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: Computational Modelling of the Brain; Modelling Approaches Michele Giugliano,Mario Negrello,Daniele Linaro Book 2022 Springer Nature Switze

[復(fù)制鏈接]
樓主: bradycardia
41#
發(fā)表于 2025-3-28 16:36:47 | 只看該作者
References and Additional Readings,s may be familiar with 1D models yet unfamiliar with the more detailed 3D description of neurons. As such, this chapter introduces some of the techniques used in detailed 3D, molecular modeling, and shows the steps required for building such models from a foundation of the more familiar 1D descripti
42#
發(fā)表于 2025-3-28 20:46:34 | 只看該作者
https://doi.org/10.1007/b138009ght on how dendrites contribute to neuronal and circuit computations. This chapter aims to help the interested reader build biophysical models incorporating dendrites by detailing how their electrophysiological properties can be described using simple mathematical frameworks. We start by discussing
43#
發(fā)表于 2025-3-29 00:25:26 | 只看該作者
44#
發(fā)表于 2025-3-29 03:32:59 | 只看該作者
45#
發(fā)表于 2025-3-29 09:49:29 | 只看該作者
https://doi.org/10.1007/978-1-4615-0759-8n quantities. Exploiting organizational principles that link the plethora of data in a unifying framework can be useful for informing computational models. Besides overarching principles, we touch upon the most prominent features of brain organization that are likely to influence predicted neuronal
46#
發(fā)表于 2025-3-29 15:09:07 | 只看該作者
47#
發(fā)表于 2025-3-29 17:52:33 | 只看該作者
48#
發(fā)表于 2025-3-29 19:59:08 | 只看該作者
Modeling Neurons in 3D at the Nanoscales may be familiar with 1D models yet unfamiliar with the more detailed 3D description of neurons. As such, this chapter introduces some of the techniques used in detailed 3D, molecular modeling, and shows the steps required for building such models from a foundation of the more familiar 1D descripti
49#
發(fā)表于 2025-3-30 01:18:02 | 只看該作者
Modeling Dendrites and Spatially-Distributed Neuronal Membrane Propertiesght on how dendrites contribute to neuronal and circuit computations. This chapter aims to help the interested reader build biophysical models incorporating dendrites by detailing how their electrophysiological properties can be described using simple mathematical frameworks. We start by discussing
50#
發(fā)表于 2025-3-30 07:32:18 | 只看該作者
The Mean Field Approach for Populations of Spiking Neuronsequations for populations of integrate-and-fire neurons. An effort is made to derive the main equations of the theory using only elementary methods from calculus and probability theory. The chapter ends with a discussion of the assumptions of the theory and some of the consequences of violating thos
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-9 07:16
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
开鲁县| 随州市| 阳江市| 贡嘎县| 广德县| 会同县| 全椒县| 朝阳县| 历史| 同德县| 鄄城县| 柳河县| 房山区| 类乌齐县| 乌兰察布市| 唐海县| 青冈县| 朝阳区| 德令哈市| 嘉义县| 天峨县| 台中市| 晋宁县| 集贤县| 晋中市| 晋州市| 临沭县| 吉木萨尔县| 泸定县| 怀集县| 九龙城区| 当阳市| 伊吾县| 龙山县| 旬邑县| 天长市| 鄂托克旗| 康乐县| 溆浦县| 田东县| 永顺县|