کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9727842 | 1480211 | 2005 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Intensity coding in two-dimensional excitable neural networks
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موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
فیزیک ریاضی
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چکیده انگلیسی
In the light of recent experimental findings that gap junctions are essential for low level intensity detection in the sensory periphery, the Greenberg-Hastings cellular automaton is employed to model the response of a two-dimensional sensory network to external stimuli. We show that excitable elements (sensory neurons) that have a small dynamical range are shown to give rise to a collective large dynamical range. Therefore the network transfer (gain) function (which is Hill or Stevens law-like) is an emergent property generated from a pool of small dynamical range cells, providing a basis for a “neural psychophysics”. The growth of the dynamical range with the system size is approximately logarithmic, suggesting a functional role for electrical coupling. For a fixed number of neurons, the dynamical range displays a maximum as a function of the refractory period, which suggests experimental tests for the model. A biological application to ephaptic interactions in olfactory nerve fascicles is proposed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica A: Statistical Mechanics and its Applications - Volume 349, Issues 3â4, 15 April 2005, Pages 431-442
Journal: Physica A: Statistical Mechanics and its Applications - Volume 349, Issues 3â4, 15 April 2005, Pages 431-442
نویسندگان
Mauro Copelli, Osame Kinouchi,