

CONCLUSIONS

Brain activity patterns in depression are predictive of treatment response to rTMS, and longitudinal change of brain activity in relevant brain circuits after rTMS is associated with treatment response in depression. Target engagement paradigms may offer opportunities to increase the efficacy of rTMS in TRD by optimal selection of patients for treatment.

TRIAL REGISTRATION

ClinicalTrials.gov Identifiers: NCT01887782 and NCT02800226.

Structural network integrity of the central executive network is associated with the therapeutic effect of rTMS in treatment resistant depression

Repetitive transcranial magnetic stimulation (rTMS) is a first-line option for treatment-resistant depression (TRD), but prediction of treatment outcome remains a clinical challenge. The present study aimed to compare structural and functional covariance networks (SCNs and FCNs) between remitters and nonremitters. We determined the predictive capacities of SCNs and FCNs to discriminate the two groups. Fifty TRD patients underwent a course of rTMS to the left dorsolateral prefrontal cortex. They were categorized into remitters (n = 22) and nonremitters (n = 28) based on HDRS≤7 at the end of treatment. Baseline structural and functional magnetic imaging (sMRI and fMRI) of the patients and 42 healthy controls were collected. SCNs and FCNs were defined based on structural and functional covariance of gray mater volume (GMV) and fractional amplitude of low-frequency fluctuations (fALFF) from sMRI and fMRI, respectively. Structural/functional network integrity of these networks (default mode network [DMN], central executive network [CEN] and salience network [SN]) were compared between the three groups. In patients, associations between SCNs and FCNs with clinical improvements were studied using linear correlation analysis. Receiver-operating characteristic (ROC) analysis was conducted to confirm the utility of the SCNs and FCNs in classifying clinical sub-groups. Nonremitters exhibited lower structural integrity in CEN than remitters and controls. Higher structural integrity of CEN was related to clinical improvement (r = 0.423, p = .002), and structural integrity distinguished remitters and nonremitters with a fairly high accuracy (AUC = 0.71, p = .008). No group differences or correlation with clinical changes were found in FCNs. Results suggest the CEN may play a role mediating clinical improvement in rTMS for depression. Structural covariance networks may be features to consider in prediction of clinical improvement.

The use of transcranial magnetic stimulation as a treatment for movement disorders: A critical review

BACKGROUND

Transcranial magnetic stimulation is a safe and painless non-invasive brain stimulation technique that has been largely used in the past 30 years to explore cortical function in healthy participants and, inter alia, the pathophysiology of movement disorders. During the years, its use has evolved from primarily research purposes to treatment of a large variety of neurological and psychiatric diseases. In this article, we illustrate the basic principles on which the therapeutic use of transcranial magnetic stimulation is based and review the clinical trials that have been performed in patients with movement disorders.

METHODS

A search of the PubMed database for research and review articles was performed on therapeutic applications of transcranial magnetic stimulation in movement disorders. The search included the following conditions: Parkinson's disease, dystonia, Tourette syndrome and other chronic tic disorders, Huntington's disease and choreas, and essential tremor. The results of the studies and possible mechanistic explanations for the relatively minor effects of transcranial magnetic stimulation are discussed. Possible ways to improve the methodology and achieve greater therapeutic efficacy are discussed.

CONCLUSION

Despite the promising and robust rationales for the use of transcranial magnetic stimulations as a treatment tool in movement disorders, the results taken as a whole are not as successful as were initially expected. There is encouraging evidence that transcranial magnetic stimulation may improve motor symptoms and depression in Parkinson's disease, but the efficacy in other movement disorders is unclear. Possible improvements in methodology are on the horizon but have yet to be implemented in large clinical studies. © 2019 International Parkinson and Movement Disorder Society © 2019 International Parkinson and Movement Disorder Society.

