Analysis of sensory information using artificial neural networks and fuzzy logic

J. P. Stitt, S. Chyb, J. L. Frazier, F. E. Hanson

Research output: Contribution to journalConference articlepeer-review

Abstract

The feeding decisions are usually made by the insect central nervous system. A computational three-stage model that simulates feeding decisions by a caterpillar choosing among acceptable and unacceptable plants is being developed. This model is being developed in line with the objectives of determining which components of the sensory data are needed in the decision process and of elucidating the rules by which these decisions are made. The model being trained to associate chemosensory data with behavioral responses to the same stimulus can be challenged with sensory responses to an untested stimulus and asked to predict the feeding decision. The accuracy of the model is verified by comparing the simulated decisions with experimentally derived behavioral data. Finally, the analysis of the structure of a successfully trained ANN provides information about which activities and interactions of the chemosensory neurons shape the decision-making process.

Original languageEnglish (US)
Pages (from-to)1063-1064
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume16
Issue numberpt 2
StatePublished - 1994
EventProceedings of the 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 1 (of 2) - Baltimore, MD, USA
Duration: Nov 3 1994Nov 6 1994

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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