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Titolo:
On the relation between brain images and brain neural networks
Autore:
Taylor, JG; Krause, B; Shah, MJ; Horwitz, B; Mueller-Gaertner, HW;
Indirizzi:
Univ London Kings Coll, Dept Math, Strand, London WC2R 2LS, England Univ London Kings Coll London England WC2R 2LS London WC2R 2LS, England Res Ctr, Inst Med, Julich, Germany Res Ctr Julich GermanyRes Ctr, Inst Med, Julich, Germany Univ Dusseldorf, Dept Nucl Med, D-4000 Dusseldorf, Germany Univ Dusseldorf Dusseldorf Germany D-4000 ed, D-4000 Dusseldorf, Germany Natl Inst Deafness & Other Commun Disorders, Voise Speech & Language Branch, NIH, Bethesda, MD USA Natl Inst Deafness & Other Commun Disorders Bethesda MD USA esda, MD USA
Titolo Testata:
HUMAN BRAIN MAPPING
fascicolo: 3, volume: 9, anno: 2000,
pagine: 165 - 182
SICI:
1065-9471(200003)9:3<165:OTRBBI>2.0.ZU;2-P
Fonte:
ISI
Lingua:
ENG
Soggetto:
PHASE-LOCKING; BLOOD-FLOW; MODEL; CHAOS; FMRI; MAP;
Keywords:
fMRI; brain; PET; neural activity;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
45
Recensione:
Indirizzi per estratti:
Indirizzo: Taylor, JG Univ London Kings Coll, Dept Math, Strand, London WC2R 2LS, England Univ London Kings Coll London England WC2R 2LS R 2LS, England
Citazione:
J.G. Taylor et al., "On the relation between brain images and brain neural networks", HUM BRAIN M, 9(3), 2000, pp. 165-182

Abstract

The relationship between brain images observed by PET and fMRI and the underlying neural activity is analysed using recent results on the detailed nature of averaged and synchronised activity of coupled neural networks and on a simplifying model of the level of blood flow caused by neural activity. The conditions bn the coupled neural systems are specified that lead to structural equation models, giving support to analysis of the covariance structural equation modelling of brain imaging data. The relation between the resulting models and possible neural codes are analysed. Furthermore, a new form of structural equation model is derived, in which all neuronal activity arises as hidden variables. We discuss how the results of such analyses can be transported back to the domain of coupled temporally dynamic neural systems in the brain appropriate to EEG and MEG observations. (C) 2000 Wiley-Liss, Inc.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 23/01/20 alle ore 03:22:25