Title :
Nonparametric interpretation and validation of the parametric short-term plasticity models
Author :
Song, D. ; Wang, Z. ; Marmarelis, V.Z. ; Berger, T.W.
Author_Institution :
Dept. of Biomed. Eng., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
Biological systems can be modeled with two different approaches: parametric and nonparametric. The parametric approach (internal model) describes underlying biological mechanisms of the system while the nonparametric approach (external model) directly maps the system´s input/output properties. In this study, two nonparametric models of short-term plasticity (STP) were estimated from both a parametric STP model and experimental STP data. These two models allowed us to study the formal mathematical relations between the parametric and nonparametric models of STP. Our results showed that 1) the nonparametric model estimated from the parametric model could efficiently extract the input/output transformational properties defined by the parametric model; 2) the nonparametric model estimated from experimental data could be used to validate the parametric model.
Keywords :
Volterra equations; biomechanics; parameter estimation; physiological models; stochastic processes; biological mechanism; biological system; laguerre expansion; nonparametric interpretation; nonparametric model; parametric short-term plasticity model; poisson input; synaptic plasticity; system kernel; volterra model; Biological system modeling; Biological systems; Computer aided instruction; Electrodes; Frequency; Kernel; Mathematical model; Neurotransmitters; Parametric statistics; Voltage;
Conference_Titel :
Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE
Print_ISBN :
0-7803-7789-3
DOI :
10.1109/IEMBS.2003.1279793