Default-Mode Network Activity Identified by Group Independent Component Analysis

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• 作者：Conghui Liu ; Jie Zhuang ; Danling Peng ; Guoliang Yu ; Yanhui Yang
• 关键词：fMRI ; default mode network ; independent component analysis
• 刊名：Lecture Notes in Computer Science
• 出版年：2007
• 出版时间：2007
• 年：2007
• 卷：4682
• 期：1
• 页码：222-233
• 全文大小：611 KB
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

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.