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空间频率对猕猴颞叶皮层中层次类别表征的影响。

The impact of spatial frequency on hierarchical category representation in macaque temporal cortex.

作者信息

Farhang Esmaeil, Toosi Ramin, Karami Behnam, Koushki Roxana, Kheirkhah Narges, Shakerian Farideh, Noroozi Jalaledin, Rezayat Ehsan, Vahabie Abdol-Hossein, Dehaqani Mohammad-Reza A

机构信息

School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.

School of Cognitive Sciences, Institute for Research in Fundamental Sciences, Tehran, Iran.

出版信息

Commun Biol. 2025 May 25;8(1):801. doi: 10.1038/s42003-025-08230-5.

DOI:10.1038/s42003-025-08230-5
PMID:40415067
Abstract

Objects are recognized in three hierarchical levels: superordinate, mid-level, and subordinate. Psychophysics shows that mid-level categories and low spatial frequency (LSF) information are rapidly recognized. However, the interaction between spatial frequency (SF) and abstraction is not well understood. To address this, we examine neural responses in the inferior temporal cortex and superior temporal sulcus of two male macaque monkeys. Our findings reveal that mid-level categories are well represented at both LSF and high SF (HSF), suggesting robust mid-level boundary maps in these areas, unaffected by SF changes. Conversely, superordinate category representation depends on HSF, indicating its crucial role in encoding global category information. The absence of subordinate representation in both LSF and HSF compared to intact stimuli further implies that full SF content is essential for fine-category processing. A supporting human psychophysics task confirms that superordinate categorization relies on HSF, while subordinate object recognition requires both LSF and HSF.

摘要

物体在三个层次水平上被识别

上级、中级和下级。心理物理学表明,中级类别和低空间频率(LSF)信息能被快速识别。然而,空间频率(SF)与抽象之间的相互作用尚未得到很好的理解。为了解决这个问题,我们研究了两只雄性猕猴的颞下回和颞上沟的神经反应。我们的研究结果表明,中级类别在LSF和高空间频率(HSF)中都有很好的表征,这表明这些区域存在强大的中级边界图,不受SF变化的影响。相反,上级类别表征依赖于HSF,表明其在编码全局类别信息中的关键作用。与完整刺激相比,LSF和HSF中均不存在下级表征,这进一步意味着完整的SF内容对于精细类别处理至关重要。一项支持性的人类心理物理学任务证实,上级分类依赖于HSF,而下级物体识别则需要LSF和HSF。

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Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer.更精细水平的物体分类更多地依赖于更高的空间频率,且耗时更长。
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