Figures
Moth antennal neurons adjust their encoding optimally with respect to pheromone fluctuations
Sensory neural systems of living organisms encode the representation of their environment with remarkable efficiency. This is manifested, e.g., in the way how male moths perform long-distance searches of their females by tracking the pheromone plumes. In the study "Moth olfactory receptor neurons adjust their encoding efficiency to temporal statistics of pheromone fluctuations" Levakova et al. analyzed responses of pheromone-specific antennal neurons to naturalistic stimulation. It was shown that the coding accuracy and the stimulus distribution are in the optimal relationship as predicted by both information theory and statistical estimation theory.
Image Credit: Marie Levakova
Citation: (2018) PLoS Computational Biology Issue Image | Vol. 14(11) November 2018. PLoS Comput Biol 14(11): ev14.i11. https://doi.org/10.1371/image.pcbi.v14.i11
Published: November 30, 2018
Copyright: © 2018 Levakova. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Sensory neural systems of living organisms encode the representation of their environment with remarkable efficiency. This is manifested, e.g., in the way how male moths perform long-distance searches of their females by tracking the pheromone plumes. In the study "Moth olfactory receptor neurons adjust their encoding efficiency to temporal statistics of pheromone fluctuations" Levakova et al. analyzed responses of pheromone-specific antennal neurons to naturalistic stimulation. It was shown that the coding accuracy and the stimulus distribution are in the optimal relationship as predicted by both information theory and statistical estimation theory.
Image Credit: Marie Levakova