Default mode network mechanisms of transcranial magnetic stimulation in depression

High-frequency repetitive transcranial magnetic stimulation promotes neural stem cell proliferation after ischemic stroke

JOURNAL/nrgr/04.03/01300535-202408000-00031/figure1/v/2023-12-16T180322Z/r/image-tiff Proliferation of neural stem cells is crucial for promoting neuronal regeneration and repairing cerebral infarction damage. Transcranial magnetic stimulation (TMS) has recently emerged as a tool for inducing endogenous neural stem cell regeneration, but its underlying mechanisms remain unclear. In this study, we found that repetitive TMS effectively promotes the proliferation of oxygen-glucose deprived neural stem cells. Additionally, repetitive TMS reduced the volume of cerebral infarction in a rat model of ischemic stroke caused by middle cerebral artery occlusion, improved rat cognitive function, and promoted the proliferation of neural stem cells in the ischemic penumbra. RNA-sequencing found that repetitive TMS activated the Wnt signaling pathway in the ischemic penumbra of rats with cerebral ischemia. Furthermore, PCR analysis revealed that repetitive TMS promoted AKT phosphorylation, leading to an increase in mRNA levels of cell cycle-related proteins such as Cdk2 and Cdk4. This effect was also associated with activation of the glycogen synthase kinase 3β/β-catenin signaling pathway, which ultimately promotes the proliferation of neural stem cells. Subsequently, we validated the effect of repetitive TMS on AKT phosphorylation. We found that repetitive TMS promoted Ca2+ influx into neural stem cells by activating the P2 calcium channel/calmodulin pathway, thereby promoting AKT phosphorylation and activating the glycogen synthase kinase 3β/β-catenin pathway. These findings indicate that repetitive TMS can promote the proliferation of endogenous neural stem cells through a Ca2+ influx-dependent phosphorylated AKT/glycogen synthase kinase 3β/β-catenin signaling pathway. This study has produced pioneering results on the intrinsic mechanism of repetitive TMS to promote neural function recovery after ischemic stroke. These results provide a strong scientific foundation for the clinical application of repetitive TMS. Moreover, repetitive TMS treatment may not only be an efficient and potential approach to support neurogenesis for further therapeutic applications, but also provide an effective platform for the expansion of neural stem cells.

Large-scale network abnormality in behavioral addiction

BACKGROUND

Researchers have endeavored to ascertain the network dysfunction associated with behavioral addiction (BA) through the utilization of resting-state functional connectivity (rsFC). Nevertheless, the identification of aberrant patterns within large-scale networks pertaining to BA has proven to be challenging.

METHODS

Whole-brain seed-based rsFC studies comparing subjects with BA and healthy controls (HC) were collected from multiple databases. Multilevel kernel density analysis was employed to ascertain brain networks in which BA was linked to hyper-connectivity or hypo-connectivity with each prior network.

RESULTS

Fifty-six seed-based rsFC publications (1755 individuals with BA and 1828 HC) were included in the meta-analysis. The present study indicate that individuals with BAs exhibit (1) hypo-connectivity within the fronto-parietal network (FN) and hypo- and hyper-connectivity within the ventral attention network (VAN); (2) hypo-connectivity between the FN and regions of the VAN, hypo-connectivity between the VAN and regions of the FN and default mode network (DMN), hyper-connectivity between the DMN and regions of the FN; (3) hypo-connectivity between the reward system and regions of the sensorimotor network (SS), DMN and VAN; (4) hypo-connectivity between the FN and regions of the SS, hyper-connectivity between the VAN and regions of the SS.

CONCLUSIONS

These findings provide impetus for a conceptual framework positing a model of BA characterized by disconnected functional coordination among large-scale networks.

The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.

Alterations in spatiotemporal characteristics of dynamic networks in juvenile myoclonic epilepsy

BACKGROUND

Juvenile myoclonic epilepsy (JME) is characterized by altered patterns of brain functional connectivity (FC). However, the nature and extent of alterations in the spatiotemporal characteristics of dynamic FC in JME patients remain elusive. Dynamic networks effectively encapsulate temporal variations in brain imaging data, offering insights into brain network abnormalities and contributing to our understanding of the seizure mechanisms and origins.

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) data were procured from 37 JME patients and 37 healthy counterparts. Forty-seven network nodes were identified by group-independent component analysis (ICA) to construct the dynamic network. Ultimately, patients' and controls' spatiotemporal characteristics, encompassing temporal clustering and variability, were contrasted at the whole-brain, large-scale network, and regional levels.

RESULTS

Our findings reveal a marked reduction in temporal clustering and an elevation in temporal variability in JME patients at the whole-brain echelon. Perturbations were notably pronounced in the default mode network (DMN) and visual network (VN) at the large-scale level. Nodes exhibiting anomalous were predominantly situated within the DMN and VN. Additionally, there was a significant correlation between the severity of JME symptoms and the temporal clustering of the VN.

CONCLUSIONS

Our findings suggest that excessive temporal changes in brain FC may affect the temporal structure of dynamic brain networks, leading to disturbances in brain function in patients with JME. The DMN and VN play an important role in the dynamics of brain networks in patients, and their abnormal spatiotemporal properties may underlie abnormal brain function in patients with JME in the early stages of the disease.

Resting-state activity and functional connectivity of insula and postcentral gyrus related to psychological resilience in female depressed patients: A preliminary study

BACKGROUND

Psychological resilience is a protective factor of depression. However, the neuroimaging characteristics of the relationship between psychological resilience and brain imaging in depression are not very clear. Our objectives were to explore the brain functional imaging characteristics of different levels of resilience in female patients with depression.

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) was performed on 58 female depressed patients. According to the resilience score, participants were divided into three groups: Low resilience (Low-res), Medium resilience (Med-res) and High resilience (High-res). We compared the differences in the amplitude of low-frequency fluctuations (ALFF) and functional connectivity (FC) among the three groups and correlated psychological resilience with ALFF and FC.

RESULTS

According to ALFF, there was a higher activation in RI and RPG in the High-res compared with Med-res and Low-res, but no significant differences between Med-res and Low-res. The FC between the RPG and supramarginal gyrus (SG) in the High-res was significantly stronger than that in the Med-res and the Low-res, and the FC of the Med-res is stronger than that of the Low-res. Both ALFF and FC were positively correlated with the score of resilience.

LIMITATIONS

The sample size of this study was relatively small and it lacked healthy controls. The results of this study could be considered preliminary.

CONCLUSIONS

Among female patients with depression, patients with higher psychological resilience had higher resting state activation in the RI and RPG and had a stronger interaction between the RPG and the SG.

Neural response during prefrontal theta burst stimulation: Interleaved TMS-fMRI of full iTBS protocols

BACKGROUND

Left prefrontal intermittent theta-burst stimulation (iTBS) has emerged as a safe and effective transcranial magnetic stimulation (TMS) treatment protocol in depression. Though network effects after iTBS have been widely studied, the deeper mechanistic understanding of target engagement is still at its beginning. Here, we investigate the feasibility of a novel integrated TMS-fMRI setup and accelerated echo planar imaging protocol to directly observe the immediate effects of full iTBS treatment sessions.

OBJECTIVE/HYPOTHESIS

In our effort to explore interleaved iTBS-fMRI feasibility, we hypothesize that TMS will induce acute BOLD signal changes in both the stimulated area and interconnected neural regions.

METHODS

Concurrent TMS-fMRI with full sessions of neuronavigated iTBS (i.e. 600 pulses) of the left dorsolateral prefrontal cortex (DLPFC) was investigated in 18 healthy participants. In addition, we conducted four TMS-fMRI sessions in a single patient on long-term maintenance iTBS for bipolar depression to test the transfer to clinical cases.

RESULTS

Concurrent TMS-fMRI was feasible for iTBS sequences with 600 pulses. During interleaved iTBS-fMRI, an increase of the BOLD signal was observed in a network including bilateral DLPFC regions. In the clinical case, a reduced BOLD response was found in the left DLPFC and the subgenual anterior cingulate cortex, with high variability across individual sessions.

CONCLUSIONS

Full iTBS sessions as applied for the treatment of depressive disorders can be established in the interleaved iTBS-fMRI paradigm. In the future, this experimental approach could be valuable in clinical samples, for demonstrating target engagement by iTBS protocols and investigating their mechanisms of therapeutic action.

Affective dysfunction mediates the link between neuroimmune markers and the default mode network functional connectivity, and the somatic symptoms in somatic symptom disorder

OBJECTIVE

Somatic symptom disorder (SSD) is characterized by physical symptoms and associated functional impairments that are often comorbid with depression and anxiety disorders. In this study, we explored relationships between affective symptoms and the functional connectivity of the default mode network (DMN) in SSD patients, as well as the impact of peripheral inflammation. We employed mediation analyses to investigate the potential pathways between these factors.

