Ketamine modulates fronto-striatal circuitry in depressed and healthy individuals.

Ketamine improves motivation-related symptoms in depression but simultaneously elicits similar symptoms in healthy individuals, suggesting that it might have different effects in health and disease. This study examined whether ketamine affects the brain's fronto-striatal system, which is known to drive motivational behavior. The study also assessed whether inflammatory mechanisms-which are known to influence neural and behavioral motivational processes-might underlie some of these changes. These questions were explored in the context of a double-blind, placebo-controlled, crossover trial of ketamine in 33 individuals with treatment-resistant major depressive disorder (TRD) and 25 healthy volunteers (HVs). Resting-state functional magnetic resonance imaging (rsfMRI) was acquired 2 days post-ketamine (final sample: TRD n = 27, HV n = 19) and post-placebo (final sample: TRD n = 25, HV n = 18) infusions and was used to probe fronto-striatal circuitry with striatal seed-based functional connectivity. Ketamine increased fronto-striatal functional connectivity in TRD participants toward levels observed in HVs while shifting the connectivity profile in HVs toward a state similar to TRD participants under placebo. Preliminary findings suggest that these effects were largely observed in the absence of inflammatory (C-reactive protein) changes and were associated with both acute and sustained improvements in symptoms in the TRD group. Ketamine thus normalized fronto-striatal connectivity in TRD participants but disrupted it in HVs independently of inflammatory processes. These findings highlight the potential importance of reward circuitry in ketamine's mechanism of action, which may be particularly relevant for understanding ketamine-induced shifts in motivational symptoms.

A Randomized Trial of the N-Methyl-d-Aspartate Receptor Glycine Site Antagonist Prodrug 4-Chlorokynurenine in Treatment-Resistant Depression.

BACKGROUND: Ketamine has rapid-acting antidepressant effects but is associated with psychotomimetic and other adverse effects. A 7-chlorokynurenic acid is a potent and specific glycine site N-methyl-d-aspartate receptor antagonist but crosses the blood-brain barrier inefficiently. Its prodrug, L-4-chlorokynurenine (4-Cl-KYN), exerts acute and sustained antidepressant-like effects in rodents and has no reported psychotomimetic effects in either rodents or healthy volunteers. This study examined whether 4-Cl-KYN has rapid antidepressant effects in individuals with treatment-resistant depression. METHODS: After a 2-week drug-free period, 19 participants with treatment-resistant depression were randomized to receive daily oral doses of 4-Cl-KYN monotherapy (1080 mg/d for 7 days, then 1440 mg/d for 7 days) or placebo for 14 days in a randomized, placebo-controlled, double-blind, crossover manner. The primary outcome measure was the Hamilton Depression Rating Scale score, assessed at several time points over a 2-week period; secondary outcome measures included additional rating scale scores. Pharmacokinetic measures of 7-chlorokynurenic acid and 4-Cl-KYN and pharmacodynamic assessments were obtained longitudinally and included 1H-magnetic resonance spectroscopy brain glutamate levels, resting-state functional magnetic resonance imaging, and plasma and cerebrospinal fluid measures of kynurenine metabolites and neurotrophic factors. RESULTS: Linear mixed models detected no treatment effects, as assessed by primary and secondary outcome measures. No difference was observed for any of the peripheral or central biological indices or for adverse effects at any time between groups. A 4-Cl-KYN was safe and well-tolerated, with generally minimal associated adverse events. CONCLUSIONS: In this small crossover trial, 4-Cl-KYN monotherapy exerted no antidepressant effects at the doses and treatment duration studied.ClinicalTrials.gov identifier: NCT02484456.

Multimodal imaging reveals a complex pattern of dysfunction in corticolimbic pathways in major depressive disorder.

