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On the similarities of the insect brain and pattern recognition algorithms

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We will describe the computational similarities between information processing in the insect brain and pattern recognition algorithms like support vector machines and the perceptron. The structural organization of the Mushroom bodies, the location of Hebbian learning, and the presence of inhibition can be framed in a convex optimization problem which is equivalent to the SVM. It is also noteworthy to show that simplified models of neurons can be mapped into realistic ones and vice versa. However, the mechanisms to keep the activity levels of neurons under controlled activity can be challenging in realistic neural networks, and perhaps this is the reason why there are some feedback control circuits in the Antennal Lobe and the Mushroom Bodies.

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Correspondence to Ramon Huerta.

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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Huerta, R. On the similarities of the insect brain and pattern recognition algorithms. Flavour 3, O16 (2014) doi:10.1186/2044-7248-3-S1-O16

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Keywords

  • Public Health
  • Neural Network
  • Support Vector Machine
  • Information Processing
  • Support Vector