METHODS

We recruited a total of 119 individuals (74 unmedicated SSD patients and 45 healthy controls), who were subjected to comprehensive psychiatric and clinical evaluations, blood tests, and resting-state functional magnetic resonance imaging scanning. We assessed neuroimmune markers (interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor-α (TNF-α), tryptophan, serotonin, and 5-hydroxyindoleacetic acid (5-HIAA)), clinical indicators of somatic symptoms, depression, anxiety, anger, alexithymia, and functional connectivity (FC) within the DMN regions. Data were analyzed using correlation and mediation analysis, with a focus on exploring potential relations between clinical symptoms, blood indices, and DMN FCs.

RESULTS

Patients with SSD had higher clinical scores as well as IL-6 and TNF-α levels compared with those in the control group (P < 0.05). The SSD group exhibited lower FC strength between the left inferior parietal lobule and left prefrontal cortex (Pfalse discovery rate (FDR) < 0.05). Exploratory correlation analysis revealed that somatic symptom scores were positively correlated with affective symptom scores, negatively correlated with the FC strength between the intra prefrontal cortex regions, and correlated with levels of IL-6, TNF- α, and tryptophan (uncorrected P < 0.01). Mediation analysis showed that levels of anxiety and trait anger significantly mediated the relations between DMN FC strength and somatic symptoms. In addition, the DMN FC mediated the level of trait anger with respect to somatic symptoms (all PFDR < 0.05). The levels of depression and trait anger exhibited significant mediating effects as suppressors of the relations between the level of 5-HIAA and somatic symptom score (all PFDR < 0.05). Further, the level of 5-HIAA had a mediating effect as a suppressor on the relation between DMN FC and state anger. Meanwhile, the levels of hs-CRP and IL-6 had full mediating effects as suppressors when explaining the relations of DMN FC strengths with the level of depression (all PFDR < 0.05). The patterns of valid mediation pathways were different in the control group.

CONCLUSIONS

Affective symptoms may indirectly mediate the associations between DMN connectivity, somatic symptoms, and neuroimmune markers. Inflammatory markers may also mediate the impact of DMN connectivity on affective symptoms. These results emphasize the importance of affective dysregulation in understanding the mechanisms of SSD and have potential implications for the development of tailored therapeutic approaches for SSD patients with affective symptoms. Furthermore, in SSD research using DMN FC or neuroimmune markers, considering and incorporating such mediating effects of affective symptoms suggests the possibility of more accurate prediction and explanation.

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

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for major depressive disorder (MDD), but substantial heterogeneity in outcomes remains. We examined a potential mechanism of action of rTMS to normalize individual variability in resting-state functional connectivity (rs-fc) before and after a course of treatment.

METHODS

Variability in rs-fc was examined in healthy controls (baseline) and individuals with MDD (baseline and after 4-6 weeks of rTMS). Seed-based connectivity was calculated to 4 regions associated with MDD: left dorsolateral prefrontal cortex (DLPFC), right subgenual anterior cingulate cortex (sgACC), bilateral insula, and bilateral precuneus. Individual variability was quantified for each region by calculating the mean correlational distance of connectivity maps relative to the healthy controls; a higher variability score indicated a more atypical/idiosyncratic connectivity pattern.

RESULTS

We included data from 66 healthy controls and 252 individuals with MDD in our analyses. Patients with MDD did not show significant differences in baseline variability of rs-fc compared with controls. Treatment with rTMS increased rs-fc variability from the right sgACC and precuneus, but the increased variability was not associated with clinical outcomes. Interestingly, higher baseline variability of the right sgACC was significantly associated with less clinical improvement (p = 0.037, uncorrected; did not survive false discovery rate correction).Limitations: The linear model was constructed separately for each region of interest.

CONCLUSION

This was, to our knowledge, the first study to examine individual variability of rs-fc related to rTMS in individuals with MDD. In contrast to our hypotheses, we found that rTMS increased the individual variability of rs-fc. Our results suggest that individual variability of the right sgACC and bilateral precuneus connectivity may be a potential mechanism of rTMS.

The Role of Subgenual Resting-State Connectivity Networks in Predicting Prognosis in Major Depressive Disorder

Background

A seminal study found higher subgenual frontal cortex resting-state connectivity with 2 left ventral frontal regions and the dorsal midbrain to predict better response to psychotherapy versus medication in individuals with treatment-naïve major depressive disorder (MDD). Here, we examined whether these subgenual networks also play a role in the pathophysiology of clinical outcomes in MDD with early treatment resistance in primary care.

Methods

Forty-five people with current MDD who had not responded to ≥2 serotonergic antidepressants (n = 43, meeting predefined functional magnetic resonance imaging minimum quality thresholds) were enrolled and followed over 4 months of standard care. Functional magnetic resonance imaging resting-state connectivity between the preregistered subgenual frontal cortex seed and 3 previously identified left ventromedial, ventrolateral prefrontal/insula, and dorsal midbrain regions was extracted. The clinical outcome was the percentage change on the self-reported 16-item Quick Inventory of Depressive Symptomatology.

Results

We observed a reversal of our preregistered hypothesis in that higher resting-state connectivity between the subgenual cortex and the a priori ventrolateral prefrontal/insula region predicted favorable rather than unfavorable clinical outcomes (rs39 = -0.43, p = .006). This generalized to the sample including participants with suboptimal functional magnetic resonance imaging quality (rs43 = -0.35, p = .02). In contrast, no effects (rs39 = 0.12, rs39 = -0.01) were found for connectivity with the other 2 preregistered regions or in a whole-brain analysis (voxel-based familywise error-corrected p < .05).

Conclusions

Subgenual connectivity with the ventrolateral prefrontal cortex/insula is relevant for subsequent clinical outcomes in current MDD with early treatment resistance. Its positive association with favorable outcomes could be explained primarily by psychosocial rather than the expected pharmacological changes during the follow-up period.

Multimodal workflows optimally predict response to repetitive transcranial magnetic stimulation in patients with schizophrenia: a multisite machine learning analysis

The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial. The models incorporated pre-treatment sMRI, clinical, sociodemographic, and polygenic risk score (PRS) data. Patients were randomly assigned to receive active (N = 45) or sham (N = 47) rTMS treatment. The prediction target was individual response, defined as ≥20% reduction in pre-treatment negative symptom sum scores of the Positive and Negative Syndrome Scale. Our multimodal sequential prediction workflow achieved a balanced accuracy (BAC) of 94% (non-responders: 92%, responders: 95%) in the active-treated group and 50% in the sham-treated group. The clinical, clinical + PRS, and sMRI-based classifiers yielded BACs of 65%, 76%, and 80%, respectively. Apparent sadness, inability to feel, educational attainment PRS, and unemployment were most predictive of non-response in the clinical + PRS model, while grey matter density reductions in the default mode, limbic networks, and the cerebellum were most predictive in the sMRI model. Our sequential modelling approach provided superior predictive performance while minimising the diagnostic burden in the clinical setting. Predictive patterns suggest that rTMS responders may have higher levels of brain grey matter in the default mode and salience networks which increases their likelihood of profiting from plasticity-inducing brain stimulation methods, such as rTMS. The future clinical implementation of our models requires findings to be replicated at the international scale using stratified clinical trial designs.

Increased anger and stress and heightened connectivity between IFG and vmPFC in victims during social interaction

Self-identification as a victim of violence may lead to increased negative emotions and stress and thus, may change both structure and function of the underlying neural network(s). In a trans-diagnostic sample of individuals who identified themselves as victims of violence and a matched control group with no prior exposure to violence, we employed a social exclusion paradigm, the Cyberball task, to stimulate the re-experience of stress. Participants were partially excluded in the ball-tossing game without prior knowledge. We analyzed group differences in brain activity and functional connectivity during exclusion versus inclusion in exclusion-related regions. The victim group showed increased anger and stress levels during all conditions. Activation patterns during the task did not differ between groups but an enhanced functional connectivity between the IFG and the right vmPFC distinguished victims from controls during exclusion. This effect was driven by aberrant connectivity in victims during inclusion rather than exclusion, indicating that victimization affects emotional responses and inclusion-related brain connectivity rather than exclusion-related brain activity or connectivity. Victims may respond differently to the social context itself. Enhanced negative emotions and connectivity deviations during social inclusion may depict altered social processing and may thus affect social interactions.

Brain Circuit-Derived Biotypes for Treatment Selection in Mood Disorders: A Critical Review and Illustration of a Functional Neuroimaging Tool for Clinical Translation

Although the lifetime burden due to major depressive disorder is increasing, we lack tools for selecting the most effective treatments for each patient. One-third to one-half of patients with major depressive disorder do not respond to treatment, and we lack strategies for selecting among available treatments or expediting access to new treatment options. This critical review concentrates on functional neuroimaging as a modality of measurement for precision psychiatry. We begin by summarizing the current landscape of how functional neuroimaging-derived circuit predictors can forecast treatment outcomes in depression. Then, we outline the opportunities and challenges in integrating circuit predictors into clinical practice. We highlight one standardized and reproducible approach for quantifying brain circuit function at an individual level, which could serve as a model for clinical translation. We conclude by evaluating the prospects and practicality of employing neuroimaging tools, such as the one that we propose, in routine clinical practice.

