PET imaging of neurotransmission using direct parametric reconstruction

Receptor ligand-based dynamic Positron Emission Tomography (PET) permits the measurement of neurotransmitter release in the human brain. For single-scan paradigms, the conventional method of estimating changes in neurotransmitter levels relies on fitting a pharmacokinetic model to activity concentration histories extracted after PET image reconstruction. However, due to the statistical fluctuations of activity concentration data at the voxel scale, parametric images computed using this approach often exhibit low signal-to-noise ratio, impeding characterization of neurotransmitter release. Numerous studies have shown that direct parametric reconstruction (DPR) approaches, which combine image reconstruction and kinetic analysis in a unified framework, can improve the signal-to-noise ratio of parametric mapping. However, there is little experience with DPR in imaging of neurotransmission and the performance of the approach in this application has not been evaluated before in humans. In this report, we present and evaluate a DPR methodology that computes 3-D distributions of ligand transport, binding potential (BP_ND) and neurotransmitter release magnitude (γ) from a dynamic sequence of PET sinograms. The technique employs the linear simplified reference region model (LSRRM) of Alpert et al. (2003), which represents an extension of the simplified reference region model that incorporates time-varying binding parameters due to radioligand displacement by release of neurotransmitter. Estimation of parametric images is performed by gradient-based optimization of a Poisson log-likelihood function incorporating LSRRM kinetics and accounting for the effects of head movement, attenuation, detector sensitivity, random and scattered coincidences. A ¹¹C-raclopride simulation study showed that the proposed approach substantially reduces the bias and variance of voxel-wise γ estimates as compared to standard methods. Moreover, simulations showed that detection of release could be made more reliable and/or conducted using a smaller sample size using the proposed DPR estimator. Likewise, images of BP_ND computed using DPR had substantially improved bias and variance properties. Application of the method in human subjects was demonstrated using ¹¹C-raclopride dynamic scans and a reward task, confirming the improved quality of the estimated parametric images using the proposed approach.

Pretreatment Reward Sensitivity and Frontostriatal Resting-State Functional Connectivity Are Associated With Response to Bupropion After Sertraline Nonresponse

BACKGROUND

Standard guidelines recommend selective serotonin reuptake inhibitors as first-line antidepressants for adults with major depressive disorder, but success is limited and patients who fail to benefit are often switched to non-selective serotonin reuptake inhibitor agents. This study investigated whether brain- and behavior-based markers of reward processing might be associated with response to bupropion after sertraline nonresponse.

METHODS

In a two-stage, double-blinded clinical trial, 296 participants were randomized to receive 8 weeks of sertraline or placebo in stage 1. Individuals who responded continued on another 8-week course of the same intervention in stage 2, while sertraline and placebo nonresponders crossed over to bupropion and sertraline, respectively. Data from 241 participants were analyzed. The stage 2 sample comprised 87 patients with major depressive disorder who switched medication and 38 healthy control subjects. A total of 116 participants with major depressive disorder treated with sertraline in stage 1 served as an independent replication sample. The probabilistic reward task and resting-state functional magnetic resonance imaging were administered at baseline.

RESULTS

Greater pretreatment reward sensitivity and higher resting-state functional connectivity between bilateral nucleus accumbens and rostral anterior cingulate cortex were associated with positive response to bupropion but not sertraline. Null findings for sertraline were replicated in the stage 1 sample.

CONCLUSIONS

Pretreatment reward sensitivity and frontostriatal connectivity may identify patients likely to benefit from bupropion following selective serotonin reuptake inhibitor failures. Results call for a prospective replication based on these biomarkers to advance clinical care.

Neurophysiological responses to safety signals and the role of cardiac vagal control

BACKGROUND

Deficits in safety signal learning are well-established in fear-related disorders (e.g., PTSD, phobias). The current study used a fear conditioning paradigm to test associations among eye blink startle and event-related brain potential (ERP) latency measures of safety signal learning, as well as the role of cardiac vagal control (a measure of top-down inhibition necessary for safety learning).

METHODS

Participants were 49 trauma-exposed women ages 17 to 28 years. Eyeblink startle response and ERP amplitudes/latencies were derived for conditioned stimuli associated (CS+) and not associated (CS-) with an aversive unconditioned stimulus. ERPs included the P100 and late positive potential (LPP), which index early visual processing and sustained emotional encoding, respectively. Cardiac vagal control was assessed with resting heart rate variability (HRV).

