Journal article
Associative learning in a network model of Hermissenda crassicornis: II. Experiments
Biological cybernetics, Vol.69(1), pp.19-28
05/1993
DOI: 10.1007/BF00201405
PMID: 8334187
Abstract
A companion paper in a previous issue of this journal presented a resistance-capacitance circuit computer model of the four-neuron visual-vestibular network of the invertebrate marine mollusk Hermissenda crassicornis. In the present paper, we demonstrate that changes in the model's output in response to simulated associative training is quantitatively similar to behavioral and electrophysiological changes in response to associative training of Hermissenda crassicornis. Specifically, the model demonstrates many characteristics of conditioning: sensitivity to stimulus contingency, stimulus specificity, extinction, and savings. The model's learning features also are shown to be devoid of non-associative components. Thus, this computational model is an excellent tool for examining the information flow and dynamics of biological associative learning and for uncovering insights concerning associative learning, memory, and recall that can be applied to the development of artificial neural networks.
Details
- Title: Subtitle
- Associative learning in a network model of Hermissenda crassicornis: II. Experiments
- Creators
- Susan A. Werness - Environmental Research Institute of MichiganS. Dale FayKim T. Blackwell - Environmental Research Institute of MichiganThomas P. Vogl - Environmental Research Institute of MichiganDaniel L. Alkon - National Institute of Neurological Disorders and Stroke
- Resource Type
- Journal article
- Publication Details
- Biological cybernetics, Vol.69(1), pp.19-28
- DOI
- 10.1007/BF00201405
- PMID
- 8334187
- NLM abbreviation
- Biol Cybern
- ISSN
- 0340-1200
- eISSN
- 1432-0770
- Language
- English
- Date published
- 05/1993
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Iowa Neuroscience Institute
- Record Identifier
- 9984446459202771
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