Electroconvulsive Therapy Regulates Brain Connectome Dynamics in Patients With Major Depressive Disorder

BACKGROUND

Electroconvulsive therapy (ECT) is an effective treatment for patients with major depressive disorder (MDD), but its underlying neural mechanisms remain largely unknown. The aim of this study was to identify changes in brain connectome dynamics after ECT in MDD and to explore their associations with treatment outcome.

METHODS

We collected longitudinal resting-state functional magnetic resonance imaging data from 80 patients with MDD (50 with suicidal ideation [MDD-SI] and 30 without [MDD-NSI]) before and after ECT and 37 age- and sex-matched healthy control participants. A multilayer network model was used to assess modular switching over time in functional connectomes. Support vector regression was used to assess whether pre-ECT network dynamics could predict treatment response in terms of symptom severity.

RESULTS

At baseline, patients with MDD had lower global modularity and higher modular variability in functional connectomes than control participants. Network modularity increased and network variability decreased after ECT in patients with MDD, predominantly in the default mode and somatomotor networks. Moreover, ECT was associated with decreased modular variability in the left dorsal anterior cingulate cortex of MDD-SI but not MDD-NSI patients, and pre-ECT modular variability significantly predicted symptom improvement in the MDD-SI group but not in the MDD-NSI group.

CONCLUSIONS

We highlight ECT-induced changes in MDD brain network dynamics and their predictive value for treatment outcome, particularly in patients with SI. This study advances our understanding of the neural mechanisms of ECT from a dynamic brain network perspective and suggests potential prognostic biomarkers for predicting ECT efficacy in patients with MDD.

Closed-Loop Brain Stimulation

In the same way that beauty lies in the eye of the beholder, what a stimulus does to the brain is determined not simply by the nature of the stimulus but by the nature of the brain that is receiving the stimulus at that instant in time. Over the past decades, therapeutic brain stimulation has typically applied open-loop fixed protocols and has largely ignored this principle. Only recent neurotechnological advancements have enabled us to predict the nature of the brain (i.e., the electrophysiological brain state in the next instance in time) with sufficient temporal precision in the range of milliseconds using feedforward algorithms applied to electroencephalography time-series data. This allows stimulation exclusively whenever the targeted brain area is in a prespecified excitability or connectivity state. Preclinical studies have shown that repetitive stimulation during a particular brain state (e.g., high-excitability state), but not during other states, results in lasting modification (e.g., long-term potentiation) of the stimulated circuits. Here, we survey the evidence that this is also possible at the systems level of the human cortex using electroencephalography-informed transcranial magnetic stimulation. We critically discuss opportunities and difficulties in developing brain state-dependent stimulation for more effective long-term modification of pathological brain networks (e.g., in major depressive disorder) than is achievable with conventional fixed protocols. The same real-time electroencephalography-informed transcranial magnetic stimulation technology will allow closing of the loop by recording the effects of stimulation. This information may enable stimulation protocol adaptation that maximizes treatment response. This way, brain states control brain stimulation, thereby introducing a paradigm shift from open-loop to closed-loop stimulation.

Research on adults with subthreshold depression after aerobic exercise: a resting-state fMRI study based on regional homogeneity (ReHo)

Objective

Subthreshold depression (StD)/subsyndromal depression refers to a threatening precursor to depression. Aerobic exercise is a promising self-supportive adjunctive intervention and an effective measure for StD. Our study utilizes regional homogeneity (ReHo) to investigate the impact of aerobic exercise on resting-state brain function.

Methods

A total of 78 subjects, aged between 18 and 48 years, (StD group, n = 44; healthy control (HC) group, n = 34) engaged in moderate-intensity aerobic exercise 3-4 times per week for 8 weeks. Resting-state brain function and structural images were acquired before and after the exercise intervention. The ReHo method was employed to analyze abnormal changes in regional brain function, and a correlation analysis was performed using the Patient Health Questionnaire-9 (PHQ-9) and Self-Rating Anxiety Scale (SAS) scores.

Results

The principal observation reveals synchronous abnormalities in the right anterior cingulate gyrus of the brain in StD subjects compared to HCs at baseline, with these differences dissipating after the implementation of aerobic exercise. After completing the aerobic exercise program, the StD group exhibited a difference in the right middle cingulate gyrus, while the left supplementary motor area (SMA) was altered in the HC group.

Conclusion

Disparities in neural synchronization are evident between HCs and StD subjects, and the implementation of aerobic exercise intervention can effectively mitigate these distinctions, leading to a significant reduction in depressive symptoms among StD subjects. The primary mechanism of StD symptoms may involve the inhibition of the anterior cingulate gyrus, while the effects of aerobic exercise may be related to the modulation of neural synchronization of emotional reflexes. The discovery of these fMRI evidence findings may offer novel strategies for early detection and intervention in cases of StD.

Effective connectivity of the locus coeruleus in patients with late-life Major Depressive Disorder or mild cognitive impairment

INTRODUCTION

We compared effective connectivity from the locus coeruleus (LC) during the resting-state in patients with late-life Major Depressive Disorder (MDD), individuals with amnestic Mild Cognitive Impairment (aMCI), and Healthy Controls (HCs).

PARTICIPANTS

23 patients with late-life MDD, 22 patients with aMCI, and 28 HCs.

MATERIAL AND METHODS

Participants were assessed in two time-points, 2 years apart. They underwent a resting-state functional magnetic resonance imaging and a high-resolution anatomical acquisition, as well as clinical assessments. Functional imaging data were analyzed with dynamic causal modeling, and parametric empirical Bayes model was used to map effective connectivity between 7 distinct nodes: 4 from the locus coeruleus and 3 regions displaying gray matter decreases during the two-year follow-up period.

RESULTS

Longitudinal analysis of structural data identified three clusters of larger over-time gray matter volume reduction in patients (MDD+aMCI vs. HCs): the right precuneus, and the visual association and parahippocampal cortices. aMCI patients showed decreased effective connectivity from the left rostral to caudal portions of the LC, while connectivity from the left rostral LC to the parahippocampal cortex increased. In MDD, there was a decline in effective connectivity across LC caudal seeds, and increased connectivity from the left rostral to the left caudal LC seed over time. Connectivity alterations with cortical regions involved cross-hemisphere increases and same-hemisphere decreases.

CONCLUSIONS

Our discoveries provide insight into the dynamic changes in effective connectivity in individuals with late-life MDD and aMCI, also shedding light on the mechanisms potentially contributing to the onset of neurodegenerative disorders.

Theta oscillatory dynamics serving cognitive control index psychosocial distress in youth

Background

Psychosocial distress among youth is a major public health issue characterized by disruptions in cognitive control processing. Using the National Institute of Mental Health's Research Domain Criteria (RDoC) framework, we quantified multidimensional neural oscillatory markers of psychosocial distress serving cognitive control in youth.

Methods

The sample consisted of 39 peri-adolescent participants who completed the NIH Toolbox Emotion Battery (NIHTB-EB) and the Eriksen flanker task during magnetoencephalography (MEG). A psychosocial distress index was computed with exploratory factor analysis using assessments from the NIHTB-EB. MEG data were analyzed in the time-frequency domain and peak voxels from oscillatory maps depicting the neural cognitive interference effect were extracted for voxel time series analyses to identify spontaneous and oscillatory aberrations in dynamics serving cognitive control as a function of psychosocial distress. Further, we quantified the relationship between psychosocial distress and dynamic functional connectivity between regions supporting cognitive control.

Results

The continuous psychosocial distress index was strongly associated with validated measures of pediatric psychopathology. Theta-band neural cognitive interference was identified in the left dorsolateral prefrontal cortex (dlPFC) and middle cingulate cortex (MCC). Time series analyses of these regions indicated that greater psychosocial distress was associated with elevated spontaneous activity in both the dlPFC and MCC and blunted theta oscillations in the MCC. Finally, we found that stronger phase coherence between the dlPFC and MCC was associated with greater psychosocial distress.

Conclusions

Greater psychosocial distress was marked by alterations in spontaneous and oscillatory theta activity serving cognitive control, along with hyperconnectivity between the dlPFC and MCC.

