Preliminary differences in resting state MEG functional connectivity pre- and post-ketamine in major depressive disorder

Ketamine and rapid antidepressant action: new treatments and novel synaptic signaling mechanisms

Ketamine is an open channel blocker of ionotropic glutamatergic N-Methyl-D-Aspartate (NMDA) receptors. The discovery of its rapid antidepressant effects in patients with depression and treatment-resistant depression fostered novel effective treatments for mood disorders. This discovery not only provided new insight into the neurobiology of mood disorders but also uncovered fundamental synaptic plasticity mechanisms that underlie its treatment. In this review, we discuss key clinical aspects of ketamine's effect as a rapidly acting antidepressant, synaptic and circuit mechanisms underlying its action, as well as how these novel perspectives in clinical practice and synapse biology form a road map for future studies aimed at more effective treatments for neuropsychiatric disorders.

Brain-based correlates of antidepressant response to ketamine: a comprehensive systematic review of neuroimaging studies

Ketamine is an effective antidepressant, but there is substantial variability in patient response and the precise mechanism of action is unclear. Neuroimaging can provide predictive and mechanistic insights, but findings are limited by small sample sizes. This systematic review covers neuroimaging studies investigating baseline (pre-treatment) and longitudinal (post-treatment) biomarkers of responses to ketamine. All modalities were included. We performed searches of five electronic databases (from inception to April 26, 2022). 69 studies were included (with 1751 participants). There was substantial methodological heterogeneity and no well replicated biomarker. However, we found convergence across some significant results, particularly in longitudinal biomarkers. Response to ketamine was associated with post-treatment increases in gamma power in frontoparietal regions in electrophysiological studies, post-treatment increases in functional connectivity within the prefrontal cortex, and post-treatment increases in the functional activation of the striatum. Although a well replicated neuroimaging biomarker of ketamine response was not identified, there are biomarkers that warrant further investigation.

Biomarkers of ketamine's antidepressant effect: An umbrella review

Ketamine is a NMDA receptor antagonist that has a rapid acting antidepressant effect with high efficacy in treatment-resistant patients. Ketamine is a beneficial antidepressant for many individuals with depression, but not all of the patients respond, and some even exhibit symptom deterioration. The discovery of repeatable and mechanistically relevant biomarkers would address a major gap in treatment response prediction. Numerous potential peripheral biomarkers have been reported, but their current utility is unclear. We conducted an umbrella review to evaluate the biomarkers of ketamine's antidepressant effect in individuals with depression. PubMed and copus were searched using terms appropriate to each area of research, from their inception until July 2022. Five systematic reviews and meta analyses including 108 studies with 4912 participants were included. Blood-based and neuroimaging biomarkers were investigated. The results of this review indicate that ketamine can produce an anti-inflammatory effect and decrease at least one inflammatory marker following administration. Data from neuroimaging studies demonstrated that the cingulate cortex is the key locus of ketamine's action. The majority of the blood-based, neuroimaging, and neurophysiological investigations reviewed herein indicate ketamine induced normalization of major depressive disorder pathogenesis via synaptic plasticity and functional connectivity. Currently, no biomarker/biosignature is sufficiently validated for clinical utility, but several are promising. Now that ketamine is more widely available, biomarker discovery and replication should be attempted in larger, real-world populations.

Association between cognitive impairments and aberrant dynamism of overlapping brain sub-networks in unmedicated major depressive disorder: A resting-state MEG study

OBJECTIVE

Little is known about the pathogenesis underlying cognitive impairment in major depressive disorder (MDD). We aimed to explore the mechanisms of cognitive impairments among patients with MDD by investigating the dynamics of overlapping brain sub-networks.

METHODS

Forty unmedicated patients with MDD and 28 healthy controls (HC) were enrolled in this study. Cognitive function was measured using the Chinese versions of MATRICS Consensus Cognitive Battery (MCCB). All participants were scanned using a whole-head resting-state magnetoencephalography (MEG) machine. The dynamism of neural sub-networks was analyzed based on the detection of overlapping communities in five frequency bands of oscillatory brain signals.

RESULTS

MDD demonstrated poorer cognitive performance in six domains compared to HC. The difference in community detection (functional integration mode) in MDD was frequency-dependent. MDD showed significantly decreased community dynamics in all frequency bands compared to HC. Specifically, differences in the visual network (VN) and default mode network (DMN) were detected in all frequency bands, differences in the cognitive control network (CCN) were detected in the alpha2 and beta frequency bands, and differences in the bilateral limbic network (BLN) were only detected in the beta frequency band. Moreover, community dynamics in the alpha2 frequency band were positively correlated with verbal learning and reasoning problem solving abilities in MDD.

