找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

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

[復制鏈接]
樓主: 共用
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.
 關于派博傳思  派博傳思旗下網站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網 吾愛論文網 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經驗總結 SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網安備110108008328) GMT+8, 2025-10-22 06:11
Copyright © 2001-2015 派博傳思   京公網安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
南溪县| 五台县| 绥德县| 屯留县| 洛宁县| 龙游县| 儋州市| 交口县| 应用必备| 绍兴县| 怀安县| 台南市| 清原| 彭泽县| 天祝| 龙泉市| 邯郸县| 嘉峪关市| 平塘县| 宁蒗| 华容县| 赫章县| 库尔勒市| 奇台县| 平和县| 石泉县| 丁青县| 板桥市| 西藏| 梓潼县| 敦煌市| 武乡县| 高雄市| 工布江达县| 和林格尔县| 郁南县| 永昌县| 玛沁县| 甘孜| 宾阳县| 济阳县|