Akaike causality in state space. Instantaneous causality between visual cortex in fMRI time series.

Akaike causality in state space. Instantaneous causality between visual cortex in fMRI time series. Research Abstract Details 

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Akaike causality in state space. Instantaneous causality between visual cortex in fMRI time series. Abstract Text:

Kin Foon Kevin Wong,Tohru Ozaki,Kin Foon Kevin Wong,Tohru Ozaki,

We present a new approach of explaining instantaneous causality in multivariate fMRI time series by a state space model. A given single time series can be divided into two noise-driven processes, a common process shared among multivariate time series and a specific process refining the common process. By assuming that noises are independent, a causality map is drawn using Akaike noise contribution ratio theory. The method is illustrated by an application to fMRI data recorded under visual stimulation.

Akaike causality in state space. Instantaneous causality between visual cortex in fMRI time series. Publishing Authors By Initials

KF Wong,T Ozaki,KF Wong,T Ozaki,

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Akaike causality in state space. Instantaneous causality between visual cortex in fMRI time series. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: Biological cybernetics

VOLUME: 97

Page Numbers: 151-7

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ISSN: 0340-1200

DAY: 20

MONTH: 06

YEAR: 2007

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LANGUAGE: eng

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AFFILIATION: Institute of Statistical Mathematics, Minami Azabu 4-6-7, Tokyo 106-8569, Japan. wong@ism.ac.jp

Country: Germany

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MEDLINETA: Biol Cybern

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