RESULTS

P100 and LPP latencies for the CS- (safety signal stimulus) were significantly negatively associated with startle to the CS-, but not the CS + . LPP CS- latencies were significantly negatively associated with PTSD Intrusion scores, and this relationship was moderated by vagal control, such that the effect was only present among those with low HRV.

CONCLUSIONS

ERP-based markers of safety signal learning were associated with startle response to the CS- (but not CS+) and PTSD symptoms, indicating that these markers may have relevance for fear-related disorders. Cardiac vagal control indexed by HRV is a moderating factor in these associations and may be relevant to safety signal learning.

Empirical validation of a touchscreen probabilistic reward task in rats

Anhedonia, the loss of pleasure from previously rewarding activities, is implicated in several neuropsychiatric conditions, including major depressive disorder (MDD). In order to accelerate drug development for mood disorders, quantitative approaches are needed to objectively measure responsiveness to reward as a means to identify deficits. One such approach, the probabilistic reward task (PRT), uses visual discrimination methodology to quantify reward learning. In this computerized task, humans make visual discriminations, and probabilistic contingencies are arranged such that correct responses to one alternative are rewarded more often (rich) than correct responses to the other (lean). Healthy participants consistently develop a response bias in favor of the rich alternative. However, participants with MDD typically exhibit lower response biases, and this blunting correlates with current and future anhedonia. The present studies validated a touchscreen-based PRT in rodents with formal and functional similarity to the human task. First, rats were trained to discriminate between two lines that differed in length. Next, parametric manipulations of probabilistic contingencies, line-length stimuli, and drug treatment (amphetamine, 0.32-3.2 mg/kg; scopolamine, 0.1-1.0 mg/kg; oxycodone, 0.1-1.0 mg/kg) on response bias were evaluated. Results demonstrated orderly shifts in bias and discriminability that varied as a function of, respectively, the asymmetry of rich/lean probabilities and disparity in line lengths. Drugs that enhance reward responsiveness (amphetamine and scopolamine, but not oxycodone) increased bias, verifying pharmacological task sensitivity. Finally, performance outcomes under optimized conditions were replicated in female rats. Collectively, the touchscreen-based rodent PRT appears to have high preclinical value as a quantitative assay of reward learning.

Reward-Related Neural Predictors and Mechanisms of Symptom Change in Cognitive Behavioral Therapy for Depressed Adolescent Girls

BACKGROUND

Approximately half of depressed adolescents fail to respond to cognitive behavioral therapy (CBT). Given the variability in response, it is important to identify pretreatment characteristics that predict prognosis. Knowledge of which depressed adolescents are likely to exhibit a positive versus poor outcome to CBT may have important clinical implications (e.g., informing treatment recommendations). Emerging evidence suggests that neural reward responsiveness represents one promising predictor.

METHODS

Adolescents with major depressive disorder (n = 36) received CBT and completed a reward task at 3 time points (pretreatment, midtreatment and posttreatment) while 128-channel electroencephalographic data were acquired. Healthy control participants (n = 29) completed the same task at 3 corresponding time points. Analyses focused on event-related potentials linked to 2 stages of neural processing: initial response to rewards (reward positivity) and later, elaborative processing (late positive potential). Moreover, time-frequency analyses decomposed the reward positivity into 2 constituent components: reward-related delta and loss-related theta activity.

RESULTS

Multilevel modeling revealed that greater pretreatment reward responsiveness, as measured by the late positive potential to rewards, predicted greater depressive symptom change. In addition, a group × condition × time interaction emerged for theta activity to losses, reflecting normalization of theta power in the group with major depressive disorder from baseline to posttreatment.

CONCLUSIONS

An event-related potential measure of sustained (late positive potential)-but not initial (reward positivity)-reward responsiveness predicted symptom improvement, which may help inform which depressed adolescents are most likely to benefit from CBT. In addition to alleviating depression, successful CBT may attenuate underlying neural (theta) hypersensitivity to negative outcomes in depressed youths.

