Linking RDoC and HiTOP: A new interface for advancing psychiatric nosology and neuroscience

Key Points Question Are there differences in reinforcement learning between patients with mood and anxiety disorders and control individuals? Findings In this systematic review and meta-analysis, a novel computational simulation method showed differences in reinforcement learning between patients and control individuals. In particular, patients showed elevated punishment learning rates compared with control individuals. Meaning These findings show that patients may be more likely than control individuals to modify their behavior in response to punishments, suggesting a possible mechanistic treatment target for negative affective bias symptoms.

/pdf/reinforcement-learning-in-patients-with-mood-and-anxiety-39u1o08d.pdf

Reinforcement Learning in Patients With Mood and Anxiety Disorders vs Control Individuals

Deficits in cognition, reward processing, and motor function are clinical features relevant to both aging and depression. Individuals with late-life depression often show impairment across these domains, all of which are moderated by the functioning of dopaminergic circuits. As dopaminergic function declines with normal aging and increased inflammatory burden, the role of dopamine may be particularly salient for late-life depression. We review the literature examining the role of dopamine in the pathogenesis of depression, as well as how dopamine function changes with aging and is influenced by inflammation. Applying a Research Domain Criteria (RDoC) Initiative perspective, we then review work examining how dopaminergic signaling affects these domains, specifically focusing on Cognitive, Positive Valence, and Sensorimotor Systems. We propose a unified model incorporating the effects of aging and low-grade inflammation on dopaminergic functioning, with a resulting negative effect on cognition, reward processing, and motor function. Interplay between these systems may influence development of a depressive phenotype, with an initial deficit in one domain reinforcing decline in others. This model extends RDoC concepts into late-life depression while also providing opportunities for novel and personalized interventions.

Influences of dopaminergic system dysfunction on late-life depression

Depressive and anxiety disorders often comorbid, which causes more severe impairments. The high comorbidity and shared genetic and psychological factors between the 2 disorders have brought arguments about whether they represent a common construct, and whether the current classification is meaningful. In this editorial, a state-of-the-art overview of recent studies on the underlying mechanism of such comorbidity, and the association between and differentiation of the 2 disorders is provided. Recent studies employing data-driven approaches such as latent class analysis (LCA) and network analysis to investigate the symptomatology of depression and anxiety have indicated unique characteristics and bridging symptoms of their comorbidity. Whereas previous neurobiological and neuroendocrinological studies reported common alterations in prefrontal-limbic pathways, serotonergic projections and the hypothalamic-pituitary-adrenal (HPA) axis, recent research suggests that distinct neural circuits and heterogeneous changes in HPA activity may exist in depression when compared to anxiety. Lastly, both depression and anxiety have been long associated with decision-making deficits; however, emerging evidence from computational psychiatry demonstrate that there may be unique neurocognitive and computational alterations in each disorder. By investigating the common and unique symptomatic characteristics and underlying neurobiological and neurocomputational mechanisms of the 2 disorders as well as their comorbidity, it can be concluded that recent studies have greatly advanced our understanding of the etiology and neuropathophysiology of these disorders.

Recent advances in the study of the comorbidity of depressive and anxiety disorders.

Positive affect and reward processing in the treatment of depression, anxiety and trauma

Importance Dysfunctional reward processing is a leading candidate mechanism for the development of certain depressive symptoms, such as anhedonia. However, to our knowledge, there has not yet been a systematic assessment of whether and to what extent depression is associated with impairments on behavioral reward-processing tasks. Objective To determine whether depression is associated with impairments in reward-processing behavior. Data Sources The MEDLINE/PubMed, Embase, and PsycInfo databases were searched for studies that investigated reward processing using performance on behavioral tasks by individuals with depression and nondepressed control groups, published between January 1, 1946, and August 16, 2019. Study Selection Studies that contained data regarding performance by depressed and healthy control groups on reward-processing tasks were included in the systematic review and meta-analysis. Data Extraction and Synthesis Summary statistics comparing performance between depressed and healthy groups on reward-processing tasks were converted to standardized mean difference (SMD) scores, from which summary effect sizes for overall impairment in reward processing and 4 subcomponent categories were calculated. Study quality, heterogeneity, replicability-index, and publication bias were also assessed. Main Outcome and Measures Performance on reward-processing tasks. Results The final data set comprised 48 case-control studies (1387 healthy control individuals and 1767 individuals with major depressive disorder). The mean age was 37.85 years and 58% of the participants were women. These studies used tasks assessing option valuation (n = 9), reward bias (n = 6), reward response vigor (n = 12), reinforcement learning (n = 20), and grip force (n = 1). Across all tasks, depression was associated with small to medium impairments in reward-processing behavior (SMD = 0.345; 95% CI, 0.209-0.480). When examining reward-processing subcomponent categories, impairment was associated with tasks assessing option valuation (SMD = 0.309; 95% CI, 0.147-0.471), reward bias (SMD = 0.644; 95% CI, 0.270-1.017), and reinforcement learning (SMD = 0.352; 95% CI, 0.115-0.588) but not reward response vigor (SMD = 0.083; 95% CI, −0.144 to 0.309). The medication status of the major depressive disorder sample did not explain any of the variance in the overall effect size. There was significant between-study heterogeneity overall and in all subcomponent categories other than option valuation. Significant publication bias was identified overall and in the reinforcement learning category. Conclusions and Relevance Relative to healthy control individuals, individuals with depression exhibit reward-processing impairments, particularly for tests of reward bias, option valuation, and reinforcement learning. Understanding the neural mechanisms driving these associations may assist in designing novel interventions.

/pdf/reward-processing-behavior-in-depressed-participants-20thy29v9i.pdf

Reward-Processing Behavior in Depressed Participants Relative to Healthy Volunteers: A Systematic Review and Meta-analysis.

Anxiety can be an adaptive process that promotes harm avoidance. It is accompanied by shifts in cognitive processing, but the precise nature of these changes and the neural mechanisms that underlie them are not fully understood. One theory is that anxiety impairs concurrent (non-harm related) cognitive processing by commandeering finite neurocognitive resources. For example, we have previously shown that anxiety reliably ‘speeds up time’, promoting temporal underestimation, possibly due to loss of temporal information. Whether this is due anxiety ‘overloading’ neurocognitive processing of time is unknown. We therefore set out to understand the neural correlates of this effect, examining whether anxiety and time processing overlap, particularly in regions of the cingulate cortex. Across two studies (an exploratory Study 1, N=13, followed by a pre-registered Study 2, N=29) we combined a well-established anxiety manipulation (threat of shock) with a temporal bisection task while participants were scanned using functional magnetic resonance imaging. Consistent with our previous work, time was perceived to pass more quickly under induced anxiety. Anxiety induction led to widespread activation in cingulate cortex, while the perception of longer intervals was associated with more circumscribed activation in a mid-cingulate area. Importantly, conjunction analysis identified convergence between anxiety and time processing in the insula and mid-cingulate cortex. These results provide tentative support for the hypothesis that anxiety impacts cognitive processing by overloading already-in-use neural resources. In particular, overloading mid-cingulate cortex capacity may drive emotion-related changes in temporal perception, consistent with the hypothesised role of this region in mediating cognitive affective and behavioural responses to anxiety.

https://biorxiv.org/content/10.1101/2020.07.11.198390v1.full.pdf

Anxiety makes time pass quicker: neural correlates

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Reward-Processing Behavior in Depressed Participants Relative to Healthy Volunteers: A Systematic Review and Meta-analysis.

Anxiety makes time pass quicker: neural correlates