Efficient Coding Principle Applied To Sense Of Smell

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Main Category: Biology / Biochemistry
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Article Date: 24 Apr 2008 - 17:00 PST

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The efficient coding principle related to neurobiological processes can also apply to the sense of smell, according to an article published on April 25, 2008 in the open-access journal PLoS Computational Biology.

The efficient coding principle, which describes the adaptation of sensory neurons to the statistical characteristics of their natural stiumuli, has been applied to the visual and auditory systems. However, in this study, the sense of smell has been studied in this light, by quantitatively examining how female moths are located by their male mates through pheromones. The team, made up of researchers from the Czech Academy of Sciences and the French National Institute for Agricultural Research (INRA), chose to study the pheromone olfactory system because it is the only one in aerial mammals for which scientists have described the quantitative properties of both the natural stimulus and the reception processes.

They used these processes to determine the characteristics of the pheromone plume that was best detected by the male neuron reception system. Then, researchers matched those characteristics with those from plume measurements in the field, which in turn provided quantitative evidence that this system follows the efficient coding principle.

The team affirms that olfactory neurons in moths process the stimuli that occur most frequently in nature. They also note that the study was confined to early detection events, in particular the interaction of pheromone molecules membrane receptors. By exploring the quantitative relationship between the properties of biological sensory systems and their natural environment should create a better understanding of neural functions and evolutionary processes while improving the design of artificial sensory systems.

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PLoS Computational Biology (www.ploscompbiol.org) features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. All works published in PLoS Computational Biology are open access. Everything is immediately available subject only to the condition that the original authorship and source are properly attributed. Copyright is retained by the authors. The Public Library of Science uses the Creative Commons Attribution License.

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Efficient Olfactory Coding in the Pheromone Receptor Neuron of a Moth.
Kostal L, Lansky P, Rospars J-P 
PLoS Comput Biol 4(4):e1000053.
doi:10.1371/journal.pcbi.1000053
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Written by Anna Sophia McKenney
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