TY - JOUR
T1 - Functional network overlap as revealed by fmri using sica and its potential relationships with functional heterogeneity, balanced excitation and inhibition, and sparseness of neuron activity
AU - Xu, Jiansong
AU - Calhoun, Vince D.
AU - Worhunsky, Patrick D.
AU - Xiang, Hui
AU - Li, Jian
AU - Wall, John T.
AU - Pearlson, Godfrey D.
AU - Potenza, Marc N.
N1 - Publisher Copyright:
© 2015 Xu et al.
PY - 2015/2/25
Y1 - 2015/2/25
N2 - Functional magnetic resonance imaging (fMRI) studies traditionally use general linear modelbased analysis (GLM-BA) and regularly report task-related activation, deactivation, or no change in activation in separate brain regions. However, several recent fMRI studies using spatial independent component analysis (sICA) find extensive overlap of functional networks (FNs), each exhibiting different task-relatedmodulation (e.g., activation vs. deactivation), different from the dominant findings of GLM-BA. This study used sICA to assess overlap of FNs extracted from four datasets, each related to a different cognitive task. FNs extracted from each dataset overlapped with each other extensively acrossmost or all brain regions and showed task-related concurrent increases, decreases, or no changes in activity. These findings indicate that neural substrates showing task-related concurrent but different modulations in activity intermix with each other and distribute across most of the brain. Furthermore, spatial correlation analyses found that most FNs were highly consistent in spatial patterns across different datasets. This finding indicates that these FNs probably reflect large-scale patterns of task-related brain activity. We hypothesize that FN overlaps as revealed by sICAmight relate to functional heterogeneity, balanced excitation and inhibition, and population sparseness of neuron activity, three fundamental properties of the brain. These possibilities deserve further investigation.
AB - Functional magnetic resonance imaging (fMRI) studies traditionally use general linear modelbased analysis (GLM-BA) and regularly report task-related activation, deactivation, or no change in activation in separate brain regions. However, several recent fMRI studies using spatial independent component analysis (sICA) find extensive overlap of functional networks (FNs), each exhibiting different task-relatedmodulation (e.g., activation vs. deactivation), different from the dominant findings of GLM-BA. This study used sICA to assess overlap of FNs extracted from four datasets, each related to a different cognitive task. FNs extracted from each dataset overlapped with each other extensively acrossmost or all brain regions and showed task-related concurrent increases, decreases, or no changes in activity. These findings indicate that neural substrates showing task-related concurrent but different modulations in activity intermix with each other and distribute across most of the brain. Furthermore, spatial correlation analyses found that most FNs were highly consistent in spatial patterns across different datasets. This finding indicates that these FNs probably reflect large-scale patterns of task-related brain activity. We hypothesize that FN overlaps as revealed by sICAmight relate to functional heterogeneity, balanced excitation and inhibition, and population sparseness of neuron activity, three fundamental properties of the brain. These possibilities deserve further investigation.
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U2 - 10.1371/journal.pone.0117029
DO - 10.1371/journal.pone.0117029
M3 - Article
C2 - 25714362
AN - SCOPUS:84923872979
SN - 1932-6203
VL - 10
JO - PloS one
JF - PloS one
IS - 2
M1 - e0117029
ER -