TY - JOUR
T1 - Independent component model of the default-mode brain function: combining individual-level and population-level analyses in resting-state fMRI
AU - Esposito, F.
AU - Aragri, A.
AU - Pesaresi, I.
AU - Cirillo, S.
AU - Tedeschi, G.
AU - Marciano, E.
AU - Goebel, R.W.
AU - Di Salle, F.
PY - 2008/1/1
Y1 - 2008/1/1
N2 - Resting-state functional magnetic resonance imaging (RS-fMRI) is a technique used to investigate the spontaneous correlations of blood-oxygen-level-dependent signals across different regions of the brain. Using functional connectivity tools, it is possible to investigate a specific RS-fMRI network, referred to as "default-mode" (DM) network, that involves cortical regions deactivated in fMRI experiments with cognitive tasks. Previous works have reported a significant effect of aging on DM regions activity. Independent component analysis (ICA) is Often Used for generating spatially distributed DM Functional connectivity patterns front RS-fMRI data without the need for a reference region. This aspect and the relatively easy setup of an RS-fMRI experiment even in clinical trials have boosted the combined use of RS-fMRI and ICA-based DM analysis for noninvasive research of brain disorders, In this work, we considered different strategies for combining ICA results from individual-level and population-level analyses and used them to evaluate and predict the effect of aging on the DM component. Using RS-fMRI data from 20 normal subjects and a previously developed group-level ICA methodology, we generated group DM maps and showed that the overall ICA-DM connectivity is negatively correlated with age. A negative correlation of the ICA voxel weights with age existed in all DM regions at it variable degree. As an alternative approach, we generated a distributed DIM spatial template and evaluated the correlation of each individual DM component fit to this template with age. Using a "leave-one-out" procedure, we discuss the importance of removing the bias from the DM template-generation process.
AB - Resting-state functional magnetic resonance imaging (RS-fMRI) is a technique used to investigate the spontaneous correlations of blood-oxygen-level-dependent signals across different regions of the brain. Using functional connectivity tools, it is possible to investigate a specific RS-fMRI network, referred to as "default-mode" (DM) network, that involves cortical regions deactivated in fMRI experiments with cognitive tasks. Previous works have reported a significant effect of aging on DM regions activity. Independent component analysis (ICA) is Often Used for generating spatially distributed DM Functional connectivity patterns front RS-fMRI data without the need for a reference region. This aspect and the relatively easy setup of an RS-fMRI experiment even in clinical trials have boosted the combined use of RS-fMRI and ICA-based DM analysis for noninvasive research of brain disorders, In this work, we considered different strategies for combining ICA results from individual-level and population-level analyses and used them to evaluate and predict the effect of aging on the DM component. Using RS-fMRI data from 20 normal subjects and a previously developed group-level ICA methodology, we generated group DM maps and showed that the overall ICA-DM connectivity is negatively correlated with age. A negative correlation of the ICA voxel weights with age existed in all DM regions at it variable degree. As an alternative approach, we generated a distributed DIM spatial template and evaluated the correlation of each individual DM component fit to this template with age. Using a "leave-one-out" procedure, we discuss the importance of removing the bias from the DM template-generation process.
U2 - 10.1016/j.mri.2008.01.045
DO - 10.1016/j.mri.2008.01.045
M3 - Article
C2 - 18486388
SN - 0730-725X
VL - 26
SP - 905
EP - 913
JO - Magnetic Resonance Imaging
JF - Magnetic Resonance Imaging
IS - 7
ER -