Baseline reward processing and ventrostriatal dopamine function are associated with pramipexole response in depression

The efficacy of dopamine agonists in treating major depressive disorder has been hypothesized to stem from effects on ventrostriatal dopamine and reward function. However, an important question is whether dopamine agonists are most beneficial for patients with reward-based deficits. This study evaluated whether measures of reward processing and ventrostriatal dopamine function predicted response to the dopamine agonist, pramipexole (ClinicalTrials.gov Identifier: NCT02033369). Individuals with major depressive disorder (n = 26) and healthy controls (n = 26) (mean ± SD age = 26.5 ± 5.9; 50% female) first underwent assessments of reward learning behaviour and ventrostriatal prediction error signalling (measured using functional MRI). 11C-(+)-PHNO PET before and after oral amphetamine was used to assess ventrostriatal dopamine release. The depressed group then received open-label pramipexole treatment for 6 weeks (0.5 mg/day titrated to a maximum daily dose of 2.5 mg). Symptoms were assessed weekly, and reward learning was reassessed post-treatment. At baseline, relative to controls, the depressed group showed lower reward learning (P = 0.02), a trend towards blunted reward-related prediction error signals (P = 0.07), and a trend towards increased amphetamine-induced dopamine release (P = 0.07). Despite symptom improvements following pramipexole (Cohen's d ranging from 0.51 to 2.16 across symptom subscales), reward learning did not change after treatment. At a group level, baseline reward learning (P = 0.001) and prediction error signalling (P = 0.004) were both associated with symptom improvement, albeit in a direction opposite to initial predictions: patients with stronger pretreatment reward learning and reward-related prediction error signalling improved most. Baseline D2/3 receptor availability (P = 0.02) and dopamine release (P = 0.05) also predicted improvements in clinical functioning, with lower D2/3 receptor availability and lower dopamine release predicting greater improvements. Although these findings await replication, they suggest that measures of reward-related mesolimbic dopamine function may hold promise for identifying depressed individuals likely to respond favourably to dopaminergic pharmacotherapy.

Dissecting the impact of depression on decision-making

BACKGROUND

Cognitive deficits in depressed adults may reflect impaired decision-making. To investigate this possibility, we analyzed data from unmedicated adults with Major Depressive Disorder (MDD) and healthy controls as they performed a probabilistic reward task. The Hierarchical Drift Diffusion Model (HDDM) was used to quantify decision-making mechanisms recruited by the task, to determine if any such mechanism was disrupted by depression.

METHODS

Data came from two samples (Study 1: 258 MDD, 36 controls; Study 2: 23 MDD, 25 controls). On each trial, participants indicated which of two similar stimuli was presented; correct identifications were rewarded. Quantile-probability plots and the HDDM quantified the impact of MDD on response times (RT), speed of evidence accumulation (drift rate), and the width of decision thresholds, among other parameters.

RESULTS

RTs were more positively skewed in depressed v. healthy adults, and the HDDM revealed that drift rates were reduced-and decision thresholds were wider-in the MDD groups. This pattern suggests that depressed adults accumulated the evidence needed to make decisions more slowly than controls did.

CONCLUSIONS

Depressed adults responded slower than controls in both studies, and poorer performance led the MDD group to receive fewer rewards than controls in Study 1. These results did not reflect a sensorimotor deficit but were instead due to sluggish evidence accumulation. Thus, slowed decision-making-not slowed perception or response execution-caused the performance deficit in MDD. If these results generalize to other tasks, they may help explain the broad cognitive deficits seen in depression.

The acute effects of nicotine on corticostriatal responses to distinct phases of reward processing

Nicotine enhances the reinforcement of non-drug rewards by increasing nucleus accumbens (NAcc) reactivity to anticipatory cues. This anticipatory effect is selective as no clear evidence has emerged showing that nicotine acutely changes reward receipt reactivity. However, repeated rewarding experiences shift peak brain reactivity from hedonic reward outcome to the motivational anticipatory cue yielding more habitual cue-induced behavior. Given nicotine's influence on NAcc reactivity and connectivity, it is plausible that nicotine acutely induces this shift and alters NAcc functional connectivity during reward processing. To evaluate this currently untested hypothesis, a randomized crossover design was used in which healthy non-smokers were administered placebo and nicotine (2-mg lozenge). Brain activation to monetary reward anticipation and outcome was evaluated with functional magnetic resonance imaging. Relative to placebo, nicotine induced more NAcc reactivity to reward anticipation. Greater NAcc activation during anticipation was significantly associated with lower NAcc activation to outcome. During outcome, nicotine reduced NAcc functional connectivity with cortical regions including the anterior cingulate cortex, orbitofrontal cortex, and insula. These regions showed the same negative relationship between reward anticipation and outcome as noted in the NAcc. The current findings significantly improve our understanding of how nicotine changes corticostriatal circuit function and communication during distinct phases of reward processing and critically show that these alterations happen acutely following a single dose. The implications of this work explain nicotinic modulation of general reward function, which offer insights into the initial drive to smoke and the subsequent difficulty in cessation.

