Dissecting the components of error in analogue report tasks

• Published in: Behavior research methods 2024-12, Vol.56 (8), p.8196-8213
• Main Authors: Tomić, Ivan, Adamcová, Dagmar, Fehér, Máté, Bays, Paul M.
• Format: Article
• Language: English
• Subjects: Adult; Attention - physiology; Attention task; Behavioral Science and Psychology; Cognitive Psychology; Color Perception - physiology; Female; Humans; Male; Memory; Memory - physiology; Mental task performance; Motor task performance; Original Manuscript; Psychology; Psychomotor Performance - physiology; Reaction Time - physiology; Reproducibility of Results; Visual perception; Visual Perception - physiology; Young Adult
• ISSN: 1554-3528; 1554-351X; 1554-3528
• DOI: 10.3758/s13428-024-02453-w

Over the last two decades, the analogue report task has become a standard method for measuring the fidelity of visual representations across research domains including perception, attention, and memory. Despite its widespread use, there has been no methodical investigation of the different task parameters that might contribute to response variability. To address this gap, we conducted two experiments manipulating components of a typical analogue report test of memory for colour hue. We found that human response errors were independently affected by changes in storage and maintenance requirements of the task, demonstrated by a strong effect of set size even in the absence of a memory delay. In contrast, response variability remained unaffected by physical size of the colour wheel, implying negligible contribution of motor noise to task performance, or by its chroma radius, highlighting non-uniformity of the standard colour space. Comparing analogue report to a matched forced-choice task, we found variation in adjustment criterion made a limited contribution to analogue report variability, becoming meaningful only with low representational noise. Our findings validate the analogue report task as a robust measure of representational fidelity for most purposes, while also quantifying non-representational sources of noise that would limit its reliability in specialized settings.