A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study.
A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study.
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DOI：
10.1186/1741-7015-10-64
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发表时间：
2012-06-26
期刊：
影响因子：
9.3
通讯作者：
Als H
中科院分区：
文献类型：
--
作者：
Duffy FH;Als H
自闭症的发病率最近已经上升到百分之一。遗传学研究表明，人们对复杂性知之甚少。环境因素显然也起了作用。磁共振成像（MRI）研究表明，大脑体积增大，连通性改变。脑电图连贯性研究证实了连通性的改变。然而，基因、核磁共振和/或脑电图为基础的诊断测试尚未可用。不同的研究结果可能反映了方法和群体差异，小样本，以及对EEG缺乏对群体特定伪像的关注。在参与这项研究的1,304名年龄在1至18岁之间的儿童中，463名儿童被诊断为自闭症谱系障碍（ASD）；571例患儿为神经典型对照(C)。经过伪影处理后，主成分分析（PCA）识别出具有相应加载模式的脑电信号频谱相干性因子。2至12岁的亚样本包括430名ASD组和554名c组受试者（n = 984）。判别函数分析（DFA）决定了两组光谱相干因子的判别成功。与对照组相比，dfa选择的相干因子的加载模式描述了asd特异性相干差异。一致性数据的总样本主成分分析确定了40个因素，解释了总体方差的50.8%。2 ~ 12岁儿童40项指标组间差异极显著（P < 0.0001）。随机生成的10个分半重复显示出较高的平均分类成功率（C, 88.5%； ASD, 86.0%）。在更严格的年龄亚样本中，使用jackknife技术获得了更高的成功率：2- 4岁儿童（C, 90.6%； ASD, 98.1%）；4 ~ 6岁（C, 90.9%； ASD, 99.1%）；6- 12岁儿童（C, 98.7%； ASD, 93.9%）。与对照组相比，asd组的一致性负载显示出短距离一致性降低，远程一致性降低或增加。每个因子的平均谱负荷较宽（10.1 Hz）。分类的成功表明了一种稳定的一致性加载模式，这种模式将ASD与c组受试者区分开来。这可能构成儿童自闭症的脑电图一致性表型。明显减少的短距离相干可能表明局域网络功能较差。增加的长距离一致性可能代表代偿过程或减少神经修剪。因子负荷的宽平均光谱范围可能表明神经网络过阻尼。
The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz). Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.
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影响因子：
6.9
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