Diffusion Modeling and Intelligence: Drift Rates Show Both Domain-General and Domain-Specific Relations With Intelligence
Diffusion Modeling and Intelligence: Drift Rates Show Both Domain-General and Domain-Specific Relations With Intelligence
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DOI：
10.1037/xge0000774
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发表时间：
2020-12-01
影响因子：
4.1
通讯作者：
Hagemann, Dirk
中科院分区：
文献类型：
--
作者：
Lerche, Veronika;von Krause, Mischa;Hagemann, Dirk
先前的一些研究报告了用扩散模型的漂移参数（Rateliff, 1978）测量的信息处理速度与一般智力之间的关系。这些研究大多只使用了很少的任务，没有一个使用更复杂的任务。相比之下，我们的研究（N = 125）基于18种不同的响应时间任务，这些任务在内容（数字、图形和语言）和复杂性（平均RTs约为600毫秒的快速任务与平均RTs约为3000毫秒的更复杂任务）方面各不相同。结构方程模型表明域通用漂移因子与一般智力之间存在很强的关系。此外，特定领域的信息处理速度因素与各自领域的智力测验分数密切相关。此外，更复杂任务中的信息处理速度解释了一般智力的额外差异。除了这些理论上的相关发现外，我们的研究还在方法上做出了贡献，表明在内容特定漂移率方面存在有意义的个体间差异，并且不仅快速任务，而且更复杂的任务也可以用扩散模型建模。
Several previous studies reported relationships between speed of information processing as measured with the drift parameter of the diffusion model (Rateliff, 1978) and general intelligence. Most of these studies utilized only few tasks and none of them used more complex tasks. In contrast, our study (N = 125) was based on a large battery of 18 different response time tasks that varied both in content (numeric, figural, and verbal) and complexity (fast tasks with mean RTs of ca. 600 ms vs. more complex tasks with mean RTs of ca. 3,000 ms). Structural equation models indicated a strong relationship between a domain-general drift factor and general intelligence. Beyond that, domain-specific speed of information processing factors were closely related to the respective domain scores of the intelligence test. Furthermore, speed of information processing in the more complex tasks explained additional variance in general intelligence. In addition to these theoretically relevant findings, our study also makes methodological contributions showing that there are meaningful interindividual differences in content specific drift rates and that not only fast tasks, but also more complex tasks can be modeled with the diffusion model.