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无关局部对象的内隐识别与分层刺激的全局/局部加工相互作用。

Implicit identification of irrelevant local objects interacts with global/local processing of hierarchical stimuli.

作者信息

Poirel N, Pineau A, Mellet E

机构信息

Groupe d'Imagerie Neurofonctionnelle (GIN) UMR 6194, CNRS, CEA, Univ. Caen and Univ. Paris V, France.

出版信息

Acta Psychol (Amst). 2006 Jul;122(3):321-36. doi: 10.1016/j.actpsy.2005.12.010. Epub 2006 Mar 29.

Abstract

This work aimed at studying interactions between automatic object identification and global/local perceptual processing. We designed a paradigm in which participants were presented with pairs of hierarchically organized items, composed of global forms made up of local forms. Both global and local forms could represent either objects or non-objects. Subjects were instructed to detect whether the two hierarchical items composing a pair were identical or different. In a dissimilar pair, items differed at one level (target level), the other level, made of similar forms on both sides, was irrelevant to perform the task. We hypothesized that the automatic identification of object could affect the global precedence principle defined by Navon. In agreement with our hypothesis, we found that when the irrelevant level was made of objects, the global precedence effect was reversed. In contrast, the irrelevant level had no effect when the target level included only objects, or when the irrelevant level was made of non-object, the global precedence principle was being preserved in these cases. This interaction is compatible with the existence of two distinct processes working in parallel, namely automatic identification and structural analysis, that could either interfere or act together for the detection of differences.

摘要

这项工作旨在研究自动物体识别与全局/局部感知处理之间的相互作用。我们设计了一种范式,向参与者呈现由局部形式构成的全局形式组成的分层组织的项目对。全局和局部形式都可以表示物体或非物体。受试者被要求检测组成一对的两个分层项目是相同还是不同。在不相似的一对中,项目在一个级别(目标级别)上不同,另一级别两侧由相似形式组成,与执行任务无关。我们假设物体的自动识别可能会影响Navon定义的全局优先原则。与我们的假设一致,我们发现当无关级别由物体组成时,全局优先效应会逆转。相反,当目标级别仅包含物体时,无关级别没有影响,或者当无关级别由非物体组成时,在这些情况下全局优先原则得以保留。这种相互作用与两个并行工作的不同过程的存在相一致,即自动识别和结构分析,它们在检测差异时可能相互干扰或共同起作用。

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