Activity-driven computational strategies of a dynamically regulated integrate-and-fire model neuron

作     者：Giugliano, M Bove, M Grattarola, M 

作者机构：Univ Genoa Dept Biophys & Elect Engn Bioelect & Neuroengn Grp I-16145 Genoa Italy 

出 版 物：《JOURNAL OF COMPUTATIONAL NEUROSCIENCE》 (计算神经科学杂志)

年 卷 期：1999年第7卷第3期

页      面：247-254页

核心收录：

学科分类：0710[理学-生物学] 1001[医学-基础医学(可授医学、理学学位)] 07[理学] 071003[理学-生理学] 

基　　金：Università degli Studi di Genova 

主　　题：integrate-and-fire dynamic regulation neural code integration coincidence detection 

摘      要：Activity-dependent slow biochemical regulation processes, affecting intrinsic properties of a neuron, might play an important role in determining information processing strategies in the nervous system. We introduce second-order biochemical phenomena into a linear leaky integrate-and-fire model neuron together with a detailed kinetic description for synaptic signal transduction. In this framework, we investigate the membrane intrinsic electrical properties differentiation, showing the appearance of activity-dependent shifts between integration and temporal coincidence detection operating mode, for the single unit of a network.