Effects of the KCNQ channel opener ezogabine on functional connectivity of the ventral striatum and clinical symptoms in patients with major depressive disorder

Major depressive disorder (MDD) is a leading cause of disability worldwide, yet current treatment strategies remain limited in their mechanistic diversity. Recent evidence has highlighted a promising novel pharmaceutical target-the KCNQ-type potassium channel-for the treatment of depressive disorders, which may exert a therapeutic effect via functional changes within the brain reward system, including the ventral striatum. The current study assessed the effects of the KCNQ channel opener ezogabine (also known as retigabine) on reward circuitry and clinical symptoms in patients with MDD. Eighteen medication-free individuals with MDD currently in a major depressive episode were enrolled in an open-label study and received ezogabine up to 900 mg/day orally over the course of 10 weeks. Resting-state functional magnetic resonance imaging data were collected at baseline and posttreatment to examine brain reward circuitry. Reward learning was measured using a computerized probabilistic reward task. After treatment with ezogabine, subjects exhibited a significant reduction of depressive symptoms (Montgomery-Asberg Depression Rating Scale score change: -13.7 ± 9.7, p < 0.001, d = 2.08) and anhedonic symptoms (Snaith-Hamilton Pleasure Scale score change: -6.1 ± 5.3, p < 0.001, d = 1.00), which remained significant even after controlling for overall depression severity. Improvement in depression was associated with decreased functional connectivity between the ventral caudate and clusters within the mid-cingulate cortex and posterior cingulate cortex (n = 14, voxel-wise p < 0.005). In addition, a subgroup of patients tested with a probabilistic reward task (n = 9) showed increased reward learning following treatment. These findings highlight the KCNQ-type potassium channel as a promising target for future drug discovery efforts in mood disorders.

Regional GABA Concentrations Modulate Inter-network Resting-state Functional Connectivity

Coordinated activity within and differential activity between large-scale neuronal networks such as the default mode network (DMN) and the control network (CN) is a critical feature of brain organization. The CN usually exhibits activations in response to cognitive tasks while the DMN shows deactivations; in addition, activity between the two networks is anti-correlated at rest. To address this issue, we used functional MRI to measure whole-brain BOLD signal during resting-state and task-evoked conditions, and MR spectroscopy (MRS) to quantify GABA and glutamate concentrations, in nodes within the DMN and CN (MPFC and DLPFC, respectively) in 19 healthy individuals at 3 Tesla. We found that GABA concentrations in the MPFC were significantly associated with DMN deactivation during a working memory task and with anti-correlation between DMN and CN at rest and during task performance, while GABA concentrations in the DLPFC weakly modulated DMN-CN anti-correlation in the opposite direction. Highlighting specificity, glutamate played a less significant role related to brain activity. These findings indicate that GABA in the MPFC is potentially involved in orchestrating between-network brain activity at rest and during task performance.

Evidence-based umbrella review of 162 peripheral biomarkers for major mental disorders

The literature on non-genetic peripheral biomarkers for major mental disorders is broad, with conflicting results. An umbrella review of meta-analyses of non-genetic peripheral biomarkers for Alzheimer's disease, autism spectrum disorder, bipolar disorder (BD), major depressive disorder, and schizophrenia, including first-episode psychosis. We included meta-analyses that compared alterations in peripheral biomarkers between participants with mental disorders to controls (i.e., between-group meta-analyses) and that assessed biomarkers after treatment (i.e., within-group meta-analyses). Evidence for association was hierarchically graded using a priori defined criteria against several biases. The Assessment of Multiple Systematic Reviews (AMSTAR) instrument was used to investigate study quality. 1161 references were screened. 110 met inclusion criteria, relating to 359 meta-analytic estimates and 733,316 measurements, on 162 different biomarkers. Only two estimates met a priori defined criteria for convincing evidence (elevated awakening cortisol levels in euthymic BD participants relative to controls and decreased pyridoxal levels in participants with schizophrenia relative to controls). Of 42 estimates which met criteria for highly suggestive evidence only five biomarker aberrations occurred in more than one disorder. Only 15 meta-analyses had a power >0.8 to detect a small effect size, and most (81.9%) meta-analyses had high heterogeneity. Although some associations met criteria for either convincing or highly suggestive evidence, overall the vast literature of peripheral biomarkers for major mental disorders is affected by bias and is underpowered. No convincing evidence supported the existence of a trans-diagnostic biomarker. Adequately powered and methodologically sound future large collaborative studies are warranted.

