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Titlebook: Neural Modeling; Electrical Signal Pr Ronald J. MacGregor,Edwin R. Lewis Book 1977 Plenum Press, New York 1977 Nervous System.brain.neural

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31#
發(fā)表于 2025-3-26 21:11:48 | 只看該作者
Statistical Analysis of Neuronal Spike Trainse other component which might comprise a “signal,” it is certainly clear that the methods and concepts of stochastic processes applied on an operational level can help to reveal many characteristics of neuroelectric events not readily apparent in other ways.
32#
發(fā)表于 2025-3-27 02:44:58 | 只看該作者
The Idealized “Standard Neuron”sed here, although in themselves not sufficient to account for all neural operation, seem to be essential ingredients used by the brain in its ongoing signal processing and certainly comprise essential background material for understanding contemporary research in the area.
33#
發(fā)表于 2025-3-27 09:19:42 | 只看該作者
Models of Spike Generation and Conductionrelated to the triggering of spikes by generator potentials and the subsequent attenuationless propagation of those spikes along neuronal fibers. We will progress from the iron-wire analogy of the 1920s, through the threshold/accommodation models of the 1930s, to the Hodgkin-Huxley model of the early 1950s.
34#
發(fā)表于 2025-3-27 09:39:03 | 只看該作者
35#
發(fā)表于 2025-3-27 13:53:19 | 只看該作者
bodying, or characterizing the processing of electrical signals in nervous systems. We believe that electrical signal processing is a vital determinant of the functional organization of the brain, and that in unraveling the inherent complexities of this processing it will be essential to utilize the
36#
發(fā)表于 2025-3-27 19:56:23 | 只看該作者
37#
發(fā)表于 2025-3-27 22:39:12 | 只看該作者
38#
發(fā)表于 2025-3-28 02:20:01 | 只看該作者
39#
發(fā)表于 2025-3-28 09:02:00 | 只看該作者
Models of Large Networks: Computer-Oriented Approaches view of neural-network dynamics which has been taken over, or at least influenced, by many analytically oriented researchers as well, as we saw in the previous chapter. In this chapter we discuss this basic source paper, its ramifications, and several contemporary examples of computer-oriented approaches to large neural networks.
40#
發(fā)表于 2025-3-28 11:47:49 | 只看該作者
Models of Passive Membraneconcentration gradient. In writing the Nernst-Planck equation, it is customary to deal with flow densities, i.e., the number of particles flowing through a unit of area in a unit of time. This quantity, usually labeled ., is particularly useful for membranes since one often is interested in the flow of particles through a given area of membrane.
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