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工作记忆对知觉类别学习的影响:问题与构想
引用本文:孙海龙,邢强,李爱梅. 工作记忆对知觉类别学习的影响:问题与构想[J]. 心理科学进展, 2017, 0(3): 424-430. DOI: 10.3724/SP.J.1042.2017.00424
作者姓名:孙海龙  邢强  李爱梅
作者单位:1. 暨南大学管理学院,广州510632;广州大学教育学院,广州510006;2. 广州大学教育学院,广州,510006;3. 暨南大学管理学院,广州,510632
基金项目:广州市第三届市属高校“羊城学者”项目“类别学习双系统模型:基于行为和ERP研究”(1201561646)
摘    要:人们学习将感知到的客体按照不同的标准或规则分类存储,即类别学习。而工作记忆作为多种认知加工的基础,对类别学习具有重要作用。基于已有研究,分别梳理了言语工作记忆和视空工作记忆对基于规则和信息整合类别结构的影响。目前,执行功能是否影响内隐类别学习系统、工作记忆负荷对内隐外显类别学习系统的影响是否一致还存在争议。此外,工作记忆影响知觉类别学习的认知加工阶段尚不清晰。未来的研究还需明确工作记忆负荷对内隐和外显类别学习的影响,进一步验证工作记忆影响类别学习的认知加工阶段假设的合理性。

关 键 词:工作记忆  视觉加工  类别学习  基于规则类别结构  信息整合类别结构

The influence of working memory on perceptual category learning: Problem and conception
SUN Hailong,XING Qiang,LI Aimei. The influence of working memory on perceptual category learning: Problem and conception[J]. Advances In Psychological Science, 2017, 0(3): 424-430. DOI: 10.3724/SP.J.1042.2017.00424
Authors:SUN Hailong  XING Qiang  LI Aimei
Abstract:People tend to classify and store the cognitive objects according to different standards or rules,namely,category learning.As the basis of various cognitive processing,the working memory has an important effect on the category learning.Based on the existing researches,this paper combs the influence of the working memory on the implicit and explicit learning from three aspects of the executive function,visual processing and working memory capacity.At present,there are controversies about whether the executive function affects the implicit and explicit learning system and whether the working memory capacity has the consistent influence on the implicit and explicit learning system.What's more,whether the working memory influences the cognitive processing stage of the category learning is unclear.Therefore,the next stage needs to make clear the influence of its executive function on the implicit and explicit learning and further tests the reasonability of the influence of the working learning on the cognitive and processing model of the category learning.
Keywords:working memory  visual processing  category learning  rule-based category structure  information-integration category structure
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