Simulating physiological and morphological properties of neurons with SNNAP (Simulator for Neural Networks and Action Potentials)
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CONTRIBUTORS:
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CONFERENCE NAME:
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CONF. LOCATION:
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Washington DC
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CONFERENCE YEAR:
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2000
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PUB TYPE:
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Conference Presentation
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SUBJECT(S):
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Neurobiology, neuroscience, simulations, computer models, neurophysiology
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DISCIPLINE:
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Biology
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HTTP:
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http://bjoern.brembs.net/download.php?view.18
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LANGUAGE:
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English
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PUB ID:
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103-425-987
(Last edited on
2006/04/13 05:27:25 GMT-6)
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SPONSOR(S):
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ABSTRACT:
Computer simulations enable researchers and students to explore processes that underlie neuronal function. To simplify and expand access to neural simulation software, we developed a general purpose Simulator for Neural Networks and Action Potentials (SNNAP; Ziv et al. 1994). SNNAP is versatile and user friendly, and it can be used by both researchers and students. SNNAP was implemented in the Java programming language, and thus, it can run on any computer. In SNNAP, the electrical properties of cells are described with Hodgkin-Huxley-type conductances; the connections among neurons can be electrical or chemical; and second messengers, modulation and synaptic plasticity can be simulated. Previous versions of SNNAP were limited in their ability to simulate multi compartmental cells, however. To address this limitation, a new version of SNNAP (Ver. 5.1b) was developed.
Version 5.1b of SNNAP incorporates tools that allow users to develop models based on morphological parameters, such as the diameter of a cell body or the width and length of a neuronal process. These morphological features, in turn, can be used to determine certain physiological parameters, such as the magnitude of ionic conductances. Simulations have been developed that illustrate several general principles of cellular neurobiology, such as the ways in which individual ionic currents contribute to the unique firing properties of cell, and the ways in which the complex morphology of a cell can effect its physiological properties and responses to synaptic inputs. Additional information is available at http://nba19.med.uth.tmc.edu/snnap/. (Supported by NIH grant RR11626)
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