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Marnix Naber, Stephen Brown, Anneke Vedder, Sander Nieuwenhuis; Stimulus strength and visual competition contribute to individual differences in Stroop-Task performance. Journal of Vision 2015;15(12):1336. doi: https://doi.org/10.1167/15.12.1336.
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© ARVO (1962-2015); The Authors (2016-present)
The Stroop task is a popular test for measuring executive control. In this task subjects are shown words describing a color in a font color that mismatches its description. The word’s meaning distracts and slows reaction times when subjects have to report the word’s font color. This is called Stroop interference. Popular computational models of the Stroop task indicate that a competition between words and colors underlies Stroop interference. It is possible that some of the variance in Stroop interference across individuals may be explained by differences in visual pathway strength and differences in competition between stimulus categories, independent of executive control. We designed an electrophysiological and psychophysical experiment to examine the effects of these variables on Stroop interference. In experiment 1, observers were presented with words and colors in isolation and event-related potentials (ERP) were measured to determine relative visual pathway strength. In experiment 2, observers reported target disappearances caused by motion-induced blindness as an indication of the strength of competition in the visual system. Observers also performed the Stroop task after experiment 1 and 2. In experiment 1 we found that the relative latencies of the P3 ERP component to words and colors highly predicted Stroop interference (50% variance explained). Furthermore, in experiment 2 the strength of motion-induced-blindness also predicted Stroop interference (40% variance explained). In neither experiment, these effects could be explained by trial-to-trial fluctuations in cognitive control. Hence, we conclude that the Stroop effect is largely determined by an individual’s pre-set characteristics in visual processing and competition between feature categories.
Meeting abstract presented at VSS 2015
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