Major depressive disorder (MDD) is highly prevalent and associated with considerable morbidity, yet its pathophysiology remains only partially understood. While numerous studies have investigated the neurobiological correlates of MDD, most have used only a single neuroimaging modality. In particular, diffusion tensor imaging (DTI) studies have failed to yield uniform results. In this context, examining key tracts and using information from multiple neuroimaging modalities may better characterize potential abnormalities in the MDD brain. This study analyzed data from 30 participants with MDD and 26 healthy participants who underwent DTI, magnetic resonance spectroscopy (MRS), resting-state functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG). Tracts connecting the subgenual anterior cingulate cortex (sgACC) and the left and right amygdala, as well as connections to the left and right hippocampus and thalamus, were examined as target areas. Reduced fractional anisotropy (FA) was observed in the studied tracts. Significant differences in the correlation between medial prefrontal glutamate concentrations and FA were also observed between MDD and healthy participants along tracts connecting the sgACC and right amygdala; healthy participants exhibited a strong correlation but MDD participants showed no such relationship. In the same tract, a correlation was observed between FA and subsequent antidepressant response to ketamine infusion in MDD participants. Exploratory models also suggested group differences in the relationship between DTI, fMRI, and MEG measures. This study is the first to combine MRS, DTI, fMRI, and MEG data to obtain multimodal indices of MDD and antidepressant response and may lay the foundation for similar future analyses.

Separating slow BOLD from non-BOLD baseline drifts using multi-echo fMRI.

The functional magnetic resonance (fMRI) baseline is known to drift over the course of an experiment and is often attributed to hardware instability. These ultraslow fMRI fluctuations are inseparable from blood oxygenation level dependent (BOLD) changes in standard single echo fMRI and they are therefore typically removed before further analysis in both resting-state and task paradigms. However, some part of these fluctuations may be of neuronal origin, as neural activity can indeed fluctuate at the scale of several minutes or even longer, such as after the administration of drugs or during the ultradian rhythms. Here, we show that it is possible to separate the slow BOLD and non-BOLD drifts automatically using multi-echo fMRI and multi-echo independent components analysis (ME-ICA) denoising by demonstrating the detection of a visual signal evoked from a flickering checkerboard with slowly changing contrast.

Hippocampal volume changes after (R,S)-ketamine administration in patients with major depressive disorder and healthy volunteers.

The hippocampus and amygdala have been implicated in the pathophysiology and treatment of major depressive disorder (MDD). Preclinical models suggest that stress-related changes in these regions can be reversed by antidepressants, including ketamine. Clinical studies have identified reduced volumes in MDD that are thought to be potentiated by early life stress and worsened by repeated depressive episodes. This study used 3T and 7T structural magnetic resonance imaging data to examine longitudinal changes in hippocampal and amygdalar subfield volumes associated with ketamine treatment. Data were drawn from a previous double-blind, placebo-controlled, crossover trial of healthy volunteers (HVs) unmedicated individuals with treatment-resistant depression (TRD) (3T: 18 HV, 26 TRD, 7T: 17 HV, 30 TRD) who were scanned at baseline and twice following either a 40 min IV ketamine (0.5 mg/kg) or saline infusion (acute: 1-2 days, interim: 9-10 days post infusion). No baseline differences were noted between the two groups. At 10 days post-infusion, a slight increase was observed between ketamine and placebo scans in whole left amygdalar volume in individuals with TRD. No other differences were found between individuals with TRD and HVs at either field strength. These findings shed light on the timing of ketamine's effects on cortical structures.

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures.

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.

Review: The use of functional magnetic resonance imaging (fMRI) in clinical trials and experimental research studies for depression.

Functional magnetic resonance imaging (fMRI) is a non-invasive technique that can be used to examine neural responses with and without the use of a functional task. Indeed, fMRI has been used in clinical trials and pharmacological research studies. In mental health, it has been used to identify brain areas linked to specific symptoms but also has the potential to help identify possible treatment targets. Despite fMRI's many advantages, such findings are rarely the primary outcome measure in clinical trials or research studies. This article reviews fMRI studies in depression that sought to assess the efficacy and mechanism of action of compounds with antidepressant effects. Our search results focused on selective serotonin reuptake inhibitors (SSRIs), the most commonly prescribed treatments for depression and ketamine, a fast-acting antidepressant treatment. Normalization of amygdala hyperactivity in response to negative emotional stimuli was found to underlie successful treatment response to SSRIs as well as ketamine, indicating a potential common pathway for both conventional and fast-acting antidepressants. Ketamine's rapid antidepressant effects make it a particularly useful compound for studying depression with fMRI; its effects on brain activity and connectivity trended toward normalizing the increases and decreases in brain activity and connectivity associated with depression. These findings highlight the considerable promise of fMRI as a tool for identifying treatment targets in depression. However, additional studies with improved methodology and study design are needed before fMRI findings can be translated into meaningful clinical trial outcomes.

