TY - JOUR
T1 - Modulations of functional connectivity in the healthy and schizophrenia groups during task and rest
AU - Ma, Sai
AU - Calhoun, Vince D.
AU - Eichele, Tom
AU - Du, Wei
AU - Adali, Tülay
N1 - Funding Information:
This work was supported by the NSF grant 1117056 and NIH grants R01 EB000840 and R01 EB005846 . Tom Eichele was supported through a BILATGRUNN grant from the Norwegian Research Council . We thank the research staff at the Olin Neuropsychiatry Research Center and the Mind Research Network who collected, processed and shared the data. We appreciate the valuable advice given by the members of Machine Learning for Signal Processing Laboratory in University of Maryland, Baltimore County.
PY - 2012/9
Y1 - 2012/9
N2 - Connectivity analysis using functional magnetic resonance imaging (fMRI) data is an important area, useful for the identification of biomarkers for various mental disorders, including schizophrenia. Most studies to date have focused on resting data, while the study of functional connectivity during task and the differences between task and rest are of great interest as well. In this work, we examine the graph-theoretical properties of the connectivity maps constructed using spatial components derived from independent component analysis (ICA) for healthy controls and patients with schizophrenia during an auditory oddball task (AOD) and at extended rest. We estimate functional connectivity using the higher-order statistical dependence, i.e., mutual information among the ICA spatial components, instead of the typically used temporal correlation. We also define three novel topological metrics based on the modules of brain networks obtained using a clustering approach. Our experimental results show that although the schizophrenia patients preserve the small-world property, they present a significantly lower small-worldness during both AOD task and rest when compared to the healthy controls, indicating a consistent tendency towards a more random organization of brain networks. In addition, the task-induced modulations to topological measures of several components involving motor, cerebellum and parietal regions are altered in patients relative to controls, providing further evidence for the aberrant connectivity in schizophrenia.
AB - Connectivity analysis using functional magnetic resonance imaging (fMRI) data is an important area, useful for the identification of biomarkers for various mental disorders, including schizophrenia. Most studies to date have focused on resting data, while the study of functional connectivity during task and the differences between task and rest are of great interest as well. In this work, we examine the graph-theoretical properties of the connectivity maps constructed using spatial components derived from independent component analysis (ICA) for healthy controls and patients with schizophrenia during an auditory oddball task (AOD) and at extended rest. We estimate functional connectivity using the higher-order statistical dependence, i.e., mutual information among the ICA spatial components, instead of the typically used temporal correlation. We also define three novel topological metrics based on the modules of brain networks obtained using a clustering approach. Our experimental results show that although the schizophrenia patients preserve the small-world property, they present a significantly lower small-worldness during both AOD task and rest when compared to the healthy controls, indicating a consistent tendency towards a more random organization of brain networks. In addition, the task-induced modulations to topological measures of several components involving motor, cerebellum and parietal regions are altered in patients relative to controls, providing further evidence for the aberrant connectivity in schizophrenia.
KW - Auditory oddball task
KW - Functional connectivity
KW - Graph theoretical analysis
KW - Resting state
KW - Schizophrenia
KW - Spatial dependence
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U2 - 10.1016/j.neuroimage.2012.05.048
DO - 10.1016/j.neuroimage.2012.05.048
M3 - Article
C2 - 22634855
AN - SCOPUS:84863533841
SN - 1053-8119
VL - 62
SP - 1694
EP - 1704
JO - NeuroImage
JF - NeuroImage
IS - 3
ER -