Probabilistic Inference in Discrete Spaces Can Be Implemented into Networks of LIF Neurons

Probabilistic Inference in Discrete Spaces Can Be Implemented into Networks of LIF Neurons

The means by which cortical neural networks are able to efficiently solve inference problems remains an open question in computational neuroscience. Recently, abstract models of Bayesian computation in neural circuits have been proposed, but they lack a mechanistic interpretation at the single-cell...

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Bibliographic Details
Main Authors: Dimitri eProbst, Mihai Alexandru Petrovici, Ilja eBytschok, Johannes eBill, Dejan ePecevski, Johannes eSchemmel, Karlheinz eMeier
Format: Article
Language:English
Published: Frontiers Media S.A. 2015-02-01
Series:Frontiers in Computational Neuroscience
Subjects:
theoretical neuroscience
Neural coding
Graphical Models
MCMC
neuromorphic hardware
Bayesian theory
Online Access:http://journal.frontiersin.org/Journal/10.3389/fncom.2015.00013/full

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http://journal.frontiersin.org/Journal/10.3389/fncom.2015.00013/full

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