從分子到網(wǎng)絡(luò)

出版時(shí)間:2010-6  出版社:科學(xué)  作者:(美)伯恩  頁(yè)數(shù):643  
Tag標(biāo)簽:無(wú)  

前言

  The second edition contains substantial improvements over the first edition. All chapters have been updated to include recent developments in the field, and major revisions have been done on the chapter son Energy Metabolism in the Brain, Molecular Properties of Ion Channels, Gap Junctions, and Learning and Memory. In addition, this edition features two new chapters, Information Processing in Neural Networks and Molecular and Cellular Mechanisms of Neurodegenerative Disease. Although the first edition covered biochemical and gene networks in significant detail, little was included on neural networks. It is the neural net-works in the brain that collect and process information about the external world and about the internal state of the body and generate motor commands. There fore, an understanding of these networks is essential to understanding the brain and also helps to put the cellular and molecular processes in perspective. However, discussing all of the brain systems is beyond the scope of a text book on cellular and molecular neuroscience. Rather, our goal is to describe the principles of operation of neural net-works and the key circuit motifs that are common to many networks. The second new chapter reports on the progress in the last 20 years on elucidating the cellular and molecular mechanisms underlying braindisorders This chapter focuses specifically on amyotrophic lateral sclerosis (ALS), Parkinson disease, and Alzheimers disease, and the progress that has been made and the strategies that have been used to study and treat the disorders. The fact that all three diseases are associated with neuronal loss, albeit indifferent brain regions and with different neurotransmitter groups, suggests that there may be commonaspects to the degenerative process.  We are once again extremely grateful to JohannesMenzel at Elsevier for his unfading support and encouragement throughout the project. Thanks also to Clare Caruana, Meg Day, Kristi Gomez, Kirsten Funk, Megan Wickline, and members of the production staff. Special thanks to Lorenzo Morales, thegraphic artist on the project, who did an out standing job of creating many of the illustrations in the secondedition and restyling all the illustrations for consistency among chapters. He also designed the coverillustration.

內(nèi)容概要

  過(guò)去二十年,人們對(duì)神經(jīng)系統(tǒng)各個(gè)層面的理解突飛猛進(jìn),其中最為突出的進(jìn)展,恐怕就是對(duì)于神經(jīng)元的細(xì)胞與分子生物學(xué)的理解。神經(jīng)元不再是個(gè)黑匣子,它的功能涉及一系列生物化學(xué)及生物物理學(xué)過(guò)程,其協(xié)同作用,最終達(dá)到加工、傳輸并存儲(chǔ)信息的目的?! ”緯?shū)是唯一一本對(duì)已知的神經(jīng)細(xì)胞形態(tài)學(xué).生物化學(xué)及生物物理學(xué)性質(zhì)進(jìn)行全面概括的教科書(shū).第二版基于第一版的成功經(jīng)驗(yàn),更新了最近五年的學(xué)科進(jìn)展。新版本擴(kuò)充了細(xì)胞神經(jīng)生物學(xué)網(wǎng)絡(luò)方面的內(nèi)容,還闡述了細(xì)胞生物學(xué)過(guò)程與多種神經(jīng)疾病的相互、作用關(guān)系?! ∈驴膳浜戏肿由飳W(xué)、神經(jīng)科學(xué)、生物化學(xué)及相關(guān)專(zhuān)業(yè)研究生和高年級(jí)本科生課程使用  導(dǎo)讀版每章前均附國(guó)內(nèi)相關(guān)領(lǐng)域?qū)<宜鞯脑敱M導(dǎo)讀一篇  被專(zhuān)家譽(yù)為”神經(jīng)科學(xué)家書(shū)架上的必備書(shū)”  附光盤(pán),內(nèi)含原書(shū)全部插圖

書(shū)籍目錄

第1章 神經(jīng)組織的細(xì)胞組成 第2章 神經(jīng)系統(tǒng)亞細(xì)胞結(jié)構(gòu):細(xì)胞器及其功能 第3章 腦能量代謝 第4章 軸突和樹(shù)突的電緊張?zhí)匦?第5章 膜電位和動(dòng)作電位 第6章 離子通道的分子特性 第7章 可興奮膜的動(dòng)力學(xué)性質(zhì) 第8章 神經(jīng)遞質(zhì)的釋放 第9章 突觸傳遞的藥理學(xué)與生物化學(xué):經(jīng)典神經(jīng)遞質(zhì) 第10章 腦內(nèi)非經(jīng)典信號(hào) 第11章 神經(jīng)遞質(zhì)受體 第12章 胞內(nèi)信號(hào)轉(zhuǎn)導(dǎo) 第13章 神經(jīng)元基因表達(dá)與蛋白合成的調(diào)節(jié) 第14章 胞內(nèi)信號(hào)通路的建模和分析 第15章 神經(jīng)系統(tǒng)中以Connexin和Pannexin為基礎(chǔ)的通道:縫隙連接及其他 第16章 突觸后電位和突觸整合 第17章 復(fù)雜信息在樹(shù)突的加工與處理 第18章 神經(jīng)網(wǎng)絡(luò)信息處理 第19章 學(xué)習(xí)與記憶:基本機(jī)理 第20章 神經(jīng)變性病的分子與細(xì)胞機(jī)理 索引

編輯推薦

  目錄、索引已譯成中文,正文保留英文原版。中文導(dǎo)讀主編為第四軍醫(yī)大學(xué)疼痛生物醫(yī)學(xué)研究所所長(zhǎng)陳軍教授和首都醫(yī)科大學(xué)神經(jīng)生物學(xué)系主任王曉民教授。

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用戶(hù)評(píng)論 (總計(jì)5條)

 
 

  •   主要還有中文導(dǎo)讀,跟其他神經(jīng)類(lèi)的書(shū)的結(jié)構(gòu)也不同,有創(chuàng)新
  •   書(shū)有點(diǎn)小壓到,應(yīng)該是正版
  •   印刷很贊,慢慢看,很厚實(shí)的
  •   價(jià)格也比較貴,不過(guò)比較值
  •   英文版的,比原版便宜了很多,內(nèi)容一樣,值!
 

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