CONCLUSIONS

Our study found that decreasing in the dynamics of overlapping sub-networks may differ by frequency bands. The aberrant dynamics of overlapping neural sub-networks revealed by frequency-specific MEG signals may provide new information on the mechanism of cognitive impairments that result from MDD.

Anterior default mode network and posterior insular connectivity is predictive of depressive symptom reduction following serial ketamine infusion

BACKGROUND

Ketamine is a rapidly-acting antidepressant treatment with robust response rates. Previous studies have reported that serial ketamine therapy modulates resting state functional connectivity in several large-scale networks, though it remains unknown whether variations in brain structure, function, and connectivity impact subsequent treatment success. We used a data-driven approach to determine whether pretreatment multimodal neuroimaging measures predict changes along symptom dimensions of depression following serial ketamine infusion.

METHODS

Patients with depression (n = 60) received structural, resting state functional, and diffusion MRI scans before treatment. Depressive symptoms were assessed using the 17-item Hamilton Depression Rating Scale (HDRS-17), the Inventory of Depressive Symptomatology (IDS-C), and the Rumination Response Scale (RRS) before and 24 h after patients received four (0.5 mg/kg) infusions of racemic ketamine over 2 weeks. Nineteen unaffected controls were assessed at similar timepoints. Random forest regression models predicted symptom changes using pretreatment multimodal neuroimaging and demographic measures.

RESULTS

Two HDRS-17 subscales, the HDRS-6 and core mood and anhedonia (CMA) symptoms, and the RRS: reflection (RRSR) scale were predicted significantly with 19, 27, and 1% variance explained, respectively. Increased right medial prefrontal cortex/anterior cingulate and posterior insula (PoI) and lower kurtosis of the superior longitudinal fasciculus predicted reduced HDRS-6 and CMA symptoms following treatment. RRSR change was predicted by global connectivity of the left posterior cingulate, left insula, and right superior parietal lobule.

CONCLUSIONS

Our findings support that connectivity of the anterior default mode network and PoI may serve as potential biomarkers of antidepressant outcomes for core depressive symptoms.

Intrinsic Connectivity Networks of Glutamate-Mediated Antidepressant Response: A Neuroimaging Review

Conventional monoamine-based pharmacotherapy, considered the first-line treatment for major depressive disorder (MDD), has several challenges, including high rates of non-response. To address these challenges, preclinical and clinical studies have sought to characterize antidepressant response through monoamine-independent mechanisms. One striking example is glutamate, the brain's foremost excitatory neurotransmitter: since the 1990s, studies have consistently reported altered levels of glutamate in MDD, as well as antidepressant effects following molecular targeting of glutamatergic receptors. Therapeutically, this has led to advances in the discovery, testing, and clinical application of a wide array of glutamatergic agents, particularly ketamine. Notably, ketamine has been demonstrated to rapidly improve mood symptoms, unlike monoamine-based interventions, and the neurobiological basis behind this rapid antidepressant response is under active investigation. Advances in brain imaging techniques, including functional magnetic resonance imaging, magnetic resonance spectroscopy, and positron emission tomography, enable the identification of the brain network-based characteristics distinguishing rapid glutamatergic modulation from the effect of slow-acting conventional monoamine-based pharmacology. Here, we review brain imaging studies that examine brain connectivity features associated with rapid antidepressant response in MDD patients treated with glutamatergic pharmacotherapies in contrast with patients treated with slow-acting monoamine-based treatments. Trends in recent brain imaging literature suggest that the activity of brain regions is organized into coherent functionally distinct networks, termed intrinsic connectivity networks (ICNs). We provide an overview of major ICNs implicated in depression and explore how treatment response following glutamatergic modulation alters functional connectivity of limbic, cognitive, and executive nodes within ICNs, with well-characterized anti-anhedonic effects and the enhancement of "top-down" executive control. Alterations within and between the core ICNs could potentially exert downstream effects on the nodes within other brain networks of relevance to MDD that are structurally and functionally interconnected through glutamatergic synapses. Understanding similarities and differences in brain ICNs features underlying treatment response will positively impact the trajectory and outcomes for adults suffering from MDD and will facilitate the development of biomarkers to enable glutamate-based precision therapeutics.

Biomarkers of ketamine's antidepressant effect: a clinical review of genetics, functional connectivity, and neurophysiology

Major depressive disorder (MDD) is one of the leading causes of morbidity and all-cause mortality (including suicide) worldwide, and, unfortunately, first-line monoaminergic antidepressants and evidence-based psychotherapies are not effective for all patients. Subanesthetic doses of the N-methyl-D-aspartate receptor antagonists and glutamate modulators ketamine and S-ketamine have rapid and robust antidepressant efficacy in such treatment-resistant depressed patients (TRD). Yet, as with all antidepressant treatments including electroconvulsive therapy (ECT), not all TRD patients adequately respond, and we are presently unable to a priori predict who will respond or not respond to ketamine. Therefore, antidepressant treatment response biomarkers to ketamine have been a major focus of research for over a decade. In this article, we review the evidence in support of treatment response biomarkers, with a particular focus on genetics, functional magnetic resonance imaging, and neurophysiological studies, i.e. electroencephalography and magnetoencephalography. The studies outlined here lay the groundwork for replication and dissemination.

