Literature DB >> 9345494

Functional magnetic resonance image analysis of a large-scale neurocognitive network.

E T Bullmore1, S Rabe-Hesketh, R G Morris, S C Williams, L Gregory, J A Gray, M J Brammer.   

Abstract

Many "higher-order" mental functions are subserved by large-scale neurocognitive networks comprising several spatially distributed and functionally specialized brain regions. We here report statistical and graphical methods of functional magnetic resonance imaging data analysis which can be used to elucidate the functional relationships (i.e., connectivity and distance) between elements of a neurocognitive network in a single subject. Data were acquired from a normal right-handed volunteer during periodic performance of a task which demanded visual and semantic processing of words and subvocalization of a decision about the meaning of each word. Major regional foci of activation were identified (by sinusoidal regression modeling and spatiotemporal randomization tests) in left extrastriate cortex, angular gyrus, supramarginal gyrus, superior and middle temporal gyri, lateral premotor cortex, and Broca's area. Principal component (PC) analysis was initially undertaken by singular value decomposition (SVD) of the "raw" time series observed at 170 activated voxels. This revealed a large functional distance (negative connectivity) between visual processing systems and all other brain regions in the space of the first PC. SVD of a matrix of fitted time series, and a matrix of six sinusoidal regression parameters estimated at each activated voxel, were developed as less noisy (more informative) alternatives to SVD of the "raw" data. Canonical variate analysis of denoised data was then used to clarify functional relationships between the major regional foci. Visual input analysis systems (extrastriate cortex and angular gyrus) were colocalized in the space of the first canonical variate (CV) and significantly separated from all other brain regions. Semantic analysis systems (supramarginal and temporal gyri) were colocalized and significantly separated in the space of the second CV from the subvocal output system (Broca's area). These results are provisionally interpreted in terms of underlying hemodynamic events and cognitive psychological theory.

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Year:  1996        PMID: 9345494     DOI: 10.1006/nimg.1996.0026

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  30 in total

Review 1.  "Dynamic" connectivity in neural systems: theoretical and empirical considerations.

Authors:  Michael Breakspear
Journal:  Neuroinformatics       Date:  2004

2.  Investigating the neural basis for functional and effective connectivity. Application to fMRI.

Authors:  Barry Horwitz; Brent Warner; Julie Fitzer; M-A Tagamets; Fatima T Husain; Theresa W Long
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-05-29       Impact factor: 6.237

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

Authors:  Jieun Kim; Wei Zhu; Linda Chang; Peter M Bentler; Thomas Ernst
Journal:  Hum Brain Mapp       Date:  2007-02       Impact factor: 5.038

4.  Detecting functional nodes in large-scale cortical networks with functional magnetic resonance imaging: a principal component analysis of the human visual system.

Authors:  Christine Ecker; Emanuelle Reynaud; Steven C Williams; Michael J Brammer
Journal:  Hum Brain Mapp       Date:  2007-09       Impact factor: 5.038

5.  Support vector machine learning-based fMRI data group analysis.

Authors:  Ze Wang; Anna R Childress; Jiongjiong Wang; John A Detre
Journal:  Neuroimage       Date:  2007-04-27       Impact factor: 6.556

Review 6.  Assessing functional connectivity in the human brain by fMRI.

Authors:  Baxter P Rogers; Victoria L Morgan; Allen T Newton; John C Gore
Journal:  Magn Reson Imaging       Date:  2007-05-11       Impact factor: 2.546

7.  Dispersion and time delay effects in synchronized spike-burst networks.

Authors:  Viktor K Jirsa
Journal:  Cogn Neurodyn       Date:  2007-10-16       Impact factor: 5.082

8.  Evaluation and comparison of GLM- and CVA-based fMRI processing pipelines with Java-based fMRI processing pipeline evaluation system.

Authors:  Jing Zhang; Lichen Liang; Jon R Anderson; Lael Gatewood; David A Rottenberg; Stephen C Strother
Journal:  Neuroimage       Date:  2008-04-03       Impact factor: 6.556

9.  Altered resting functional connectivity of expressive language regions after speed reading training.

Authors:  Michael A Ferguson; Jared A Nielsen; Jeffrey S Anderson
Journal:  J Clin Exp Neuropsychol       Date:  2014-04-28       Impact factor: 2.475

10.  Bootstrapping GEE models for fMRI regional connectivity.

Authors:  Gina M D'Angelo; Nicole A Lazar; Gongfu Zhou; William F Eddy; John C Morris; Yvette I Sheline
Journal:  Neuroimage       Date:  2012-08-18       Impact factor: 6.556

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