Default mode network mechanisms of transcranial magnetic stimulation in depression

Reconstruction and application of multilayer brain network for juvenile myoclonic epilepsy based on link prediction

Juvenile myoclonic epilepsy (JME) exhibits abnormal functional connectivity of brain networks at multiple frequencies. We used the multilayer network model to address the heterogeneous features at different frequencies and assess the mechanisms of functional integration and segregation of brain networks in JME patients. To address the possibility of false edges or missing edges during network construction, we combined multilayer networks with link prediction techniques. Resting-state functional magnetic resonance imaging (rs-fMRI) data were procured from 40 JME patients and 40 healthy controls. The Multilayer Network framework is utilized to integrate information from different frequency bands and to fuse similarity metrics for link prediction. Finally, calculate the entropy of the multiplex degree and multilayer clustering coefficient of the reconfigured multilayer frequency network. The results showed that the multilayer brain network of JME patients had significantly reduced ability to integrate and separate information and significantly correlated with severity of JME symptoms. This difference was particularly evident in default mode network (DMN), motor and somatosensory network (SMN), and auditory network (AN). In addition, significant differences were found in the precuneus, suboccipital gyrus, middle temporal gyrus, thalamus, and insula. Results suggest that JME patients have abnormal brain function and reduced cross-frequency interactions. This may be due to changes in the distribution of connections within and between the DMN, SMN, and AN in multiple frequency bands, resulting in unstable connectivity patterns. The generation of these changes is related to the pathological mechanisms of JME and may exacerbate cognitive and behavioral problems in patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-024-10191-0.

Ovarian hormone effects on cognitive flexibility in social contexts: Evidence from resting-state and task-based fMRI

Accumulating evidence suggests that the menstrual cycle and its endogenous ovarian hormones, including progesterone (PROG) and estradiol (E2), affect cognitive performance in women, particularly by modulating the prefrontal regions. In this study, we investigated whether differences in PROG and E2 levels modulate attentional control by affecting the prefrontal cognitive control areas. An fMRI scan was conducted on 53 naturally cycling healthy women in their late follicular phase (FP, n = 28) or mid-luteal phase (LP, n = 25) to examine the resting and task states during the completion of a face‒gender Stroop task. PROG was found to be positively correlated with the nodal efficiency of the inferior frontal gyrus (IFG) in the resting-state executive control network. At the behavioral level, while accuracy in categorizing male faces remained similar, participants in the mid-LP were significantly more accurate in categorizing female faces than those in the late FP. At the neural level, both the univariate and multivariate results indicated that higher levels of PROG enhance the detection and resolution of female incongruent faces through the activation of the bilateral IFG. These findings expand evidence of the effects of ovarian hormones on prefrontal-based attentional control in the social context.

Psychophysiological indices of late-life depression: A systematic review

BACKGROUND

Major depression in the older population has a profound impact on patients' quality of life and is associated with an increased risk of developing several medical illnesses. Psychophysiological methods, such as electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and eye-tracking, have provided evidence of physiological changes associated with depression in adult life. However, these aspects have not been thoroughly investigated during late-life (over 60 years of age).

METHODS

A systematic review of the scientific literature covering the studies published between 1990 and 2022 was performed to describe the current evidence on easily attainable psychophysiological factors (detected by EEG, fNIRS and eye-tracking) associated with depression in late-life.

RESULTS

Twelve studies were included in the systematic review. The included studies showed some consistent physiological patterns associated with late-life depression, such as brain hypoactivation in frontal and temporal areas and attentional biases toward emotional stimuli. No reliable patterns in EEG asymmetry and power spectrum were found, in contrast to studies on early-life depression.

LIMITATIONS

The small number of available studies, together with the heterogeneity in the techniques and methods used, highlight the need for further research to reliably identify the psychophysiological aspects of depression in late-life.

CONCLUSIONS

Physiological indices of late-life depression, as assessed by EEG, fNIRS and eye-tracking, may differ from those of early-life. The study of these indices could better clarify the physiological mechanisms underlying late-life depression with possible clinical and research implications. Recommendations for future research are also discussed.

The Use of MRI and TMS in Treatment-Resistant Depression: Advances in Pediatric Applications

Treatment-resistant depression (TRD) is a substantial burden for psychiatric care, affecting approximately one-third of patients with major depressive disorder (MDD). Adolescent populations with depression are a particularly challenging demographic to treat as early intervention is crucial to prevent treatment resistance, but treatment options are limited. Transcranial magnetic stimulation (TMS) has emerged as a promising non-invasive option for TRD in adults as well as adolescents, offering hope for patients who have not responded to conventional therapies. This review examines the convergence of functional magnetic resonance imaging (fMRI) as a tool to examine how TMS modulates functional connectivity in adolescents with MDD. Such analyses have led to advances in our understanding of the pathophysiology of MDD, TRD, and the mechanisms of TMS. We review this evidence, evaluate methodological approaches, and identify critical gaps in the existing literature, highlighting how neuroimaging-guided TMS protocols offer a promising therapeutic avenue for adolescent TRD, particularly in cases where conventional treatments have proven ineffective.

Decoding neural circuit dysregulation in bipolar disorder: Toward an advanced paradigm for multidimensional cognitive, emotional, and psychomotor treatment

Bipolar disorder (BD) is characterized by a complex constellation of emotional, cognitive, and psychomotor disturbances, each deeply intertwined with underlying dysfunctions in large-scale brain networks and neurotransmitter systems. This manuscript integrates recent advances in neuroimaging, neuromodulation, and pharmacological research to provide a comprehensive view of BD's pathophysiology, emphasizing the role of network-specific dysfunctions and their clinical manifestations. We explore how dysregulation within the fronto-limbic network, particularly involving the prefrontal cortex (PFC) and amygdala, underpins the emotional instability that defines both manic and depressive episodes. Additionally, impairments in the central executive network (CEN) and default mode network (DMN) are linked to cognitive deficits, with hyperactivity in the DMN driving rumination and cognitive inflexibility, while CEN underactivity contributes to attentional lapses and impaired executive function. Psychomotor symptoms, which oscillate between hyperactivity in mania and retardation in depression, are closely associated with imbalances in neurotransmitter systems, particularly dopamine and serotonin, within the basal ganglia-thalamo-cortical motor pathway. Recent studies indicate that these psychomotor disturbances are further exacerbated by disruptions in network connectivity, leading to impairments in both motor control and emotional regulation. Emerging therapeutic strategies are discussed, with a focus on neuromodulation techniques such as transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS), which show promise in restoring balance within these critical networks. Furthermore, pharmacological interventions that modulate synaptic functioning and neuronal plasticity offer potential for addressing both the emotional and motor symptoms of BD. This manuscript underscores the need for an integrative treatment approach that simultaneously targets neural circuits and neurotransmitter systems to address the full spectrum of symptoms in BD. Drawing on recent advancements in neurobiological models and therapeutic frameworks, this proposal outlines a pathway for the development of precision-tailored interventions. These approaches are designed to optimize cognitive, emotional, and psychomotor outcomes, ultimately striving to elevate the quality of life for individuals living with bipolar disorder (BD), while remaining firmly grounded in the latest empirical evidence and theoretical insights.

