PLoS Biology: Towards a Mathematical Theory of Cortical Micro-circuits (about Hawkins' ... - 1 views
www.ploscompbiol.org/...10.1371%2Fjournal.pcbi.1000532
neuroinformatics neuroscience HTM cortex PLoS hawkins
shared by Matvey Ezhov on 16 Oct 09
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The theoretical setting of hierarchical Bayesian inference is gaining acceptance as a framework for understanding cortical computation.
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Matvey Ezhov on 16 Oct 09Statement needs checking
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Friston recently expanded on this to suggest an inversion method for hierarchical Bayesian dynamic models and to point out that the brain, in principle, has the infrastructure needed to invert hierarchical dynamic models [6].
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In a recent review, Hegde and Felleman pointed out that the “Bayesian framework is not yet a neural model. [The Bayesian] framework currently helps explain the computations that underlie various brain functions, but not how the brain implements these computations” [2]. This paper is an attempt to fill this gap by deriving a computational model for cortical circuits based on the mathematics of Bayesian belief propagation in the context of a particular Bayesian framework called Hierarchical Temporal Memory (HTM).
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This paper's other author, George, recognized that the Memory-Prediction framework could be formulated in Bayesian terms and given a proper mathematical foundation [8],[9].
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Other researchers [4],[13] have proposed detailed mechanisms by which Bayesian belief propagation techniques can be implemented in neurons.