A randomized proof-of-mechanism trial applying the 'fast-fail' approach to evaluating κ-opioid antagonism as a treatment for anhedonia

The National Institute of Mental Health (NIMH) 'fast-fail' approach seeks to improve too-often-misleading early-phase drug development methods by incorporating biomarker-based proof-of-mechanism (POM) testing in phase 2a. This first comprehensive application of the fast-fail approach evaluated the potential of κ-opioid receptor (KOR) antagonism for treating anhedonia with a POM study determining whether robust target engagement favorably impacts the brain circuitry hypothesized to mediate clinical effects. Here we report the results from a multicenter, 8-week, double-blind, placebo-controlled, randomized trial in patients with anhedonia and a mood or anxiety disorder (selective KOR antagonist (JNJ-67953964, 10 mg; n = 45) and placebo (n = 44)). JNJ-67953964 significantly increased functional magnetic resonance imaging (fMRI) ventral striatum activation during reward anticipation (primary outcome) as compared to placebo (baseline-adjusted mean: JNJ-67953964, 0.72 (s.d. = 0.67); placebo, 0.33 (s.d. = 0.68); F(1,86) = 5.58, P < 0.01; effect size = 0.58 (95% confidence interval, 0.13-0.99)). JNJ-67953964, generally well tolerated, was not associated with any serious adverse events. This study supports proceeding with assessment of the clinical impact of target engagement and serves as a model for implementing the 'fast-fail' approach.

Experimental sleep disruption and reward learning: moderating role of positive affect responses

STUDY OBJECTIVES

Sleep disturbances increase vulnerability for depression, but the mechanisms underlying this relationship are not well known. We investigated the effects of experimental sleep disruption on response bias (RB), a measure of reward learning previously linked to depression, and the moderating role of positive affect responses.

METHODS

Participants (N = 42) were healthy adults enrolled in a within-subject crossover sleep disruption experiment that incorporated one night of uninterrupted sleep (US) and one night of forced awakenings (FA) in random order. On the day following each experimental sleep night, participants completed a probabilistic reward task to assess RB, and the Positive and Negative Affect Schedule-X. Participants were subgrouped according to positive affect responses: Preserved Positive Affect (i.e. positive affect scores maintained or increased; n = 15) or Reduced Positive Affect (i.e. positive affect scores decreased; n = 27) following FA.

RESULTS

Contrary to our hypotheses, across participants, RB did not significantly differ between the US and FA sleep conditions (p = .67). However, the effect of sleep condition on RB was moderated by positive affect response (p = .01); those with preserved positive affect showed heightened RB following FA, whereas those with reduced positive affect showed diminished RB following FA. Changes in negative affect between US and FA did not moderate RB.

CONCLUSION

The inability to preserve positive affect through periods of sleep disruption may be a marker of diminished reward learning capability. Understanding how sleep disruption impacts positive affect responses and reward learning identifies a pathway by which sleep disturbances may confer risk for depression.

Fear Extinction Recall Modulates Human Frontomedial Theta and Amygdala Activity

Human functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) studies, as well as animal studies, indicate that the amygdala and frontomedial brain regions are critically involved in conditioned fear and that frontomedial oscillations in the theta range (4-8 Hz) may support communication between these brain regions. However, few studies have used a multimodal approach to probe interactions among these key regions in humans. Here, our goal was to bridge the gap between prior human fMRI, EEG, and animal findings. Using simultaneous EEG-fMRI recordings 24 h after fear conditioning and extinction, conditioned stimuli presented (CS+E, CS-E) and not presented during extinction (CS+N, CS-N) were compared to identify effects specific to extinction versus fear recall. Differential (CS+ vs. CS-) electrodermal, frontomedial theta (EEG) and amygdala responses (fMRI) were reduced for extinguished versus nonextinguished stimuli. Importantly, effects on theta power covaried with effects on amygdala activation. Fear and extinction recall as indicated by theta explained 60% of the variance for the analogous effect in the right amygdala. Our findings show for the first time the interplay of amygdala and frontomedial theta activity during fear and extinction recall in humans and provide insight into neural circuits consistently linked with top-down amygdala modulation in rodents.

