Specialist Neurons in Feature Extraction Are Responsible for Pattern Recognition Process in Insect Olfaction

  • Aaron Montero
  • Ramon Huerta
  • Francisco B. Rodriguez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9107)

Abstract

In the olfactory system we can observe two types of neurons based on their responses to odorants. Specialist neurons react to a few odorants, while generalist neurons respond to a wide range of them. These kinds of neurons can be observed in different parts of the olfactory system. In the antennal lobe (AL), these neurons encode odorant information and in the extrinsic neurons (ENs) of the mushroom bodies (MB) they can learn and identify different kind of odorants based on the selective and generalist response. The classification of specialists and generalists neurons in Kenyon cells (KCs), which serve as a bridge between AL and ENs, may seem arbitrary. However KCs have the unique mission of increasing the separability between different odorants, to achieve a better information processing performance. To carry out this function, the connections between the antennal lobe and Kenyon cells do not require a specific connectivity pattern. Since KCs can be specialists or generalists by chance and olfactory learning performance relies on their feature extraction capabilities, we analyze the role of generalist and specialist neurons in an olfactory discrimination task. Role that we studied by varying the percentage of these two kind of neurons in KC layer. We determined that specialist neurons are a decisive factor to perform optimal odorant classification.

Keywords

Pattern recognition Specialist neuron Generalist neuron Olfactory system Neural variability Supervised learning Heterogeneous threshold Lateral inhibition 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Aaron Montero
    • 1
  • Ramon Huerta
    • 1
    • 2
  • Francisco B. Rodriguez
    • 1
  1. 1.Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica SuperiorUniversidad Autónoma de MadridMadridSpain
  2. 2.BioCircuits InstituteUniversity of CaliforniaSan DiegoUSA

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