Your browser doesn't support javascript.
loading
Response-mode decomposition of spatio-temporal haemodynamics.
Pang, J C; Robinson, P A; Aquino, K M.
Afiliação
  • Pang JC; School of Physics, University of Sydney, Sydney, New South Wales 2006, Australia Center for Integrative Brain Function, University of Sydney, Sydney, New South Wales 2006, Australia james.pang@sydney.edu.au.
  • Robinson PA; School of Physics, University of Sydney, Sydney, New South Wales 2006, Australia Center for Integrative Brain Function, University of Sydney, Sydney, New South Wales 2006, Australia.
  • Aquino KM; School of Physics, University of Sydney, Sydney, New South Wales 2006, Australia Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK.
J R Soc Interface ; 13(118)2016 05.
Article em En | MEDLINE | ID: mdl-27170653
ABSTRACT
The blood oxygen-level dependent (BOLD) response to a neural stimulus is analysed using the transfer function derived from a physiologically based poroelastic model of cortical tissue. The transfer function is decomposed into components that correspond to distinct poles, each related to a response mode with a natural frequency and dispersion relation; together these yield the total BOLD response. The properties of the decomposed components provide a deeper understanding of the nature of the BOLD response, via the components' frequency dependences, spatial and temporal power spectra, and resonances. The transfer function components are then used to separate the BOLD response to a localized impulse stimulus, termed the Green function or spatio-temporal haemodynamic response function, into component responses that are explicitly related to underlying physiological quantities. The analytical results also provide a quantitative tool to calculate the linear BOLD response to an arbitrary neural drive, which is faster to implement than direct Fourier transform methods. The results of this study can be used to interpret functional magnetic resonance imaging data in new ways based on physiology, to enhance deconvolution methods and to design experimental protocols that can selectively enhance or suppress particular responses, to probe specific physiological phenomena.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Oxigênio / Hemodinâmica / Modelos Cardiovasculares Limite: Animals / Humans Idioma: En Revista: J R Soc Interface Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Oxigênio / Hemodinâmica / Modelos Cardiovasculares Limite: Animals / Humans Idioma: En Revista: J R Soc Interface Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Austrália