Individualized, connectome-based, non-invasive stimulation of OCD deep-brain targets: A proof-of-concept

Treatment-resistant obsessive-compulsive disorder (OCD) generally improves with deep-brain stimulation (DBS), thought to modulate neural activity at both the implantation site and in connected brain regions. However, its invasive nature, side-effects, and lack of customization, make non-invasive treatments preferable. Harnessing the established remote effects of cortical transcranial magnetic stimulation (TMS), connectivity-based approaches have emerged for depression that aim at influencing distant regions connected to the stimulation site. We here investigated whether effective OCD DBS targets (here subthalamic nucleus [STN] and nucleus accumbens [NAc]) could be modulated non-invasively with TMS. In a proof-of-concept study with nine healthy individuals, we used 7T magnetic resonance imaging (MRI) and probabilistic tractography to reconstruct the fiber tracts traversing manually segmented STN/NAc. Two TMS targets were individually selected based on the strength of their structural connectivity to either the STN, or both the STN and NAc. In a sham-controlled, within-subject cross-over design, TMS was administered over the personalized targets, located around the precentral and middle frontal gyrus. Resting-state functional 3T MRI was acquired before, and at 5 and 25 min after stimulation to investigate TMS-induced changes in the functional connectivity of the STN and NAc with other regions of the brain. Static and dynamic seed-to-voxel correlation analyses were conducted. TMS over both targets was able to modulate the functional connectivity of the STN and NAc, engaging both overlapping and distinct regions, and unfolding following different temporal dynamics. Given the relevance of the engaged connected regions to OCD pathology, we argue that a personalized, connectivity-based procedure is worth investigating as potential treatment for refractory OCD.

The Association between Default-mode Network Functional Connectivity and Childhood Trauma on the Symptom Load in Male Adults with Methamphetamine Use Disorder

Objective

: The relationship between adverse childhood experiences and methamphetamine use disorder (MUD) has been shown in previous studies; nevertheless, the underlying neural mechanisms remain elusive. Childhood trauma is associated with aberrant functional connectivity (FC) within the default-mode network (DMN). Furthermore, within the DMN, FC may contribute to impaired self-awareness in addiction, while cross-network FC is critical for relapse. We aimed to investigate whether childhood trauma was associated with DMN-related resting-state FC among healthy controls and patients with MUD and to examine whether DMN-related FC affected the effect of childhood trauma on the symptom load of MUD diagnosis.

Methods

: Twenty-seven male patients with MUD and 27 male healthy controls were enrolled and completed the Childhood Trauma Questionnaire. DMN-related resting-state FC was examined using functional magnetic resonance imaging.

Results

: There were 47.1% healthy controls and 66.7% MUD patients in this study with adverse childhood experiences. Negative correlations between adverse childhood experiences and within-DMN FC were observed in both healthy controls and MUD patients, while within-DMN FC was significantly altered in MUD patients. The detrimental effects of adverse childhood experiences on MUD patients may be attenuated through DMN-executive control networks (ECN) FC.

Conclusion

: Adverse childhood experiences were negatively associated with within-DMN FC in MUD patients and healthy controls. However, DMN-ECN FC may attenuate the effects of childhood trauma on symptoms load of MUD.

Efficacy and safety of non-invasive brain stimulation in combination with antidepressants in adolescents with depression: a systematic review and meta-analysis

Objective

Non-invasive brain stimulation (NIBS) is beneficial to adult patients with depression, but its safety and efficacy in combination with antidepressants in children and adolescents with depression are not clear. We conducted a preliminary meta-analysis to objectively evaluate its clinical effect and provide information for future research and clinical practice.

Methods

PubMed, Cochrane Library, Embase, and Web of Science were searched systematically to find clinical trials published in English before April 11, 2023. Stata software was used for meta-analysis, and random or fixed effect models were used to combine effect sizes.

Results

Nine studies were eligible and included (n = 393). No articles about children were included in the analysis. The results showed that the remission rate was 40% (95% confidence interval [CI]: 13% to 71%). The scores of Children's Depression Rating Scale (CRDS) and Hamilton's depression scale (HAMD) significantly decreased compared to baseline value (MD = -27.04, 95% CI: -30.95, -23.12 and MD = -12.78, 95% CI: -19.55 to -6.01). In addition, the incidence of all adverse events was 13% (95% CI: 5%, 23%), and all were minor pain-related events.

Conclusion

The combination of NIBS and antidepressants has been shown to notably alleviate depressive symptoms in adolescents, offering a considerable level of safety. This therapeutic synergy is particularly effective in patients with major depressive disorder, where repetitive transcranial magnetic stimulation augmented with antidepressants can enhance the amelioration of depressive symptoms.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023442215, PROSPERO CRD42023442215.

Aberrant brain dynamics of large-scale functional networks across schizophrenia and mood disorder

INTRODUCTION

The dynamics of large-scale networks, which are known as distributed sets of functionally synchronized brain regions and include the visual network (VIN), somatomotor network (SMN), dorsal attention network (DAN), salience network (SAN), limbic network (LIN), frontoparietal network (FPN), and default mode network (DMN), play important roles in emotional and cognitive processes in humans. Although disruptions in these large-scale networks are considered critical for the pathophysiological mechanisms of psychiatric disorders, their role in psychiatric disorders remains unknown. We aimed to elucidate the aberrant dynamics across large-scale networks in patients with schizophrenia (SZ) and mood disorders.

METHODS

We performed energy-landscape analysis to investigate the aberrant brain dynamics of seven large-scale networks across 50 healthy controls (HCs), 36 patients with SZ, and 42 patients with major depressive disorder (MDD) recruited at Wakayama Medical University. We identified major patterns of brain activity using energy-landscape analysis and estimated their duration, occurrence, and ease of transition.

RESULTS

We identified four major brain activity patterns that were characterized by the activation patterns of the DMN and VIN (state 1, DMN (-) VIN (-); state 2, DMN (+) VIN (+); state 3, DMN (-) VIN (+); and state 4, DMN (+) VIN (-)). The duration of state 1 and the occurrence of states 1 and 2 were shorter in the SZ group than in HCs and the MDD group, and the duration of state 3 was longer in the SZ group. The ease of transition between states 3 and 4 was larger in the SZ group than in the HCs and the MDD group. The ease of transition from state 3 to state 4 was negatively associated with verbal fluency in patients with SZ. The current study showed that the brain dynamics was more disrupted in SZ than in MDD.

CONCLUSIONS

Energy-landscape analysis revealed aberrant brain dynamics across large-scale networks between SZ and MDD and their associations with cognitive abilities in SZ, which cannot be captured by conventional functional connectivity analyses. These results provide new insights into the pathophysiological mechanisms underlying SZ and mood disorders.

Elevating the field for applying neuroimaging to individual patients in psychiatry

Although neuroimaging has been widely applied in psychiatry, much of the exuberance in decades past has been tempered by failed replications and a lack of definitive evidence to support the utility of imaging to inform clinical decisions. There are multiple promising ways forward to demonstrate the relevance of neuroimaging for psychiatry at the individual patient level. Ultra-high field magnetic resonance imaging is developing as a sensitive measure of neurometabolic processes of particular relevance that holds promise as a new way to characterize patient abnormalities as well as variability in response to treatment. Neuroimaging may also be particularly suited to the science of brain stimulation interventions in psychiatry given that imaging can both inform brain targeting as well as measure changes in brain circuit communication as a function of how effectively interventions improve symptoms. We argue that a greater focus on individual patient imaging data will pave the way to stronger relevance to clinical care in psychiatry. We also stress the importance of using imaging in symptom-relevant experimental manipulations and how relevance will be best demonstrated by pairing imaging with differential treatment prediction and outcome measurement. The priorities for using brain imaging to inform psychiatry may be shifting, which compels the field to solidify clinical relevance for individual patients over exploratory associations and biomarkers that ultimately fail to replicate.

Connectivity-guided intermittent theta burst versus repetitive transcranial magnetic stimulation for treatment-resistant depression: a randomized controlled trial

Disruption in reciprocal connectivity between the right anterior insula and the left dorsolateral prefrontal cortex is associated with depression and may be a target for neuromodulation. In a five-center, parallel, double-blind, randomized controlled trial we personalized resting-state functional magnetic resonance imaging neuronavigated connectivity-guided intermittent theta burst stimulation (cgiTBS) at a site based on effective connectivity from the right anterior insula to the left dorsolateral prefrontal cortex. We tested its efficacy in reducing the primary outcome depression symptoms measured by the GRID Hamilton Depression Rating Scale 17-item over 8, 16 and 26 weeks, compared with structural magnetic resonance imaging (MRI) neuronavigated repetitive transcranial magnetic stimulation (rTMS) delivered at the standard stimulation site (F3) in patients with 'treatment-resistant depression'. Participants were randomly assigned to 20 sessions over 4-6 weeks of either cgiTBS (n = 128) or rTMS (n = 127) with resting-state functional MRI at baseline and 16 weeks. Persistent decreases in depressive symptoms were seen over 26 weeks, with no differences between arms on the primary outcome GRID Hamilton Depression Rating Scale 17-item score (intention-to-treat adjusted mean, -0.31, 95% confidence interval (CI) -1.87, 1.24, P = 0.689). Two serious adverse events were possibly related to TMS (mania and psychosis). MRI-neuronavigated cgiTBS and rTMS were equally effective in patients with treatment-resistant depression over 26 weeks (trial registration no. ISRCTN19674644).

