Detection of feedback in the central nervous system using system identification techniques
type: Item
instance of: scholarly article
title: Detection of feedback in the central nervous system using system identification techniques
zbMATH Open document ID: 0667.92004
DOI: 10.1007/BF00207288
author: S. M. Schnider
author: F. A. Lenz
author: Raymond H. Kwong
author: Hon C. Kwan
published in: Biological Cybernetics
publication date: 1989-01-01T00:00:00Z
review text: The paper introduces a linear stochastic model to describe the physiological system and a joint process model for system identification. Several methodologies for detection of feedback in linear stochastic systems are discussed. These tools are then applied to the central nervous system modelled by neuronal spike trains considered as a stochastic point process. The utility of the technique is demonstrated by examination of the relationships between Parkinsonian tremor and certain thalamic cells.
Mathematics Subject Classification ID: 92Cxx
Mathematics Subject Classification ID: 93E12
Mathematics Subject Classification ID: 60G55
zbMATH DE Number: 4093224
zbMATH Keywords: linear stochastic model
zbMATH Keywords: detection of feedback
zbMATH Keywords: central nervous system
zbMATH Keywords: neuronal spike trains
zbMATH Keywords: Parkinsonian tremor
zbMATH Keywords: thalamic cells
Wikidata QID: Q69961165
reviewed by: J.Horejs
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 4093224