Theory and Simulation in Neuroscience

被引：124

作者：

Gerstner, Wulfram ^{[1
,2
]}

Sprekeler, Henning ^{[3
,4
,5
]}

Deco, Gustavo ^{[6
,7
]}

机构：

[1] Ecole Polytech Fed Lausanne, Sch Comp & Commun Sci, CH-1015 Lausanne, Switzerland

[2] Ecole Polytech Fed Lausanne, Brain Mind Inst, Sch Life Sci, CH-1015 Lausanne, Switzerland

[3] Tech Univ Berlin, D-10587 Berlin, Germany

[4] Humboldt Univ, D-10115 Berlin, Germany

[5] Bernstein Ctr Computat Neurosci Berlin, D-10115 Berlin, Germany

[6] Univ Pompeu Fabra, Ctr Brain & Cognit, Dept Informat & Commun Technol, Barcelona 08018, Spain

[7] Inst Catalana Recerca & Estudis Avancats, Barcelona 2308010, Spain

来源：

SCIENCE | 2012年 / 338卷 / 6103期

基金：

瑞士国家科学基金会; 欧洲研究理事会;

关键词：

LARGE-SCALE SIMULATIONS; SYNAPTIC PLASTICITY; SPIKING NEURONS; NEURAL-NETWORKS; ASSOCIATIVE MEMORY; RECURRENT NETWORK; DECISION-MAKING; MODEL; DYNAMICS; REWARD;

D O I：

10.1126/science.1227356

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Modeling work in neuroscience can be classified using two different criteria. The first one is the complexity of the model, ranging from simplified conceptual models that are amenable to mathematical analysis to detailed models that require simulations in order to understand their properties. The second criterion is that of direction of workflow, which can be from microscopic to macroscopic scales (bottom-up) or from behavioral target functions to properties of components (top-down). We review the interaction of theory and simulation using examples of top-down and bottom-up studies and point to some current developments in the fields of computational and theoretical neuroscience.

引用

页码：60 / 65

页数：6

共 111 条

[11]

Barlow H.B., 1961, SENS COMMUN, V1, DOI DOI 10.7551/MITPRESS/9780262518420.003.0013

[12]

Barto AG, 2003, DISCRETE EVENT DYN S, V13, P343

[13] NEURONLIKE ADAPTIVE ELEMENTS THAT CAN SOLVE DIFFICULT LEARNING CONTROL-PROBLEMS [J].