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From symbols to icons: the return of resemblance in the cognitive neuroscience revolution

Published version
Peer-reviewed

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Authors

Colling, L 

Abstract

We argue that one important aspect of the "cognitive neuroscience revolution" identified by Boone and Piccinini (2015) is a dramatic shift away from thinking of cognitive representations as arbitrary symbols towards thinking of them as icons that replicate structural characteristics of their targets. We argue that this shift has been driven both "from below" and "from above" - that is, from a greater appreciation of what mechanistic explanation of information-processing systems involves ("from below"), and from a greater appreciation of the problems solved by bio-cognitive systems, chiefly regulation and prediction ("from above"). We illustrate these arguments by reference to examples from cognitive neuroscience, principally representational similarity analysis and the emergence of (predictive) dynamical models as a central postulate in neurocognitive research.

Description

Keywords

Cognitive neuroscience revolution, Cognitive representation, Structural resemblance, Predictive processing, Representational similarity analysis, Emulation, Bayesian brain, Bayesian networks, Iconic, Mechanistic explanation, Information-processing, Free energy principle, Homeostasis, Predictive brain

Journal Title

Synthese

Conference Name

Journal ISSN

0039-7857
1573-0964

Volume Title

195

Publisher

Springer Science and Business Media LLC