Olfactory sensor processing in neural networks: lessons from modeling the fruit fly antennal lobe.

Frontiers in Neuroengineering
J Henning ProskeC Giovanni Galizia

Abstract

The insect olfactory system can be a model for artificial olfactory devices. In particular, Drosophila melanogaster due to its genetic tractability has yielded much information about the design and function of such systems in biology. In this study we investigate possible network topologies to separate representations of odors in the primary olfactory neuropil, the antennal lobe. In particular we compare networks based on stochastic and homogeneous connection weight distributions to connectivities that are based on the input correlations between the glomeruli in the antennal lobe. We show that moderate homogeneous inhibition implements a soft winner-take-all mechanism when paired with realistic input from a large meta-database of odor responses in receptor cells (DoOR database). The sparseness of representations increases with stronger inhibition. Excitation, on the other hand, pushes the representation of odors closer together thus making them harder to distinguish. We further analyze the relationship between different inhibitory network topologies and the properties of the receptor responses to different odors. We show that realistic input from the DoOR database has a relatively high entropy of activation values over all odor...Continue Reading

Citations

Feb 26, 2016·Scientific Reports·Daniel Münch, C Giovanni Galizia

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