Navigating the depths: A comprehensive narrative review on depression in people with epilepsy

Epilepsy presents a significant global health challenge, impacting millions worldwide. Alarmingly, over half of individuals living with epilepsy (PWE) also face concurrent medical conditions, with psychiatric complications, particularly depression, standing out as prevalent issues. The relationship between epilepsy and depression is complex and bidirectional, with approximately a quarter of adults with epilepsy receiving a diagnosis of depression. This complexity underscores the challenges in diagnosing depression in epilepsy patients, hindered by overlapping symptoms and distinct manifestations of depression in this population. Our review highlights that the use of most antidepressant pharmacotherapies does not increase the risk of seizure occurrences. On the contrary, compelling evidence suggests that such treatments may even decrease seizure frequency, offering hope for patients. In addition to pharmacology, non-pharmacological interventions are emerging as vital alternatives, enriching the therapeutic landscape. However, despite these promising avenues, a significant gap in our understanding persists, characterized by a lack of comprehensive, prospective research. Our review rigorously explores the latest pathophysiological insights linking depression and epilepsy while critically evaluating contemporary treatment paradigms for individuals grappling with these comorbid conditions. By focusing on the most current developments, this review aims to equip clinicians with cutting-edge knowledge, fostering a more nuanced and effective approach to managing the intricate interplay between epilepsy and comorbid depression.

Resting fMRI-guided TMS evokes subgenual anterior cingulate response in depression

BACKGROUND

Depression alleviation following treatment with repetitive transcranial magnetic stimulation (rTMS) tends to be more effective when TMS is targeted to cortical areas with high (negative) resting state functional connectivity (rsFC) with the subgenual anterior cingulate cortex (sgACC). However, the relationship between sgACC-cortex rsFC and the TMS-evoked response in the sgACC is still being explored and has not yet been established in depressed patients.

OBJECTIVES

In this study, we investigated the relationship between sgACC-cortical (site of stimulation) rsFC and induced evoked responses in the sgACC in healthy controls and depressed patients.

METHODS

For each participant (N = 115, 34 depressed patients), a peak rsFC cortical 'hotspot' for the sgACC and control targets were identified at baseline. Single pulses of TMS interleaved with fMRI readouts were administered to these targets to evoke downstream fMRI blood-oxygen-level-dependent (BOLD) responses in the sgACC. Generalized estimating equations were used to investigate the association between TMS-evoked BOLD responses in the sgACC and rsFC between the stimulation site and the sgACC.

RESULTS

Stimulations over cortical sites with high rsFC to the sgACC were effective in modulating activity in the sgACC in both healthy controls and depressed patients. Moreover, we found that in depressed patients, sgACC rsFC at the site of stimulation was associated with the induced evoked response amplitude in the sgACC: stronger positive rsFC values leading to stronger evoked responses in the sgACC.

CONCLUSIONS

rsFC-based targeting is a viable strategy to causally modulate the sgACC. Assuming an anti-depressive mechanism working through modulation of the sgACC, the field's exclusive focus on sites anticorrelated with the sgACC for treating depression should be broadened to explore positively-connected sites.

TMS-induced modulation of brain networks and its associations to rTMS treatment for depression: a concurrent fMRI-EEG-TMS study

Transcranial magnetic stimulation (TMS) over the left dorsolateral prefrontal cortex (L-DLPFC) is an established intervention for treatment-resistant depression (TRD), yet the underlying therapeutic mechanisms remain not fully understood. This study employs an integrative approach that combines TMS with concurrent functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), aimed at assessing the acute/immediate effects of TMS on brain network dynamics and their correlation with clinical outcomes. Our study demonstrates that TMS acutely modulates connectivity within vital brain circuits, particularly the cognitive control and default mode networks. We found that the baseline TMS-evoked responses in the cognitive control and limbic networks significantly predicted clinical improvement in patients receiving a novel EEG-synchronized repetitive TMS treatment. Furthermore, this study explored the brain-state dependent effects of TMS, as the brain-state indexed by the phase of EEG prefrontal alpha oscillation. We found that clinical outcomes in this novel treatment are linked to state-specific TMS-modulated functional connectivity within a pivotal brain circuit of the L-DLPFC and the posterior subgenual anterior cingulate cortex within the limbic system. These findings contribute to our understanding of the therapeutic effects underlying TMS treatment in depression and support the potential of assessing state-dependent TMS effects in TMS timing target selection. This study emphasizes the importance of personalized timing of TMS for optimizing target engagement of specific clinically relevant brain circuits. Our results are crucial for future research into the development of personalized neuromodulation therapies for TRD patients.

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.

In perspective of specific symptoms of major depressive disorder: Functional connectivity analysis of electroencephalography and potential biomarkers of treatment response

BACKGROUND

The symptom variability in major depressive disorder (MDD) complicates treatment assessment, necessitating a thorough understanding of MDD symptoms and potential biomarkers.

METHODS

In this prospective study, we enrolled 54 MDD patients and 39 controls. Over the course of weeks 1, 2, and 4 participants underwent evaluations, with electroencephalograms (EEG) recorded at baseline and week 1. Our investigation considered five previously identified syndromal factors derived from the 17-item Hamilton Depression Rating Scale (17-item HAMD) for assessing depression: core, insomnia, somatic anxiety, psychomotor-insight, and anorexia. We assessed treatment response and EEG characteristics across all syndromal factors and total scores, all of which are based on the 17-item HAMD. To analyze the topology of brain networks, we employed functional connectivity (FC) and a graph theory-based method across various frequency bands.

RESULTS

The healthy control group had notably higher values in delta band EEG FC compared to the MDD patient group. Similar distinctions were observed between the responder and non-responder patient groups. Further exploration of baseline FC values across distinct syndromal factors revealed significant variations among the core, psychomotor-insight, and anorexia subgroups when using a specific graph theory-based approach, focusing on global efficiency and average clustering coefficient.

