Anatomical insights into disrupted small-world networks in schizophrenia
Anatomical insights into disrupted small-world networks in schizophrenia
复制标题
对精神分裂症中小世界网络破坏的解剖学见解
DOI：
10.1016/j.neuroimage.2011.09.035
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发表时间：
2012-01
期刊：
影响因子：
5.7
通讯作者：
Lin, Ching-Po
中科院分区：
文献类型：
--
作者：
Wang, Qifeng;Su, Tung-Ping;Zhou, Yuan;Chou, Kun-Hsien;Chen, I-Yun;Jiang, Tianzi;Lin, Ching-Po
精神分裂症的特征是分布式信息处理效率降低，研究表明，这是一个中断的小世界功能网络。然而，小世界功能网络被破坏所表现出的连接失调是否反映在精神分裂症潜在的解剖破坏中仍未得到解决。这项研究检测了精神分裂症患者和健康对照组通过扩散张量成像获得的人脑解剖网络的拓扑特性。我们用扩散张量束成像技术构建了79例精神分裂症患者和96例年龄、性别匹配的健康受试者的加权脑解剖网络，并用图论方法计算了网络的拓扑性质。患者解剖网络的拓扑属性发生了变化，全局效率降低，但局部效率保持不变。精神分裂症对网络性能的有害影响似乎局限于中枢的区域效率降低，如额叶联合皮质、边缘旁/边缘区域和皮质下结构(左壳核)。此外，精神分裂症患者在阳性和阴性症状量表上的得分与有效网络属性呈负相关。这些发现表明，复杂的大脑网络分析可能被用于检测精神分裂症的成像生物标记物。
Schizophrenia is characterized by lowered efficiency in distributed information processing, as indicated by research that identified a disrupted small-world functional network. However, whether the dysconnection manifested by the disrupted small-world functional network is reflected in underlying anatomical disruption in schizophrenia remains unresolved. This study examined the topological properties of human brain anatomical networks derived from diffusion tensor imaging in patients with schizophrenia and in healthy controls. We constructed the weighted brain anatomical network for each of 79 schizophrenia patients and for 96 age and gender matched healthy subjects using diffusion tensor tractography and calculated the topological properties of the networks using a graph theoretical method. The topological properties of the patients' anatomical networks were altered, in that global efficiency decreased but local efficiency remained unchanged. The deleterious effects of schizophrenia on network performance appear to be localized as reduced regional efficiency in hubs such as the frontal associative cortices, the paralimbic/limbic regions and a subcortical structure (the left putamen). Additionally, scores on the Positive and Negative Symptom Scale correlated negatively with efficient network properties in schizophrenia. These findings suggest that complex brain network analysis may potentially be used to detect an imaging biomarker for schizophrenia.
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DOI：
10.1523/jneurosci.1929-08.2008
发表时间：
2008-09-10
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Bassett DS;Bullmore E;Verchinski BA;Mattay VS;Weinberger DR;Meyer-Lindenberg A
通讯作者：
Meyer-Lindenberg A
影响因子：
4.3
作者：
Achard S;Bullmore E
通讯作者：
Bullmore E
影响因子：
3.7
作者：
Hagmann, Patric;Kurant, Maciej;Gigandet, Xavier;Thiran, Patrick;Wedeen, Van J.;Meuli, Reto;Thiran, Jean-Philippe
通讯作者：
Thiran, Jean-Philippe
影响因子：
4.5
作者：
Yuan Zhou;N. Shu;Yong Liu;Ming Song;Yihui Hao;Haihong Liu;Chunshui Yu;Zhening Liu;T. Jiang-T.
通讯作者：
Yuan Zhou;N. Shu;Yong Liu;Ming Song;Yihui Hao;Haihong Liu;Chunshui Yu;Zhening Liu;T. Jiang-T.
影响因子：
17.7
作者：
Lang, DJ;Kopala, LC;Honer, WG
通讯作者：
Honer, WG