Computational Neuroscience: Trends in Research, 1997 by Andrew DeWan, Lana C. Rutherford, Gina G. Turrigiano PDF

By Andrew DeWan, Lana C. Rutherford, Gina G. Turrigiano (auth.), James M. Bower (eds.)

ISBN-10: 1475798008

ISBN-13: 9781475798005

ISBN-10: 1475798024

ISBN-13: 9781475798029

This quantity comprises papers provided on the 5th Annual Computational Neurosci­ ence assembly (CNS*96) held in Boston, Massachusetts, July 14 - 17, 1996. This assortment contains 148 of the 234 papers provided on the assembly. recognition for mceting presenta­ tion used to be in accordance with the peer overview of initial papers initially submitted in may well of 1996. The papers during this quantity symbolize ultimate types of this paintings submitted in January of 1997. As represented through this quantity, computational neuroscience maintains to extend in caliber, dimension and breadth of concentration as expanding numbers of neuroscientists are taking a computational method of knowing worried approach functionality. Defining computa­ tional neuroscience because the exploration of the way brains compute, it really is transparent that there's al­ such a lot no topic or region of recent neuroscience examine that isn't applicable for computational reports. The CNS conferences in addition to this quantity mirror this scope and di­ versity.

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Meffert MK . Premack BA and Schulman H l\itric oxide stimulates Ca2+ - independent synaptic vesicle release. Neuron 12: 1235-44, 1994 9. Hoyt KR , Tang LH . et al. Nitric oxide modulates NMDA-induced increases in intracellular Ca++ in cultured rat forebrain neurons. Brain Res. 592:310-6. 1992. 10. Tanaka T . Endogenous nitric oxide inhibits NMDA- and kainates- responses by a negative feedback system in rat hippocampal neurons. Brain Res. 631 :72--6. 1993 II. Meulemans A , Diffusion coefficients and half-lives of nitric oxide and N-nitroso-L-arginine in rat cortex Nellrosci.

1 Kinetics of NO Reacting with Its Target. The following kinetics of NO reacting with its target is assumed in this paper: NO + R <-> NO*R (2) R is the target of NO in either pre- or postsynaptic site. The cellular response to the presence of NO is considered to be: G = a[NORJ, a is a constant. (3 ) When at steady-state, G has a form of G = a[R] [NO] / { K + [NO] }, (4) where, K, a are constants. If we further assume [RJ retains as a constant during the reaction, G can be rewritten as: G = c[R] [NO] / { K + [NO] }, c is a constant.

We were interested to see how the graded synapses respond to more realistic waveforms. In response to square pulses in LP, the GrpSp in PO has a transient and a persistent component. These components depend differently on presynaptic potential. The response to a realistic waveform was a mixture of the two components seen with square pulses, both in amplitude and its dependence on the presynaptic potential. The graded synapse between LP and PO shows temporal depression when LP is stimulated repeatedly.

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Computational Neuroscience: Trends in Research, 1997 by Andrew DeWan, Lana C. Rutherford, Gina G. Turrigiano (auth.), James M. Bower (eds.)


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