Identify schizophrenia using resting-state functional connectivity: an exploratory research and analysis.
Identify schizophrenia using resting-state functional connectivity: an exploratory research and analysis.
复制标题
使用静息态功能连接识别精神分裂症：探索性研究和分析
DOI：
10.1186/1475-925x-11-50
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发表时间：
2012-08-16
影响因子：
3.9
通讯作者：
Tan L
中科院分区：
文献类型：
--
作者：
Tang Y;Wang L;Cao F;Tan L
精神分裂症是一种严重的精神疾病，伴有幻觉和妄想等症状。本研究的目的是调查精神分裂症患者的异常静息态功能连接模式，以识别与健康对照最远的患者。对诊断为精神分裂症的患者 (n = 22) 以及年龄和性别匹配的健康对照受试者 (n = 22) 进行了全脑静息态 fMRI。为了区分精神分裂症患者与健康对照者，采用了多变量分类分析。通过重建算法获得加权的大脑区域，以提取具有高度辨别力的功能连接信息。结果表明，93.2% (p<0.001) 的受试者通过留一交叉验证方法被正确分类。大多数改变的功能连接都位于视觉皮层、默认模式和感觉运动网络内。此外，在重建算术中，梭状回表现出最大的重量。本研究表明，利用全脑静息态功能磁共振成像可以成功区分精神分裂症患者与健康受试者，并且梭状回可能在精神分裂症患者所表现的生理症状中发挥重要的功能作用。大脑重量较大的区域可能是精神分裂症患者信息交换的问题区域。因此，我们的结果可能为识别精神分裂症临床诊断的潜在有效生物标志物提供见解。
Schizophrenia is a severe mental illness associated with the symptoms such as hallucination and delusion. The objective of this study was to investigate the abnormal resting-state functional connectivity patterns of schizophrenic patients which could identify furthest patients from healthy controls. The whole-brain resting-state fMRI was performed on patients diagnosed with schizophrenia (n = 22) and on age- and gender-matched, healthy control subjects (n = 22). To differentiate schizophrenic individuals from healthy controls, the multivariate classification analysis was employed. The weighted brain regions were got by reconstruction arithmetic to extract highly discriminative functional connectivity information. The results showed that 93.2% (p < 0.001) of the subjects were correctly classified via the leave-one-out cross-validation method. And most of the altered functional connections identified located within the visual cortical-, default-mode-, and sensorimotor network. Furthermore, in reconstruction arithmetic, the fusiform gyrus exhibited the greatest amount of weight. This study demonstrates that schizophrenic patients may be successfully differentiated from healthy subjects by using whole-brain resting-state fMRI, and the fusiform gyrus may play an important functional role in the physiological symptoms manifested by schizophrenic patients. The brain region of great weight may be the problematic region of information exchange in schizophrenia. Thus, our result may provide insights into the identification of potentially effective biomarkers for the clinical diagnosis of schizophrenia.