对象(语法)
视觉对象识别的认知神经科学
范畴变量
解码方法
心理学
可视对象
人工智能
视觉处理
视觉感受
模式识别(心理学)
计算机科学
认知心理学
沟通
认知科学
感知
机器学习
神经科学
电信
作者
Erika Contini,Susan G. Wardle,Thomas A. Carlson
标识
DOI:10.1016/j.neuropsychologia.2017.02.013
摘要
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.
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