The effectiveness of microcurrent neurofeedback on depression, anxiety, post-traumatic stress disorder, and quality of life

BACKGROUND

The world faces a mental health crisis with elevated rates of depression, anxiety, and post-traumatic stress, leaving a profound impact on daily quality of life (QOL). Current treatments show varying degrees of efficacy and carry burdensome challenges. Evidence exists for use of an innovative neurotechnology to reduce symptoms of depression, anxiety, and post-traumatic stress disorder (PTSD), but the science is lacking for use in the general population.

PURPOSES

The purpose of this pilot study was to explore the effects of microcurrent neurofeedback on depression, anxiety, PTSD symptoms, and QOL in adults.

METHODOLOGY

This was a one-group, exploratory pilot study that tested outcomes of depression, anxiety, PTSD risk, suicide risk, and QOL in 20 adults using convenience sampling. IASIS microcurrent neurofeedback (I-MCN) was the intervention that was delivered twice a week for 10 weeks; data collection was baseline, 5 weeks, and 10 weeks.

RESULTS

Depression, anxiety, PTSD risk, and QOL improved significantly by the 10th and 20th session; suicidal risk showed nonsignificant reduction. Use of a more feasible interventional procedure established a foundation for use in clinical settings for the population.

CONCLUSIONS

Using a more simpler procedure than what was used in a previous study reflected positive outcomes earlier and sustained over 10 weeks. This safe and effective technology carries rare but easily overcome adverse effects and could be an alternative to existing treatments or treatment-resistant conditions.

IMPLICATIONS

Advanced practice nurses can apply the evidence to reduce symptoms of depression, anxiety, and PTSD. Randomized controlled trials and testing on diverse populations are needed.

The association of total pulses with the efficacy of repetitive transcranial magnetic stimulation for treatment-resistant major depression: A dose-response meta-analysis

AIM

This study aimed to examine dose-effects of total pulses on improvement of depressive symptoms in patients with treatment-resistant depression (TRD) receiving repetitive transcranial magnetic stimulation (rTMS) over the left dorsal lateral prefrontal cortex (DLPFC).

MATERIALS AND METHODS

The MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL), EMBASE, PsycINFO, and ClinicalTrial.gov databases were systematically searched. We included randomized, double-blind, placebo-controlled trials (RCT) that used rTMS over left DLPFC in patients with TRD. Excluded studies were non-TRD, non-RCTs, or combined other brain stimulation interventions. The outcome of interest was the difference between rTMS arms and sham controls in improvement of depressive symptoms in a dose-response manner. A random-effects meta-analysis and dose-response meta-analysis(DRMA) was used to examine antidepressant efficacy of rTMS and association with total pulses.

RESULTS

We found that rTMS over left DLPFC is superior to sham controls (reported as standardized mean difference[SMD] with 95% confidence interval: 0.77; 0.56-0.98). The best-fitting model of DRMA was bell-shaped (estimated using restricted cubic spline model; R2 =0.42), indicating that higher doses (>26,660 total pulses) were not associated with increased improvement of depressive symptoms. Stimulation frequency(R2 =0.53) and age(R2 =0.51) were significant moderators for the dose-response curve. Furthermore, 15-20 Hz rTMS was superior to 10 Hz rTMS (0.61, 0.15-1.10) when combining all doses.

CONCLUSIONS

Our findings suggest higher doses(total pulses) of rTMS were not always associated with increased improvement of depressive symptoms in patients with TRD, and that the dose-response relationship was moderated by stimulation frequency and age. These associations emphasize the importance of determining dosing parameters to achieve maximum efficacy.

Enhanced group-level dorsolateral prefrontal cortex subregion parcellation through functional connectivity-based distance-constrained spectral clustering with application to autism spectrum disorder

The dorsolateral prefrontal cortex (DLPFC) assumes a central role in cognitive and behavioral control, emerging as a crucial target region for interventions in autism spectrum disorder neuroregulation. Consequently, we endeavor to unravel the functional subregions within the DLPFC to shed light on the intricate functions of the brain. We introduce a distance-constrained spectral clustering (SC-DW) methodology that leverages functional connection to identify distinctive functional subregions within the DLPFC. Furthermore, we verify the relationship between the functional characteristics of these subregions and their clinical implications. Our methodology begins with principal component analysis to extract the salient features. Subsequently, we construct an adjacency matrix, which is constrained by the spatial properties of the brain, by linearly combining the distance matrix and a similarity matrix. The quality of spectral clustering is further optimized through multiple cluster evaluation coefficient. The results from SC-DW revealed four uniform and contiguous subregions within the bilateral DLPFC. Notably, we observe a substantial positive correlation between the functional characteristics of the third and fourth subregions in the left DLPFC with clinical manifestations. These findings underscore the unique insights offered by our proposed methodology in the realms of brain subregion delineation and therapeutic targeting.

A Retrospective Case-Control Study on the Differences in the Effectiveness of Theta-Burst Stimulation Therapy for Depression with and without Antidepressant Medication

Transcranial magnetic stimulation (TMS) therapy has few side effects and comparable therapeutic effects to antidepressant treatment, but few studies have introduced TMS therapy as an initial treatment for MDD. The objective of this study was to retrospectively compare the clinical outcomes between 50 MDD patients without antidepressants (i.e., TMS monotherapy) and 50 MDD patients with antidepressants plus TMS therapy, matched for age, sex, and depression severity. The presence or absence of antidepressant therapy in first-line treatment was determined via a detailed interview by psychiatrists. The study design was a retrospective observational case-control study using the TMS registry data. The key inclusion criteria were adult patients who met the diagnosis of MDD and received 20-30 sessions of intermittent theta-burst stimulation (iTBS) therapy to the left dorsolateral prefrontal cortex (DLPFC). In this study, the Montgomery-Åsberg Depression Rating Scale (MADRS) was used as the primary outcome measure. No significant group differences existed in the baseline MADRS total score between the unmedicated and medicated patient groups. Following TMS therapy, no significant group differences in response rate, remission rate, or relative total score change in the MADRS were observed. The main limitations were the retrospective design and the use of registry data as a source. Our findings suggest that TMS monotherapy may be as effective as TMS add-on therapy to antidepressants when used as the first-line therapy for MDD, but randomized controlled trials are needed.

Targeting Human Glucocorticoid Receptors in Fear Learning: A Multiscale Integrated Approach to Study Functional Connectivity

Fear extinction is a phenomenon that involves a gradual reduction in conditioned fear responses through repeated exposure to fear-inducing cues. Functional brain connectivity assessments, such as functional magnetic resonance imaging (fMRI), provide valuable insights into how brain regions communicate during these processes. Stress, a ubiquitous aspect of life, influences fear learning and extinction by changing the activity of the amygdala, prefrontal cortex, and hippocampus, leading to enhanced fear responses and/or impaired extinction. Glucocorticoid receptors (GRs) are key to the stress response and show a dual function in fear regulation: while they enhance the consolidation of fear memories, they also facilitate extinction. Accordingly, GR dysregulation is associated with anxiety and mood disorders. Recent advancements in cognitive neuroscience underscore the need for a comprehensive understanding that integrates perspectives from the molecular, cellular, and systems levels. In particular, neuropharmacology provides valuable insights into neurotransmitter and receptor systems, aiding the investigation of mechanisms underlying fear regulation and potential therapeutic targets. A notable player in this context is cortisol, a key stress hormone, which significantly influences both fear memory reconsolidation and extinction processes. Gaining a thorough understanding of these intricate interactions has implications in terms of addressing psychiatric disorders related to stress. This review sheds light on the complex interactions between cognitive processes, emotions, and their neural bases. In this endeavor, our aim is to reshape the comprehension of fear, stress, and their implications for emotional well-being, ultimately aiding in the development of therapeutic interventions.

Targeting suicidal ideation in major depressive disorder with MRI-navigated Stanford accelerated intelligent neuromodulation therapy

High suicide risk represents a serious problem in patients with major depressive disorder (MDD), yet treatment options that could safely and rapidly ameliorate suicidal ideation remain elusive. Here, we tested the feasibility and preliminary efficacy of the Stanford Accelerated Intelligent Neuromodulation Therapy (SAINT) in reducing suicidal ideation in patients with MDD. Thirty-two MDD patients with moderate to severe suicidal ideation participated in the current study. Suicidal ideation and depression symptoms were assessed before and after 5 days of open-label SAINT. The neural pathways supporting rapid-acting antidepressant and suicide prevention effects were identified with dynamic causal modelling based on resting-state functional magnetic resonance imaging. We found that 5 days of SAINT effectively alleviated suicidal ideation in patients with MDD with a high response rate of 65.63%. Moreover, the response rates achieved 78.13% and 90.63% with 2 weeks and 4 weeks after SAINT, respectively. In addition, we found that the suicide prevention effects of SAINT were associated with the effective connectivity involving the insula and hippocampus, while the antidepressant effects were related to connections of the subgenual anterior cingulate cortex (sgACC). These results show that SAINT is a rapid-acting and effective way to reduce suicidal ideation. Our findings further suggest that distinct neural mechanisms may contribute to the rapid-acting effects on the relief of suicidal ideation and depression, respectively.

