Zeithamova Dagmar, Maddox W Todd
Department of Psychology, University of Texas, Austin, Texas 78712, USA.
Mem Cognit. 2006 Mar;34(2):387-98. doi: 10.3758/bf03193416.
The effect of a working-memory-demanding dual task on perceptual category learning was investigated. In Experiment 1, participants learned unidimensional rule-based or information integration category structures. In Experiment 2, participants learned a conjunctive rule-based category structure. In Experiment 1, unidimensional rule-based category learning was disrupted more by the dual working memory task than was information integration category learning. In addition, rule-based category learning differed qualitatively from information integration category learning in yielding a bimodal, rather than a normal, distribution of scores. Experiment 2 showed that rule-based learning can be disrupted by a dual working memory task even when both dimensions are relevant for optimal categorization. The results support the notion of at least two systems of category learning a hypothesis-testing system that seeks verbalizable rules and relies on working memory and selective attention, and an implicit system that is procedural-learning based and is essentially automatic.
研究了一项需要工作记忆的双重任务对知觉类别学习的影响。在实验1中,参与者学习基于单维度规则或信息整合的类别结构。在实验2中,参与者学习基于合取规则的类别结构。在实验1中,基于单维度规则的类别学习比信息整合类别学习更容易受到双重工作记忆任务的干扰。此外,基于规则的类别学习在分数分布上产生双峰而非正态分布,这在性质上不同于信息整合类别学习。实验2表明,即使两个维度都与最优分类相关,基于规则的学习也会受到双重工作记忆任务的干扰。这些结果支持了至少存在两种类别学习系统的观点:一种是寻求可言语化规则并依赖工作记忆和选择性注意的假设检验系统,另一种是基于程序学习且本质上是自动的内隐系统。