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

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

Preliminary evidence that ketamine alters anterior cingulate resting-state functional connectivity in depressed individuals.

Activity changes within the anterior cingulate cortex (ACC) are implicated in the antidepressant effects of ketamine, but the ACC is cytoarchitectonically and functionally heterogeneous and ketamine's effects may be subregion specific. In the context of a double-blind randomized placebo-controlled crossover trial investigating the clinical and resting-state fMRI effects of intravenous ketamine vs. placebo in patients with treatment resistant depression (TRD) vs. healthy volunteers (HV), we used seed-based resting-state functional connectivity (rsFC) analyses to determine differential changes in subgenual ACC (sgACC), perigenual ACC (pgACC) and dorsal ACC (dACC) rsFC two days post-infusion. Across cingulate subregions, ketamine differentially modulated rsFC to the right insula and anterior ventromedial prefrontal cortex, compared to placebo, in TRD vs. HV; changes to pgACC-insula connectivity correlated with improvements in depression scores. Post-hoc analysis of each cingulate subregion separately revealed differential modulation of sgACC-hippocampal, sgACC-vmPFC, pgACC-posterior cingulate, and dACC-supramarginal gyrus connectivity. By comparing rsFC changes following ketamine vs. placebo in the TRD group alone, we found that sgACC rsFC was most substantially modulated by ketamine vs. placebo. Changes to sgACC-pgACC, sgACC-ventral striatal, and sgACC-dACC connectivity correlated with improvements in anhedonia symptoms. This preliminary evidence suggests that accurate segmentation of the ACC is needed to understand the precise effects of ketamine's antidepressant and anti-anhedonic action.

An exploration of actigraphy in the context of ketamine and treatment-resistant depression.

OBJECTIVES: This study explored the potential of non-parametric and complexity analysis metrics to detect changes in activity post-ketamine and their association with depressive symptomatology. METHODS: Individuals with treatment-resistant depression (TRD: n = 27, 16F, 35.9 ± 10.8 years) and healthy volunteers (HVs: n = 9, 4F, 36.4 ± 9.59 years) had their activity monitored during an inpatient, double-blind, crossover study where they received an infusion of ketamine or saline placebo. All participants were 18-65 years old, medication-free, and had a MADRS score ≥20. Non-parametric metrics averaged over each study day, metrics derived from complexity analysis, and traditionally calculated non-parametric metrics averaged over two weeks were calculated from the actigraphy time series. A separate analysis was conducted for a subsample (n = 17) to assess the utility of these metrics in a hospital setting. RESULTS: In HVs, lower intradaily variability was observed within daily rest/activity patterns post-ketamine versus post-placebo (F = 5.16(1,15), p = 0.04). No other significant effects of drug or drug-by-time or correlations between depressive symptomatology and activity were detected. CONCLUSIONS: Weak associations between non-parametric variables and ketamine were found but were not consistent across actigraphy measures. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT00088699.

Differentiating BOLD and non-BOLD signals in fMRI time series using multi-echo EPI.

A central challenge in the fMRI based study of functional connectivity is distinguishing neuronally related signal fluctuations from the effects of motion, physiology, and other nuisance sources. Conventional techniques for removing nuisance effects include modeling of noise time courses based on external measurements followed by temporal filtering. These techniques have limited effectiveness. Previous studies have shown using multi-echo fMRI that neuronally related fluctuations are Blood Oxygen Level Dependent (BOLD) signals that can be characterized in terms of changes in R(2)* and initial signal intensity (S(0)) based on the analysis of echo-time (TE) dependence. We hypothesized that if TE-dependence could be used to differentiate BOLD and non-BOLD signals, non-BOLD signal could be removed to denoise data without conventional noise modeling. To test this hypothesis, whole brain multi-echo data were acquired at 3 TEs and decomposed with Independent Components Analysis (ICA) after spatially concatenating data across space and TE. Components were analyzed for the degree to which their signal changes fit models for R(2)* and S(0) change, and summary scores were developed to characterize each component as BOLD-like or not BOLD-like. These scores clearly differentiated BOLD-like "functional network" components from non BOLD-like components related to motion, pulsatility, and other nuisance effects. Using non BOLD-like component time courses as noise regressors dramatically improved seed-based correlation mapping by reducing the effects of high and low frequency non-BOLD fluctuations. A comparison with seed-based correlation mapping using conventional noise regressors demonstrated the superiority of the proposed technique for both individual and group level seed-based connectivity analysis, especially in mapping subcortical-cortical connectivity. The differentiation of BOLD and non-BOLD components based on TE-dependence was highly robust, which allowed for the identification of BOLD-like components and the removal of non BOLD-like components to be implemented as a fully automated procedure.

