Journal article
Does function follow form?: Methods to fuse structural and functional brain images show decreased linkage in schizophrenia
NeuroImage (Orlando, Fla.), Vol.49(3), pp.2626-2637
02/01/2010
DOI: 10.1016/j.neuroimage.2009.08.056
PMCID: PMC2911118
PMID: 19733247
Abstract
When both structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) data are collected they are typically analyzed separately and the joint information is not examined. Techniques that examine joint information can help to find hidden traits in complex disorders such as schizophrenia. The brain is vastly interconnected, and local brain morphology may influence functional activity at distant regions. In this paper we introduce three methods to identify inter-correlations among sMRI and fMRI voxels within the whole brain. We apply these methods to examine sMRI gray matter data and fMRI data derived from an auditory sensorimotor task from a large study of schizophrenia. In Method 1 the sMRI–fMRI cross-correlation matrix is reduced to a histogram and results show that healthy controls (HC) have stronger correlations than do patients with schizophrenia (SZ). In Method 2 the spatial information of sMRI–fMRI correlations is retained. Structural regions in the cerebellum and frontal regions show more positive and more negative correlations, respectively, with functional regions in HC than in SZ. In Method 3 significant sMRI–fMRI inter-regional links are detected, with regions in the cerebellum showing more significant positive correlations with functional regions in HC relative to SZ. Results from all three methods indicate that the linkage between gray matter and functional activation is stronger in HC than SZ. The methods introduced can be easily extended to comprehensively correlate large data sets.
Details
- Title: Subtitle
- Does function follow form?: Methods to fuse structural and functional brain images show decreased linkage in schizophrenia
- Creators
- Andrew M Michael - The Mind Research Network, Albuquerque, NM 87106, USAStefi A Baum - Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USATonya White - Department of Psychiatry, University of Minnesota, Minneapolis, MN 55454, USAOguz Demirci - The Mind Research Network, Albuquerque, NM 87106, USANancy C Andreasen - Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USAJudith M Segall - The Mind Research Network, Albuquerque, NM 87106, USARex E Jung - The Mind Research Network, Albuquerque, NM 87106, USAGodfrey Pearlson - Department of Psychiatry, Yale School of Medicine, New Haven, CT 06520, USAVince P Clark - The Mind Research Network, Albuquerque, NM 87106, USARandy L Gollub - Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USAS. Charles Schulz - Department of Psychiatry, University of Minnesota, Minneapolis, MN 55454, USAJoshua L Roffman - Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USAKelvin O Lim - Department of Psychiatry, University of Minnesota, Minneapolis, MN 55454, USABeng-Choon Ho - Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USAH. Jeremy Bockholt - The Mind Research Network, Albuquerque, NM 87106, USAVince D Calhoun - The Mind Research Network, Albuquerque, NM 87106, USA
- Resource Type
- Journal article
- Publication Details
- NeuroImage (Orlando, Fla.), Vol.49(3), pp.2626-2637
- DOI
- 10.1016/j.neuroimage.2009.08.056
- PMID
- 19733247
- PMCID
- PMC2911118
- NLM abbreviation
- Neuroimage
- ISSN
- 1053-8119
- eISSN
- 1095-9572
- Publisher
- Elsevier Inc
- Language
- English
- Date published
- 02/01/2010
- Academic Unit
- Psychiatry; Iowa Neuroscience Institute
- Record Identifier
- 9984003420502771
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