The anterior cingulate cortex as a key locus of ketamine's antidepressant action

The subdivisions of the anterior cingulate cortex (ACC) - including subgenual, perigenual and dorsal zones - are implicated in the etiology, pathogenesis and treatment of major depression. We review an emerging body of evidence which suggests that changes in ACC activity are critically important in mediating the antidepressant effects of ketamine, the prototypical member of an emerging class of rapidly acting antidepressants. Infusions of ketamine induce acute (over minutes) and post-acute (over hours to days) modulations in subgenual and perigenual activity, and importantly, these changes can correlate with antidepressant efficacy. The subgenual and dorsal zones of the ACC have been specifically implicated in ketamine's anti-anhedonic effects. We emphasize the synergistic relationship between neuroimaging studies in humans and brain manipulations in animals to understand the causal relationship between changes in brain activity and therapeutic efficacy. We conclude with circuit-based perspectives on ketamine's action: first, related to ACC function in a central network mediating affective pain, and second, related to its role as the anterior node of the default mode network.

Fronto-limbic neuroimaging biomarkers for diagnosis and prediction of treatment responses in major depressive disorder

The neuroimaging is an important tool for understanding the biomarkers and predicting treatment responses in major depressive disorder (MDD). The potential biomarkers and prediction of treatment response in MDD will be addressed in the review article. The brain regions of cognitive control and emotion regulation, such as the frontal and limbic regions, might represent the potential targets for MDD biomarkers. The potential targets of frontal lobes might include anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC). For the limbic system, hippocampus and amygdala might be the potentially promising targets for MDD. The potential targets of fronto-limbic regions have been found in the studies of several major neuroimaging modalities, such as the magnetic resonance imaging, near-infrared spectroscopy, electroencephalography, positron emission tomography, and single-photon emission computed tomography. Additional regions, such as brainstem and midbrain, might also play a part in the MDD biomarkers. For the prediction of treatment response, the gray matter volumes, white matter tracts, functional representations and receptor bindings of ACC, DLPFC, OFC, amygdala, and hippocampus might play a role in the prediction of antidepressant responses in MDD. For the response prediction of psychotherapies, the fronto-limbic, reward regions, and insula will be the potential targets. For the repetitive transcranial magnetic stimulation, the DLPFC, ACC, limbic, and visuospatial regions might represent the predictive targets for treatment. The neuroimaging targets of MDD might be focused in the fronto-limbic regions. However, the neuroimaging targets for the prediction of treatment responses might be inconclusive and beyond the fronto-limbic regions.

Magnetoencephalography: physics, techniques, and applications in the basic and clinical neurosciences

Magnetoencephalography (MEG) is a technique used to measure the magnetic fields generated from neuronal activity in the brain. MEG has a high temporal resolution on the order of milliseconds and provides a more direct measure of brain activity when compared with hemodynamic-based neuroimaging methods such as magnetic resonance imaging and positron emission tomography. The current review focuses on basic features of MEG such as the instrumentation and the physics that are integral to the signals that can be measured, and the principles of source localization techniques, particularly the physics of beamforming and the techniques that are used to localize the signal of interest. In addition, we review several metrics that can be used to assess functional coupling in MEG and describe the advantages and disadvantages of each approach. Lastly, we discuss the current and future applications of MEG.

Altered EEG Oscillatory Brain Networks During Music-Listening in Major Depression

To examine the electrophysiological underpinnings of the functional networks involved in music listening, previous approaches based on spatial independent component analysis (ICA) have recently been used to ongoing electroencephalography (EEG) and magnetoencephalography (MEG). However, those studies focused on healthy subjects, and failed to examine the group-level comparisons during music listening. Here, we combined group-level spatial Fourier ICA with acoustic feature extraction, to enable group comparisons in frequency-specific brain networks of musical feature processing. It was then applied to healthy subjects and subjects with major depressive disorder (MDD). The music-induced oscillatory brain patterns were determined by permutation correlation analysis between individual time courses of Fourier-ICA components and musical features. We found that (1) three components, including a beta sensorimotor network, a beta auditory network and an alpha medial visual network, were involved in music processing among most healthy subjects; and that (2) one alpha lateral component located in the left angular gyrus was engaged in music perception in most individuals with MDD. The proposed method allowed the statistical group comparison, and we found that: (1) the alpha lateral component was activated more strongly in healthy subjects than in the MDD individuals, and that (2) the derived frequency-dependent networks of musical feature processing seemed to be altered in MDD participants compared to healthy subjects. The proposed pipeline appears to be valuable for studying disrupted brain oscillations in psychiatric disorders during naturalistic paradigms.

