Abstract

Generative models of decision now permeate all subfields of psychology, cognitive, and clinical neuroscience. To successfully investigate decision mechanisms from behavior, it is necessary to assume the presence of delays prior and after the decision process itself. However, directly observing this "non-decision time (NDT)" from behavior long appeared beyond reach, the field mainly 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 NDT with the minimum sensorimotor delay, or "deadtime." We show how this delay is directly observable in behavioral data, without modeling assumptions, using the visual interference approach. We apply this approach to 11 novel and archival data sets from humans and monkeys gathered from multiple labs. We validate the method by showing that visual properties (brightness, color, size) consistently affect empirically measured visuomotor deadtime (VMDT), as predicted by neurophysiology. We then show that endogenous factors (strategic slowing, attention) do not affect VMDT. Therefore, VMDT consistently satisfies widespread selective influence assumptions, in contrast to NDT parameters from model fits. Last, contrasting empirically observed VMDT with NDT estimates from the EZ, drift diffusion, and linear ballistic accumulator models, we conclude that NDT parameters from these models are unlikely to consistently reflect visuomotor delays, neither at a group level nor for individual differences, in contrast to a widely held assumption. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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