CCN meeting | Andrew Heathcote and Dora Matzke (University of Amsterdam, The Netherlands)
- When
- 11-10-2022 from 15:00 to 16:00
- Where
- Henri Dunantlaan 2, room 2.3 & https://teams.microsoft.com/l/meetup-join/19%3ameeting_Y2UzMWM1ZmUtODE2NS00ODNhLTg0MDgtZjhkN2VlMzU5ZWM1%40thread.v2/0?context=%7b%22Tid%22%3a%22d7811cde-ecef-496c-8f91-a1786241b99c%22%2c%22Oid%22%3a%2277e57739-e6a9-4a09-9c92-66fb4b3fd5e7%22%7d
- Language
- English
CCN meeting Andrew Heathcote and Dora Matzke, University of Amsterdam, The Netherlands) invited by: Roos Doekemeijer and Nico Boehler
A Discrete Activation-Suppression Model of Choice Conflict
Tasks like the Stroop, Simon and Flanker examine choice performance when where choice-relevant stimulus attributes are put in conflict with choice-irrelevant attributes. Such conflict tasks present a unique challenge for developing tractable evidence-accumulation models because evidence is thought to change during accumulation. The Diffusion Model for Conflict tasks (Ulrich et al., 2015) assumes a continuous change, with the impact of irrelevant information first increasing then decreasing due to the engagement of suppression mechanism, but applications are hampered by problems with parameter identifiability (White et al., 2018). Miller and Ulrich (2021) proposed a discrete approximation addressing only response time, where suppression races with stimulus encoding, with performance modelled by a mixture between the case where suppression wins and where it loses, and so responding is slowed. We extend their approach to address accuracy as well as response time, and also propose a tractable simplification. References: - Miller, J., & Schwarz, W. (2021). Delta plots for conflict tasks: An activation-suppression race model. Psychonomic Bulletin & Review, 28(6), 1776–1795. https://doi.org/10.3758/s13423-021-01900-5 - Ulrich, R., Schröter, H., Leuthold, H., & Birngruber, T. (2015). Automatic and controlled stimulus processing in conflict tasks: Superimposed diffusion processes and delta functions. Cognitive Psychology, 78(C), 148–174. https://doi.org/10.1016/j.cogpsych.2015.02.005 - White, C. N., Servant, M., & Logan, G. D. (2018). Testing the validity of conflict drift-diffusion models for use in estimating cognitive processes: A parameter-recovery study. Psychonomic Bulletin & Review, 25(1), 286–301. https://doi.org/10.3758/s13423-017-1271-2