The neurophysiology of ketamine: an integrative review

The drug ketamine has been extensively studied due to its use in anaesthesia, as a model of psychosis and, most recently, its antidepressant properties. Understanding the physiology of ketamine is complex due to its rich pharmacology with multiple potential sites at clinically relevant doses. In this review of the neurophysiology of ketamine, we focus on the acute effects of ketamine in the resting brain. We ascend through spatial scales starting with a complete review of the pharmacology of ketamine and then cover its effects on in vitro and in vivo electrophysiology. We then summarise and critically evaluate studies using EEG/MEG and neuroimaging measures (MRI and PET), integrating across scales where possible. While a complicated and, at times, confusing picture of ketamine’s effects are revealed, we stress that much of this might be caused by use of different species, doses, and analytical methodologies and suggest strategies that future work could use to answer these problems.

Neurobiological biomarkers of response to ketamine

As a field, psychiatry is undergoing an exciting paradigm shift toward early identification and intervention that will likely minimize both the burden associated with severe mental illnesses as well as their duration. In this context, the rapid-acting antidepressant ketamine has revolutionized our understanding of antidepressant response and greatly expanded the pharmacologic armamentarium for treatment-resistant depression. Efforts to characterize biomarkers of ketamine response support a growing emphasis on early identification, which would allow clinicians to identify biologically enriched subgroups with treatment-resistant depression who are more likely to benefit from ketamine therapy. This chapter presents a broad overview of a range of translational biomarkers, including those drawn from imaging and electrophysiological studies, sleep and circadian rhythms, and HPA axis/endocrine function as well as metabolic, immune, (epi)genetic, and neurotrophic biomarkers related to ketamine response. Ketamine's unique, rapid-acting properties may serve as a model to explore a whole new class of novel rapid-acting treatments with the potential to revolutionize drug development and discovery. However, it should be noted that although several of the biomarkers reviewed here provide promising insights into ketamine's mechanism of action, most studies have focused on acute rather than longer-term antidepressant effects and, at present, none of the biomarkers are ready for clinical use.

Chronic stress pathology and ketamine-induced alterations in functional connectivity in major depressive disorder: An abridged review of the clinical evidence

A paradigm shift in the conceptualization of the neurobiology of depression and the serendipitous discovery of ketamine's rapid-acting antidepressant (RAAD) effects has ushered in a new era of innovative research and novel drug development. Since the initial discovery of ketamine's RAAD effects, multiple studies have supported its short-term efficacy for fast-tracked improvements in treatment-resistant depression. Evidence from MRI studies have repeatedly demonstrated functional connectivity alterations in stress- and trauma-related disorders suggesting this may be a viable biomarker of chronic stress pathology (CSP). Human mechanistic studies further support this by coupling functional connectivity to ketamine's RAAD effects including connectivity to glutamate neurotransmission, ketamine to normalized connectivity, and these advantageous normalizations to symptom improvement/ketamine response. This review provides an abridged discussion of the suspected neurobiological underpinnings of ketamine's RAAD effects, highlighting ketamine-induced alterations in prefrontal, striatal, and anterior cingulate cortex functional connectivity in major depressive disorder. We present a model of CSP underscoring the role of synaptic loss and dysconnectivity and discuss how ketamine may be used both as (1) a treatment to restore and normalize these stress-induced neural alterations and (2) a tool to study potential biomarkers of CSP and treatment response. We conclude by noting challenges and future directions including heterogeneity, sex differences, the role of early life stress, and the need for proliferation of new methods, paradigms, and tools that will optimize signal and allow analyses at different levels of complexity, according to the needs of the question at hand, perhaps by thinking hierarchically about both clinical and biological phenotypes.

The Effect of Ketamine on Electrophysiological Connectivity in Major Depressive Disorder

Major depressive disorder (MDD) is highly prevalent and frequently disabling. Only about 30% of patients respond to a first-line antidepressant treatment, and around 30% of patients are classified as "treatment-resistant" after failing to respond to multiple adequate trials. While most antidepressants target monoaminergic targets, ketamine is an N-methyl-D-aspartate (NMDA) antagonist that has shown rapid antidepressant effects when delivered intravenously or intranasally. While there is evidence that ketamine exerts its effects via enhanced α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) throughput, its mechanism for relieving depressive symptoms is largely unknown. This study acquired resting-state magnetoencephalography (MEG) recordings after both ketamine and placebo infusions and investigated functional connectivity using a multilayer amplitude-amplitude correlation technique spanning the canonical frequency bands. Twenty-four healthy volunteers (HVs) and 27 unmedicated participants with MDD took part in a double-blind, placebo-controlled, crossover trial of 0.5 mg/kg IV ketamine. Order of infusion was randomized, and participants crossed over to receive the second infusion after two weeks. The results indicated widespread ketamine-induced reductions in connectivity in the alpha and beta bands that did not correlate with magnitude of antidepressant response. In contrast, the magnitude of ketamine's antidepressant effects in MDD participants was associated with cross-frequency connectivity for delta-alpha and delta-gamma bands, with HVs and ketamine non-responders showing connectivity decreases post-ketamine and ketamine responders demonstrating small increases in connectivity. These results may indicate functional subtypes of MDD and also suggest that neural responses to ketamine are fundamentally different between responders and non-responders.

