摘要
基于COVIS模型与认知加工阶段假设,通过2个实验探讨嵌套范式下,视空工作记忆对基于规则类别学习的影响。实验1采用类别学习中嵌套视空工作记忆的范式,结果发现视空工作记忆削弱基于规则类别学习成绩,与COVIS模型的预测相一致。实验2则采用视空工作记忆中嵌套类别学习任务的范式,结果却发现视空工作记忆对基于规则类别学习的影响消失。实验结果表明嵌套范式下视空工作记忆的位置影响基于规则类别学习,初步验证了类别学习存在多个认知加工阶段的假设,视空工作记忆主要影响基于规则类别学习中规则的发现和检验阶段。
Perceptual categorization refers to organizing different perceptual objects into groups. Perceptual category structure is adopted by category learning, which repeatedly appears in an experiment with simple sensory stimulation (such as the length and angle changes on line, frequency and direction of grating). Rule-based category structure (RB) and Information Integration category structure (Ⅱ) are two kinds of perceptual categories. RB structures define category membership by the values of salient stimulus dimensions. The verbal system is able to learn to categorize such structures by identifying the relevant dimensions and discovering the appropriate rule. In contrast, Ⅱ structures define category membership by the conjoint rules which are not easily verbalizable in two or more dimensions. Consequently, such structures could not be learned by the verbal system. According to the COVIS model, which assumes that there are multiple systems in category learning, explicit category learning generates and tests simple verbalizable hypotheses and rules and depends on working memory. Thus visuo-spatial working memory will affect the rule-based category structure (RB), but not Information Integration category structure (II). Some studies have showed that working memory has different effects on implicit category learning and explicit category learning. But how the visuo-spatial working memory affects rule-based category learning? The mechanism of cognitive processing is still not yet clear, which is discussed in two experiments.
出处
《心理科学》
CSSCI
CSCD
北大核心
2017年第1期44-50,共7页
Journal of Psychological Science
基金
国家自然科学基金(31571144)
国家自然科学基金项目(71271101
71571087)的资助
关键词
视空工作记忆
认知加工阶段
基于规则类别学习
嵌套范式
visuo-spatial working memory, cognitive processing stage, based-ruled category learning, embedded paradigm