Characterizing the dynamics of mental representations: the temporal generalization method.

Characterizing the dynamics of mental representations: the temporal generalization method.
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DOI:
10.1016/j.tics.2014.01.002
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发表时间:
2014-04
影响因子:
19.9
通讯作者:
Dehaene S
Dehaene S
中科院分区:
心理学1区
文献类型:
--
作者:
King JR;Dehaene S

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将认知任务解析为一系列操作是认知神经科学的中心问题。我们认为,由于将模式分类器应用于大脑活动的时间分辨记录[脑电图(EEG)、脑磁图(MEG)或颅内记录],现在可能取得重大进展。通过测试特定心理内容在大脑活动中何时可被解码,我们可以表征认知代码的时间过程。最重要的是,经过训练的分类器跨时间、从一种实验条件到另一种实验条件的泛化方式揭示了信息处理阶段的时间组织。在各种实验和大脑区域中观察到了一系列典型的动力学模式。因此,这种方法提供了一种理解心理表征如何被操纵和转化的新方法。
Parsing a cognitive task into a sequence of operations is a central problem in cognitive neuroscience. We argue that a major advance is now possible owing to the application of pattern classifiers to time-resolved recordings of brain activity [electroencephalography (EEG), magnetoencephalography (MEG), or intracranial recordings]. By testing at which moment a specific mental content becomes decodable in brain activity, we can characterize the time course of cognitive codes. Most importantly, the manner in which the trained classifiers generalize across time, and from one experimental condition to another, sheds light on the temporal organization of information-processing stages. A repertoire of canonical dynamical patterns is observed across various experiments and brain regions. This method thus provides a novel way to understand how mental representations are manipulated and transformed.
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