Abstract
relying on models to estimate it. Here, we propose a biological definition of decision that includes perceptual discrimination and action selection, and in turn explicitly equates non-decision time with the minimum sensorimotor delay, or “deadtime”. We show how this delay is directly observable in behavioural data, without modelling assumptions, using the visual interference
approach. We apply this approach to 11 novel and archival datasets from humans and monkeys gathered from multiple labs. We validate the method by showing that visual properties (brightness, colour, size) consistently affect empirically measured visuomotor deadtime, as predicted by neurophysiology. We then show that endogenous factors (strategic slowing, attention) do not affect visuomotor deadtime. Therefore, visuomotor deadtime consistently satisfies widespread selective influence assumptions, in contrast to non-decision time parameters from model fits. Last, contrasting empirically observed visuomotor deadtime with non-decision
time estimates from the EZ, DDM and LBA models, we conclude that non-decision time parameter from these models is unlikely to consistently reflect visuomotor delays, neither at a group level nor for individual differences, in contrast to a widely held assumption.
| Original language | English |
|---|---|
| Journal | Psychological Review |
| Early online date | 11 Jul 2024 |
| DOIs | |
| Publication status | E-pub ahead of print - 11 Jul 2024 |
Bibliographical note
Copyright © 2024 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0; https://creativecommons.org/licenses/by/4.0). This license permits copying and redistributing the work in any medium or format, as well as adapting the material for any purpose, even commercially.Data Access Statement
All the data sets collected by the authors are available on the Open Science Framework, alongside the code used for analyses (any other study material, such as experiment code and raw data files, is available upon request). All links are inserted in the relevant methods section, where each data set is introduced. The raw data files from studies collected elsewhere can be requested to the corresponding author, Aline Bompas, pending permission from their owners (identified in the article and the acknowledgements). The code used to produce all the empirical and modeling figures in the article is available on the Open Science Framework (https://osf.io/gz9uc/, and this repository also contains links to all the other shared data sets mentioned above.Funding
The authors acknowledge funding from the School of Psychology at Cardiff University, the Economic and Social Research Council (Grant ES/K002325/1) and the Wellcome Trust (Grant 104943/Z/14/Z) awarded to Petroc Sumner. The authors are grateful to Steven P. Errington, Jeff Schall, and Antimo Buonocore for sharing data, and to Georgie Powell for useful feedback on the article. Authors declare no competing interest. None of the results in this article were preregistered. The original submitted version of this article was published on BIORXIV/2023/529290. Some of the results were presented at the Annual meeting of the Mathematical Psychology Association in 2020, the Christmas meeting of the Applied Vision Association in 2021, and the European Conference on Eye Movements in 2022. Open Access funding provided by Cardiff University.
| Funders | Funder number |
|---|---|
| Cardiff University | |
| Economic and Social Research Council | ES/K002325/1 |
| Wellcome Trust | 104943/Z/14/Z |
Keywords
- reaction time
- sensorimotor processes
- vision
- decision model