Multidimensional imaging techniques for prediction of treatment response in major depressive disorder

A large number of studies have attempted to use neuroimaging tools to aid in treatment prediction models for major depressive disorder (MDD). Most such studies have reported on only one dimension of function and prediction at a time. In this study, we used three different tasks across domains of function (emotion processing, reward anticipation, and cognitive control, plus resting state connectivity completed prior to start of medication to predict treatment response in 13-36 adults with MDD. For each experiment, adults with MDD were prescribed only label duloxetine (all experiments), whereas another subset were prescribed escitalopram. We used a KeyNet (both Task derived masks and Key intrinsic Network derived masks) approach to targeting brain systems in a specific match to tasks. The most robust predictors were (Dichter et al., 2010) positive response to anger and (Gong et al., 2011) negative response to fear within relevant anger and fear TaskNets and Salience and Emotion KeyNet (Langenecker et al., 2018) cognitive control (correct rejections) within Inhibition TaskNet (negative) and Cognitive Control KeyNet (positive). Resting state analyses were most robust for Cognitive control Network (positive) and Salience and Emotion Network (negative). Results differed by whether an -fwhm or -acf (more conservative) adjustment for multiple comparisons was used. Together, these results implicate the importance of future studies with larger sample sizes, multidimensional predictive models, and the importance of using empirically derived masks for search areas.

Segregation of salience network predicts treatment response of depression to repetitive transcranial magnetic stimulation

Background

The present study tested the hypothesis that network segregation, a graph theoretic measure of functional organization of the brain, is correlated with treatment response in patients with major depressive disorder (MDD) undergoing repetitive transcranial magnetic stimulation (rTMS).

Methods

Network segregation, calculated from resting state functional magnetic resonance imaging scans, was measured in 32 patients with MDD who entered a sham-controlled, double-blinded, randomized trial of rTMS to the left dorsolateral prefrontal cortex, and a cohort of 20 healthy controls (HCs). Half of the MDD patients received sham treatment in the blinded phase, followed by active rTMS in the open-label phase. The analyses focused on segregation of the following networks: default mode (DMN), salience (SN), fronto-parietal (FPN), cingulo-opercular (CON), and memory retrieval (MRN).

Results

There was no differential change in network segregation comparing sham to active treatment. However, in the combined group of patients who completed active rTMS treatment (in the blinded plus open-label phases), higher baseline segregation of SN significantly predicted more symptom improvement after rTMS. Compared to HCs at baseline, MDD patients showed decreased segregation in DMN, and trend-level decreases in SN and MRN.

Conclusion

The results highlight the importance of network segregation in MDD, particularly in the SN, where more normal baseline segregation of SN may predict better treatment response to rTMS in depression.

•

We examined network segregation in a cohort of MDD patients receiving rTMS treatment.

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More normal segregation of SN predicted better response of depression to rTMS.

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Patients with MDD had decreased network segregation in DMN.

The Impact of Whole Brain Global Functional Connectivity Density Following MECT in Major Depression: A Follow-Up Study

To explore the alteration of global functional connectivity density (gFCD) in depressive patients after modified electroconvulsive therapy (MECT) and analyze the relationship between gFCD and clinical outcome. Thirty-seven subjects were evaluated based on the diagnostic criteria of the International Classification of Diseases-10 (ICD-10), consisting of a depressive group (24 patients after follow-ups) and a healthy control group with 13 normal individuals. All participants received Hamilton Depression Scale (HAMD) scores and resting-state functional magnetic resonance imaging scans. The gFCD significantly increased in the posterior-middle insula, the supra-marginal gyrus and the dorsal medial prefrontal cortex (dmPFC) before MECT treatment compared to healthy controlled patients. The gFCD statistically expanded in the perigenual anterior cingulate cortex (pgACC), the orbitofrontal cortex bilaterally and the left-supra-marginal gyrus after MECT, and it decreased notably in the posterior insula. The gFCD in the pgACC and the right orbital frontal cortex of depressive group before MECT showed a positive correlation with HAMD scores with treatment. Conforming to the impact of gFCD in depressive patients after MECT, the aforementioned brain region may become an indicator of MECT effect.