Hyperactive frontolimbic and frontocentral resting-state gamma connectivity in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a system-level disorder affecting multiple functionally integrated cerebral networks. Nevertheless, their temporospatial organization and potential disturbance remain mostly unknown. The present report tested the hypothesis that deficient temporospatial network organization separates MDD and healthy controls (HC), and is linked to symptom severity of the disorder.

METHODS

Eyes-closed resting-state magnetoencephalographic (MEG) recordings were obtained from twenty-two MDD and twenty-two HC subjects. Beamforming source localization and functional connectivity analysis were applied to identify frequency-specific network interactions. Then, a novel virtual cortical resection approach was used to pinpoint putatively critical network controllers, accounting for aberrant cerebral connectivity patterns in MDD.

RESULTS

We found significantly elevated frontolimbic and frontocentral connectivity mediated by gamma (30-48 Hz) activity in MDD versus HC, and the right amygdala was the key differential network controller accounting for aberrant cerebral connectivity patterns in MDD. Furthermore, this frontolimbic and frontocentral gamma-band hyper-connectivity was positively correlated with depression severity.

LIMITATIONS

The overall sample size was small, and we found significant effects in the deep limbic regions with resting-state MEG, the reliability of which was difficult to corroborate further.

CONCLUSIONS

Overall, these findings support a notion that the right amygdala critically controls the exaggerated gamma-band frontolimbic and frontocentral connectivity in MDD during the resting-state condition, which potentially constitutes pre-established aberrant pathways during task processing and contributes to MDD pathology.

Promising Neuroimaging Biomarkers in Depression

The neuroimaging has been applied in the study of pathophysiology in major depressive disorder (MDD). In this review article, several kinds of methodologies of neuroimaging would be discussed to summarize the promising biomarkers in MDD. For the magnetic resonance imaging (MRI) and magnetoencephalography field, the literature review showed the potentially promising roles of frontal lobes, such as anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC). In addition, the limbic regions, such as hippocampus and amygdala, might be the potentially promising biomarkers for MDD. The structures and functions of ACC, DLPFC, OFC, amygdala and hippocampus might be confirmed as the biomarkers for the prediction of antidepressant treatment responses and for the pathophysiology of MDD. The functions of cognitive control and emotion regulation of these regions might be crucial for the establishment of biomarkers. The near-infrared spectroscopy studies demonstrated that blood flow in the frontal lobe, such as the DLPFC and OFC, might be the biomarkers for the field of near-infrared spectroscopy. The electroencephalography also supported the promising role of frontal regions, such as the ACC, DLPFC and OFC in the biomarker exploration, especially for the sleep electroencephalogram to detect biomarkers in MDD. The positron emission tomography (PET) and single-photon emission computed tomography (SPECT) in MDD demonstrated the promising biomarkers for the frontal and limbic regions, such as ACC, DLPFC and amygdala. However, additional findings in brainstem and midbrain were also found in PET and SPECT. The promising neuroimaging biomarkers of MDD seemed focused in the fronto-limbic regions.

Combination therapy with transcranial magnetic stimulation and ketamine for treatment-resistant depression: A long-term retrospective review of clinical use

Background

Both transcranial magnetic stimulation (TMS) and infused ketamine are recognized treatments for patients suffering from major depressive disorder (MDD). A novel therapy named combination TMS with ketamine (CTK) is introduced. This retrospective review examined the safety and clinical benefits of CTK in patients suffering from treatment-resistant depression (TRD) during the routine practice of psychiatry in a private clinic.

Methods

TRD patients (N = 28) received a coincident application of high-output TMS (30 minutes) with biomarker-determined ketamine infusions (20 minutes). Frequency of treatment was dependent on patient responsiveness (10–30 sessions). Clinical global impression (CGI) data was collected pre- and post-treatment and then two years later.

Results

The mean reduction in CGI severity for the patient group following CTK was 4.46 ± 0.54 at a 99% confidence interval and was deemed statistically significant using a paired t-test (α = 0.01, t = 22.81 p < 0.0001). This reduction was sustained for two years following treatment completion and this remission was deemed statistically significant by a second paired t-test (α = 0.01, t = 27.36, p < 0.0001).

