Literature DB >> 19733247

Does function follow form?: methods to fuse structural and functional brain images show decreased linkage in schizophrenia.

Andrew M Michael1, Stefi A Baum, Tonya White, Oguz Demirci, Nancy C Andreasen, Judith M Segall, Rex E Jung, Godfrey Pearlson, Vince P Clark, Randy L Gollub, S Charles Schulz, Joshua L Roffman, Kelvin O Lim, Beng-Choon Ho, H Jeremy Bockholt, Vince D Calhoun.   

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. Copyright (c) 2009. Published by Elsevier Inc.

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Year:  2009        PMID: 19733247      PMCID: PMC2911118          DOI: 10.1016/j.neuroimage.2009.08.056

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


  45 in total

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2.  What is the best similarity measure for motion correction in fMRI time series?

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4.  Delayed hemodynamic responses in schizophrenia.

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5.  Dynamic causal modelling.

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6.  A large scale (N=400) investigation of gray matter differences in schizophrenia using optimized voxel-based morphometry.

Authors:  Shashwath A Meda; Nicole R Giuliani; Vince D Calhoun; Kanchana Jagannathan; David J Schretlen; Anne Pulver; Nicola Cascella; Matcheri Keshavan; Wendy Kates; Robert Buchanan; Tonmoy Sharma; Godfrey D Pearlson
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Review 8.  Regional deficits in brain volume in schizophrenia: a meta-analysis of voxel-based morphometry studies.

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Journal:  Am J Psychiatry       Date:  2005-12       Impact factor: 18.112

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Review 10.  "Cognitive dysmetria" as an integrative theory of schizophrenia: a dysfunction in cortical-subcortical-cerebellar circuitry?

Authors:  N C Andreasen; S Paradiso; D S O'Leary
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  23 in total

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Journal:  Schizophr Res       Date:  2010-10-08       Impact factor: 4.939

5.  Three-way (N-way) fusion of brain imaging data based on mCCA+jICA and its application to discriminating schizophrenia.

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6.  Multimodal analyses identify linked functional and white matter abnormalities within the working memory network in schizophrenia.

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Review 7.  A review of multivariate methods for multimodal fusion of brain imaging data.

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9.  Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia.

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

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