Default mode network mechanisms of transcranial magnetic stimulation in depression

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Discriminative functional connectivity signature of cocaine use disorder links to rTMS treatment response

Cocaine use disorder (CUD) is prevalent, and repetitive transcranial magnetic stimulation (rTMS) shows promise in reducing cravings. However, the association between a consistent CUD-specific functional connectivity signature and treatment response remains unclear. Here we identify a validated functional connectivity signature from functional magnetic resonance imaging to discriminate CUD, with successful independent replication. We found increased connectivity within the visual and dorsal attention networks and between the frontoparietal control and ventral attention networks, alongside reduced connectivity between the default mode and limbic networks in patients with CUD. These connections were associated with drug use history and cognitive impairments. Using data from a randomized clinical trial, we also established the prognostic value of these functional connectivities for rTMS treatment outcomes in CUD, especially involving the frontoparietal control and default mode networks. Our findings reveal insights into the neurobiological mechanisms of CUD and link functional connectivity biomarkers with rTMS treatment response, offering potential targets for future therapeutic development.

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.