Brain Correlates of Suicide Attempt in 18,925 Participants Across 18 International Cohorts.

BACKGROUND: Neuroimaging studies of suicidal behavior have so far been conducted in small samples, prone to biases and false-positive associations, yielding inconsistent results. The ENIGMA-MDD Working Group aims to address the issues of poor replicability and comparability by coordinating harmonized analyses across neuroimaging studies of major depressive disorder and related phenotypes, including suicidal behavior. METHODS: Here, we pooled data from 18 international cohorts with neuroimaging and clinical measurements in 18,925 participants (12,477 healthy control subjects and 6448 people with depression, of whom 694 had attempted suicide). We compared regional cortical thickness and surface area and measures of subcortical, lateral ventricular, and intracranial volumes between suicide attempters, clinical control subjects (nonattempters with depression), and healthy control subjects. RESULTS: We identified 25 regions of interest with statistically significant (false discovery rate < .05) differences between groups. Post hoc examinations identified neuroimaging markers associated with suicide attempt including smaller volumes of the left and right thalamus and the right pallidum and lower surface area of the left inferior parietal lobe. CONCLUSIONS: This study addresses the lack of replicability and consistency in several previously published neuroimaging studies of suicide attempt and further demonstrates the need for well-powered samples and collaborative efforts. Our results highlight the potential involvement of the thalamus, a structure viewed historically as a passive gateway in the brain, and the pallidum, a region linked to reward response and positive affect. Future functional and connectivity studies of suicidal behaviors may focus on understanding how these regions relate to the neurobiological mechanisms of suicide attempt risk.

Evaluating global brain connectivity as an imaging marker for depression: influence of preprocessing strategies and placebo-controlled ketamine treatment.

Major depressive disorder (MDD) is associated with altered global brain connectivity (GBC), as assessed via resting-state functional magnetic resonance imaging (rsfMRI). Previous studies found that antidepressant treatment with ketamine normalized aberrant GBC changes in the prefrontal and cingulate cortices, warranting further investigations of GBC as a putative imaging marker. These results were obtained via global signal regression (GSR). This study is an independent replication of that analysis using a separate dataset. GBC was analyzed in 28 individuals with MDD and 22 healthy controls (HCs) at baseline, post-placebo, and post-ketamine. To investigate the effects of preprocessing, three distinct pipelines were used: (1) regression of white matter (WM)/cerebrospinal fluid (CSF) signals only (BASE); (2) WM/CSF + GSR (GSR); and (3) WM/CSF + physiological parameter regression (PHYSIO). Reduced GBC was observed in individuals with MDD only at baseline in the anterior and medial cingulate cortices, as well as in the prefrontal cortex only after regressing the global signal. Ketamine had no effect compared to baseline or placebo in either group in any pipeline. PHYSIO did not resemble GBC preprocessed with GSR. These results concur with several studies that used GSR to study GBC. Further investigations are warranted into disease-specific components of global fMRI signals that may drive these results and of GBCr as a potential imaging marker in MDD.

Correction to: Mapping anticipatory anhedonia: an fMRI study.

The image of the Figure 2b in Figure 2 in the published article was incorrect and the authors would like to correct them. The original article has been corrected.

Neural correlates of personally familiar faces: parents, partner and own faces.

