MODELING OF NEURAL SYSTEMS BY USE OF NEURONAL MODES

被引:55
作者
MARMARELIS, VZ
ORME, ME
机构
[1] UNIV SO CALIF,DEPT ELECT ENGN,LOS ANGELES,CA 90089
[2] UNIV CALIF IRVINE,DEPT MECH & AEROSP ENGN,IRVINE,CA 92717
[3] UNIV SO CALIF,DEPT AEROSP ENGN,LOS ANGELES,CA 90089
关键词
D O I
10.1109/10.245633
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
A methodology for modeling spike-output neural systems from input-output data is proposed, which makes use of ''neuronal modes'' (NM) and ''multi-input threshold'' (MT) operators. The modeling concept of NM's was introduced in a previously published paper [4] in order to provide concise and general mathematical representations of the nonlinear dynamics involved in signal transformation and coding by a class of neural systems. This paper presents and demonstrates (with computer simulations) a method by which the NM's are determined using the 1st- and 2nd-order kernel estimates of the system, obtained from input-output data. The MT operator (i.e., a binary operator with multiple real-valued operands which are the outputs of the NM's) possesses an intrinsic refractory mechanism and generates the sequence of output spikes. The spike-generating characteristics of the MT operator are determined by the ''trigger regions'' defined on the basis of data. This approach is offered as a reasonable compromise between modeling complexity and prediction accuracy, which may provide a common methodological framework for modeling a certain class of neural systems.
引用
收藏
页码:1149 / 1158
页数:10
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