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范畴学习对视觉皮层注意调制的影响。

The effect of category learning on attentional modulation of visual cortex.

机构信息

Florida State University, United States.

Florida State University, United States.

出版信息

Neuropsychologia. 2017 Sep;104:18-30. doi: 10.1016/j.neuropsychologia.2017.07.025. Epub 2017 Jul 25.

Abstract

Learning about visual object categories causes changes in the way we perceive those objects. One likely mechanism by which this occurs is the application of attention to potentially relevant objects. Here we test the hypothesis that category membership influences the allocation of attention, allowing attention to be applied not only to object features, but to entire categories. Participants briefly learned to categorize a set of novel cartoon animals after which EEG was recorded while participants distinguished between a target and non-target category. A second identical EEG session was conducted after two sessions of categorization practice. The category structure and task design allowed parametric manipulation of number of target features while holding feature frequency and category membership constant. We found no evidence that category membership influenced attentional selection: a postero-lateral negative component, labeled the selection negativity/N250, increased over time and was sensitive to number of target features, not target categories. In contrast, the right hemisphere N170 was not sensitive to target features. The P300 appeared sensitive to category in the first session, but showed a graded sensitivity to number of target features in the second session, possibly suggesting a transition from rule-based to similarity based categorization.

摘要

学习视觉对象类别会导致我们感知这些对象的方式发生变化。一种可能的机制是将注意力应用于潜在相关的对象。在这里,我们测试了这样一个假设,即类别成员身份会影响注意力的分配,从而不仅可以将注意力应用于对象特征,还可以应用于整个类别。参与者在短暂学习分类一组新的卡通动物后,记录了 EEG,而参与者则在目标和非目标类别之间进行区分。在进行了两次分类练习后,进行了第二次相同的 EEG 会话。类别结构和任务设计允许在保持特征频率和类别成员不变的情况下,对目标特征的数量进行参数化操作。我们没有发现类别成员身份会影响注意力选择的证据:一个后外侧负成分,标记为选择负性/N250,随着时间的推移而增加,并且对目标特征的数量敏感,而不是目标类别。相比之下,右半球 N170 对目标特征不敏感。在第一次会议中,P300 对类别敏感,但在第二次会议中,对目标特征的数量表现出分级敏感性,这可能表明从基于规则的分类到基于相似性的分类的转变。

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