Using diffusion models for symbolic numeracy tasks to examine aging effects.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Roger Ratcliff, Gail McKoon
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Abstract

We present a model-based analysis of aging effects in three symbolic numeracy tasks using three groups of subjects (young adults, 60- to 69-year-olds, and 70- to 90-year-olds). The tasks are number discrimination (is this number greater or less than 50), number memory (was this number in the list of numbers just displayed), and number line (point to where this number is on this number line). The first two tasks were fit by the standard two-choice diffusion model and the last one by the spatially continuous diffusion model (Ratcliff, 2018). Results showed good fits of the models to accuracy (choices) and response time distributions. In the tasks, nondecision time (the time to encode a stimulus and make a response) increased with age, but the amount of evidence needed for a decision (boundary settings) increased in the number discrimination and number memory tasks, but not the number line task. The number discrimination task produced conflicting accuracy and response time results as a function of age, but the model-based analyses resolved these differences. In the number memory task, drift rates (evidence used to drive the decision process) were lower for the older adults than for young adults, but for the other two (easier) tasks, there was no change in drift rate with age. The analyses extracted differences among individuals in model components, some of which were systematic across tasks. In particular, drift rates were correlated across tasks, which shows consistent individual differences across tasks, results that could not have been obtained without model-based analyses. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

利用符号运算任务的扩散模型研究老化效应。
我们利用三组受试者(年轻成年人、60 至 69 岁的老年人和 70 至 90 岁的老年人)对三种符号运算任务中的衰老效应进行了基于模型的分析。这些任务分别是数字辨别(这个数字大于或小于 50)、数字记忆(这个数字是否在刚才显示的数字列表中)和数列(指出这个数字在这条数列上的位置)。前两项任务采用标准双选扩散模型,最后一项任务采用空间连续扩散模型(Ratcliff,2018 年)。结果显示,模型与准确率(选择)和反应时间分布的拟合效果良好。在这些任务中,非决策时间(对刺激进行编码并做出反应的时间)随着年龄的增长而增加,但在数字辨别和数字记忆任务中,做出决策所需的证据量(边界设置)会增加,而在数字线任务中则不会。在数字辨别任务中,准确率和反应时间与年龄的函数关系产生了矛盾,但基于模型的分析解决了这些差异。在数字记忆任务中,老年人的漂移率(用于驱动决策过程的证据)低于年轻人,但在其他两项(较简单的)任务中,漂移率没有随年龄变化而变化。分析提取了不同个体在模型组成方面的差异,其中一些差异在不同任务中是系统性的。特别是,漂移率在不同任务间存在相关性,这表明不同任务间的个体差异是一致的,如果没有基于模型的分析,是无法得到这样的结果的。(PsycInfo Database Record (c) 2024 APA, 版权所有)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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