Time-order error and scalar variance in a computational model of human timing: simulations and predictions

Maciej Komosinski,Adam Kups

doi:10.1186/s40469-015-0002-0

Abstract

This work introduces a computational model of human temporal discrimination mechanism – the Clock-Counter Timing Network. It is an artificial neural network implementation of a timing mechanism based on the informational architecture of the popular Scalar Timing Model. The model has been simulated in a virtual environment enabling computational experiments which imitate a temporal discrimination task – the two-alternative forced choice task. The influence of key parameters of the model (including the internal pacemaker speed and the variability of memory translation) on the network accuracy and the time-order error phenomenon has been evaluated. The results of simulations reveal how activities of different modules contribute to the overall performance of the model. While the number of significant effects is quite large, the article focuses on the relevant observations concerning the influence of the pacemaker speed and the scalar source of variance on the measured indicators of network performance. The results of performed experiments demonstrate consequences of the fundamental assumptions of the clock-counter model for the results in a temporal discrimination task. The results can be compared and verified in empirical experiments with human participants, especially when the modes of activity of the internal timing mechanism are changed because of some external conditions, or are impaired due to some kind of a neural degradation process.

Highlights

This work introduces a computational model of human temporal discrimination mechanism – the Clock-Counter Timing Network
The coefficient of variation in memory buffers was highly influenced by the activity of the Scalar Variance Module, the dependence of the coefficient of variation on the Pacemaker speed was especially visible when the presented stimuli lasted shortly
A high relative variability added by the Scalar Variance Module accompanied by the increased Pacemaker speed led to a faster stabilization of the coefficient of variation (cf. discussion on Weber’s law in (Komosinski, 2012))

Summary

Introduction

This work introduces a computational model of human temporal discrimination mechanism – the Clock-Counter Timing Network. Weiss 1987; Rammsayer and Ulrich 2001) These models are usually represented as sets of equations describing dependencies between physical properties of a stimulus and an internal, subjective representation of time. These psychophysical equations are sometimes closely related to the other groups of models, and may be seen as their specification. Models that are outside of the classification outlined above are described in (Shi et al 2013; Staddon and Higga 1999; Yamazaki and Tanaka 2005) Overall, these are good theoretical frameworks: they provide explanations to experimental data, some of them are equipped with tools allowing to perform advanced simulations, and some of them integrate knowledge and data from different scientific disciplines. A unified, commonly accepted theory of human timing is yet to be proposed

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