Cingulate-mediated depressive symptoms in neurologic disease and therapeutics

The depressive syndrome includes a number of symptoms that are clinically diverse. Research in the past decades has consistently demonstrated that the cingulate cortex plays an essential role in these manifestations. With anatomic studies initially showing volumetric changes, followed by the insights that functional imaging and physiology contributed to neuroscience and psychiatry, the distinct areas of the cingulate subdivisions were seen to have unique contributions. The subcallosal cingulate, with its functional responsivity to mood states and to antidepressant therapies, has been identified as a central node within the mood regulation network. In this chapter, detailed descriptions of the anatomic and functional changes that are seen in depression will be discussed. Finally, a focus on the development of deep brain stimulation in the subcallosal cingulate area will be used to emphasize the conceptualization of a network model with the cingulate as a hub, where engagement of remote areas of the depression network is needed to treat depression.

Intrinsic Brain Network Biomarkers of Antidepressant Response: a Review

PURPOSE OF REVIEW

Poor treatment response is a hallmark of major depressive disorder. To tackle this problem, recent neuroimaging studies have sought to characterize antidepressant response in terms of pretreatment differences in intrinsic functional brain networks. Our aim is to review recent studies that predict antidepressant response using intrinsic network connectivity. We discuss current methodological limitations and directions for future antidepressant biomarker studies.

RECENT FINDINGS

Functional connectivity stemming from the subgenual and rostral anterior cingulate has shown particular consistency in predicting antidepressant response. Differences in this connectivity may prove fruitful in differentiating treatment responders to many antidepressant interventions. Future biomarker studies should integrate biological MDD subtypes to address the disorder's inherent clinical heterogeneity. These clinical and scientific advancements have the potential to address this population marked by limited treatment response. Methodological considerations, including patient selection, response criteria, and model overfitting, will require future investigation to ensure that biomarkers generalize for prospective prediction of treatment response.

Behavioral and Resting State Functional Connectivity Effects of High Frequency rTMS on Disorders of Consciousness: A Sham-Controlled Study

Objectives: A combined approach of behavioral characteristics and network properties was applied to explore the effect of repetitive transcranial magnetic stimulation (rTMS) on disorders of consciousness (DOC) and to observe changes in brain network connections before and after the stimulation.

Methods: A total of 7 DOC patients and 11 healthy controls were enrolled. The study was designed as a randomized, sham-controlled study. All DOC patients were given 20 Hz rTMS real and sham stimuli to the left M1 region, with each stimulus lasting for 5 consecutive working days and the interval between two stimuli being 1 week. Coma Recovery Scale-Revised (CRS-R) and resting state functional MRI data before and after stimuli were collected. The functional connection (FC) of the default mode network and the frontoparietal network were chosen as the central target to compare differences in network connections between the DOC group and the normal control group. For DOC patients, changes in behavior and brain function before and after real and sham stimuli were also assessed as a group and individually.

Results: (1). The overall analyses showed no significant changes of CRS-R scores or brain FC following real or sham rTMS stimuli in the DOC patients. However, real rTMS stimuli tended to enhance the FC of nodes in left lateral parietal cortex (LPC), left inferior temporal cortex (ITC) and right dorsolateral prefrontal cortex (DLPFC). (2). The individual analyses showed one minimally conscious state (MCS) patient presented with a obviously increased CRS-R score following real rTMS stimuli, and a visibly enhanced connectivity was observed in the nodes of left LPC, left ITC and right DLPFC of this patient.

Conclusion: Our findings did not provide sufficient evidence of therapeutic effect of 20 Hz rTMS over the left M1 in DOC. However, MCS patients shortly after brain injury may possibly benefit from rTMS. Reconstruction of the left LPC, the left ITC and the right DLPFC may be the brain networking foundation of improvements in consciousness from rTMS.