Identification of imaging biomarkers in schizophrenia: a coefficient-constrained independent component analysis of the mind multi-site schizophrenia study.
Identification of imaging biomarkers in schizophrenia: a coefficient-constrained independent component analysis of the mind multi-site schizophrenia study.
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DOI：
10.1007/s12021-010-9077-7
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发表时间：
2010-12
期刊：
影响因子：
3
通讯作者：
Calhoun, Vince D.
中科院分区：
文献类型：
--
作者：
Kim, Dae Il;Sui, Jing;Rachakonda, Srinivas;White, Tonya;Manoach, Dara S.;Clark, V. P.;Ho, Beng Choon;Schulz, S. Charles;Calhoun, Vince D.
关键词：
最近的一些研究结合了多种实验范式和模式来寻找精神分裂症的相关生物学标志物。在这项研究中，我们从分析大量（n=154）精神分裂症患者和匹配的健康对照者的三种实验范式（听觉怪球、Sternberg项目识别、感觉运动）中提取了fMRI特征图。我们使用一般线性模型（GLM）和独立成分分析（ICA）来提取特征图（即ICA成分图和GLM对比图），然后进行系数约束独立成分分析（CCICA）来识别潜在的神经生物学标记。每个受试者总共提取了29个不同的特征图。我们的研究结果显示了一些最优的特征组合，这些特征组合反映了一组大脑区域，这些区域在特征信号的空间异质性和幅度上明显区别于患者和对照组。在颞上/中颞回和额回、双侧顶叶和丘脑等区域可见空间异质性。最引人注目的是，当根据特征信号幅度的差异进行排名时，代表双侧额极网络的ICA特征始终被视为十个最高的特征结果。这种额极网络的含义和跨越双侧额叶/颞叶和顶叶区域的空间变异性表明，这些区域可能在精神分裂症的病理生理中发挥重要作用。
A number of recent studies have combined multiple experimental paradigms and modalities to find relevant biological markers for schizophrenia. In this study, we extracted fMRI features maps from the analysis of three experimental paradigms (auditory oddball, Sternberg item recognition, sensorimotor) for a large number (n=154) of patients with schizophrenia and matched healthy controls. We used the general linear model (GLM) and independent component analysis (ICA) to extract feature maps (i.e. ICA component maps and GLM contrast maps), which were then subjected to a coefficient-constrained independent component analysis (CCICA) to identify potential neurobiological markers. A total of 29 different feature maps were extracted for each subject. Our results show a number of optimal feature combinations that reflect a set of brain regions that significantly discriminate between patients and controls in the spatial heterogeneity and amplitude of their feature signals. Spatial heterogeneity was seen in regions such as the superior/middle temporal and frontal gyri, bilateral parietal lobules, and regions of the thalamus. Most strikingly, an ICA feature representing a bilateral frontal pole network was consistently seen the ten highest feature results when ranked on differences found in the amplitude of their feature signals. The implication of this frontal pole network and the spatial variability which spans regions comprising of bilateral frontal/temporal lobes and parietal lobules suggests that these regions might play a significant role in the pathophysiology of schizophrenia.
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DOI：
10.1098/rstb.2005.1634
发表时间：
2005-05-29
影响因子：
6.3
作者：
Beckmann, CF;DeLuca, M;Smith, SM
通讯作者：
Smith, SM
影响因子：
5.7
作者：
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通讯作者：
Liddle, PF
影响因子：
10.6
作者：
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通讯作者：
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影响因子：
5.7
作者：
Friedman, Lee;Glover, Gary H.
通讯作者：
Glover, Gary H.
影响因子：
10.6
作者：
Freire, L;Roche, A;Mangin, JF
通讯作者：
Mangin, JF