LIMITATIONS

Different antidepressants were included in this study. Therefore, the results should be interpreted with caution.

CONCLUSIONS

Our findings suggest that delta band EEG FC holds promise as a valuable predictor of antidepressant efficacy. It demonstrates an ability to adapt to individual variations in depressive symptomatology, offering insights into personalized treatment for patients with depression.

A systematic review of the effects of rumination-focused cognitive behavioral therapy in reducing depressive symptoms

There is still potential room for improving the effectiveness of standard Cognitive Behavioral Therapy (CBT) in preventing the onset of depression, achieving full remission, and preventing relapse or recurrence of depression. Standard CBT seems less effective in reducing depressive rumination, a key risk factor leading to the onset and persistence of depression. To improve treatment efficacy for depression, rumination-focused cognitive behavioral therapy (RFCBT) was developed, which was modified from CBT and specifically targeted to manage rumination. This systematic review aimed to assess the effects of RFCBT by evaluating whether RFCBT could contribute to reducing depressive symptoms pre-post intervention. A literature search was conducted up to April 30, 2024, across four English-language databases, including PubMed, Web of Science, Google Scholar, and Embase. The search terms employed were: (depress* OR mood OR affect OR rumination) AND ("Rumination Focused Cognitive behavio* Therapy" OR RFCBT). Among the initial 328 studies identified, 12 met the inclusion criteria, of which 10 were randomized controlled trials. Intervention characteristics and results were narratively synthesized to address the review aims. This review found preliminary evidence that the RFCBT could eliminate depressive symptoms post-intervention, and might prevent individuals from developing depression, alleviate depressive symptoms, and prevent relapse of depression, as well as reduce rumination. RFCBT could be promoted to treat depressive symptoms, especially for those with a high tendency toward rumination. However, more studies with rigorous designs are required to confirm its efficacy across different stages of depression. Future studies could compare RFCBT with other psychotherapies, dismantle the psychological therapies to identify their effective components, and explore which specific groups of people might benefit most from this intervention.

Cortical hypometabolism as a predictor of intermittent theta burst stimulation response in treatment-resistant depression patients: An open-label study

Background

Intermittent theta burst stimulation (iTBS) is an accepted and approved brain stimulation technique to treat patients with treatment-resistant depression.

Aim

Using neuroimaging, this open-label study aimed to predict the response by observing glucose metabolism with the help of 18-FDG PET scan.

Methods

A total of 25 treatment-resistant depression patients received 15 sessions of iTBS on the left dorsolateral prefrontal cortex. Two FDG-PET scans were done for all the patients. Fifty-six percent of patients responded to treatment with iTBS.

Results

We found that there was hypometabolism in left and right prefrontal lateral regions, left and right inferior parietal regions, and left prefrontal medial regions at baseline but no statistically significant difference in the metabolism between responders and nonresponders.

Conclusion

We did not find any statistically significant difference in the metabolism between responders and nonresponders in any brain regions at T0 as well as T1. Further large-scale studies are required.

Association of inflammatory cytokines with magnetic resonance imaging features of the brain in patients with depression

There is growing evidence that the imbalance of inflammatory cytokines plays an important role in the pathophysiological mechanism of depression. However, the effects of inflammatory cytokines on the whole brain in patients with depression are still not fully elucidated. The present study aimed to investigate the relationship between inflammatory cytokines and cerebral magnetic resonance imaging (MRI) features using voxel-based whole-brain analysis in patients with depression. A total of 60 patients with depression and 60 healthy controls (HCs) were included. Interleukin-1 was positively correlated with gray matter volume (GMV) in the left putamen and negatively correlated with regional homogeneity (ReHo) and degree centrality (DC) in the left anterior cingulate cortex. Interleukin-6 was positively correlated with GMV in the right superior parietal lobule and ReHo in the left pallidum and putamen. Interferon-α was negatively correlated with DC in the left postcentral gyrus. The ReHo in the left pallidum in depressed patients was lower than that in HCs. The FCs based on the left pallidum as the seed in depressed patients were significantly reduced. The imaging features of the left pallidum had good performance (area under the curve: 0.891) for identifying depressed patients. Inflammatory cytokines are associated with cerebral imaging features in patients with depression and in particular, the abnormal imaging features of the left pallidum may be a potential neuroimaging biomarker of depression.

Preliminary findings of a randomized controlled trial investigating the efficacy of transcranial magnetic stimulation in treatment-resistant depression: a post-hoc analysis on the role of co-occurring personality disorders

Introduction

Despite the high hopes for the use of transcranial magnetic stimulation (TMS) in the treatment of depression, between 30% and 60.5% of patients do not respond to stimulation. The factors contributing to non-response, especially those related to personality, remain insufficiently investigated. The main aim of our study was to compare the efficacy of active TMS and sham-placebo protocols in combined therapy of treatment-resistant depression with evaluation of possible personality disorders comorbidity.

Methods

The study was conducted between December 2019 and December 2022, as a randomized, double-blind, active comparator-controlled and sham-controlled parallel trial. Patients (n = 41) were randomized into one of two experimental conditions (active TMS vs. placebo) and screened before and after stimulation as well as at a 3-month follow-up. Personality disorders were assessed with The Structured Clinical Interview for DSM-5 Personality Disorders.

Results

There were no significant differences between the TMS active and sham groups in terms of general characteristics, coexisting personality disorders, and Montgomery-Åsberg Depression Rating Scale scores before stimulation, at the end of stimulation, and after 3 months of stimulation. However, linear regression analysis revealed significant negative associations between the coexistence of personality disorders and the reduction of depressive symptoms from baseline to the end of stimulation. The post-hoc exploratory analysis on the first phase of the RCT confirmed the presence of personality disorders to be a consistent negative influence on the reduction of depressive symptoms post-stimulation, regardless of protocol and experimental condition and demonstrated a smaller percentage reduction in depressive symptoms after stimulation in patients with personality disorders.

Discussion

A central conclusion, based on our study, is that transcranial magnetic stimulation for treatment-resistant depression cannot be considered as a method independent of co-occurring personality disorders.