Limitations

Retrospective review of a limited number of patients undergoing CTK in a clinical practice.

Conclusions

This clinical review indicated that CTK is an effective, long-term therapy (after two years) and can be used for TRD patients. The coincident administration of ketamine allowed for higher TMS intensities than otherwise would be tolerated by patients. Further studies for optimization of CTK are warranted.

Ketamine-Associated Brain Changes: A Review of the Neuroimaging Literature

Major depressive disorder (MDD) is one of the most prevalent conditions in psychiatry. Patients who do not respond to traditional monoaminergic antidepressant treatments have an especially difficult-to-treat type of MDD termed treatment-resistant depression. Subanesthetic doses of ketamine-a glutamatergic modulator-have shown great promise for rapidly treating patients with the most severe forms of depression. As such, ketamine represents a promising probe for understanding the pathophysiology of depression and treatment response. Through neuroimaging, ketamine's mechanism may be elucidated in humans. Here, we review 47 articles of ketamine's effects as revealed by neuroimaging studies. Some important brain areas emerge, especially the subgenual anterior cingulate cortex. Furthermore, ketamine may decrease the ability to self-monitor, may increase emotional blunting, and may increase activity in reward processing. Further studies are needed, however, to elucidate ketamine's mechanism of antidepressant action.

Personalized repetitive transcranial magnetic stimulation temporarily alters default mode network in healthy subjects

High frequency repetitive transcranial magnetic stimulation (HF-rTMS) delivered to the left dorsolateral prefrontal cortex (DLPFC) is an effective treatment option for treatment resistant depression. However, the underlying mechanisms of a full session of HF-rTMS in healthy volunteers have not yet been described. Here we investigated, with a personalized selection of DLPFC stimulation sites, the effects driven by HF-rTMS in healthy volunteers (n = 23) over the default mode network (DMN) in multiple time windows. After a complete 10 Hz rTMS (3000 pulses) session, we observe a decrease of functional connectivity between the DMN and the subgenual Anterior Cingulate Cortex (sgACC), as well as the ventral striatum (vStr). A negative correlation between the magnitude of this decrease in the right sgACC and the harm avoidance domain measure from the Temperament and Character Inventory was observed. Moreover, we identify that coupling strength of right vStr with the DMN post-stimulation was proportional to a decrease in self-reports of negative mood from the Positive and Negative Affect Schedule. This shows HF-rTMS attenuates perception of negative mood in healthy recipients in agreement with the expected effects in patients. Our study, by using a personalized selection of DLPFC stimulation sites, contributes understanding the effects of a full session of rTMS approved for clinical use in depression over related brain regions in healthy volunteers.

Leveraging Neuroplasticity to Enhance Adaptive Learning: The Potential for Synergistic Somatic-Behavioral Treatment Combinations to Improve Clinical Outcomes in Depression

Until recently, therapeutic development in psychiatry was targeted solely toward symptom reduction. While this is a worthwhile goal, it has yielded little progress in improved therapeutics in the last several decades in the field of mood disorders. Recent advancements in our understanding of pathophysiology suggests that an impairment of neuroplasticity may be a critical part of the development of neuropsychiatric disorders. Interventions that enhance or modulate neuroplasticity often reduce depressive symptoms when applied as stand-alone treatments. Unfortunately, when treatments are discontinued, the disease state often returns as patients relapse. However, treatments that enhance or modulate plasticity not only reduce symptom burden, but also may provide an opportune window wherein cognitive or behavioral interventions could be introduced to harness a state of enhanced neuroplasticity and lead to improved longer-term clinical outcomes. Here, we review the potential of synergistically combining plasticity-enhancing and behavioral therapies to develop novel translational treatment approaches for depression. After reviewing relevant neuroplasticity deficits in depression, we survey biological treatments that appear to reverse such deficits in humans, including N-methyl-D-aspartate receptor modulators (ketamine, D-cycloserine), electroconvulsive therapy, and transcranial brain stimulation. We then review evidence that either directly or indirectly supports the hypothesis that a robust enhancement of neuroplasticity through these methods might promote the uptake of cognitive and behavioral interventions to enhance longer-term treatment outcomes through a synergistic effect. We identify key missing pieces of evidence and discuss future directions to enhance this emerging line of research.

