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2 results

  • Computational modelling of attentional selectivity in depression reveals perceptual deficits

  • James A. Grange, Michelle Rydon-Grange
  • Journal:
    Psychological Medicine / Volume 52 / Issue 5 / April 2022
    Published online by Cambridge University Press:
    27 July 2020, pp. 904-913
  • Background

    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.

    Method

    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.

    Results

    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.

    Conclusions

    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.

  • 9 - Beyond CODA

  • Thora Tenbrink, Bangor University
  • Book:
    Cognitive Discourse Analysis
    Published online:
    23 January 2020
    Print publication:
    13 February 2020, pp 226-250

  • Summary

    Chapter 9 looks beyond CODA in two ways. On the one hand, CODA is only one among many established ways to examine human thought; linguistic analysis can be easily and fruitfully combined with other methods. The first half of this chapter addresses triangulation with performance and other observable data as well as subtler measures such as reaction times and eye movements, and also includes brief discussions of cognitive modelling and corpus linguistic methods. On the other hand, CODA is rarely used purely for its own sake; more often than not, linguistic analysis is part of a wider goal. Results can be used for a multitude of applications and purposes, including implementation in automatic systems that support human everyday needs. Therefore, the second half of Chapter 9 concludes the book with a discussion of practical applications for the methodology in academia and beyond, in applied and interdisciplinary fields such as architecture and artificial intelligence, and also looks at how CODA results can be made more accessible using suitable visualisation tools. The final section provides a brief wrap–up of the book's main messages.