Aberrant resting-state co-activation network dynamics in major depressive disorder

Major depressive disorder (MDD) is a globally prevalent and highly disabling disease characterized by dysfunction of large-scale brain networks. Previous studies have found that static functional connectivity is not sufficient to reflect the complicated and time-varying properties of the brain. The underlying dynamic interactions between brain functional networks of MDD remain largely unknown, and it is also unclear whether neuroimaging-based dynamic properties are sufficiently robust to discriminate individuals with MDD from healthy controls since the diagnosis of MDD mainly depends on symptom-based criteria evaluated by clinical observation. Resting-state functional magnetic resonance imaging (fMRI) data of 221 MDD patients and 215 healthy controls were shared by REST-meta-MDD consortium. We investigated the spatial-temporal dynamics of MDD using co-activation pattern analysis and made individual diagnoses using support vector machine (SVM). We found that MDD patients exhibited aberrant dynamic properties (such as dwell time, occurrence rate, transition probability, and entropy of Markov trajectories) in some transient networks including subcortical network (SCN), activated default mode network (DMN), de-activated SCN-cerebellum network, a joint network, activated attention network (ATN), and de-activated DMN-ATN, where some dynamic properties were indicative of depressive symptoms. The trajectories of other networks to deactivated DMN-ATN were more accessible in MDD patients. Subgroup analyses also showed subtle dynamic changes in first-episode drug-naïve (FEDN) MDD patients. Finally, SVM achieved preferable accuracies of 84.69%, 76.77%, and 88.10% in discriminating patients with MDD, FEDN MDD, and recurrent MDD from healthy controls with their dynamic metrics. Our findings reveal that MDD is characterized by aberrant dynamic fluctuations of brain network and the feasibility of discriminating MDD patients using dynamic properties, which provide novel insights into the neural mechanism of MDD.

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.

Closed-loop neurostimulation for the treatment of psychiatric disorders

Despite increasing prevalence and huge personal and societal burden, psychiatric diseases still lack treatments which can control symptoms for a large fraction of patients. Increasing insight into the neurobiology underlying these diseases has demonstrated wide-ranging aberrant activity and functioning in multiple brain circuits and networks. Together with varied presentation and symptoms, this makes one-size-fits-all treatment a challenge. There has been a resurgence of interest in the use of neurostimulation as a treatment for psychiatric diseases. Initial studies using continuous open-loop stimulation, in which clinicians adjusted stimulation parameters during patient visits, showed promise but also mixed results. Given the periodic nature and fluctuations of symptoms often observed in psychiatric illnesses, the use of device-driven closed-loop stimulation may provide more effective therapy. The use of a biomarker, which is correlated with specific symptoms, to deliver stimulation only during symptomatic periods allows for the personalized therapy needed for such heterogeneous disorders. Here, we provide the reader with background motivating the use of closed-loop neurostimulation for the treatment of psychiatric disorders. We review foundational studies of open- and closed-loop neurostimulation for neuropsychiatric indications, focusing on deep brain stimulation, and discuss key considerations when designing and implementing closed-loop neurostimulation.

Effects of the combination of neurostimulation techniques in patients with mental disorders: A systematic review

BACKGROUND

despite years of development, response to neurostimulation remains partial and variable. Combining techniques could improve clinical efficacy and tolerance.

OBJECTIVE

to examine the literature on the effects of combining several neurostimulation techniques in patients with mental disorders.

METHODS

this systematic review follows the PRISMA guidelines RESULTS: 23 studies were included. The most studied combination was electroconvulsive therapy (ECT) along with another neurostimulation technique in depression. The RCTs that showed a significant effect targeted the left dorsolateral prefrontal cortex with high-frequency repetitive transcranial magnetic stimulation, before ECT. Combining neurostimulation techniques is a promising field of research.

Accelerated TMS - moving quickly into the future of depression treatment

Accelerated TMS is an emerging application of Transcranial Magnetic Stimulation (TMS) aimed to reduce treatment length and improve response time. Extant literature generally shows similar efficacy and safety profiles compared to the FDA-cleared protocols for TMS to treat major depressive disorder (MDD), yet accelerated TMS research remains at a very early stage in development. The few applied protocols have not been standardized and vary significantly across a set of core elements. In this review, we consider nine elements that include treatment parameters (i.e., frequency and inter-stimulation interval), cumulative exposure (i.e., number of treatment days, sessions per day, and pulses per session), individualized parameters (i.e., treatment target and dose), and brain state (i.e., context and concurrent treatments). Precisely which of these elements is critical and what parameters are most optimal for the treatment of MDD remains unclear. Other important considerations for accelerated TMS include durability of effect, safety profiles as doses increase over time, the possibility and advantage of individualized functional neuronavigation, use of biological readouts, and accessibility for patients most in need of the treatment. Overall, accelerated TMS appears to hold promise to reduce treatment time and achieve rapid reduction in depressive symptoms, but at this time significant work remains to be done. Rigorous clinical trials combining clinical outcomes and neuroscientific measures such as electroencephalogram, magnetic resonance imaging and e-field modeling are needed to define the future of accelerated TMS for MDD.

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.

Reviewing the neurobiology of electroconvulsive therapy on a micro- meso- and macro-level

BACKGROUND

Electroconvulsive therapy (ECT) remains the one of the most effective of biological antidepressant interventions. However, the exact neurobiological mechanisms underlying the efficacy of ECT remain unclear. A gap in the literature is the lack of multimodal research that attempts to integrate findings at different biological levels of analysis METHODS: We searched the PubMed database for relevant studies. We review biological studies of ECT in depression on a micro- (molecular), meso- (structural) and macro- (network) level.

RESULTS

ECT impacts both peripheral and central inflammatory processes, triggers neuroplastic mechanisms and modulates large scale neural network connectivity.

CONCLUSIONS

Integrating this vast body of existing evidence, we are tempted to speculate that ECT may have neuroplastic effects resulting in the modulation of connectivity between and among specific large-scale networks that are altered in depression. These effects could be mediated by the immunomodulatory properties of the treatment. A better understanding of the complex interactions between the micro-, meso- and macro- level might further specify the mechanisms of action of ECT.

A common symptom geometry of mood improvement under sertraline and placebo associated with distinct neural patterns

Importance

Understanding the mechanisms of major depressive disorder (MDD) improvement is a key challenge to determine effective personalized treatments.

Objective

To perform a secondary analysis quantifying neural-to-symptom relationships in MDD as a function of antidepressant treatment.

Design

Double blind randomized controlled trial.

Setting

Multicenter.

Participants

Patients with early onset recurrent depression from the public Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study.

Interventions

Either sertraline or placebo during 8 weeks (stage 1), and according to response a second line of treatment for 8 additional weeks (stage 2).

Main Outcomes and Measures

To identify a data-driven pattern of symptom variations during these two stages, we performed a Principal Component Analysis (PCA) on the variations of individual items of four clinical scales measuring depression, anxiety, suicidal ideas and manic-like symptoms, resulting in a univariate measure of clinical improvement. We then investigated how initial clinical and neural factors predicted this measure during stage 1. To do so, we extracted resting-state global brain connectivity (GBC) at baseline at the individual level using a whole-brain functional network parcellation. In turn, we computed a linear model for each brain parcel with individual data-driven clinical improvement scores during stage 1 for each group.

Results

192 patients (127 women), age 37.7 years old (standard deviation: 13.5), were included. The first PC (PC1) capturing 20% of clinical variation was similar across treatment groups at stage 1 and stage 2, suggesting a reproducible pattern of symptom improvement. PC1 patients' scores significantly differed according to treatment during stage 1, whereas no difference of response was evidenced between groups with the Clinical Global Impressions (CGI). Baseline GBC correlated to stage 1 PC1 scores in the sertraline, but not in the placebo group.

Conclusions and Relevance

Using data-driven reduction of symptoms scales, we identified a common profile of symptom improvement across placebo and sertraline. However, the neural patterns of baseline that mapped onto symptom improvement distinguished between treatment and placebo. Our results underscore that mapping from data-driven symptom improvement onto neural circuits is vital to detect treatment-responsive neural profiles that may aid in optimal patient selection for future trials.

