Decoding the time-course of object recognition in the human brain: From visual features to categorical decisions
Decoding the time-course of object recognition in the human brain: From visual features to categorical decisions
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DOI：
10.1016/j.neuropsychologia.2017.02.013
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发表时间：
2017-10-01
期刊：
影响因子：
2.6
通讯作者：
Carlson, Thomas A.
中科院分区：
文献类型：
--
作者：
Contini, Erika W.;Wardle, Susan G.;Carlson, Thomas A.
视觉对象识别是一个复杂的动态过程。多元模式分析方法，如解码，已经开始揭示大脑如何处理复杂的视觉信息。近年来，EEG和MEG的时间解码方法为评估目标识别的时间动态提供了潜力。本文综述了M/EEG时间序列解码方法对理解人脑视觉物体识别的贡献。与目前对视觉处理层次的理解一致，低层次的视觉特征在早期的可解码对象表征中占主导地位，而与对象类别相关的更抽象的表征则在后期出现。一个关键的发现是，对象处理的时间过程是高度动态和快速发展的，具有有限的可解码信息的时间泛化。一些研究考察了对象类别结构的出现，我们考虑了类别解码在多大程度上可以通过对低层次视觉特征的敏感性来解释。最后，我们评估了最近试图将人类行为与对象处理的神经时间过程联系起来的工作。
Visual object recognition is a complex, dynamic process. Multivariate pattern analysis methods, such as decoding, have begun to reveal how the brain processes complex visual information. Recently, temporal decoding methods for EEG and MEG have offered the potential to evaluate the temporal dynamics of object recognition. Here we review the contribution of M/EEG time-series decoding methods to understanding visual object recognition in the human brain. Consistent with the current understanding of the visual processing hierarchy, low-level visual features dominate decodable object representations early in the time-course, with more abstract representations related to object category emerging later. A key finding is that the time-course of object processing is highly dynamic and rapidly evolving, with limited temporal generalisation of decodable information. Several studies have examined the emergence of object category structure, and we consider to what degree category decoding can be explained by sensitivity to low-level visual features. Finally, we evaluate recent work attempting to link human behaviour to the neural time-course of object processing.