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Estimating non-decision time in visuo-saccadic response time

Authors
Dr. Aline Bompas
Cardiff University ~ CUBRIC - School of Psychology
Petroc Sumner
CUBRIC - School of Psychology, Cardiff University, United Kingdom
Craig Hedge
CUBRIC - School of Psychology, Cardiff University, United Kingdom
Abstract

The concept of non-decision time is essential to developing correct understanding and mathematical formulation of decision. Non-decision time represents the portion of a reaction time not devoted to the choice, and corresponds to the sum of sensory conduction delay and motor execution time. More accurate modelling assumptions regarding non-decision time are essential for obtaining reliable estimates of decision parameters.In recent work, we have shown how saccades’ sensitivity to visual transients can be used to precisely estimate non-decision time (Bompas et al. Psychological review 2020). This work relies on protocols where visual signals are presented after the onset of the saccade target (saccadic inhibition or stop-task). Using the biologically inspired model DINASAUR, we showed how the timing of interference (or dips) caused by visual transient within the reaction time distribution leads to precise estimates of non-decision time.However, these protocols are not commonly run in the field and often involve a large number of trials. Here we ask to what extent similar conclusions can be reached from simple reaction time data and quantify the impact of lower trial numbers. We first introduce data in which the same stimuli were used either as interfering signals (creating dips) or as saccade targets (producing simple RT distributions) in different blocks. We compare non-decision time estimates from 1) dip timing, 2) shortest RT and 3) drift diffusion model fits. Subsampling from several previous interference protocols with large numbers of trials, we then estimate the robustness of this methods across decreasing sample sizes.

Tags

Keywords

eye-movements
saccadic inhibition

Topics

Decision Making
Reaction Times
Accumulator/Diffusion models
Discussion
New
Estimation methods Last updated 2 months ago

Great work, Aline! Very nice ideas. There are broad statistical problems associated with estimating the lower bound in shifted distributions - these can cause the bad estimates for all three models you’ve observed. My collaborators and I have recently made great progress in addressing this. We now can get much better recovery of nondecision...

Dr. Scott Brown 1 comment

Thank you for your talk Dr. Bompas! I have a couple of questions. Are there two choices in the non-distractor task? While assuming a linear ballistic or sequential sampling process may be appropriate in these tasks, there may be a fundamental difference in these tasks compared to other tasks (even in the case of a non-saccadic response). The par...

Dr. Michael D. Nunez 1 comment

Thank you for your really clear and interesting talk. I have one major question that I assume you get asked often. You have extremely fast RTs in your data, so fast that most of them would be removed by most modelers when they apply decision making models in classical decision making tasks. Additionally there is a direct stimulus/response mappin...

Mr. Gabriel Weindel 1 comment