A population study of integrate-and-fire-or-burst neurons

Authors:
A. R. R. Casti;A. Omurtag;A. Sornborger;E. Kaplan;B. Knight;J. Victor;L. Sirovich
Affiliations:
Laboratory of Applied Mathematics, Mount Sinai School of Medicine, New York, NY;Laboratory of Applied Mathematics, Mount Sinai School of Medicine, New York, NY;Laboratory of Applied Mathematics, Mount Sinai School of Medicine, New York, NY;Laboratory of Applied Mathematics and Department of Ophthalmology, Mount Sinai School of Medicine, New York, NY;Laboratory of Applied Mathematics, Mount Sinai School of Medicine, New York, NY;Department of Neurology and Neuroscience, Weill Medical College of Cornell University, New York, NY;Laboratory of Applied Mathematics, Mount Sinai School of Medicine, New York, NY
Venue:
Neural Computation
Year:
2002

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Abstract

Any realistic model of the neuronal pathway from the retina to the visual cortex (V1) must account for the bursting behavior of neurons in the lateral geniculate nucleus (LGN). A robust but minimal model, the integrate-and-fire-or-burst (IFB) model, has recently been proposed for individual LGN neurons. Based on this, we derive a dynamic population model and study a population of such LGN cells. This population model, the first simulation of its kind evolving in a two-dimensional phase space, is used to study the behavior of bursting populations in response to diverse stimulus conditions.