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Realistic neurons can compute the operations needed by quantum probability theory and other vector symbolic architectures

Published online by Cambridge University Press:  14 May 2013

Terrence C. Stewart
Affiliation:
Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, ON N2L 3G1, Canada. tcstewar@uwaterloo.cahttp://ctn.uwaterloo.ca/celiasmith@uwaterloo.ca
Chris Eliasmith
Affiliation:
Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, ON N2L 3G1, Canada. tcstewar@uwaterloo.cahttp://ctn.uwaterloo.ca/celiasmith@uwaterloo.ca

Abstract

Quantum probability (QP) theory can be seen as a type of vector symbolic architecture (VSA): mental states are vectors storing structured information and manipulated using algebraic operations. Furthermore, the operations needed by QP match those in other VSAs. This allows existing biologically realistic neural models to be adapted to provide a mechanistic explanation of the cognitive phenomena described in the target article by Pothos & Busemeyer (P&B).

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2013 

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