Inflammation, stress and depression: An exploration of ketamine's therapeutic profile

Well-established animal models of depression have described a proximal relationship between stress and central nervous system (CNS) inflammation - a relationship mirrored in the peripheral inflammatory biomarkers of individuals with depression. Evidence also suggests that stress-induced proinflammatory states can contribute to the neurobiology of treatment-resistant depression. Interestingly, ketamine, a rapid-acting antidepressant, can partially exert its therapeutic effects via anti-inflammatory actions on the hypothalamic-pituitary adrenal (HPA) axis, the kynurenine pathway or by cytokine suppression. Further investigations into the relationship between ketamine, inflammation and stress could provide insight into ketamine's unique therapeutic mechanisms and stimulate efforts to develop rapid-acting, anti-inflammatory-based antidepressants.

Reliability of Decision-Making and Reinforcement Learning Computational Parameters

Computational models can offer mechanistic insight into cognition and therefore have the potential to transform our understanding of psychiatric disorders and their treatment. For translational efforts to be successful, it is imperative that computational measures capture individual characteristics reliably. Here we examine the reliability of reinforcement learning and economic models derived from two commonly used tasks. Healthy individuals (N = 50) completed a restless four-armed bandit and a calibrated gambling task twice, two weeks apart. Reward and punishment learning rates from the reinforcement learning model showed good reliability and reward and punishment sensitivity from the same model had fair reliability; while risk aversion and loss aversion parameters from a prospect theory model exhibited good and excellent reliability, respectively. Both models were further able to predict future behaviour above chance within individuals. This prediction was better when based on participants' own model parameters than other participants' parameter estimates. These results suggest that reinforcement learning, and particularly prospect theory parameters, as derived from a restless four-armed bandit and a calibrated gambling task, can be measured reliably to assess learning and decision-making mechanisms. Overall, these findings indicate the translational potential of clinically-relevant computational parameters for precision psychiatry.

How Representative are Neuroimaging Samples? Large-Scale Evidence for Trait Anxiety Differences Between fMRI and Behaviour-Only Research Participants

Over the past three decades, functional magnetic resonance imaging (fMRI) has become crucial to study how cognitive processes are implemented in the human brain. However, the question of whether participants recruited into fMRI studies differ from participants recruited into other study contexts has received little to no attention. This is particularly pertinent when effects fail to generalize across study contexts: for example, a behavioural effect discovered in a non-imaging context not replicating in a neuroimaging environment. Here, we tested the hypothesis, motivated by preliminary findings (N = 272), that fMRI participants differ from behaviour-only participants on one fundamental individual difference variable: trait anxiety. Analysing trait anxiety scores and possible confounding variables from healthy volunteers across multiple institutions (N = 3317), we found robust support for lower trait anxiety in fMRI study participants, consistent with a sampling or self-selection bias. The bias was larger in studies that relied on phone screening (compared with full in-person psychiatric screening), recruited at least partly from convenience samples (compared with community samples), and in pharmacology studies. Our findings highlight the need for surveying trait anxiety at recruitment and for appropriate screening procedures or sampling strategies to mitigate this bias.

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.

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.

Decision-Making in Suicidal Behavior: The Protective Role of Loss Aversion

BACKGROUND

Loss aversion is a central and well operationalized trait behavior that describes the tendency for humans to strongly prefer avoiding losses to making equivalent gains. Human decision-making is thus biased toward safer choices.

AIM

The aim of this study was to explore the relationship between loss aversion and suicidal behavior in a large cohort of adolescents recruited in 30 schools of seven European countries for a longitudinal study (Current Controlled Trials ISRCTN65120704). We hypothesized that individuals with higher loss aversion would be less likely to attempt suicide.

METHODS

A mixed monetary gamble task was used to generate loss aversion scores for each participant. Logistic regression was used to estimate the cross-sectional association between loss aversion and life-time suicide attempts in the baseline sample (N = 2,158; 156 attempters), and incident attempts were predicted in a 4-month prospective model (N = 1,763; 75 attempters). Multiple regression was used to estimate the association between loss aversion and suicidal ideation.

RESULTS

Loss aversion was a significant predictor of attempted suicide in both the cross-sectional (OR = 0.79; P = 0.005) and prospective analysis (OR = 0.81; P = 0.040), adjusting for depression, anxiety, stress, and sex. The correlation between pre and post measures of loss aversion was r = 0.52 (P < 0.001). Interestingly, although depression, anxiety, and stress were associated with suicidal ideation, loss aversion was not (cross-sectional model: P = 0.092; Prospective model: P = 0.390). This suggests that the concept of loss aversion may be useful in understanding the transition from suicidal thoughts to attempts.

CONCLUSION

This and previous studies suggest that altered decision-making is involved in suicide attempts. In our study, we show the involvement of loss aversion in particular, and propose that individuals high in loss aversion are discouraged from carrying out the suicide attempt because of a greater focus on the negative consequences of the decision.

Modeling Avoidance in Mood and Anxiety Disorders Using Reinforcement Learning

BACKGROUND

Serious and debilitating symptoms of anxiety are the most common mental health problem worldwide, accounting for around 5% of all adult years lived with disability in the developed world. Avoidance behavior-avoiding social situations for fear of embarrassment, for instance-is a core feature of such anxiety. However, as for many other psychiatric symptoms the biological mechanisms underlying avoidance remain unclear.

METHODS

Reinforcement learning models provide formal and testable characterizations of the mechanisms of decision making; here, we examine avoidance in these terms. A total of 101 healthy participants and individuals with mood and anxiety disorders completed an approach-avoidance go/no-go task under stress induced by threat of unpredictable shock.

