机构:[1]National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, People’s Republic of China,[2]Department of Physiology, Anatomy, and Genetics University of Oxford, Oxford OX13QX, UK,[3]McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal,Quebec H3A 2B4, Canada,[4]Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha 410011, Hunan, China[5]Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, People’s Republic of China放射科首都医科大学宣武医院
The human brain has been described as a large, sparse, complex network characterized by efficient small-world properties, which assure that the brain generates and integrates information with high efficiency. Many previous neuroimaging studies have provided consistent evidence of dysfunctional connectivity among the brain regions in schizophrenia; however, little is known about whether or not this dysfunctional connectivity causes disruption of the topological properties of brain functional networks. To this end, we investigated the topological properties of human brain functional networks derived from resting-state functional magnetic resonance imaging (fMRI). Data was obtained from 31 schizophrenia patients and 31 healthy subjects; then functional connectivity between 90 cortical and sub-cortical regions was estimated by partial correlation analysis and thresholded to construct a set of undirected graphs. Our findings demonstrated that the brain functional networks had efficient small-world properties in the healthy subjects; whereas these properties were disrupted in the patients with schizophrenia. Brain functional networks have efficient small-world properties which support efficient parallel information transfer at a relatively low cost. More importantly, in patients with schizophrenia the small-world topological properties are significantly altered in many brain regions in the prefrontal, parietal and temporal lobes. These findings are consistent with a hypothesis of dysfunctional integration of the brain in this illness. Specifically, we found that these altered topological measurements correlate with illness duration in schizophrenia. Detection and estimation of these alterations could prove helpful for understanding the pathophysiological mechanism as well as for evaluation of the severity of schizophrenia.
基金:
Natural Science Foundation of China, Grant Nos. 30425004, 30530290 and 30670752, and the National Key Basic Research and Development Program (973), Grant No. 2004CB318107.
第一作者机构:[1]National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, People’s Republic of China,
通讯作者:
通讯机构:[1]National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, People’s Republic of China,
推荐引用方式(GB/T 7714):
Yong Liu ,Meng Liang ,Yuan Zhou ,et al.Disrupted small-world networks in schizophrenia[J].BRAIN.2008,131(4):945-961.doi:10.1093/brain/awn018.