Computational modelling of attentional selectivity in depression reveals perceptual deficits.

James A Grange,Michelle Rydon-Grange

doi:10.1017/s0033291720002652

Abstract

Depression is associated with broad deficits in cognitive control, including in visual selective attention tasks such as the flanker task. Previous computational modelling of depression and flanker task performance showed reduced pre-potent response bias and reduced executive control efficiency in depression. In the current study, we applied two computational models that account for the full dynamics of attentional selectivity. Across three large-scale online experiments (one exploratory experiment followed by two confirmatory - and pre-registered - experiments; total N = 923), we measured attentional selectivity via the flanker task and obtained measures of depression symptomology as well as anhedonia. We then fit two computational models that account for the dynamics of attentional selectivity: The dual-stage two-phase model, and the shrinking spotlight (SSP) model. No behavioural measures were related to depression symptomology or anhedonia. However, a parameter of the SSP model that indexes the strength of perceptual input was consistently negatively associated with the magnitude of depression symptomatology. The findings provide evidence for deficits in perceptual representations in depression. We discuss the implications of this in relation to the hypothesis that perceptual deficits potentially exacerbate control deficits in depression.

Highlights

Depression is associated with broad deficits in cognitive control, including in visual selective attention tasks such as the flanker task
Before presenting the results of the computational modelling, we provide an overview of the behavioural results to explore the magnitude of the flanker effect in both response time (RT) and error, as well as the relationship between these outcomes and questionnaire scores
The aim of the current study was to extend the findings of Dillon et al (2015) by fitting two computational models able to account jointly for accuracy and response time performance, as well as the ubiquitous improvement of attentional selectivity with time found in the flanker task

Summary

Introduction

Depression is associated with broad deficits in cognitive control, including in visual selective attention tasks such as the flanker task. Previous computational modelling of depression and flanker task performance showed reduced preprotent response bias and reduced executive control efficiency in depression. In the current study we applied two computational models that account for the full dynamics of attentional selectivity. Across 3 large-scale online experiments (one exploratory experiment followed by two confirmatory—and pre-registered—experiments; Total N = 923) we measured attentional selectivity via the flanker task and obtained measures of depression symptomology as well as anhedonia. We fit two computational models that account for the dynamics of attentional selectivity: The Dual-Stage Two Phase model, and the Shrinking Spotlight model. A parameter of the Shrinking Spotlight model that indexes the strength of perceptual input was consistently negatively associated with the magnitude of depression symtomology. We discuss the implications of this in relation to the hypothesis that perceptual deficits potentially exacerbate control deficits in depression

Objectives

Methods

Results

Conclusion