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Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization

机译:注意局部和全局Navon层次图会影响场景的快速分类

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摘要

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks.
机译:在四个实验中,我们调查了对局部和全局Navon层次图的关注如何影响场景分类中使用的诊断空间尺度信息的选择。我们通过要求观察者对全局图像和局部Navon任务立即进行混合的图像(即包含一幅图像的低空间频率(LSF)内容和来自另一幅图像的高空间频率(HSF)内容的图像)进行分类来探讨此问题。可以根据混合图像的LSF或HSF内容对其进行分类。因此,使其成为调查诊断空间比例偏好的理想选择。尽管观察者对两个空间尺度都很敏感(实验1),但他们绝大多数还是倾向于根据LSF的含量对杂种进行分类(实验2)。在实验3中,我们证明了在全局Navon任务之后基于LSF的混合分类更快,这表明与全局Navon任务相关的LSF处理引发了混合图像中LSF的选择。在实验4中,复制实验3但通过对比平衡刺激抑制了Navon字母中的LSF信息,从而检验了这一假设。与实验3相似,观察者更喜欢根据LSF含量对杂交种进行分类。但是,与之相反,基于LSF的混合分类在全局跟踪之后比本地Navon任务慢。

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