Bias and discriminability during emotional signal detection in melancholic depression

Abstract

BackgroundCognitive disturbances in depression are pernicious and so contribute strongly to the burden of the disorder. Cognitive function has been traditionally studied by challenging subjects with modality-specific psychometric tasks and analysing performance using standard analysis of variance. Whilst informative, such an approach may miss deeper perceptual and inferential mechanisms that potentially unify apparently divergent emotional and cognitive deficits. Here, we sought to elucidate basic psychophysical processes underlying the detection of emotionally salient signals across individuals with melancholic and non-melancholic depression.MethodsSixty participants completed an Affective Go/No-Go (AGN) task across negative, positive and neutral target stimuli blocks. We employed hierarchical Bayesian signal detection theory (SDT) to model psychometric performance across three equal groups of those with melancholic depression, those with a non-melancholic depression and healthy controls. This approach estimated likely response profiles (bias) and perceptual sensitivity (discriminability). Differences in the means of these measures speak to differences in the emotional signal detection between individuals across the groups, while differences in the variance reflect the heterogeneity of the groups themselves.ResultsMelancholic participants showed significantly decreased sensitivity to positive emotional stimuli compared to those in the non-melancholic group, and also had a significantly lower discriminability than healthy controls during the detection of neutral signals. The melancholic group also showed significantly higher variability in bias to both positive and negative emotionally salient material.ConclusionsDisturbances of emotional signal detection in melancholic depression appear dependent on emotional context, being biased during the detection of positive stimuli, consistent with a noisier representation of neutral stimuli. The greater heterogeneity of the bias across the melancholic group is consistent with a more labile disorder (i.e. variable across the day). Future work will aim to understand how these findings reflect specific individual differences (e.g. prior cognitive biases) and clarify whether such biases change dynamically during cognitive tasks as internal models of the sensorium are refined and updated in response to experience.

Deep brain stimulation for depression: Scientific issues and future directions

“…The latency of response observed in the open trials and the tendency of benefit to accrue as the duration of follow-up increases could in part reflect a gradual reorganisation of these pathoplastic personality changes. For the purposes of a placebo-controlled trial where it is not feasible to measure outcomes at 5 years, it may be more appropriate to assess specific aspects of the depression construct that approximate more ‘ biological ’ endophenotypes, such as emotional signal detection in a neuropsychological task (Hyett et al, 2014). These behavioural measures could themselves be measured more sensitively than clinician-rated scaled items, increasing the prospect of detecting a benefit from active treatment.…”

“…For the purposes of a placebo-controlled trial where it is not feasible to measure outcomes at 5 years, it may be more appropriate to assess specific aspects of the depression construct that approximate more 'biological' endophenotypes, such as emotional signal detection in a neuropsychological task (Hyett et al, 2014). All research groups exclude those with significant co-morbid personality vulnerabilities, but treatment-resistant psychiatric disorders are likely to have adverse effects on personality.…”

The conditional approach to evaluating detection performance

“…3 We set aside Bayesian approaches (Agresti, 2013, Ch. 3.6) at this point, which have so far not played a prominent role in applied studies evaluating detection performance; for an instructive example, see Hyett et al (2014).…”

The association between implicit and explicit affective inhibitory control, rumination and depressive symptoms

“…The AGN task has been shown to measure similar constructs as the original GNG task 32 , while also capturing the influence of emotional modulation of inhibitory processes 36 . Most studies that have used the GNG and AGN tasks in depressed individuals have collectively shown altered patterns of inhibitory control to specific emotional categories compared to healthy participants rather than a general inhibitory deficit irrespective of emotional valence 37 – 40 (but see 41 ). The few studies that have employed this paradigm in non-clinical or at-risk samples found reduced pre-potent inhibition to sad expressions in high ruminators 42 and in adolescents who later developed depression 43 .…”