Default-Mode Network Activity Identified by Group Independent Component Analysis

Authors:
Conghui Liu;Jie Zhuang;Danling Peng;Guoliang Yu;Yanhui Yang
Affiliations:
Institute of Psychology, Renmin University of China, Beijing, 100872, China and State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China;Department of Experimental Psychology, University of Cambridge, Cambridge, CB23EB, UK;State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China;Institute of Psychology, Renmin University of China, Beijing, 100872, China;Department of Radiology, Xuanwu Hospital, Capital University of Medical Sciences, Beijing, 100053, China
Venue:
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Year:
2009

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Abstract

Default-mode network activity refers to some regional increase in blood oxygenation level-dependent (BOLD) signal during baseline than cognitive tasks. Recent functional imaging studies have found co-activation in a distributed network of cortical regions, including ventral anterior cingulate cortex (vACC) and posterior cingulate cortex (PPC) that characterize the default mode of human brain. In this study, general linear model and group independent component analysis (ICA) were utilized to analyze the fMRI data obtained from two language tasks. Both methods yielded similar, but not identical results and detected a resting deactivation network at some midline regions including anterior and posterior cingulate cortex and precuneus. Particularly, the group ICA method segregated functional elements into two separate maps and identified ventral cingulate component and fronto-parietal component. These results suggest that these two components might be linked to different mental function during "resting" baseline.