The Decisive Role of Non-Decision Time for Interpreting the Parameters of Decision Making Models

Gabriel Weindel (), Thibault Gajdos (), Boris Burle () and Francois Xavier Alario ()
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Gabriel Weindel: LPC - Laboratoire de psychologie cognitive - AMU - Aix Marseille Université - CNRS - Centre National de la Recherche Scientifique, LNC - Laboratoire de Neurosciences Cognitives [Marseille] - AMU - Aix Marseille Université - CNRS - Centre National de la Recherche Scientifique
Thibault Gajdos: LPC - Laboratoire de psychologie cognitive - AMU - Aix Marseille Université - CNRS - Centre National de la Recherche Scientifique
Boris Burle: LNC - Laboratoire de Neurosciences Cognitives [Marseille] - AMU - Aix Marseille Université - CNRS - Centre National de la Recherche Scientifique
Francois Xavier Alario: LPC - Laboratoire de psychologie cognitive - AMU - Aix Marseille Université - CNRS - Centre National de la Recherche Scientifique

Working Papers from HAL

Abstract: Computational models of decision making are becoming increasingly popular to interpret reaction time and choice data in terms of decision and non-decision related processes. But current evidence remains scarce as to whether parameters of a mathematical model such as the Drift Diffusion Model (DDM) can recover genuine latent psychological processes. In this study, we combine an experimental approach using a decision making task with a physiological decomposition of each reaction time into a motor and pre-motor time using electro-myography. The aim is to test whether the non-decision time parameter of a DDM, assumed to contain encoding and motor processes, varies according to both psychophysical predictions of stimulus encoding and the physiological measurement of motor processes. Our results show that 1) the encoding time is accounted by a DDM only in the case of instructions emphasizing speed over accuracy and 2) that the onset of muscular activity does not sign the end of the accumulation of evidence. This questions the ability of DDM to account for how participants achieve speed-accuracy tradeoff as well as the interpretability of its parameters in terms of decision and non-decision processes.

Date: 2022-01-05
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Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:hal-03512930

DOI: 10.31234/osf.io/gewb3

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