Literature DB >> 8260324

An application of autoregressive model to pattern discrimination of brain electrical activity mapping.

T Ogawa1, H Sonoda, S Ishiwa, Y Shigeta.   

Abstract

Using the autoregressive model, we developed a method of illustrating significant regional differences between two records of brain electrical activity mapping. This new approach of brain electrical activity mapping analysis through a statistical taxonomy may be clinically useful for evaluation of the normal development of EEG in children and for localizing functional brain abnormality.

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Year:  1993        PMID: 8260324     DOI: 10.1007/bf01234121

Source DB:  PubMed          Journal:  Brain Topogr        ISSN: 0896-0267            Impact factor:   3.020


  6 in total

1.  Developmental characteristics of topographic EEG in the newborn using an autoregressive model.

Authors:  S Ishiwa; T Ogawa; H Sonoda
Journal:  Brain Topogr       Date:  1991       Impact factor: 3.020

2.  Objective evaluation of differences in patterns of EEG topographical maps by Mahalanobis distance.

Authors:  J Tatsuno; H Ashida; A Takao
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1988-03

3.  On some methods for EEG pattern discrimination.

Authors:  K Sato; K Ono; G Chiba; K Fukata
Journal:  Int J Neurosci       Date:  1977       Impact factor: 2.292

4.  Component activities in the autoregressive activity of physiological systems.

Authors:  K Sato; K Ono; G Chiba; K Fukata
Journal:  Int J Neurosci       Date:  1977       Impact factor: 2.292

5.  Significance probability mapping: an aid in the topographic analysis of brain electrical activity.

Authors:  F H Duffy; P H Bartels; J L Burchfiel
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1981-05

6.  Ontogenic development of autoregressive component waves of waking EEG in normal infants and children.

Authors:  T Ogawa; A Sugiyama; S Ishiwa; M Suzuki; T Ishihara; K Sato
Journal:  Brain Dev       Date:  1984       Impact factor: 1.961

  6 in total

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