Associative learning in a network model of Hermissenda crassicornis |
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Authors: | Susan A. Werness S. Dale Fay Kim T. Blackwell Thomas P. Vogl Daniel L. Alkon |
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Affiliation: | (1) Environmental Research Institute of Michigan, P.O. Box 134001, 48113-4001 Ann Arbor, MI, USA;(2) Environmental Research Institute of Michigan, 1101 Wilson Blvd, Suite 1100, 22209 Arlington, VA, USA;(3) Neural Systems Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, 20892 Bethesda, MD, USA |
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Abstract: | A time-varying Resistance-Capacitance (RC) circuit computer model was constructed based on known membrane and synaptic properties of the visualvestibular network of the marine snail Hermissenda crassicornis. Specific biophysical properties and synaptic connections of identified neurons are represented as lumped parameters (circuit elements) in the model; in the computer simulation, differential equations are approximated by difference equations. The model's output, membrane potential, an indirect measure of firing frequency, closely parallels the behavioral and electrophysiologic outputs of Hermissenda in response to the same input stimuli presented during and after associative learning. The parallelism of the computer modeled and the biologic outputs suggests that the model captures the features necessary and sufficient for associative learning. |
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