Transcranial Magnetic Stimulation for Posttraumatic Stress Disorder and Generalized Anxiety Disorder

Posttraumatic stress disorder (PTSD) and generalized anxiety disorder (GAD) are debilitating psychiatric disorders. While treatments are often effective, many patients do not adequately respond or experience significant side effects. Transcranial magnetic stimulation (TMS) is an emerging approach for treating PTSD and GAD. Several randomized clinical trials have demonstrated that TMS over the dorsolateral prefrontal cortex may be efficacious in reducing psychiatric symptoms; however, results are inconsistent regarding whether any parameter or treatment paradigm is superior. Other RCTs have targeted novel brain regions using newer TMS modalities. Combining TMS with psychotherapy may augment response in patients with PTSD, yet results are inconclusive. Little research has been done on TMS in combination with psychotherapy for GAD, indicating a need for further investigation. Future studies may assess TMS parameter optimization for enhancing effectiveness and improving therapeutic response duration. Identifying response biomarkers through functional magnetic resonance imaging and electroencephalography may offer a means to predict and monitor clinical response as precision methods to improve treatment response.

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

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

Common and divergent neuroimaging features in major depression, posttraumatic stress disorder, and their comorbidity

Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are common stress-related psychiatric disorders. Genetic and neurobiology research has supported the viewpoint that PTSD and MDD may possess common and disorder-specific underlying mechanisms. In this systematic review, we summarize evidence for the similarities and differences in brain functional and structural features of MDD, PTSD, and their comorbidity, as well as the effects of extensively used therapies in patients with comorbid PTSD and MDD (PTSD + MDD). These functional magnetic resonance imaging (MRI) studies highlight the (i) shared hypoactivation in the prefrontal cortex during cognitive and emotional processing in MDD and PTSD; (ii) higher activation in fear processing regions including amygdala, hippocampus, and insula in PTSD compared to MDD; and (iii) distinct functional deficits in brain regions involved in fear and reward processing in patients with PTSD + MDD relative to those with PTSD alone. These structural MRI studies suggested that PTSD and MDD share features of reduced volume in focal frontal areas. The treatment effects in patients with PTSD + MDD may correlate with the normalization trend of structural alterations. Neuroimaging predictors of repetitive transcranial magnetic stimulation response in patients with PTSD + MDD may differ from the mono-diagnostic groups. In summary, neuroimaging studies to date have provided limited information about the shared and disorder-specific features in MDD and PTSD. Further research is essential to pave the way for developing improved diagnostic markers and eventually targeted treatment approaches for the shared and distinct brain alterations presented in patients with MDD and PTSD.

Different stimulation targets of rTMS modulate specific triple-network and hippocampal-cortex functional connectivity

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) is widely applied to treat Alzheimer's disease (AD). Various treatment targets are currently being explored in clinical research. However, target diversity can result in considerable heterogeneity.

OBJECTIVE

This study aimed to investigate whether different rTMS targets can enhance cognitive domains by modulating functional connectivity (FC) of the hippocampus (HIP) and triple network, which comprises the salience network (SN), central executive network (CEN), and default mode network (DMN).

METHODS

We enrolled 63 patients with AD, of whom 48 and 15 underwent rTMS targeting the left dorsolateral prefrontal cortex (dlPFC) and the bilateral angular gyrus (ANG), respectively. We examined the network-level FC differences within the triple-network before and after treatment. Additionally, we utilized HIP as a seed for voxel-level analysis. We compared the similarities and differences in the effects of dlPFC and ANG rTMS.

RESULTS

rTMS targeting the dlPFC primarily influenced the FC of the CEN, whereas rTMS targeting the ANG primarily influenced the SN and DMN. Moreover, the right temporal lobe within the DMN exhibited reduced FC with the left HIP following both therapies. The results of least absolute shrinkage and selection operator (LASSO) analysis indicated that hippocampal-cortex FC played a dominant role in the therapeutic effect. The observed FC changes significantly correlated with improvements in multiple cognitive scales.

CONCLUSION

rTMS targeting different regions affected the FC of specific networks. Both stimulation targets modulate the FC of hippocampal-cortex to influence therapeutic outcomes. Classification of patients based on damaged networks can further inform subsequent treatment strategies.

Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression

Treatment outcomes widely vary for individuals diagnosed with major depressive disorder, implicating a need for deeper understanding of the biological mechanisms conferring a greater likelihood of response to a particular treatment. Our improved understanding of intrinsic brain networks underlying depression psychopathology via magnetic resonance imaging and other neuroimaging modalities has helped reveal novel and potentially clinically meaningful biological markers of response. And while we have made considerable progress in identifying such biomarkers over the last decade, particularly with larger, multisite trials, there are significant methodological and practical obstacles that need to be overcome to translate these markers into the clinic. The aim of this review is to review current literature on brain network structural and functional biomarkers of treatment response or selection in depression, with a specific focus on recent large, multisite trials reporting predictive accuracy of candidate biomarkers. Regarding pharmaco- and psychotherapy, we discuss candidate biomarkers, reporting that while we have identified candidate biomarkers of response to a single intervention, we need more trials that distinguish biomarkers between first-line treatments. Further, we discuss the ways prognostic neuroimaging may help to improve treatment outcomes to neuromodulation-based therapies, such as transcranial magnetic stimulation and deep brain stimulation. Lastly, we highlight obstacles and technical developments that may help to address the knowledge gaps in this area of research. Ultimately, integrating neuroimaging-derived biomarkers into clinical practice holds promise for enhancing treatment outcomes and advancing precision psychiatry strategies for depression management. By elucidating the neural predictors of treatment response and selection, we can move towards more individualized and effective depression interventions, ultimately improving patient outcomes and quality of life.

Local brain abnormalities in emotional disorders: Evidence from resting state fMRI studies

Emotional disorders inflict an enormous burden on society. Research on brain abnormalities implicated in emotional disorders has witnessed great progress over the past decades. Using cross-sectional and longitudinal designs, resting state functional magnetic resonance imaging (rs-fMRI) and its analytic approaches have been applied to characterize the local properties of patients with emotional disorders. Additionally, brain activity alterations of emotional disorders have shown frequency-specific. Despite the gains in understanding the roles of brain abnormalities in emotional disorders, the limitation of the small sample size needs to be highlighted. Lastly, we proposed that evidence from the positive psychology research stream presents it as a viable discipline, whose suggestions could be developed in future emotional disorders research. Such interdisciplinary research may produce novel treatments and intervention options. This article is categorized under: Psychology > Brain Function and Dysfunction.

The prevalence of neuropsychiatric symptoms and correlation with MRI findings in CADASIL patients

OBJECTIVE

To assess the prevalence, timing, and functional impact of neuropsychiatric symptoms in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) and to assess whether these neuropsychiatric symptoms are associated with magnetic resonance imaging (MRI) features of the patients.