Investigations of the neural correlates of face recognition have typically used old/new paradigms where subjects learn to recognize new faces or identify famous faces. Familiar faces, however, include one's own face, partner's and parents' faces. Using event-related fMRI, we examined the neural correlates of these personally familiar faces. Ten participants were presented with photographs of own, partner, parents, famous and unfamiliar faces and responded to a distinct target. Whole brain, two regions of interest (fusiform gyrus and cingulate gyrus), and multiple linear regression analyses were conducted. Compared with baseline, all familiar faces activated the fusiform gyrus; own faces also activated occipital regions and the precuneus; partner faces activated similar areas, but in addition, the parahippocampal gyrus, middle superior temporal gyri and middle frontal gyrus. Compared with unfamiliar faces, only personally familiar faces activated the cingulate gyrus and the extent of activation varied with face category. Partner faces also activated the insula, amygdala and thalamus. Regions of interest analyses and laterality indices showed anatomical distinctions of processing the personally familiar faces within the fusiform and cingulate gyri. Famous faces were right lateralized whereas personally familiar faces, particularly partner and own faces, elicited bilateral activations. Regression analyses show experiential predictors modulated with neural activity related to own and partner faces. Thus, personally familiar faces activated the core visual areas and extended frontal regions, related to semantic and person knowledge and the extent and areas of activation varied with face type.

Effects of Ketamine on Brain Activity During Emotional Processing: Differential Findings in Depressed Versus Healthy Control Participants.

BACKGROUND: In the search for novel treatments for depression, ketamine has emerged as a unique agent with rapid antidepressant effects. Experimental tasks involving emotional processing can be used during functional magnetic resonance imaging scanning to investigate ketamine's effects on brain function in major depressive disorder (MDD). This study examined ketamine's effects on functional magnetic resonance imaging activity during an emotional processing task. METHODS: A total of 33 individuals with treatment-resistant MDD and 24 healthy control participants (HCs) took part in this double-blind, placebo-controlled crossover study. Participants received ketamine and placebo infusions 2 weeks apart, and functional magnetic resonance imaging scans were conducted at baseline and 2 days after each infusion. Blood oxygen level-dependent signal was measured during an emotional processing task, and a linear mixed-effects model was used to analyze differences in activation among group, drug, and task-specific factors. RESULTS: A group-by-drug interaction was observed in several brain regions, including a right frontal cluster extending into the anterior cingulate cortex and insula. Participants with MDD had greater activity than HCs after placebo infusion but showed lower activity after ketamine infusion, which was similar to the activity in HCs after placebo. A group-by-drug-by-task condition interaction was also found, which showed further differences that varied between implicit and explicit emotional conditions. CONCLUSIONS: The main results indicate that ketamine had differential effects on brain activity in participants with MDD versus HCs. The pattern of activation in participants with MDD after ketamine infusion resembled the activation in HCs after placebo infusion, suggesting a normalization of function during emotional processing. The findings contribute to a better understanding of ketamine's actions in the brain.

Mapping anticipatory anhedonia: an fMRI study.

Anhedonia-broadly defined as loss of interest and/or an inability to experience pleasure-is an important feature of several psychiatric disorders. Research into the clinical presentation and neurobiology of this symptom has identified components related to motivation, learning, anticipation, and experience of pleasure as important constructs that inform therapeutic interventions. The experimental study of anhedonia is largely based on incentive processing paradigms, most often with monetary rewards, though studies have also used pleasantness ratings of various stimuli. However, linking an individual's own system of reinforcers and ability to enjoy them with anhedonia and neural activity remains comparatively under-explored. A previous study of participants with major depressive disorder (MDD) and healthy controls found that activity word ratings correlated with measures of anhedonia, depression, and motivation. The present study collected functional magnetic resonance imaging (fMRI) images in healthy controls while they rated activity words and pictures showing activities in order to identify networks differentially responsive to subjective decisions about the appetitive value of activities. The study sought to measure individually-relevant hedonic capacity as demonstrated by correlations between task measures and anticipatory anhedonia ratings. Ratings of potential pleasure were associated with neural activity in areas previously identified as relevant to pleasure and reward processing, such as anterior and posterior cingulate, middle frontal areas, and dorsal and ventral striatum. Although the study included only healthy controls, the results demonstrate a link between anhedonia measures, behavior, and brain responses and also test a paradigm that could be used to study anhedonia in clinical populations.