Ketamine treatment modulates habenular and nucleus accumbens static and dynamic functional connectivity in major depression

Dysfunctional reward processing in major depressive disorder (MDD) involves functional circuitry of the habenula (Hb) and nucleus accumbens (NAc). Ketamine elicits rapid antidepressant and alleviates anhedonia in MDD. To clarify how ketamine perturbs reward circuitry in MDD, we examined how serial ketamine infusions (SKI) modulate static and dynamic functional connectivity (FC) in Hb and NAc networks. MDD participants (n=58, mean age=40.7 years, female=28) received four ketamine infusions (0.5mg/kg) 2-3 times weekly. Resting-state fMRI scans and clinical assessments were collected at baseline and 24 hours post-SKI completion. Static FC (sFC) and dynamic FC variability (dFCv) were calculated from left and right Hb and NAc seeds to all other brain regions. Paired t-tests examined changes in FC pre-to-post SKI, and correlations were used to determine relationships between FC changes with mood and anhedonia. Following SKI, significant increases in left Hb-bilateral visual cortex FC, decreases in left Hb-left inferior parietal cortex FC, and decreases in left NAc-right cerebellum FC occurred. Decreased dFCv between left Hb and right precuneus and visual cortex, and decreased dFCv between right NAc and right visual cortex both significantly correlated with improvements in Hamilton Depression Rating Scale. Decreased FC between left Hb and bilateral visual/parietal cortices as well as increased FC between left NAc and right visual/parietal cortices both significantly correlated with improvements in anhedonia. Subanesthetic ketamine modulates functional pathways linking the Hb and NAc with visual, parietal, and cerebellar regions. Overlapping effects between Hb and NAc functional systems were associated with ketamine's therapeutic response.

Transcranial alternating current stimulation ameliorates emotional attention through neural oscillations modulation

Background

Numerous clinical reports have suggested that psychopathy like schizophrenia, anxiety and depression is accompanied by early attentional abnormalities in emotional processing. Recently, the efficacy of transcranial alternating current stimulation (tACS) in changing emotional functioning has been repeatedly observed and demonstrated a causal relationship between endogenous oscillations and emotional processing.

Aims

Up to now, tACS effects on emotional attention have not yet been tested. To assess such ability, we delivered active-tACS at individual alpha frequency (IAF), 10 Hz or sham-tACS for 7 consecutive days in the bilaterally dorsolateral prefrontal cortex (dlPFC) to totally 79 healthy participants.

Results

IAF-tACS group showed significant alpha entrainment at-rest, especially in open state around stimulation area and showed an obvious advantage compared to 10 Hz-tACS. Event-related potential revealed a significant larger P200 amplitude after active-tACS and IAF group showed wider range of emotions than 10 Hz-tACS, indicating the attentional improvement in facial emotion processing. A notable positive correlation between alpha power and P200 amplitude provided an electrophysiological interpretation regarding the role of tACS in emotional attention modulation instead of somatosensory effects.

Conclusion

These results support a seminal outcome for the effect of IAF-tACS on emotional attention modulation, demonstrating a feasible and individual-specific therapy for neuropsychiatric disorders related to emotion processing, especially regarding oscillatory disturbances.

Mechanism of Action of ECT in Depression

Electroconvulsive therapy (ECT) remains the most potent antidepressant treatment available for patients with major depressive disorder (MDD). ECT is highly effective, achieving a response rate of 70-80% and a remission rate of 50-60% even in treatment-resistant patients. The underlying mechanisms of ECT are not fully understood, although several hypotheses have been proposed, including the monoamine hypothesis, anticonvulsive hypothesis, neuroplastic effects, and immunomodulatory properties. In this paper, we provide an overview of magnetic resonance imaging evidence that addresses the neuroplastic changes that occur after ECT at the human systems level and elaborate further on ECTs potent immunomodulatory properties. Despite a growing body of evidence that suggests ECT may normalize many of the structural and functional changes in the brain associated with severe depression, there is a lack of convergence between neurobiological changes and the robust clinical effects observed in depression. This may be due to sample sizes used in ECT studies being generally small and differences in data processing and analysis pipelines. Collaborations that acquire large datasets, such as the GEMRIC consortium, can help translate ECT's clinical efficacy into a better understanding of its mechanisms of action.

Transcranial Magnetic Stimulation for Developmental Neuropsychiatric Disorders with Inflammation

BACKGROUND

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique that may potentially be helpful for neuropsychiatric symptoms of developmental disorders with inflammatory aspects. TMS utilizes a varying magnetic field to induce electrical changes in the brain. Repetitive use of TMS modulates plasticity at multiple levels, particularly at the synapse and network level.

SUMMARY

As inflammation can affect synaptic plasticity negatively, TMS may theoretically be a tool to address this inflammation-induced dysfunction. There are also data to suggest that TMS can directly downregulate inflammation. Neuropsychiatric consequences of multiple disorders with inflammatory aspects, particularly neurodevelopmental disorders like autism, Tourette syndrome, and obsessive-compulsive disorder (OCD), maybe treated effectively with TMS. Treatment of OCD, treatment-resistant major depression, and nicotine cessation (all in adults) are currently FDA-cleared indications, while migraine is cleared for ages 12 and above.

KEY MESSAGES

TMS will likely continue to grow in terms of indications as research continues to assess what brain networks are dysfunctional in various disorders and it becomes clearer how to modulate these networks. TMS may thus be best understood as a technology platform that can be utilized to modulate different brain networks affected in neuropsychiatric disorders. TMS is likely to become an increasingly important tool in targeting brain networks that could become dysfunctional in part due to inflammation in the developing brain and addressing consequent neuropsychiatric symptoms.

Baseline markers of cortical excitation and inhibition predict response to theta burst stimulation treatment for youth depression

Theta burst stimulation (TBS), a specific form of repetitive transcranial magnetic stimulation (TMS), is a promising treatment for youth with Major Depressive Disorder (MDD) who do not respond to conventional therapies. However, given the variable response to TBS, a greater understanding of how baseline features relate to clinical response is needed to identify which patients are most likely to benefit from this treatment. In the current study, we sought to determine if baseline neurophysiology, specifically cortical excitation and/or inhibition, is associated with antidepressant response to TBS. In two independent open-label clinical trials, youth (aged 16-24 years old) with MDD underwent bilateral dorsolateral prefrontal cortex (DLPFC) TBS treatment. Clinical trial one and two consisted of 10 and 20 daily sessions of bilateral DLPFC TBS, respectively. At baseline, single-pulse TMS combined with electroencephalography was used to assess the neurophysiology of 4 cortical sites: bilateral DLPFC and inferior parietal lobule. Measures of cortical excitation and inhibition were indexed by TMS-evoked potentials (i.e., P30, N45, P60, N100, and P200). Depression severity was measured before, during and after treatment completion using the Hamilton Rating Scale for Depression-17. In both clinical trials, the baseline left DLPFC N45 and P60, which are believed to reflect inhibitory and excitatory mechanisms respectively, were predictors of clinical response. Specifically, greater (i.e., more negative) N45 and smaller P60 baseline values were associated with greater treatment response to TBS. Accordingly, cortical excitation and inhibition circuitry of the left DLPFC may have value as a TBS treatment response biomarker for youth with MDD.Clinical trial 1 registration number: NCT02472470 (June 15, 2015).Clinical trial 2 registration number: NCT03708172 (October 17, 2018).

Mindfulness-based real-time fMRI neurofeedback: a randomized controlled trial to optimize dosing for depressed adolescents

BACKGROUND

Adolescence is characterized by a heightened vulnerability for Major Depressive Disorder (MDD) onset, and currently, treatments are only effective for roughly half of adolescents with MDD. Accordingly, novel interventions are urgently needed. This study aims to establish mindfulness-based real-time fMRI neurofeedback (mbNF) as a non-invasive approach to downregulate the default mode network (DMN) in order to decrease ruminatory processes and depressive symptoms.

METHODS

Adolescents (N = 90) with a current diagnosis of MDD ages 13-18-years-old will be randomized in a parallel group, two-arm, superiority trial to receive either 15 or 30 min of mbNF with a 1:1 allocation ratio. Real-time neurofeedback based on activation of the frontoparietal network (FPN) relative to the DMN will be displayed to participants via the movement of a ball on a computer screen while participants practice mindfulness in the scanner. We hypothesize that within-DMN (medial prefrontal cortex [mPFC] with posterior cingulate cortex [PCC]) functional connectivity will be reduced following mbNF (Aim 1: Target Engagement). Additionally, we hypothesize that participants in the 30-min mbNF condition will show greater reductions in within-DMN functional connectivity (Aim 2: Dosing Impact on Target Engagement). Aim 1 will analyze data from all participants as a single-group, and Aim 2 will leverage the randomized assignment to analyze data as a parallel-group trial. Secondary analyses will probe changes in depressive symptoms and rumination.

DISCUSSION

Results of this study will determine whether mbNF reduces functional connectivity within the DMN among adolescents with MDD, and critically, will identify the optimal dosing with respect to DMN modulation as well as reduction in depressive symptoms and rumination.