METHODS

Our study included a total of 78 patients with CADASIL. To assess neuropsychiatric symptoms, we evaluated the caregivers using the Neuropsychiatric Inventory (NPI). Patients were considered to have an irritability, depression, apathy, aggression, or anxiety disorder if they scored ≥1 in the NPI. Subsequently, we conducted a more detailed assessment of irritability, depression, apathy, aggression, and anxiety. Multivariate logistic regression was employed to analyze the relationships between neuropsychiatric symptoms and clinical/MRI features in the patients.

RESULTS

Overall, 57.69% of patients with CADASIL experienced neuropsychiatric symptoms. Among these symptoms, irritability was the most prevalent (52.56%), followed by depression (19.23%), apathy (17.95%), aggression (7.69%), and anxiety (6.41%). The mean age of onset for irritability was the youngest, followed by anxiety, apathy, aggression, and depression. Among patients with both stroke/TIA and neuropsychiatric symptoms, 31.03% reported experiencing neuropsychiatric symptoms prior to stroke/TIA. Furthermore, both irritability and apathy had a negative impact on the patients' daily functioning. Additionally, there was a correlation between the presence of neuropsychiatric symptoms and the patients' MRI lesion burden.

INTERPRETATION

Our study has discovered that neuropsychiatric symptoms are highly prevalent in patients with CADASIL and may occur before cerebrovascular events, suggesting that neuropsychiatric symptoms of CADASIL deserve more attention and earlier exploration.

Dissociable Default Mode Network Connectivity Patterns Underlie Distinct Symptoms in Psychosis Risk

The Clinical High Risk (CHR) stage of psychosis is characterized by subthreshold symptoms of schizophrenia including negative symptoms, dysphoric mood, and functional deterioration. Hyperconnectivity of the default-mode network (DMN) has been observed in early schizophrenia, but the extent to which hyperconnectivity is present in CHR, and the extent to which such hyperconnectivity may underlie transdiagnostic symptoms, is not clear. As part of the Shanghai At-Risk for Psychosis (SHARP) program, resting-state fMRI data were collected from 251 young adults (158 CHR and 93 controls, M = 18.72, SD = 4.68, 129 male). We examined functional connectivity of the DMN by performing a whole-brain seed-to-voxel analysis with the MPFC as the seed. Symptom severity across a number of dimensions, including negative symptoms, positive symptoms, and affective symptoms were assessed. Compared to controls, CHRs exhibited significantly greater functional connectivity (p < 0.001 uncorrected) between the MPFC and 1) other DMN nodes including the posterior cingulate cortex (PCC), and 2) auditory cortices (superior and middle temporal gyri, STG/MTG). Furthermore, these two patterns of hyperconnectivity were differentially associated with distinct symptom clusters. Within CHR, MPFC-PCC connectivity was significantly correlated with anxiety (r= 0.23, p=0.006), while MPFC-STG/MTG connectivity was significantly correlated with negative symptom severity (r=0.26, p=0.001). Secondary analyses using item-level symptom scores confirmed a similar dissociation. These results demonstrate that two dissociable patterns of DMN hyperconnectivity found in the CHR stage may underlie distinct dimensions of symptomatology.

A novel dual-site OFC-dlPFC accelerated repetitive transcranial magnetic stimulation for depression: a pilot randomized controlled study

BACKGROUND

This study aimed to evaluate a novel rTMS protocol for treatment-resistant depression (TRD), using an EEG 10-20 system guided dual-target accelerated approach of right lateral orbitofrontal cortex (lOFC) inhibition followed by left dorsolateral prefrontal cortex (dlPFC) excitation, along with comparing 20 Hz dlPFC accelerated TMS v. sham.

METHODS

Seventy five patients participated in this trial consisting of 20 sessions over 5 consecutive days comparing dual-site (cTBS of right lOFC followed sequentially by 20 Hz rTMS of left dlPFC), active control (sham right lOFC followed by 20 Hz rTMS of left dlPFC) and sham control (sham for both targets). Resting-state fMRI was acquired prior to and following treatment.

RESULTS

Hamilton Rating Scale for Depression (HRSD-24) scores were similarly significantly improved at 4 weeks in both the Dual and Single group relative to Sham. Planned comparisons immediately after treatment highlighted greater HRSD-24 clinical responders (Dual: 47.8% v. Single:18.2% v. Sham:4.3%, χ2 = 13.0, p = 0.002) and in PHQ-9 scores by day 5 in the Dual relative to Sham group. We further showed that accelerated 20 Hz stimulation targeting the left dlPFC (active control) is significantly better than sham at 4 weeks. Dual stimulation decreased lOFC-subcallosal cingulate functional connectivity. Greater baseline lOFC-thalamic connectivity predicted better therapeutic response, while decreased lOFC-thalamic connectivity correlated with better response.

CONCLUSIONS

Our novel accelerated dual TMS protocol shows rapid clinically relevant antidepressant efficacy which may be related to state-modulation. This study has implications for community-based accessible TMS without neuronavigation and rapid onset targeting suicidal ideation and accelerated discharge from hospital.

Neuro-cardiac-guided transcranial magnetic stimulation: Unveiling the modulatory effects of low-frequency and high-frequency stimulation on heart rate

Transcranial magnetic stimulation (TMS) is pivotal in the field of major depressive disorder treatment. Due to its unsatisfied response rate, an increasing number of researchers have turned their attention towards optimizing TMS site localization. Since the influence of TMS in reducing heart rate (HR) offers insights into its regulatory impact on the autonomic nervous system, a novel approach, called neurocardiac-guided TMS (NCG-TMS), has been proposed to pinpoint the brain region eliciting the maximal individual reduction in HR as a personalized optimal stimulation target. The present study intends to systematically explore the effects of stimulation frequency, left and right hemispheres, stimulation positions, and individual differences on HR modulation using the NCG-TMS method. In experiment 1, low-frequency TMS was administered to 30 subjects, and it was found that low-frequency NCG-TMS significantly downregulated HR, with more significant effects in the right hemisphere than in the left hemisphere and the prefrontal cortex than in other brain areas. In experiment 2, high-frequency NCG-TMS stimulation was administered to 30 subjects, showing that high-frequency NCG-TMS also downregulated HR and had the greatest modulatory effect in the right prefrontal region. Simultaneously, both experiments revealed sizeable individual variability in the optimal stimulation site, which in turn validated the feasibility of the NCG-TMS method. In conclusion, the present experiments independently replicated the effect of NCG-TMS, provided an effect of high-/low-frequency TMS stimulation to downregulate HR, and identified a right lateralization of the HR modulation effect.

