
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:
9780956494467 27^{th}
European Conference on Modelling and Simulation, Aalesund, Norway, May 27^{th} –
30^{th}, 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:10.7148/20130022 
DOI: 
http://dx.doi.org/10.7148/20130022 
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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