TY - GEN
T1 - A maximal-correlation approach using ICA for testing functional network connectivity applied to schizophrenia
AU - Jafri, Madiha J.
AU - Pearlson, Godfrey D.
AU - Calhoun, Vince D.
PY - 2007/11/27
Y1 - 2007/11/27
N2 - There has been a growing interest in analyzing brain activation differences between patients and controls by studying resting-state fMRI brain networks. Functional connectivity of the resting brain has been studied by analyzing correlation differences in time courses among seed voxels, regions, or volume of interest with other voxels of the brain in patients versus controls. Spatial differences have also been analyzed among component maps derived from independent component analysis (ICA) in patients with schizophrenia and in healthy controls. However, the relationship among ICA component time courses, (which we define as functional network connectivity), has not been studied. We propose a novel technique to determine FNC applied to schizophrenia which does not rely on the time series of specific brain voxels or regions of interest and instead focuses upon the connectivity between functional networks (components) estimated from ICA using maximal correlation between component time series.
AB - There has been a growing interest in analyzing brain activation differences between patients and controls by studying resting-state fMRI brain networks. Functional connectivity of the resting brain has been studied by analyzing correlation differences in time courses among seed voxels, regions, or volume of interest with other voxels of the brain in patients versus controls. Spatial differences have also been analyzed among component maps derived from independent component analysis (ICA) in patients with schizophrenia and in healthy controls. However, the relationship among ICA component time courses, (which we define as functional network connectivity), has not been studied. We propose a novel technique to determine FNC applied to schizophrenia which does not rely on the time series of specific brain voxels or regions of interest and instead focuses upon the connectivity between functional networks (components) estimated from ICA using maximal correlation between component time series.
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U2 - 10.1109/ISBI.2007.356890
DO - 10.1109/ISBI.2007.356890
M3 - Conference contribution
AN - SCOPUS:36348952598
SN - 1424406722
SN - 9781424406722
T3 - 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
SP - 468
EP - 471
BT - 2007 4th IEEE International Symposium on Biomedical Imaging
T2 - 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07
Y2 - 12 April 2007 through 15 April 2007
ER -