Functional Imaging of the Implicit Association of the Self With Life and Death.

OBJECTIVE: A critical need exists to identify objective markers of suicide ideation. One potential suicide risk marker is the Suicide Implicit Association Task (S-IAT), a behavioral task that uses differential reaction times to compare the implicit association between the self and death to the implicit association between the self and life. Individuals with a stronger association between the self and death on the S-IAT are more likely to attempt suicide in the future. To better understand the neural underpinnings of the implicit association between self and either life or death, a functional magnetic resonance imaging (fMRI) version of the S-IAT was adapted and piloted in healthy volunteers. METHOD: An fMRI version of the S-IAT was administered to 28 healthy volunteers (ages 18-65, 14F/14M). RESULTS: Behavioral results were comparable to those seen in non-scanner versions of the task. The task was associated with patterns of neural activation in areas relevant to emotional processing, specifically the insula and right ventrolateral prefrontal cortex. CONCLUSIONS: Performance on the S-IAT fMRI task may reflect scores obtained outside of the scanner. In future evaluations, this task could help assess whether individuals at increased risk of suicide display a different pattern of neural activation in response to self/death and self/life stimuli.

Ketamine normalizes brain activity during emotionally valenced attentional processing in depression.

Background: An urgent need exists for faster-acting pharmacological treatments in major depressive disorder (MDD). The glutamatergic modulator ketamine has been shown to have rapid antidepressant effects, but much remains unknown about its mechanism of action. Functional MRI (fMRI) can be used to investigate how ketamine impacts brain activity during cognitive and emotional processing. Methods: This double-blind, placebo-controlled, crossover study of 33 unmedicated participants with MDD and 26 healthy controls (HCs) examined how ketamine affected fMRI activation during an attentional bias dot probe task with emotional face stimuli across multiple time points. A whole brain analysis was conducted to find regions with differential activation associated with group, drug session, or dot probe task-specific factors (emotional valence and congruency of stimuli). Results: A drug session by group interaction was observed in several brain regions, such that ketamine had opposite effects on brain activation in MDD versus HC participants. Additionally, there was a similar finding related to emotional valence (a drug session by group by emotion interaction) in a large cluster in the anterior cingulate and medial frontal cortex. Conclusions: The findings show a pattern of brain activity in MDD participants following ketamine infusion that is similar to activity observed in HCs after placebo. This suggests that ketamine may act as an antidepressant by normalizing brain function during emotionally valenced attentional processing. Clinical trial: NCT#00088699: https://www.clinicaltrials.gov/ct2/show/NCT00088699.

Default Mode Connectivity in Major Depressive Disorder Measured Up to 10 Days After Ketamine Administration.

BACKGROUND: The symptoms of major depressive disorder (MDD) are rapidly alleviated by administration of a single dose of the glutamatergic modulator ketamine. However, few studies have investigated the potential sustained neural effects of this agent beyond immediate infusion. This study used functional magnetic resonance imaging to examine the effect of a single ketamine infusion on the resting state default mode network (DMN) at 2 and 10 days after a single ketamine infusion in unmedicated subjects with MDD as well as healthy control subjects (HCs). METHODS: Data were drawn from a double-blind, placebo-controlled crossover study of 58 participants (33 with MDD and 25 HCs) who received an intravenous infusion of either ketamine hydrochloride (0.5 mg/kg) or placebo on 2 separate test days spaced 2 weeks apart. Eight minutes of functional magnetic resonance imaging resting state data was acquired at baseline and at about 2 and 10 days after both infusions. The DMN was defined using seed-based correlation and was compared across groups and scans. RESULTS: In subjects with MDD, connectivity between the insula and the DMN was normalized compared with HCs 2 days postketamine infusion. This change was reversed after 10 days and did not appear in either of the placebo scans. Group-specific connectivity differences in drug response were observed, most notably in the insula in subjects with MDD and in the thalamus in HCs. CONCLUSIONS: Connectivity changes in the insula in subjects with MDD suggest that ketamine may normalize the interaction between the DMN and salience networks, supporting the triple network dysfunction model of MDD.