Exploratory genome-wide association analysis of response to ketamine and a polygenic analysis of response to scopolamine in depression

Growing evidence suggests that the glutamatergic modulator ketamine has rapid antidepressant effects in treatment-resistant depressed subjects. The anticholinergic agent scopolamine has also shown promise as a rapid-acting antidepressant. This study applied genome-wide markers to investigate the role of genetic variants in predicting acute antidepressant response to both agents. The ketamine-treated sample included 157 unrelated European subjects with major depressive disorder (MDD) or bipolar disorder (BD). The scopolamine-treated sample comprised 37 unrelated European subjects diagnosed with either MDD or BD who had a current Major Depressive Episode (MDE), and had failed at least two adequate treatment trials for depression. Change in Montgomery-Asberg Depression Rating Scale (MADRS) or the 17-item Hamilton Depression Rating Scale (HAM-D) scale scores at day 1 (24 h post-treatment) was considered the primary outcome. Here, we conduct pilot genome-wide association study (GWAS) analyses to identify potential markers of ketamine response and dissociative side effects. Polygenic risk score analysis of SNPs ranked by the strength of their association with ketamine response was then calculated in order to assess whether common genetic markers from the ketamine study could predict response to scopolamine. Findings require replication in larger samples in light of low power of analyses of these small samples. Neverthless, these data provide a promising illustration of our future potential to identify genetic variants underlying rapid treatment response in mood disorders and may ultimately guide individual patient treatment selection in the future.

An enriched granger causal model allowing variable static anatomical constraints

The anatomical connectivity constrains but does not fully determine functional connectivity, especially when one explores into the dynamics over the course of a trial. Therefore, an enriched granger causal model (GCM) integrated with anatomical prior information is proposed in this study, to describe the dynamic effective connectivity to distinguish the depression and explore the pathogenesis of depression. In the proposed frame, the anatomical information was converted via an optimized transformation model, which was then integrated into the normal GCM by variational bayesian model. Magnetoencephalography (MEG) signals and diffusion tensor imaging (DTI) of 24 depressive patients and 24 matched controls were utilized for performance comparison. Together with the sliding windowed MEG signals under sad facial stimuli, the enriched GCM was applied to calculate the regional-pair dynamic effective connectivity, which were repeatedly sifted via feature selection and fed into different classifiers. From the aspects of model errors and recognition accuracy rates, results supported the superiority of the enriched GCM with anatomical priors over the normal GCM. For the effective connectivity with anatomical priors, the best subject discrimination accuracy of SVM was 85.42% (the sensitivity was 87.50% and the specificity was 83.33%). Furthermore, discriminative feature analysis suggested that the enriched GCM that detect the variable anatomical constraint on function could better detect more stringent and less dynamic brain function in depression. The proposed approach is valuable in dynamic functional dysfunction exploration in depression and could be useful for depression recognition.

Task-positive and task-negative networks in major depressive disorder: A combined fMRI and EEG study

BACKGROUND

The study of intrinsic connectivity networks, i.e., sets of brain regions that show a high degree of interconnectedness even in the absence of a task, showed that major depressive disorder (MDD) patients demonstrate an increased connectivity within the default mode network (DMN), which is active in a resting state and is implicated in self-referential processing, and a decreased connectivity in task-positive networks (TPNs), which increase their activity in attention tasks. Cortical localization of this 'dominance' of the DMN over the TPN in MDD patients is not fully understood. Besides, this effect has been investigated using fMRI and its electrophysiological underpinning is not known.

METHOD

In this study, we tested the dominance hypothesis using seed-based connectivity analysis of resting-state fMRI and EEG data obtained in 41 MDD patients and 23 controls.

RESULTS

In MDD patients, as compared to controls, insula, pallidum/putamen, amygdala, and left dorso- and ventrolateral prefrontal cortex are more strongly connected with DMN than with TPN seeds. In EEG, all significant effects were obtained in the delta frequency band.

LIMITATIONS

fMRI and EEG data were not obtained simultaneously during the same session.

CONCLUSIONS

In MDD patients, major emotion and attention regulation circuits are more strongly connected with DMN than with TPN implying they are more prepared to respond to internally generated self-related thoughts than to environmental challenges.

Features of dissociation differentially predict antidepressant response to ketamine in treatment-resistant depression

BACKGROUND

Ketamine induces rapid and robust antidepressant effects, and many patients also describe dissociation, which is associated with antidepressant response. This follow-up study investigated whether antidepressant efficacy is uniquely related to dissociative symptom clusters.

METHODS

Treatment-resistant patients with major depressive disorder (MDD) or bipolar disorder (BD) (n = 126) drawn from three studies received a single subanesthetic (0.5 mg/kg) ketamine infusion. Dissociative effects were measured using the Clinician-Administered Dissociative States Scale (CADSS). Antidepressant response was measured using the 17-item Hamilton Depression Rating Scale (HAM-D). A confirmatory factor analysis established the validity of CADSS subscales (derealization, depersonalization, amnesia), and a general linear model with repeated measures was fitted to test whether subscale scores were associated with antidepressant response.

