title: Quantitative modeling of responses of anuran retina: stimulus shape and size dependency.
abstract: Teeters and Arbib presented a model of the anuran retina which qualitatively accounts for the characteristic response properties used to distinguish ganglion cell type in anurans. In this paper we test the model's ability to reproduce quantitatively tabulated data on the dependency on stimulus shape and size, with a new implementation of the model in the neural simulation language NSL. Data of Ewert and Hock relating toad R2, R3, and R4 ganglion cell responses to moving worm, antiworm, and square-shaped stimuli of various edge lengths are used to test stimulus shape and size dependency. A close match to the data can be achieved by tuning some of the model parameters while still retaining the characteristic responses to the typical stimulus types. We stress here the importance of a populational approach to the models. We place more emphasis on the variation of response properties in a population of neurons of the same class, rather than questing for the neuron of a given type. As an example of the populational approach we offer a model for the respiratory R3 response following researchers who argue that a subclass of R3 neurons are activated by stationary boundaries owing to the anuran's self induced respiratory eye movement.
authors.affiliation: Center for Neural Engineering, University of Southern California, Los Angeles 90089-2520.
authors.forename: J L
authors.initials: JL
authors.lastname: Teeters
authors.forename: M A
authors.initials: MA
authors.lastname: Arbib
authors.forename: F
authors.initials: F
authors.lastname: Corbacho
authors.forename: H B
authors.initials: HB
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D000818:Animals; D001001:Anura / Q000502:physiology*; D005556:Form Perception / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net; D012165:Retinal Ganglion Cells / Q000502:physiology*; D013997:Time Factors