Neuroimaging signatures and a deep learning modeling for early diagnosing and predicting non-pharmacological therapy success for subclinical depression comorbid sleep disorders in college students

Objective

College students with subclinical depression often experience sleep disturbances and are at high risk of developing major depressive disorder without early intervention. Clinical guidelines recommend non-pharmacotherapy as the primary option for subclinical depression with comorbid sleep disorders (sDSDs). However, the neuroimaging mechanisms and therapeutic responses associated with these treatments are poorly understood. Additionally, the lack of an early diagnosis and therapeutic effectiveness prediction model hampers the clinical promotion and acceptance of non-pharmacological interventions for subclinical depression.

Methods

This study involved pre- and post-treatment resting-state functional Magnetic Resonance Imaging (rs-fMRI) and clinical data from a multicenter, single-blind, randomized clinical trial. The trial included 114 first-episode, drug-naïve university students with subclinical depression and comorbid sleep disorders (sDSDs; Mean age=22.8±2.3 years; 73.7% female) and 93 healthy controls (HCs; Mean age=22.2±1.7 years; 63.4% female). We examined altered functional connectivity (FC) and brain network connective mode related to subregions of Default Mode Network (sub-DMN) using seed-to-voxel analysis before and after six weeks of non-pharmacological antidepressant treatment. Additionally, we developed an individualized diagnosing and therapeutic effect predicting model to realize early recognition of subclinical depression and provide objective suggestions to select non-pharmacological therapy by using the newly proposed Hierarchical Functional Brain Network (HFBN) with advanced deep learning algorithms within the transformer framework.

Results

Neuroimaging responses to non-pharmacologic treatments are characterized by alterations in functional connectivity (FC) and shifts in brain network connectivity patterns, particularly within the sub-DMN. At baseline, significantly increased FC was observed between the sub-DMN and both Executive Control Network (ECN) and Dorsal Attention Network (DAN). Following six weeks of non-pharmacologic intervention, connectivity patterns primarily shifted within the sub-DMN and ECN, with a predominant decrease in FCs. The HFBN model demonstrated superior performance over traditional deep learning models, accurately predicting therapeutic outcomes and diagnosing subclinical depression, achieving cumulative scores of 80.47% for sleep quality prediction and 84.67% for depression prediction, along with an overall diagnostic accuracy of 82.34%.

Conclusions

Two-scale neuroimaging signatures related to the sub-DMN underlying the antidepressant mechanisms of non-pharmacological treatments for subclinical depression. The HFBN model exhibited supreme capability in early diagnosing and predicting non-pharmacological treatment outcomes for subclinical depression, thereby promoting objective clinical psychological treatment decision-making.

Task-based default mode network connectivity predicts cognitive impairment and negative symptoms in first-episode schizophrenia

Individuals diagnosed with schizophrenia (SZ) demonstrate difficulty distinguishing between internally and externally generated stimuli. These aberrations in "source monitoring" have been theorized as contributing to symptoms of the disorder, including hallucinations and delusions. Altered connectivity within the default mode network (DMN) of the brain has been proposed as a mechanism through which discrimination between self-generated and externally generated events is disrupted. Source monitoring abnormalities in SZ have additionally been linked to impairments in selective attention and inhibitory processing, which are reliably observed via the N100 component of the event-related brain potential elicited during an auditory paired-stimulus paradigm. Given overlapping constructs associated with DMN connectivity and N100 in SZ, the present investigation evaluated relationships between these measures of disorder-related dysfunction and sought to clarify the nature of task-based DMN function in SZ. DMN connectivity and N100 measures were assessed using EEG recorded from SZ during their first episode of illness (N = 52) and demographically matched healthy comparison participants (N = 25). SZ demonstrated less evoked theta-band connectivity within DMN following presentation of pairs of identical auditory stimuli than HC. Greater DMN connectivity among SZ was associated with better performance on measures of sustained attention (p = .03) and working memory (p = .09), as well as lower severity of negative symptoms, though it was not predictive of N100 measures. Together, present findings provide EEG evidence of lower task-based connectivity among first-episode SZ, reflecting disruptions of DMN functions that support cognitive processes. Attentional processes captured by N100 appear to be supported by different neural mechanisms.

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.

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.

Characterizing PTSD symptom profiles in special forces operators and support personnel: Justification for a Precision Medicine Approach

Given the large number and diverse types of PTSD symptoms, examination of subtypes within the comprehensive PTSD criteria is necessary. This is especially true for subpopulations of active-duty service members such as specialized military units that undergo assessment and selection, receive extensive training, and have significant operational experience and trauma exposure. The current study identified PTSD subtypes in 16,284 U.S. Special Operations Forces (SOF) personnel who completed the Preservation of the Force and Family Needs Assessment Survey. Results identified a 4-profile solution. When stratifying the sample by occupation type (Operator vs Support), findings suggest that SOF Support personnel symptom presentations are primarily characterized by dysphoric and negative alterations in cognitions and mood symptoms. In contrast, SOF Operator personnel symptoms are best characterized by traditional profiles, consistent with the existing PTSD subtype literature. Results provide support for pursuing precision medicine approaches based on PTSD symptom profiles.

Enhanced Cognition and Modulation of Brain Connectivity in Mild Neurocognitive Disorder: The Promise of Transcranial Pulse Stimulation

Existing pharmacological treatments for mild neurocognitive disorder (NCD) offer limited effectiveness and adverse side effects. Transcranial pulse stimulation (TPS) utilizing ultrashort ultrasound pulses reaches deep brain regions and may circumvent conductivity issues associated with brain stimulation. This study addresses the gap in TPS research for mild NCD during a critical intervention period before irreversible cognitive degradation. Our objective was to explore the effectiveness and tolerability of TPS in older adults with mild NCD. In an open-label study, 17 older adults (including 10 females and 7 males) with mild NCD underwent TPS for two weeks with three sessions per week. Cognitive evaluations and fMRI scans were conducted pre- and post-intervention. The results indicated changes in functional connectivity in key brain regions, correlating with cognitive improvement at B = 0.087 (CI, 0.007-0.167; p = 0.038). However, cortical thickness measurements showed no significant differences. Here we show that TPS can enhance cognitive function within mild NCD. This proof-of-concept study suggests that TPS has potential as a non-invasive therapy used to attenuate cognitive decline, encouraging further investigation in larger randomized trials. The findings could influence clinical practice by introducing TPS as an adjunctive treatment option and potentially impact policy by promoting its inclusion in new treatment strategies for mild NCD.

rTMS as a Next Step in Antidepressant Nonresponders: A Randomized Comparison With Current Antidepressant Treatment Approaches

OBJECTIVE

Although repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression, little is known about the comparative effectiveness of rTMS and other treatment options, such as antidepressants. In this multicenter randomized controlled trial, rTMS was compared with the next pharmacological treatment step in patients with treatment-resistant depression.

