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Characterizing the dynamics of mental representations: the temporal generalization method
Author(s):
J-R. King
,
S. Dehaene
Publication date
Created:
April 2014
Publication date
(Print):
April 2014
Journal:
Trends in Cognitive Sciences
Publisher:
Elsevier BV
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There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.
Abstract
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. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Stigmatisation of mental illnesses
Author and article information
Journal
Title:
Trends in Cognitive Sciences
Abbreviated Title:
Trends in Cognitive Sciences
Publisher:
Elsevier BV
ISSN (Print):
13646613
Publication date Created:
April 2014
Publication date (Print):
April 2014
Volume
: 18
Issue
: 4
Pages
: 203-210
Article
DOI:
10.1016/j.tics.2014.01.002
PMC ID:
5635958
PubMed ID:
24593982
SO-VID:
a7ee0826-8b38-4356-988c-99b2d87a5a50
Copyright ©
© 2014
License:
https://www.elsevier.com/tdm/userlicense/1.0/
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