TRIAL REGISTRATION

This study has been registered with clinicaltrials.gov, most recently updated on July 6, 2023 (trial identifier: NCT05617495).

Parcellation-Based Connectivity Model of the Judgement Core

Judgement is a higher-order brain function utilized in the evaluation process of problem solving. However, heterogeneity in the task methodology based on the many definitions of judgement and its expansive and nuanced applications have prevented the identification of a unified cortical model at a level of granularity necessary for clinical translation. Forty-six task-based fMRI studies were used to generate activation-likelihood estimations (ALE) across moral, social, risky, and interpersonal judgement paradigms. Cortical parcellations overlapping these ALEs were used to delineate patterns in neurocognitive network engagement for the four judgement tasks. Moral judgement involved the bilateral superior frontal gyri, right temporal gyri, and left parietal lobe. Social judgement demonstrated a left-dominant frontoparietal network with engagement of right-sided temporal limbic regions. Moral and social judgement tasks evoked mutual engagement of the bilateral DMN. Both interpersonal and risk judgement were shown to involve a right-sided frontoparietal network with accompanying engagement of the left insular cortex, converging at the right-sided CEN. Cortical activation in normophysiological judgement function followed two separable patterns involving the large-scale neurocognitive networks. Specifically, the DMN was found to subserve judgement centered around social inferences and moral cognition, while the CEN subserved tasks involving probabilistic reasoning, risk estimation, and strategic contemplation.

Differences in White Matter Structural Networks in Family Risk of Major Depressive Disorder and Suicidality: A Connectome Analysis

Background

Depression and suicide are leading global causes of disability and death and are highly familial. Family and individual history of depression are associated with neurobiological differences including decreased white matter connectivity; however, this has only been shown for individual regions. We use graph theory models to account for the network structure of the brain with high levels of specialization and integration and examine whether they differ by family history of depression or of suicidality within a three-generation longitudinal family study with well-characterized clinical histories.

Methods

Clinician interviews across three generations were used to classify family risk of depression and suicidality. Then, we created weighted network models using 108 cortical and subcortical regions of interest for 96 individuals using diffusion tensor imaging derived fiber tracts. Global and local summary measures (clustering coefficient, characteristic path length, and global and local efficiencies) and network-based statistics were utilized for group comparison of family history of depression and, separately, of suicidality, adjusted for personal psychopathology.

Results

Clustering coefficient (connectivity between neighboring regions) was lower in individuals at high family risk of depression and was associated with concurrent clinical symptoms. Network-based statistics showed hypoconnected subnetworks in individuals with high family risk of depression and of suicidality, after controlling for personal psychopathology. These subnetworks highlighted cortical-subcortical connections including between the superior frontal cortex, thalamus, precuneus, and putamen.

Conclusions

Family history of depression and of suicidality are associated with hypoconnectivity between subcortical and cortical regions, suggesting brain-wide impaired information processing, even in those personally unaffected.

Multisite rTMS combined with cognitive training modulates effective connectivity in patients with Alzheimer's disease

Purpose

To investigate the effective connectivity (EC) changes after multisite repetitive transcranial magnetic stimulation (rTMS) combined with cognitive training (COG).

Method

We selected 51 patients with mild or moderate Alzheimer's disease (AD) and delivered 10 Hz rTMS over the left dorsal lateral prefrontal cortex (DLPFC) and the lateral temporal lobe (LTL) combined with COG or sham stimulation for 4 weeks. The selected AD patients were divided into real (real rTMS+COG, n = 11) or sham (sham rTMS+COG, n = 8) groups to undergo neuropsychological assessment, resting-state fMRI, and 3D brain structural imaging before (T0), immediately at the end of treatment (T4), and 4 weeks after treatment (T8). A 2 × 3 factorial design with "time" as the within-subjects factor (three levels: T0, T4, and T8) and "group" as the between-subjects factor (two levels: real and sham) was used to investigate the EC changes related to the stimulation targets in the rest of the brain, as well as the causal interactions among seven resting-state networks based on Granger causality analysis (GCA).

Results

At the voxel level, the EC changes from the left DLPFC out to the left inferior parietal lobe and the left superior frontal gyrus, as well as from the left LTL out to the left orbital frontal cortex, had a significant group × time interaction effect. At the network level, a significant interaction effect was identified in the increase in EC from the limbic network out to the default mode network. The decrease in EC at the voxel level and the increase in EC at the network level were both associated with the improved ability to perform activities of daily living and cognitive function.

Conclusion

Multisite rTMS combined with cognitive training can modulate effective connectivity in patients with AD, resulting in improved ability to perform activities of daily living and cognitive function.

Intensity of repetitive negative thinking in depression is associated with greater functional connectivity between semantic processing and emotion regulation areas

BACKGROUND

Repetitive negative thinking (RNT), a cognitive process that encompasses past (rumination) and future (worry) directed thoughts focusing on negative experiences and the self, is a transdiagnostic construct that is especially relevant for major depressive disorder (MDD). Severe RNT often occurs in individuals with severe levels of MDD, which makes it challenging to disambiguate the neural circuitry underlying RNT from depression severity.

METHODS

We used a propensity score, i.e., a conditional probability of having high RNT given observed covariates to match high and low RNT individuals who are similar in the severity of depression, anxiety, and demographic characteristics. Of 148 MDD individuals, we matched high and low RNT groups (n = 50/group) and used a data-driven whole-brain voxel-to-voxel connectivity pattern analysis to investigate the resting-state functional connectivity differences between the groups.

RESULTS

There was an association between RNT and connectivity in the bilateral superior temporal sulcus (STS), an important region for speech processing including inner speech. High relative to low RNT individuals showed greater connectivity between right STS and bilateral anterior insular cortex (AI), and between bilateral STS and left dorsolateral prefrontal cortex (DLPFC). Greater connectivity in those regions was specifically related to RNT but not to depression severity.

CONCLUSIONS

RNT intensity is directly related to connectivity between STS and AI/DLPFC. This might be a mechanism underlying the role of RNT in perceptive, cognitive, speech, and emotional processing. Future investigations will need to determine whether modifying these connectivities could be a treatment target to reduce RNT.

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.

Functional MRI Lateralization [M1] of dlPFC and Implications for Transcranial Magnetic Stimulation (TMS) Targeting

The present study investigates a potential method of optimizing effective strategies for the functional lateralization of the dorsolateral prefrontal cortex (dlPFC) while in a scanner. Effective hemisphere lateralization of the dlPFC is crucial for lowering the functional risks connected to specific interventions (such as neurosurgery and transcranial magnetic stimulation (TMS), as well as increasing the effectiveness of a given intervention by figuring out the optimal location. This task combines elements of creative problem solving, executive decision making based on an internal rule set, and working memory. A retrospective analysis was performed on a total of 58 unique participants (34 males, 24 females, Mage = 42.93 years, SDage = 16.38). Of these participants, 47 were classified as right-handed, 7 were classified as left-handed, and 4 were classified as ambidextrous, according to the Edinburgh Handedness Inventory. The imaging data were qualitatively judged by two trained, blinded investigators (neurologist and neuropsychologist) for dominant handedness (primary motor cortex) and dominant dorsolateral prefrontal cortex (dlPFC). The results demonstrated that 21.4% of right-handed individuals showed a dominant dlPFC localized to the right hemisphere rather than the assumed left, and 16.7% of left-handers were dominant in their left hemisphere. The task completed in the scanner might be an efficient method for localizing a potential dlPFC target for the purpose of brain stimulation (e.g., TMS), though further study replications are needed to extend and validate these findings.

Alterations of large-scale functional network connectivity in patients with infantile esotropia before and after surgery

BACKGROUND

Growing evidences have indicated neurodevelopmental disorders in infantile esotropia (IE). However, few studies have analyzed the characteristics of large-scale functional networks of IE patients or their postoperative network-level alterations.

METHODS

Here, individuals with IE (n = 32) and healthy subjects (n = 30) accomplished the baseline clinical examinations and resting-state MRI scans. A total of 17 IE patients also underwent corrective surgeries and completed the longitudinal clinical assessments and resting-state MRI scans. Linear mixed effects models were applied for cross-sectional and longitudinal network-level analyses. Correlation analysis was performed to assess the relationship between longitudinal functional connectivity (FC) alterations and baseline clinical variables.

RESULTS

In cross-sectional analyses, network-level FC were apparently aberrant in IE patients compared to controls. In longitudinal analyses, intra- and internetwork connectivity were observed with significant alterations in postoperative IE patients compared to the preoperative counterparts. Longitudinal FC changes are negatively correlated to the age at surgery in IE.

CONCLUSIONS

Obviously, altered network-level FC benefiting from the corrective surgery serves as the neurobiological substrate of the observed improvement of stereovision, visuomotor coordination, and emotional management in postoperative IE patients. Corrective surgery should be performed as early as possible to obtain more benefits for IE in brain function recovery.