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
中科院分区:
文献类型:
--
作者:
King JR;Dehaene S
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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