Caudate reactivity to smoking cues is associated with increased responding to monetary reward in nicotine-dependent individuals

Quitting smoking is challenging in part because environmental smoking cues can trigger the desire to smoke. Neurobiological responses to smoking cues are often observed in reward-related brain regions such as the caudate and nucleus accumbens (NAc). While reward plays a well-established role in the formation of cue reactivity, whether general reward responsiveness contributes to individual differences in cue-reactivity among chronic smokers is unclear; establishing such link could provide insight into the mechanisms maintaining cue reactivity. The current study explored this relationship by assessing smoking cue reactivity during functional magnetic imaging followed by an out-of-scanner probabilistic reward task (PRT) in 24 nicotine-dependent smokers (14 women). In addition, owing to sex differences in cue reactivity and reward function, this same relationship was examined as a function of sex. Following recent smoking, greater reward responsiveness on the PRT was associated with enhanced left caudate reactivity to smoking cues. No relationship was found in any other striatal subregion. The positive relationship between reward responsiveness and caudate smoking cue reactivity was significant only in male smokers, fitting with the idea that males and females respond to the reinforcing elements of smoking cues differently. These findings are clinically relevant as they show that, following recent smoking, nicotine-dependent individuals who are more cue reactive are also more likely to be responsive to non-drug rewards, which may be useful for making individualized treatment decisions that involve behavioral reward contingencies.

Cortical Connectivity Moderators of Antidepressant vs Placebo Treatment Response in Major Depressive Disorder: Secondary Analysis of a Randomized Clinical Trial

IMPORTANCE

Despite the widespread awareness of functional magnetic resonance imaging findings suggesting a role for cortical connectivity networks in treatment selection for major depressive disorder, its clinical utility remains limited. Recent methodological advances have revealed functional magnetic resonance imaging-like connectivity networks using electroencephalography (EEG), a tool more easily implemented in clinical practice.

OBJECTIVE

To determine whether EEG connectivity could reveal neural moderators of antidepressant treatment.

DESIGN, SETTING, AND PARTICIPANTS

In this nonprespecified secondary analysis, data were analyzed from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinic Care study, a placebo-controlled, double-blinded randomized clinical trial. Recruitment began July 29, 2011, and was completed December 15, 2015. A random sample of 221 outpatients with depression aged 18 to 65 years who were not taking medication for depression was recruited and assessed at 4 clinical sites. Analysis was performed on an intent-to-treat basis. Statistical analysis was performed from November 16, 2018, to May 23, 2019.

INTERVENTIONS

Patients received either the selective serotonin reuptake inhibitor sertraline hydrochloride or placebo for 8 weeks.

MAIN OUTCOMES AND MEASURES

Electroencephalographic orthogonalized power envelope connectivity analyses were applied to resting-state EEG data. Intent-to-treat prediction linear mixed models were used to determine which pretreatment connectivity patterns were associated with response to sertraline vs placebo. The primary clinical outcome was the total score on the 17-item Hamilton Rating Scale for Depression, administered at each study visit.

RESULTS

Of the participants recruited, 9 withdrew after first dose owing to reported adverse effects, and 221 participants (150 women; mean [SD] age, 37.8 [12.7] years) underwent EEG recordings and had high-quality pretreatment EEG data. After correction for multiple comparisons, connectome-wide analyses revealed moderation by connections within and between widespread cortical regions-most prominently parietal-for both the antidepressant and placebo groups. Greater alpha-band and lower gamma-band connectivity predicted better placebo outcomes and worse antidepressant outcomes. Lower connectivity levels in these moderating connections were associated with higher levels of anhedonia. Connectivity features that moderate treatment response differentially by treatment group were distinct from connectivity features that change from baseline to 1 week into treatment. The group mean (SD) score on the 17-item Hamilton Rating Scale for Depression was 18.35 (4.58) at baseline and 26.14 (30.37) across all time points.

CONCLUSIONS AND RELEVANCE

These findings establish the utility of EEG-based network functional connectivity analyses for differentiating between responses to an antidepressant vs placebo. A role emerged for parietal cortical regions in predicting placebo outcome. From a treatment perspective, capitalizing on the therapeutic components leading to placebo response differentially from antidepressant response should provide an alternative direction toward establishing a placebo signature in clinical trials, thereby enhancing the signal detection in randomized clinical trials.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01407094.