METHODS

Patients with unipolar nonpsychotic depression (N=89) with an inadequate response to at least two treatment trials were randomized to treatment with rTMS or to a switch of antidepressants, both in combination with psychotherapy. Treatment duration was 8 weeks and consisted of either 25 high-frequency rTMS sessions to the left dorsolateral prefrontal cortex or a switch of antidepressant medication following the Dutch treatment algorithm. The primary outcome was change in depression severity based on the Hamilton Depression Rating Scale (HAM-D). Secondary outcomes were response and remission rates as well as change in symptom dimensions (anhedonia, anxiety, sleep, rumination, and cognitive reactivity). Finally, expectations regarding treatment were assessed.

RESULTS

rTMS resulted in a significantly larger reduction in depressive symptoms than medication, which was also reflected in higher response (37.5% vs. 14.6%) and remission (27.1% vs. 4.9%) rates. A larger decrease in symptoms of anxiety and anhedonia was observed after rTMS compared with a switch in antidepressants, and no difference from the medication group was seen for symptom reductions in rumination, cognitive reactivity, and sleep disorders. Expectations regarding treatment correlated with changes in HAM-D scores.

CONCLUSIONS

In a sample of patients with moderately treatment-resistant depression, rTMS was more effective in reducing depressive symptoms than a switch of antidepressant medication. In addition, the findings suggest that the choice of treatment may be guided by specific symptom dimensions.

Early efficacy of rTMS intervention at week 2 predicts subsequent responses at week 24 in schizophrenia in a randomized controlled trial

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique for modulating cortical activities and improving neural plasticity. Several studies investigated the effects of rTMS, etc., but the results are inconsistent. This study was designed to examine whether rTMS applied on the left dorsolateral prefrontal cortex (l-DLPFC) showed an effect on improving cognitive deficits in SZ and whether the early efficacy could predict efficacy at subsequent follow-ups. Cognitive ability was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) scale at baseline, weeks 2, 6, and 24. We found a significant interaction between time (weeks 0, 2, 6, and 24) and intervention on immediate memory and RBANS total scores (p ​= ​0.02 and p ​= ​0.04), indicating that both 10-Hz and 20-Hz rTMS stimulations had a delayed beneficial effect on immediate memory in SZ. Moreover, we found that 20-Hz rTMS stimulation, but not 10-Hz rTMS improved immediate memory at week 6 compared to the sham group (p ​= ​0.029). More importantly, improvements in immediate memory at week 2 were positively correlated with improvements at week 24 (β ​= ​0.461, t ​= ​3.322, p ​= ​0.002). Our study suggests that active rTMS was beneficial for cognitive deficits in patients with SZ. Furthermore, efficacy at week 2 could predict the subsequent efficacy at 24-week follow-up.

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

OBJECTIVE

Transcranial magnetic stimulation (TMS) can efficiently and robustly modulate synaptic plasticity, but little is known about how TMS affects functional connectivity (rs-fMRI). Accordingly, this project characterized TMS-induced rsFC changes in depressed patients who received 3 days of left prefrontal intermittent theta burst stimulation (iTBS).

METHODS

rs-fMRI was collected from 16 subjects before and after iTBS. Correlation matrices were constructed from the cleaned rs-fMRI data. Electric-field models were conducted and used to predict pre-post changes in rs-fMRI. Site by orientation heatmaps were created for vectors centered on the stimulation site and a control site (contralateral motor cortex).

RESULTS

For the stimulation site, there was a clear relationship between both site and coil orientation, and connectivity changes. As distance from the stimulation site increased, prediction accuracy decreased. Similarly, as eccentricity from the optimal orientation increased, prediction accuracy decreased. The systematic effects described above were not apparent in the heatmap centered on the control site.

CONCLUSIONS

These results suggest that rs-fMRI following iTBS changes systematically as a function of the distribution of electrical energy delivered from the TMS pulse, as represented by the e-field model.

SIGNIFICANCE

This finding lays the groundwork for future studies to individualize TMS targeting based on how predicted rs-fMRI changes might impact psychiatric symptoms.

Childhood maltreatment and transdiagnostic connectivity of the default-mode network: The importance of duration of exposure

Childhood maltreatment (CM) has been demonstrated to be associated with changes in resting-state functional connectivity of the default-mode network (DMN) across various mental disorders. Growing evidence regarding severity of CM is available but transdiagnostic research considering the role of both severity and duration of CM for DMN connectivity at rest is still scarce. We recruited a sample of participants with varying levels of CM suffering from three disorders in which a history of CM is frequently found, namely, post-traumatic stress disorder, major depressive disorder, or somatic symptom disorder, as well as healthy volunteers to examine DMN connectivity in a transdiagnostic sample. We expected to find changes in inter-network connectivity of the DMN related to higher self-reported levels of CM severity and duration. Resting-state functional magnetic resonance imaging scans of 128 participants were analyzed focusing on regions of interest (ROI-to-ROI approach) and whole-brain Seed-to-Voxel analyses with retrospectively assessed CM as predictor in a regression model. Changes in connectivity between nodes of the DMN and the visual network were identified to be associated with CM duration but not severity. CM duration showed associations with increased connectivity of the precuneus and visual regions, as well as sensory-motor regions. The observed changes in connectivity could be interpreted as an impairment of information transfer between the transmodal DMN and unimodal visual and sensory-motor regions with impairment increasing with duration of exposure to CM.

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.

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.

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

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

Increased anti-correlation between the left dorsolateral prefrontal cortex and the default mode network following Stanford Neuromodulation Therapy (SNT): analysis of a double-blinded, randomized, sham-controlled trial

SNT is a high-dose accelerated intermittent theta-burst stimulation (iTBS) protocol coupled with functional-connectivity-guided targeting that is an efficacious and rapid-acting therapy for treatment-resistant depression (TRD). We used resting-state functional MRI (fMRI) data from a double-blinded sham-controlled randomized controlled trial1 to reveal the neural correlates of SNT-based symptom improvement. Neurobehavioral data were acquired at baseline, post-treatment, and 1-month follow-up. Our primary analytic objective was to investigate changes in seed-based functional connectivity (FC) following SNT and hypothesized that FC changes between the treatment target and the sgACC, DMN, and CEN would ensue following active SNT but not sham. We also investigated the durability of post-treatment observed FC changes at a 1-month follow-up. Study participants included transcranial magnetic stimulation (TMS)-naive adults with a primary diagnosis of moderate-to-severe TRD. Fifty-four participants were screened, 32 were randomized, and 29 received active or sham SNT. An additional 5 participants were excluded due to imaging artifacts, resulting in 12 participants per group (Sham: 5F; SNT: 5F). Although we did not observe any significant group × time effects on the FC between the individualized stimulation target (L-DLPFC) and the CEN or sgACC, we report an increased magnitude of negative FC between the target site and the DMN post-treatment in the active as compared to sham SNT group. This change in FC was sustained at the 1-month follow-up. Further, the degree of change in FC was correlated with improvements in depressive symptoms. Our results provide initial evidence for the putative changes in the functional organization of the brain post-SNT.

