Brand John, Johnson Aaron P
Department of Psychology, Concordia University Montreal, QC, Canada.
Department of Psychology, Concordia University Montreal, QC, Canada ; Centre for Interdisciplinary Research in Rehabilitation of Greater Montreal Montreal, QC, Canada.
Front Psychol. 2014 Dec 2;5:1274. doi: 10.3389/fpsyg.2014.01274. eCollection 2014.
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.
在四项实验中,我们研究了对分层纳冯图形的局部和全局水平的关注如何影响场景分类中使用的诊断性空间尺度信息的选择。我们通过要求观察者在完成全局和局部纳冯任务后立即对混合图像(即包含一幅图像的低空间频率(LSF)内容和另一幅图像的高空间频率(HSF)内容的图像)进行分类来探讨这个问题。混合图像可以根据其LSF或HSF内容进行分类;因此,使其成为研究诊断性空间尺度偏好的理想选择。尽管观察者对两种空间尺度都很敏感(实验1),但他们绝大多数更喜欢根据LSF内容对混合图像进行分类(实验2)。在实验3中,我们证明在完成全局纳冯任务后,基于LSF的混合图像分类更快,这表明与全局纳冯任务相关的LSF处理启动了混合图像中LSF的选择。在实验4中,重复实验3,但通过对刺激进行对比度平衡来抑制纳冯字母中的LSF信息,从而检验了这一假设。与实验3类似,观察者更喜欢根据LSF内容对混合图像进行分类;然而,与之相反的是,在完成全局纳冯任务后,基于LSF的混合图像分类比完成局部纳冯任务后要慢。