An electroencephalographic signature predicts antidepressant response in major depression

Antidepressants are widely prescribed, but their efficacy relative to placebo is modest, in part because the clinical diagnosis of major depression encompasses biologically heterogeneous conditions. Here, we sought to identify a neurobiological signature of response to antidepressant treatment as compared to placebo. We designed a latent-space machine-learning algorithm tailored for resting-state electroencephalography (EEG) and applied it to data from the largest imaging-coupled, placebo-controlled antidepressant study (n = 309). Symptom improvement was robustly predicted in a manner both specific for the antidepressant sertraline (versus placebo) and generalizable across different study sites and EEG equipment. This sertraline-predictive EEG signature generalized to two depression samples, wherein it reflected general antidepressant medication responsivity and related differentially to a repetitive transcranial magnetic stimulation treatment outcome. Furthermore, we found that the sertraline resting-state EEG signature indexed prefrontal neural responsivity, as measured by concurrent transcranial magnetic stimulation and EEG. Our findings advance the neurobiological understanding of antidepressant treatment through an EEG-tailored computational model and provide a clinical avenue for personalized treatment of depression.

Image acquisition and quality assurance in the Boston Adolescent Neuroimaging of Depression and Anxiety study

The Connectomes Related to Human Diseases (CRHD) initiative was developed with the Human Connectome Project (HCP) to provide high-resolution, open-access, multi-modal MRI data to better understand the neural correlates of human disease. Here, we present an introduction to a CRHD project, the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, which is collecting multimodal neuroimaging, clinical, and neuropsychological data from 225 adolescents (ages 14-17), 150 of whom are expected to have a diagnosis of depression and/or anxiety. Our transdiagnostic recruitment approach samples the full spectrum of depressed/anxious symptoms and their comorbidity, consistent with NIMH Research Domain Criteria (RDoC). We focused on an age range that is critical for brain development and for the onset of mental illness. This project sought to harmonize imaging sequences, hardware, and functional tasks with other HCP studies, although some changes were made to canonical HCP methods to accommodate our study population and questions. We present a thorough overview of our imaging sequences, hardware, and scanning protocol. We detail similarities and differences between this study and other HCP studies. We evaluate structural-, diffusion-, and functional-image-quality measures that may be influenced by clinical factors (e.g., disorder, symptomatology). Signal-to-noise and motion estimates from the first 140 adolescents suggest minimal influence of clinical factors on image quality. We anticipate enrollment of an additional 85 participants, most of whom are expected to have a diagnosis of anxiety and/or depression. Clinical and neuropsychological data from the first 140 participants are currently freely available through the National Institute of Mental Health Data Archive (NDA).

Brain function and clinical characterization in the Boston adolescent neuroimaging of depression and anxiety study

We present a Human Connectome Project study tailored toward adolescent anxiety and depression. This study is one of the first studies of the Connectomes Related to Human Diseases initiative and is collecting structural, functional, and diffusion-weighted brain imaging data from up to 225 adolescents (ages 14-17 years), 150 of whom are expected to have a current diagnosis of an anxiety and/or depressive disorder. Comprehensive clinical and neuropsychological evaluations and longitudinal clinical data are also being collected. This article provides an overview of task functional magnetic resonance imaging (fMRI) protocols and preliminary findings (N = 140), as well as clinical and neuropsychological characterization of adolescents. Data collection is ongoing for an additional 85 adolescents, most of whom are expected to have a diagnosis of an anxiety and/or depressive disorder. Data from the first 140 adolescents are projected for public release through the National Institutes of Health Data Archive (NDA) with the timing of this manuscript. All other data will be made publicly-available through the NDA at regularly scheduled intervals. This article is intended to serve as an introduction to this project as well as a reference for those seeking to clinical, neurocognitive, and task fMRI data from this public resource.

Approach-Avoidance Conflict in Major Depressive Disorder: Congruent Neural Findings in Humans and Nonhuman Primates

BACKGROUND

Maladaptive approach-avoidance behavior has been implicated in the pathophysiology of major depressive disorder (MDD), but the neural basis of these abnormalities in decision making remains unclear. Capitalizing on recent preclinical findings, we adapted an approach-avoidance conflict task from nonhuman primate research for use in human functional magnetic resonance imaging (fMRI).

