Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data.

Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data. Research Abstract Details 

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Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data. Abstract Text:

Jieun Kim,Wei Zhu,Linda Chang,Peter M Bentler,Thomas Ernst,

The ultimate goal of brain connectivity studies is to propose, test, modify, and compare certain directional brain pathways. Path analysis or structural equation modeling (SEM) is an ideal statistical method for such studies. In this work, we propose a two-stage unified SEM plus GLM (General Linear Model) approach for the analysis of multisubject, multivariate functional magnetic resonance imaging (fMRI) time series data with subject-level covariates. In Stage 1, we analyze the fMRI multivariate time series for each subject individually via a unified SEM model by combining longitudinal pathways represented by a multivariate autoregressive (MAR) model, and contemporaneous pathways represented by a conventional SEM. In Stage 2, the resulting subject-level path coefficients are merged with subject-level covariates such as gender, age, IQ, etc., to examine the impact of these covariates on effective connectivity via a GLM. Our approach is exemplified via the analysis of an fMRI visual attention experiment. Furthermore, the significant path network from the unified SEM analysis is compared to that from a conventional SEM analysis without incorporating the longitudinal information as well as that from a Dynamic Causal Modeling (DCM) approach.

Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data. Publishing Authors By Initials

J Kim,W Zhu,L Chang,PM Bentler,T Ernst,

For similar natural sciences: time: time factors research abstracts see: natural sciences: time: time factors research

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MEDLINE DATE:

Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data. Journal Published:

PUBLICATION TYPE: Research Support, U.S. Gov't,

Journal: Human brain mapping

VOLUME: 28

Page Numbers: 85-93

Journal Abbreviation:

ISSN: 1065-9471

DAY: 3

MONTH: Feb

YEAR: 2007

Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 9419065

Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data. Keywords Mesh Terms:

KEYWORDS: Time Factors

MESH TERMS: methods

Chemical & Substance for Abstract: Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data. Information

Substance Name: Oxygen

Registry Number: 7782-44-7

Grant and Affiliation Information for Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data.

AFFILIATION: Department of Applied Mathematics and Statistics, State University of New York at Stony Brook, Stony Brook, New York, USA. kimjieun@nidcd.nih.gov

Country: United States

AGENCY: United States NIDA

GRANT: K24 DA16170

ACRONYM: DA

MEDLINETA: Hum Brain Mapp

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