间隔计时:使用无启动/停止阈值漂移-扩散模型建模中断-运行-中断模式

IF 2.2 4区 心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Jason Zwicker, Francois Rivest
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引用次数: 1

摘要

动物的间隔时间通常是通过峰值间隔(PI)程序来研究的。在这个过程中,动物在刺激开始后的固定延迟后的第一个反应得到奖励,但在一些试验中,刺激仍然存在而不给予奖励。分析反应模式的标准方法和模型将其描述为中断-运行-中断,即低反应率随后是快速反应,然后是低反应率。对这种模式的研究发现,在不同物种和实验中,开始、停止和持续时间之间存在相关性。通常认为,为了实现起搏器累加器模型的统计,有必要具有启动和停止阈值。在本文中,我们将开发一个新的模型,根据事件发生的可能性来改变响应率,而不是一个阈值,以改变响应率。新模型再现了3篇不同论文中14个不同PI实验中观察到的开始和停止统计数据。该模型还与双阈值时间自适应漂移扩散模型(TDDM)和最新的包含标量期望理论的累加器模型(SET)进行了比较。结果表明,不需要明确的启动和停止阈值或内部等效的中断-运行-中断状态来重现单个试验统计数据,平均行为和中断-运行-中断分析结果。与TDDM相比,新模型还产生了更真实的个体试验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interval timing: Modelling the break-run-break pattern using start/stop threshold-less drift–diffusion model

Animal interval timing is often studied through the peak interval (PI) procedure. In this procedure, the animal is rewarded for the first response after a fixed delay from the stimulus onset, but on some trials, the stimulus remains and no reward is given. The standard methods and models to analyse the response pattern describe it as break-run-break, a period of low rate response followed by rapid responding, followed by a low rate of response. The study of the pattern has found correlations between start, stop, and duration of the run period that hold across species and experiments.

It is commonly assumed that to achieve the statistics with a pacemaker accumulator model, it is necessary to have start and stop thresholds. In this paper, we will develop a new model that varies response rate in relation to the likelihood of event occurrence, as opposed to a threshold, for changing the response rate. The new model reproduced the start and stop statistics that have been observed in 14 different PI experiments from 3 different papers. The developed model is also compared to the two-threshold Time-adaptive Drift–diffusion Model (TDDM), and the latest accumulator model subsuming the scalar expectancy theory (SET) on all 14 datasets. The results show that it is unnecessary to have explicit start and stop thresholds or an internal equivalent to break-run-break states to reproduce the individual trials statistics, the average behaviour, and the break-run-break analysis results. The new model also produces more realistic individual trials compared to TDDM.

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来源期刊
Journal of Mathematical Psychology
Journal of Mathematical Psychology 医学-数学跨学科应用
CiteScore
3.70
自引率
11.10%
发文量
37
审稿时长
20.2 weeks
期刊介绍: The Journal of Mathematical Psychology includes articles, monographs and reviews, notes and commentaries, and book reviews in all areas of mathematical psychology. Empirical and theoretical contributions are equally welcome. Areas of special interest include, but are not limited to, fundamental measurement and psychological process models, such as those based upon neural network or information processing concepts. A partial listing of substantive areas covered include sensation and perception, psychophysics, learning and memory, problem solving, judgment and decision-making, and motivation. The Journal of Mathematical Psychology is affiliated with the Society for Mathematical Psychology. Research Areas include: • Models for sensation and perception, learning, memory and thinking • Fundamental measurement and scaling • Decision making • Neural modeling and networks • Psychophysics and signal detection • Neuropsychological theories • Psycholinguistics • Motivational dynamics • Animal behavior • Psychometric theory
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