Behavioral Activation and Brain Network Changes in Depression

Behavioral activation (BA) is a well-established method of evidence-based treatment for depression. There are clear links between the neural mechanisms underlying reward processing and BA treatment for depressive symptoms, including anhedonia; however, integrated interpretations of these two domains are lacking. Here we examine brain imaging studies involving BA treatments to investigate how changes in brain networks, including the reward networks, mediate the therapeutic effects of BA, and whether brain circuits are predictors of BA treatment responses. Increased activation of the prefrontal and subcortical regions associated with reward processing has been reported after BA treatment. Activation of these regions improves anhedonia. Conversely, some studies have found decreased activation of prefrontal regions after BA treatment in response to cognitive control stimuli in sad contexts, which indicates that the therapeutic mechanism of BA may involve disengagement from negative or sad contexts. Furthermore, the decrease in resting-state functional connectivity of the default-mode network after BA treatment appears to facilitate the ability to counteract depressive rumination, thereby promoting enjoyable and valuable activities. Conflicting results suggest that an intact neural response to rewards or defective reward functioning is predictive of the efficacy of BA treatments. Increasing the benefits of BA treatments requires identification of the unique individual characteristics determining which of these conflicting findings are relevant for the personalized treatment of each individual with depression.

Default Mode Network Detection using EEG in Real-time

Mental health disorders affect countless people worldwide and present a major challenge for mental health services, which are struggling with the demand on a global scale. Recent studies have indicated that activity of the brain's Default Mode Network (DMN) could prove insightful in monitoring patient recovery from depression and has been used as a therapeutic target itself. An opportunity exists to replicate recent therapeutic protocols targeting DMN connectivity via functional magnetic resonance imaging using the more economically scalable modality of electroencephalogram (EEG). The aim of this work was to validate the accuracy of real-time DMN detection methods applied to EEG data, using a publicly available dataset. Using a Hidden Markov Model to identify a 12-state resting-state network, this work achieved an overall DMN detection accuracy of 95%. Furthermore, the model was able to achieve a correlation of 0.617 between the baseline and calculated DMN fractional occupancy. These results demonstrate the ability of real-time analysis to effectively identify the DMN through EEG data providing an avenue for further applications that monitor and treat mental health disorders.

Functional Connectivity of Salience Network Predicts Treatment Outcome for rTMS in Mild Cognitive Impairment

Repetitive transcranial magnetic stimulation (rTMS) has been proved a potential therapeutic approach for improving the cognitive performance of patients with mild cognitive impairment (MCI). However, no biomarker is available for identifying who is most likely to respond to rTMS. The purpose of this study was to demonstrate that cognitive improvement after rTMS may be associated with functional connectivity of salience network at baseline. Resting-state functional magnetic resonance imaging (rs-fMRI) data of fifty-three MCI patients were collected before a 10-day of rTMS treatment. Multivoxel pattern analysis was applied to realize the classification of the MCI patients responded or not to rTMS treatment, and the prediction to the cognitive scores. The analysis yielded a significant overall accuracy of 84.91% (90.00% sensitivity, 78.26% specificity). Right anterior cingulate cortex contributed most to the classification. Besides, regression analysis also showed the predictive value of salience network to the changes of cognitive performance. Our study demonstrated that the functional connectivity of salience network is predictive of treatment response to rTMS.

Trajectories of improvement with repetitive transcranial magnetic stimulation for treatment-resistant major depression in the BRIGhTMIND trial

Repetitive transcranial magnetic stimulation (rTMS) is an established non-invasive brain stimulation treatment for major depressive disorder, but there is marked inter-individual variability in response. Using latent class growth analysis with session-by-session patient global impression ratings from the recently completed BRIGhTMIND trial, we identified five distinct classes of improvement trajectory during a 20-session treatment course. This included a substantial class of patients noticing delayed onset of improvement. Contrary to prior expectations, members of a class characterised by early and continued improvement showed greatest inter-session variability in stimulated location. By relating target locations and inter-session variability to a well-studied atlas, we estimated an average of 3.0 brain networks were stimulated across the treatment course in this group, compared to 1.1 in a group that reported symptom worsening (p < 0.001, d = 0.893). If confirmed, this would suggest that deliberate targeting of multiple brain networks could be beneficial to rTMS outcomes.

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.

Modulation of habenular and nucleus accumbens functional connectivity by ketamine in major depression

INTRODUCTION

Major depressive disorder (MDD) is associated with dysfunctional reward processing, which involves functional circuitry of the habenula (Hb) and nucleus accumbens (NAc). Since ketamine elicits rapid antidepressant and antianhedonic effects in MDD, this study sought to investigate how serial ketamine infusion (SKI) treatment modulates static and dynamic functional connectivity (FC) in Hb and NAc functional networks.

METHODS

MDD participants (n = 58, mean age = 40.7 years, female = 28) received four ketamine infusions (0.5 mg/kg) 2-3 times weekly. Resting-state functional magnetic resonance imaging (fMRI) scans and clinical assessments were collected at baseline and 24 h post-SKI. Static FC (sFC) and dynamic FC variability (dFCv) were calculated from left and right Hb and NAc seeds to all other brain regions. Changes in FC pre-to-post SKI, and correlations with changes with mood and anhedonia were examined. Comparisons of FC between patients and healthy controls (HC) at baseline (n = 55, mean age = 32.6, female = 31), and between HC assessed twice (n = 16) were conducted as follow-up analyses.

RESULTS

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 mood ratings. 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. No differences were observed between HC at baseline or over time.

CONCLUSION

Subanesthetic ketamine modulates functional pathways linking the Hb and NAc with visual, parietal, and cerebellar regions in MDD. Overlapping effects between Hb and NAc functional systems were associated with ketamine's therapeutic response.

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.

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.

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.

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.