Synthese

, Volume 193, Issue 5, pp 1409–1432 | Cite as

Can visual cognitive neuroscience learn anything from the philosophy of language? Ambiguity and the topology of neural network models of multistable perception

Article

Abstract

The Necker cube and the productive class of related stimuli involving multiple depth interpretations driven by corner-like line junctions are often taken to be ambiguous. This idea is normally taken to be as little in need of defense as the claim that the Necker cube gives rise to multiple distinct percepts. In the philosophy of language, it is taken to be a substantive question whether a stimulus that affords multiple interpretations is a case of ambiguity. If we take into account what have been identified as hallmark features of ambiguity and look at the empirical record, it appears that the Necker cube and related stimuli are not ambiguous. I argue that this raises problems for extant models of multistable perception in cognitive neuroscience insofar as they are purported to apply to these stimuli. Helpfully, similar considerations also yield reasons to suggest that the relevant models are well motivated for other instances of multistable perception. However, a different breed of model seems to be required for the Necker cube and related stimuli. I end with a sketch how one may go about designing such a model relying on oscillatory patters in neural firing. I suggest that distinctions normally confined to the philosophy of language are important for the study of perception, a perspective with a growing number of adherents.

Keywords

Ambiguous figures Nonspecificity Neural models  Multistable perception Necker cube Communication-through-coherence (CTC) hypothesis Attention 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Faculty of PhilosophyUniversity of OxfordOxford UK

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