Time pressure affects the efficiency of perceptual processing in decisions under conflict
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The negative correlation between speed and accuracy in perceptual decision making is often explained as a tradeoff, where lowered decision boundaries under time pressure result in faster but more error-prone responses. Corresponding implementations in sequential sampling models confirmed the success of this account, which has led to the prevalent assumption that a second component of decision making, the efficiency of perceptual processing, is largely independent from temporal demands. To test the generality of this claim, we examined time pressure effects on decisions under conflict. Data from a flanker task were fit with a sequential sampling model that incorporates two successive phases of response selection, driven by the output of an early and late stage of stimulus selection, respectively. The fits revealed the canonical decrease of response boundaries with increasing time pressure. In addition, time pressure reduced the duration of non-decisional processes and impaired the early stage of stimulus selection, together with the subsequent first phase of response selection. The results show that the relation between speed and accuracy not only relies on the strategic adjustment of response boundaries but involves variations of processing efficiency. The findings support recent evidence of drift rate modulations in response to time pressure in simple perceptual decisions and confirm their validity in the context of more complex tasks.
KeywordsTime Pressure Response Selection Congruency Effect Drift Rate Incongruent Condition
We thank Michaela Rach for data acquisition and Leendert van Maanen for valuable comments on a previous version of this article. This research was supported by the German Research Foundation (DFG) through research unit FOR 1882 Psychoeconomics.
Conflict of interest
The authors declare that no competing interests exist.
- Abdi, H., & Williams, L. J. (2010). Jackknife. In N. Salkind (Ed.), Encyclopedia of Research Design (pp. 655–661). Thousand Oaks: Sage.Google Scholar
- Brent, R. P. (1973). Algorithms for function minimization without derivatives. Englewood-Cliffs: Prentice-Hall.Google Scholar
- Forstmann, B. U., Anwander, A., Schäfer, A., Neumann, J., Brown, S., Wagenmakers, E.-J., et al. (2010). Cortico-striatal connections predict control over speed and accuracy in perceptual decision making. Proceedings of the National Academy of Sciences of the United States of America, 107(36), 15916–15920. doi: 10.1073/pnas.1004932107.PubMedCentralPubMedCrossRefGoogle Scholar
- Forstmann, B. U., Dutilh, G., Brown, S., Neumann, J., von Cramon, D. Y., Ridderinkhof, K. R., et al. (2008). Striatum and pre-SMA facilitate decision-making under time pressure. Proceedings of the National Academy of Sciences of the United States of America, 105(45), 17538–17542. doi: 10.1073/pnas.0805903105.PubMedCentralPubMedCrossRefGoogle Scholar
- Forstmann, B. U., Tittgemeyer, M., Wagenmakers, E.-J., Derrfuss, J., Imperati, D., & Brown, S. (2011). The speed-accuracy tradeoff in the elderly brain: a structural model-based approach. The Journal of Neuroscience, 31(47), 17242–17249. doi: 10.1523/jneurosci.0309-11.2011.PubMedCrossRefGoogle Scholar
- Garrett, H.E. (1922). A study of the relation of accuracy to speed. Archives of Psychology, 56, 1–104.Google Scholar
- Gray, H. L., & Schucany, W. R. (1972). The generalized jackknife statistic. New York: Marcel Dekker.Google Scholar
- Hübner, R., & Töbel, L. (2012). Does attentional selectivity in the flanker task improve discretely or gradually? Frontiers in Psychology, 3, 434. doi: 10.3389/fpsyg.2012.00434.
- Jackson, P. R. (1986). Robust methods in statistics. In A. D. Lovie (Ed.), New developments in statistics for psychology and the social sciences (pp. 22–43). London: The British Psychological Society and Methuen.Google Scholar
- Mosteller, F., & Tukey, J. (1977). Data analysis and regression. Reading: Addison-Wesley.Google Scholar
- Rae, B., Heathcote, A., Donkin, C., Averell, L., & Brown, S. (2014). The hare and the tortoise: emphasizing speed can change the evidence used to make decisions. Journal of Experimental Psychology: Learning, Memory, and Cognition (in press).Google Scholar
- Rinkenauer, G., Osman, A., Ulrich, R., Müller-Gethmann, H., & Mattes, S. (2004). On the locus of speed-accuracy trade-off in reaction time: inferences from the lateralized readiness potential. Journal of Experimental Psychology: General, 133(2), 261–282. doi: 10.1037/0096-34126.96.36.1991.CrossRefGoogle Scholar
- Simon, J. R. (1990). The effects of an irrelevant directional cue on human information processing. In R. W. Proctor & T. G. Reeve (Eds.), Stimulus-response compatibility: an integrated perspective (pp. 31–86). Amsterdam: North-Holland.Google Scholar
- Vandekerckhove, J., Tuerlinckx, F., & Lee, M.D. (2008). A Bayesian approach to diffusion process models of decision-making. In V. Sloutsky, B. Love, & K. McRae (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 1429–1434). Austin.Google Scholar