Literature DB >> 19777078

Multimodal and Multi-tissue Measures of Connectivity Revealed by Joint Independent Component Analysis.

Alexandre R Franco1, Josef Ling, Arvind Caprihan, Vince D Calhoun, Rex E Jung, Gregory L Heileman, Andrew R Mayer.   

Abstract

The human brain functions as an efficient system where signals arising from gray matter are transported via white matter tracts to other regions of the brain to facilitate human behavior. However, with a few exceptions, functional and structural neuroimaging data are typically optimized to maximize the quantification of signals arising from a single source. For example, functional magnetic resonance imaging (FMRI) is typically used as an index of gray matter functioning whereas diffusion tensor imaging (DTI) is typically used to determine white matter properties. While it is likely that these signals arising from different tissue sources contain complementary information, the signal processing algorithms necessary for the fusion of neuroimaging data across imaging modalities are still in a nascent stage. In the current paper we present a data-driven method for combining measures of functional connectivity arising from gray matter sources (FMRI resting state data) with different measures of white matter connectivity (DTI). Specifically, a joint independent component analysis (J-ICA) was used to combine these measures of functional connectivity following intensive signal processing and feature extraction within each of the individual modalities. Our results indicate that one of the most predominantly used measures of functional connectivity (activity in the default mode network) is highly dependent on the integrity of white matter connections between the two hemispheres (corpus callosum) and within the cingulate bundles. Importantly, the discovery of this complex relationship of connectivity was entirely facilitated by the signal processing and fusion techniques presented herein and could not have been revealed through separate analyses of both data types as is typically performed in the majority of neuroimaging experiments. We conclude by discussing future applications of this technique to other areas of neuroimaging and examining potential limitations of the methods.

Entities:  

Year:  2008        PMID: 19777078      PMCID: PMC2748354          DOI: 10.1109/JSTSP.2008.2006718

Source DB:  PubMed          Journal:  IEEE J Sel Top Signal Process        ISSN: 1932-4553            Impact factor:   6.856


  63 in total

1.  Reduction of eddy-current-induced distortion in diffusion MRI using a twice-refocused spin echo.

Authors:  T G Reese; O Heid; R M Weisskoff; V J Wedeen
Journal:  Magn Reson Med       Date:  2003-01       Impact factor: 4.668

2.  Functional connectivity in the resting brain: a network analysis of the default mode hypothesis.

Authors:  Michael D Greicius; Ben Krasnow; Allan L Reiss; Vinod Menon
Journal:  Proc Natl Acad Sci U S A       Date:  2002-12-27       Impact factor: 11.205

3.  Brain magnetic resonance imaging with contrast dependent on blood oxygenation.

Authors:  S Ogawa; T M Lee; A R Kay; D W Tank
Journal:  Proc Natl Acad Sci U S A       Date:  1990-12       Impact factor: 11.205

4.  Neuronal chronometry of target detection: fusion of hemodynamic and event-related potential data.

Authors:  V D Calhoun; T Adali; G D Pearlson; K A Kiehl
Journal:  Neuroimage       Date:  2005-10-24       Impact factor: 6.556

5.  Cognitive functions correlate with white matter architecture in a normal pediatric population: a diffusion tensor MRI study.

Authors:  Vincent J Schmithorst; Marko Wilke; Bernard J Dardzinski; Scott K Holland
Journal:  Hum Brain Mapp       Date:  2005-10       Impact factor: 5.038

6.  Spontaneous low-frequency BOLD signal fluctuations: an fMRI investigation of the resting-state default mode of brain function hypothesis.

Authors:  Peter Fransson
Journal:  Hum Brain Mapp       Date:  2005-09       Impact factor: 5.038

7.  Increased corpus callosum size in musicians.

Authors:  G Schlaug; L Jäncke; Y Huang; J F Staiger; H Steinmetz
Journal:  Neuropsychologia       Date:  1995-08       Impact factor: 3.139

8.  The effect of filter size on VBM analyses of DT-MRI data.

Authors:  Derek K Jones; Mark R Symms; Mara Cercignani; Robert J Howard
Journal:  Neuroimage       Date:  2005-04-09       Impact factor: 6.556

Review 9.  Searching for a baseline: functional imaging and the resting human brain.

Authors:  D A Gusnard; M E Raichle; M E Raichle
Journal:  Nat Rev Neurosci       Date:  2001-10       Impact factor: 34.870

10.  Performance of blind source separation algorithms for fMRI analysis using a group ICA method.

Authors:  Nicolle Correa; Tülay Adali; Vince D Calhoun
Journal:  Magn Reson Imaging       Date:  2006-12-08       Impact factor: 2.546

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  17 in total

1.  Constrained source-based morphometry identifies structural networks associated with default mode network.

Authors:  Li Luo; Lai Xu; Rex Jung; Godfrey Pearlson; Tülay Adali; Vince D Calhoun
Journal:  Brain Connect       Date:  2012

2.  Independent component analysis of DTI reveals multivariate microstructural correlations of white matter in the human brain.

Authors:  Yi-Ou Li; Fanpei G Yang; Christopher T Nguyen; Shelly R Cooper; Sara C LaHue; Sandya Venugopal; Pratik Mukherjee
Journal:  Hum Brain Mapp       Date:  2011-05-12       Impact factor: 5.038

Review 3.  Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging.

Authors:  Kenichi Oishi; Andreia V Faria; Shoko Yoshida; Linda Chang; Susumu Mori
Journal:  Int J Dev Neurosci       Date:  2013-06-21       Impact factor: 2.457

4.  Functional connectivity in mild traumatic brain injury.

Authors:  Andrew R Mayer; Maggie V Mannell; Josef Ling; Charles Gasparovic; Ronald A Yeo
Journal:  Hum Brain Mapp       Date:  2011-01-21       Impact factor: 5.038

5.  Reprint of "Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging".

Authors:  Kenichi Oishi; Andreia V Faria; Shoko Yoshida; Linda Chang; Susumu Mori
Journal:  Int J Dev Neurosci       Date:  2013-12-02       Impact factor: 2.457

Review 6.  A review of multivariate methods for multimodal fusion of brain imaging data.

Authors:  Jing Sui; Tülay Adali; Qingbao Yu; Jiayu Chen; Vince D Calhoun
Journal:  J Neurosci Methods       Date:  2011-11-11       Impact factor: 2.390

7.  Discriminating schizophrenia and bipolar disorder by fusing fMRI and DTI in a multimodal CCA+ joint ICA model.

Authors:  Jing Sui; Godfrey Pearlson; Arvind Caprihan; Tülay Adali; Kent A Kiehl; Jingyu Liu; Jeremy Yamamoto; Vince D Calhoun
Journal:  Neuroimage       Date:  2011-05-27       Impact factor: 6.556

8.  Age-related cognitive gains are mediated by the effects of white matter development on brain network integration.

Authors:  Michael C Stevens; Pawel Skudlarski; Godfrey D Pearlson; Vince D Calhoun
Journal:  Neuroimage       Date:  2009-07-03       Impact factor: 6.556

9.  A pilot multivariate parallel ICA study to investigate differential linkage between neural networks and genetic profiles in schizophrenia.

Authors:  Shashwath A Meda; Kanchana Jagannathan; Joel Gelernter; Vince D Calhoun; Jingyu Liu; Michael C Stevens; Godfrey D Pearlson
Journal:  Neuroimage       Date:  2009-11-26       Impact factor: 6.556

10.  Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness.

Authors:  Vince D Calhoun; Jing Sui
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2016-05
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