City Research Online

Abstract

Events often unfold over a time course that is amenable to prediction, as when a sprinter learns the constant foreperiod from set to go. This lets us temporally prepare. For many foreperiod distributions, the conditional probability of an event (e.g. of a traffic light turning green) increases over time, so preparation should similarly increase, improving reaction times (RTs). Modelling has demonstrated such a quantitative match between mean RT across different foreperiods and the (inverted) subjective hazard function (or some related preparation function). However, modelling has provided few insights into how temporal preparation sculpts the tradeoff between RTs and anticipatory errors. Furthermore, the standard simplifying assumption that the subjective foreperiod distribution is stable offers no account of well-established history effects. To address these and several further issues, here we present a modelling architecture that incorporates an initial Stimulus Independent Process into a Non-Stationary Poisson account of simple Reaction Time (SIP-theN-SPuRT). SIP-theN-SPuRT derives a temporal preparation signal from an estimated foreperiod distribution that is updated from trial to trial. This signal, which may saturate at a physiological limit, feeds into three processes, reflecting urgency, modulation of drive from change detectors, and residual sensorimotor delays. We compared the predictions of nine SIP-theN-SPuRT model variants with new and existing simple-RT datasets. Best fits were obtained by the model in which each trial’s putative preparation signal gradually asymptotes (or saturates), after initially following a subjective hazard function. SIP-theN-SPuRT is, to our knowledge, unprecedented in explaining both foreperiod and history effects across entire simple RT distributions.

Publication Type:	Article
Additional Information:	© 2026 American Psychological Association. This is the accepted manuscript of an article published by American Psychological Association. Please refer to the publisher’s terms and conditions for information on re-use.
Publisher Keywords:	Temporal expectation, foreperiod effects, interval timing, simple RT, multilevel models
Subjects:	B Philosophy. Psychology. Religion > BF Psychology
Departments:	School of Health & Medical Sciences School of Health & Medical Sciences > Department of Psychology & Neuroscience
SWORD Depositor:	Symplectic Administrator

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