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使用高密度脑电图探索视觉皮层中物体类别的时空表示。

Using High-Density Electroencephalography to Explore Spatiotemporal Representations of Object Categories in Visual Cortex.

机构信息

Medical College of Wisconsin.

College of the Holy Cross.

出版信息

J Cogn Neurosci. 2022 May 2;34(6):967-987. doi: 10.1162/jocn_a_01845.

Abstract

Visual object perception involves neural processes that unfold over time and recruit multiple regions of the brain. Here, we use high-density EEG to investigate the spatiotemporal representations of object categories across the dorsal and ventral pathways. In , human participants were presented with images from two animate object categories (birds and insects) and two inanimate categories (tools and graspable objects). In , participants viewed images of tools and graspable objects from a different stimulus set, one in which a shape confound that often exists between these categories (elongation) was controlled for. To explore the temporal dynamics of object representations, we employed time-resolved multivariate pattern analysis on the EEG time series data. This was performed at the electrode level as well as in source space of two regions of interest: one encompassing the ventral pathway and another encompassing the dorsal pathway. Our results demonstrate shape, exemplar, and category information can be decoded from the EEG signal. Multivariate pattern analysis within source space revealed that both dorsal and ventral pathways contain information pertaining to shape, inanimate object categories, and animate object categories. Of particular interest, we note striking similarities obtained in both ventral stream and dorsal stream regions of interest. These findings provide insight into the spatio-temporal dynamics of object representation and contribute to a growing literature that has begun to redefine the traditional role of the dorsal pathway.

摘要

视觉物体感知涉及随时间展开并招募大脑多个区域的神经过程。在这里,我们使用高密度 EEG 来研究背侧和腹侧通路中物体类别的时空表示。在 ,人类参与者观看了来自两个有生命物体类别(鸟类和昆虫)和两个无生命类别(工具和可抓握物体)的图像。在 ,参与者观看了来自不同刺激集的工具和可抓握物体的图像,其中控制了这些类别之间经常存在的形状混淆(伸长)。为了探索物体表示的时间动态,我们对 EEG 时间序列数据进行了时间分辨的多变量模式分析。这是在电极水平以及两个感兴趣区域的源空间中进行的:一个包含腹侧通路,另一个包含背侧通路。我们的结果表明,可以从 EEG 信号中解码形状、范例和类别信息。源空间中的多变量模式分析表明,背侧和腹侧通路都包含与形状、无生命物体类别和有生命物体类别的信息。特别值得注意的是,我们注意到在感兴趣的腹侧流和背侧流区域都获得了惊人的相似性。这些发现提供了对物体表示的时空动态的深入了解,并为越来越多的文献做出了贡献,这些文献开始重新定义背侧通路的传统作用。

相似文献

本文引用的文献

1
What Does Dorsal Cortex Contribute to Perception?背侧皮质对感知有何作用?
Open Mind (Camb). 2020 Aug;4:40-56. doi: 10.1162/opmi_a_00033.
2
Untangling featural and conceptual object representations.解开特征和概念物体表示。
Neuroimage. 2019 Nov 15;202:116083. doi: 10.1016/j.neuroimage.2019.116083. Epub 2019 Aug 7.
7
Mid-level visual features underlie the high-level categorical organization of the ventral stream.中层视觉特征是腹侧流高级类别组织的基础。
Proc Natl Acad Sci U S A. 2018 Sep 18;115(38):E9015-E9024. doi: 10.1073/pnas.1719616115. Epub 2018 Aug 31.

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