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Digital Library

of the European Council for Modelling and Simulation

 

Title:

Olfaction As Probabilistic Inference – Abstract

Authors:

Peter Latham

Published in:

 

(2013).ECMS 2013 Proceedings edited by: W. Rekdalsbakken, R. T. Bye, H. Zhang  European Council for Modeling and Simulation. doi:10.7148/2013

 

ISBN: 978-0-9564944-6-7

 

27th European Conference on Modelling and Simulation,

Aalesund, Norway, May 27th – 30th, 2013

 

Citation format:

Peter Latham (2013). Olfaction As Probabilistic Inference - Abstract, ECMS 2013 Proceedings edited by: W. Rekdalsbakken, R. T. Bye, H. Zhang, European Council for Modeling and Simulation. doi:10.7148/2013-0022

 

DOI:

http://dx.doi.org/10.7148/2013-0022

Abstract:

Inferring what odors are in the air is a hard problem, for at least two reasons: the number of odorant receptor neurons (the first neurons in the olfactory pathway) is smaller than the number of possible odors, and multiple odors can be present at once. Consequently, even if there is a simple mapping from odors to odorant receptor neurons that mapping cannot be uniquely inverted. Presumably, the brain solves this problem by computing the probability that any particular odor is present. We present an inference algorithm that does this, discuss how it maps onto olfactory circuitry, and comment on what we learn about sensory processing in general.

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