RESULTS

We show an increased reliance in the mood and anxiety group on a parameter of our reinforcement learning model that characterizes a prepotent (pavlovian) bias to withhold responding in the face of negative outcomes. This was particularly the case when the mood and anxiety group was under stress.

CONCLUSIONS

This formal description of avoidance within the reinforcement learning framework provides a new means of linking clinical symptoms with biophysically plausible models of neural circuitry and, as such, takes us closer to a mechanistic understanding of mood and anxiety disorders.

Threat of shock and aversive inhibition: Induced anxiety modulates Pavlovian-instrumental interactions

Anxiety can be an adaptive response to potentially threatening situations. However, if experienced in inappropriate contexts, it can also lead to pathological and maladaptive anxiety disorders. Experimentally, anxiety can be induced in healthy individuals using the threat of shock (ToS) paradigm. Accumulating work with this paradigm suggests that anxiety promotes harm–avoidant mechanisms through enhanced inhibitory control. However, the specific cognitive mechanisms underlying anxiety-linked inhibitory control are unclear. Critically, behavioral inhibition can arise from at least 2 interacting valuation systems: instrumental (a goal-directed system) and Pavlovian (a “hardwired” reflexive system). The present study (N = 62) replicated a study showing improved response inhibition under ToS in healthy participants, and additionally examined the impact of ToS on aversive and appetitive Pavlovian-instrumental interactions in a reinforced go/no-go task. When Pavlovian and instrumental systems were in conflict, ToS increased inhibition to aversive events, while leaving appetitive interactions unperturbed. We argue that anxiety promotes avoidant behavior in potentially harmful situations by potentiating aversive Pavlovian reactions (i.e., promoting avoidance in the face of threats). Critically, such a mechanism would drive adaptive harm–avoidant behavior in threatening situations where Pavlovian and instrumental processes are aligned, but at the same time, result in maladaptive behaviors when misaligned and where instrumental control would be advantageous. This has important implications for our understanding of the mechanisms that underlie pathological anxiety.

The impact of induced anxiety on affective response inhibition

Studying the effects of experimentally induced anxiety in healthy volunteers may increase our understanding of the mechanisms underpinning anxiety disorders. Experimentally induced stress (via threat of unpredictable shock) improves accuracy at withholding a response on the sustained attention to response task (SART), and in separate studies improves accuracy to classify fearful faces, creating an affective bias. Integrating these findings, participants at two public science engagement events (n = 46, n = 55) were recruited to explore the effects of experimentally induced stress on an affective version of the SART. We hypothesized that we would see an improved accuracy at withholding a response to affectively congruent stimuli (i.e. increased accuracy at withholding a response to fearful 'no-go' distractors) under threat of shock. Induced anxiety slowed reaction time, and at the second event quicker responses were made to fearful stimuli. However, we did not observe improved inhibition overall during induced anxiety, and there was no evidence to suggest an interaction between induced anxiety and stimulus valence on response accuracy. Indeed Bayesian analysis provided decisive evidence against this hypothesis. We suggest that the presence of emotional stimuli might make the safe condition more anxiogenic, reducing the differential between conditions and knocking out any threat-potentiated improvement.

Mental Health First Aid is an effective public health intervention for improving knowledge, attitudes, and behaviour: a meta-analysis

Mental Health First Aid (MHFA) is a standardized, psychoeducational programme developed to empower the public to approach, support and refer individuals in distress by improving course participants' knowledge, attitudes and behaviours related to mental ill-health. The present paper aims to synthesize published evaluations of the MHFA programme in a meta-analysis to estimate its effects and potential as a public mental health awareness-increasing strategy. Fifteen relevant papers were identified through a systematic literature search. Standardized effect sizes were calculated for three different outcome measures: change in knowledge, attitudes, and helping behaviours. The results of the meta-analysis for these outcomes yielded a mean effect size of Glass's Δ = 0.56 (95% CI = 0.38 - 0.74; p < 0.001), 0.28 (95% CI = 0.22 - 0.35; p < 0.001) and 0.25 (95% CI = 0.12 - 0.38; p < 0.001), respectively. Results were homogenous, and moderator analyses suggested no systematic bias or differences in results related to study design (with or without control group) or 'publication quality' (journal impact factor). The results demonstrate that MHFA increases participants' knowledge regarding mental health, decreases their negative attitudes, and increases supportive behaviours toward individuals with mental health problems. The MHFA programme appears recommendable for public health action.

Improved effectiveness of performance monitoring in amateur instrumental musicians

Here we report a cross-sectional study investigating the influence of instrumental music practice on the ability to monitor for and respond to processing conflicts and performance errors. Behavioural and electrophysiological indicators of response monitoring in amateur musicians with various skill levels were collected using simple conflict tasks. The results show that instrumental musicians are better able than non-musicians to detect conflicts and errors as indicated by systematic increases in the amplitude of the error-related negativity and the N200 with increasing levels of instrumental practice. Also, high levels of musical training were associated with more efficient and less reactive responses after experience of conflicts and errors as indicated by reduced post-error interference and post-conflict processing adjustments. Together, the present findings suggest that playing a musical instrument might improve the ability to monitor our behavior and adjust our responses effectively when needed. As these processes are amongst the first to be affected by cognitive aging, our evidence could promote musical activity as a realistic intervention to slow or even prevent age-related decline in frontal cortex mediated executive functioning.

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We evaluated the effects of instrumental practice on cognitive control functions.

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We show that Instrumental practice affects the ability to detect errors and conflicts.

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We found an enlarged ERN and N200 in musicians compared to non-musicians.

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Musical training predicted less reactive control adjustments after conflicts/errors.