METHODS

Forty-two female participants, including 18 unmedicated individuals with current MDD (mean age 25.2 ± 5.1 years) and 24 psychiatrically healthy control subjects (mean age 26.3 ± 7.6 years) completed the adapted approach-avoidance task during fMRI. To probe potential mechanistic factors underlying the observed behavioral and fMRI findings and to inform interpretation of putative group differences, we examined electrophysiological data from 2 female Macaca mulatta monkeys performing the approach-avoidance conflict task mimicked in the fMRI study.

RESULTS

Findings demonstrated congruent neural correlates of approach-avoidance conflict and aversive responsiveness in the anterior cingulate cortex, including the pregenual cortex, of human subjects and macaques (humans: p < .05 whole-brain corrected; macaques: p < .05). The MDD group exhibited aberrant task-related activations in the anterior cingulate cortex, prefrontal cortex, and striatum (all ps < .05). Neural effects in the MDD group were cross-sectionally associated with stress and depressive symptoms. Importantly, they also prospectively predicted stress at 6-month follow-up (all ps < .05).

CONCLUSIONS

Findings indicate that there is conservation of anterior cingulate activation across species and that frontal and striatal regions, in unmedicated humans with MDD, are abnormally responsive during cost-benefit decision making. We suggest that these disruptions could be valuable candidates for translational biomarkers.

Striatal hypofunction as a neural correlate of mood alterations in chronic pain patients

BACKGROUND

Chronic pain and mood disorders share common neuroanatomical substrates involving disruption of the reward system. Although increase in negative affect (NA) and decrease in positive affect (PA) are well-known factors complicating the clinical presentation of chronic pain patients, our understanding of the mechanisms underlying the interaction between pain and PA/NA remains limited. Here, we used a validated task probing behavioral and neural responses to monetary rewards and losses in conjunction with functional magnetic resonance imaging (fMRI) to test the hypothesis that dysfunction of the striatum, a key mesolimbic structure involved in the encoding of motivational salience, relates to mood alterations comorbid with chronic pain.

METHODS

Twenty-eight chronic musculoskeletal pain patients (chronic low back pain, n=15; fibromyalgia, n=13) and 18 healthy controls underwent fMRI while performing the Monetary Incentive Delay (MID) task. Behavioral and neural responses were compared across groups and correlated against measures of depression (Beck Depression Inventory) and hedonic capacity (Snaith-Hamilton Pleasure Scale).

RESULTS

Compared to controls, patients demonstrated higher anhedonia and depression scores, and a dampening of striatal activation and incentive-related behavioral facilitation (reduction in reaction times) during reward and loss trials of the MID task (ps ​< ​0.05). In all participants, lower activation of the right striatum during reward trials was correlated with lower incentive-related behavioral facilitation and higher anhedonia scores (ps ​< ​0.05). Finally, among patients, lower bilateral striatal activation during loss trials was correlated with higher depression scores (ps ​< ​0.05).

CONCLUSIONS

In chronic pain, PA reduction and NA increase are accompanied by striatal hypofunction as measured by the MID task.

The AURORA Study: a longitudinal, multimodal library of brain biology and function after traumatic stress exposure

Adverse posttraumatic neuropsychiatric sequelae (APNS) are common among civilian trauma survivors and military veterans. These APNS, as traditionally classified, include posttraumatic stress, postconcussion syndrome, depression, and regional or widespread pain. Traditional classifications have come to hamper scientific progress because they artificially fragment APNS into siloed, syndromic diagnoses unmoored to discrete components of brain functioning and studied in isolation. These limitations in classification and ontology slow the discovery of pathophysiologic mechanisms, biobehavioral markers, risk prediction tools, and preventive/treatment interventions. Progress in overcoming these limitations has been challenging because such progress would require studies that both evaluate a broad spectrum of posttraumatic sequelae (to overcome fragmentation) and also perform in-depth biobehavioral evaluation (to index sequelae to domains of brain function). This article summarizes the methods of the Advancing Understanding of RecOvery afteR traumA (AURORA) Study. AURORA conducts a large-scale (n = 5000 target sample) in-depth assessment of APNS development using a state-of-the-art battery of self-report, neurocognitive, physiologic, digital phenotyping, psychophysical, neuroimaging, and genomic assessments, beginning in the early aftermath of trauma and continuing for 1 year. The goals of AURORA are to achieve improved phenotypes, prediction tools, and understanding of molecular mechanisms to inform the future development and testing of preventive and treatment interventions.