RESULTS

Factor validity was supported, with a root mean square error of approximation of .06, a comparative fit index of .97, and a Tucker-Lewis index of .96. Across all studies and timepoints, the depersonalization subscale was positively related to HAM-D percent change. A significant effect of derealization on HAM-D percent change was observed at one timepoint (Day 7) in one study. The amnesia subscale was unrelated to HAM-D percent change.

LIMITATIONS

Possible inadequate blinding; combined MDD/BD datasets might have underrepresented ketamine's antidepressant efficacy; the possibility of Type I errors in secondary analyses.

CONCLUSIONS

From a psychometric perspective, researchers may elect to administer only the CADSS depersonalization subscale, given that it was most closely related to antidepressant response. From a neurobiological perspective, mechanistic similarities may exist between ketamine-induced depersonalization and antidepressant response, although off-target effects cannot be excluded.

A Comparison of Neuroimaging Abnormalities in Multiple Sclerosis, Major Depression and Chronic Fatigue Syndrome (Myalgic Encephalomyelitis): is There a Common Cause?

There is copious evidence of abnormalities in resting-state functional network connectivity states, grey and white matter pathology and impaired cerebral perfusion in patients afforded a diagnosis of multiple sclerosis, major depression or chronic fatigue syndrome (CFS) (myalgic encephalomyelitis). Systemic inflammation may well be a major element explaining such findings. Inter-patient and inter-illness variations in neuroimaging findings may arise at least in part from regional genetic, epigenetic and environmental variations in the functions of microglia and astrocytes. Regional differences in neuronal resistance to oxidative and inflammatory insults and in the performance of antioxidant defences in the central nervous system may also play a role. Importantly, replicated experimental findings suggest that the use of high-resolution SPECT imaging may have the capacity to differentiate patients afforded a diagnosis of CFS from those with a diagnosis of depression. Further research involving this form of neuroimaging appears warranted in an attempt to overcome the problem of aetiologically heterogeneous cohorts which probably explain conflicting findings produced by investigative teams active in this field. However, the ionising radiation and relative lack of sensitivity involved probably preclude its use as a routine diagnostic tool.

Alterations of Intrinsic Brain Connectivity Patterns in Depression and Bipolar Disorders: A Critical Assessment of Magnetoencephalography-Based Evidence

Despite being the object of a thriving field of clinical research, the investigation of intrinsic brain network alterations in psychiatric illnesses is still in its early days. Because the pathological alterations are predominantly probed using functional magnetic resonance imaging (fMRI), many questions about the electrophysiological bases of resting-state alterations in psychiatric disorders, particularly among mood disorder patients, remain unanswered. Alongside important research using electroencephalography (EEG), the specific recent contributions and future promise of magnetoencephalography (MEG) in this field are not fully recognized and valued. Here, we provide a critical review of recent findings from MEG resting-state connectivity within major depressive disorder (MDD) and bipolar disorder (BD). The clinical MEG resting-state results are compared with those previously reported with fMRI and EEG. Taken together, MEG appears to be a promising but still critically underexploited technique to unravel the neurophysiological mechanisms that mediate abnormal (both hyper- and hypo-) connectivity patterns involved in MDD and BD. In particular, a major strength of MEG is its ability to provide source-space estimations of neuromagnetic long-range rhythmic synchronization at various frequencies (i.e., oscillatory coupling). The reviewed literature highlights the relevance of probing local and interregional rhythmic synchronization to explore the pathophysiological underpinnings of each disorder. However, before we can fully take advantage of MEG connectivity analyses in psychiatry, several limitations inherent to MEG connectivity analyses need to be understood and taken into account. Thus, we also discuss current methodological challenges and outline paths for future research. MEG resting-state studies provide an important window onto perturbed spontaneous oscillatory brain networks and hence supply an important complement to fMRI-based resting-state measurements in psychiatric populations.

Ketamine: 50 Years of Modulating the Mind

Ketamine was introduced into clinical practice in the 1960s and continues to be both clinically useful and scientifically fascinating. With considerably diverse molecular targets and neurophysiological properties, ketamine’s effects on the central nervous system remain incompletely understood. Investigators have leveraged the unique characteristics of ketamine to explore the invariant, fundamental mechanisms of anesthetic action. Emerging evidence indicates that ketamine-mediated anesthesia may occur via disruption of corticocortical information transfer in a frontal-to-parietal (“top down”) distribution. This proposed mechanism of general anesthesia has since been demonstrated with anesthetics in other pharmacological classes as well. Ketamine remains invaluable to the fields of anesthesiology and critical care medicine, in large part due to its ability to maintain cardiorespiratory stability while providing effective sedation and analgesia. Furthermore, there may be an emerging role for ketamine in treatment of refractory depression and Post-Traumatic Stress Disorder. In this article, we review the history of ketamine, its pharmacology, putative mechanisms of action and current clinical applications.