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Representation in Cognitive Science| old_uid | 17192 |
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| title | Representation in Cognitive Science |
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| start_date | 2019/02/04 |
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| schedule | 15h15 |
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| online | no |
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| details | Host: Benedetto de Martino |
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| summary | Representation lies at the heart of the cognitive sciences. Appeals to representational content are pervasive in psychology and cognitive neuroscience. They are the contents that are computed by the brain to generate behaviour. They carry the ‘information’ of information-processing psychology, but it is not just the information of mathematical information theory (e.g. Shannon information).
deCharms & Zador (2000, p. 614) argue that representation in the brain depends, not just on neural activity carrying information about the world, but also on its effect on cognitive processes and functional behaviour. Hunt et al. (2012, p. 474) argue that the ‘functional representations’ that are used by the brain can be quite different from the information content that an external observer would decode from neural activity. Grill-Spector & Weiner (2014) argue that functional representations should be identified with those found at David Marr’s algorithmic level of explanation (Marr 1982). There is thus some consensus that we need to go beyond information theory in order to home in on representational content. Nevertheless, the fundamental natural of this central explanatory construct is not yet fully understood.
Representation in Cognitive Science (2018) shows that these ideas can be turned into a fully worked-out theory of representational content – of how representations arise out of neural processing in the brain of an organism that performs tasks in its environment. This talk will introduce the framework set out in the book and show how it applies in one detailed case study.
The book is published by Oxford University Press with open access and can be downloaded for free from:http://bit.ly/RepnCognSci |
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| responsibles | Lawrence |
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