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Neural Signaling of Probabilistic Vectors

Nicholas Shea
Philosophy of Science
Vol. 81, No. 5 (December 2014), pp. 902-913
DOI: 10.1086/678354
Stable URL: http://www.jstor.org/stable/10.1086/678354
Page Count: 12
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Neural Signaling of Probabilistic Vectors
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Abstract

Recent work combining cognitive neuroscience with computational modeling suggests that distributed patterns of neural firing may represent probability distributions. This article asks, what makes it the case that distributed patterns of firing, as well as carrying information about (correlating with) probability distributions over worldly parameters, represent such distributions? In examples of probabilistic population coding, it is the way information is used in downstream processing so as to lead to successful behavior. In these cases content depends on factors beyond bare information, contra Brian Skyrms’s view that representational content can be fully characterized in information-theoretic terms.

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