ArticleBiological cybernetics1992
Associative learning in a network model of Hermissenda crassicornis. I. Theory.
Article in Biological cybernetics, 1992. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- The Model Organism Hermissenda crassicornis (Gastropoda: Heterobranchia) Is a Species Complex.PloS one · 2016Article
- Modeling Hermissenda: II. Effects of variations in type-B cell excitability, synaptic strength, and network architecture.Journal of computational neuroscience · 1996Article
- Modeling Hermissenda: I. Differential contributions of IA and IC to type-B cell plasticity.Journal of computational neuroscience · 1996Article
- Associative learning in a network model of Hermissenda crassicornis. II. Experiments.Biological cybernetics · 1993Article
- Associative learning in a network model of Hermissenda crassicornis. I. Theory.Biological cybernetics · 1992Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
A time-varying Resistance-Capacitance (RC) circuit computer model was constructed based on known membrane and synaptic properties of the visual-vestibular 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.