Altered resting state complexity in schizophrenia.
Altered resting state complexity in schizophrenia.
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DOI：
10.1016/j.neuroimage.2011.10.002
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发表时间：
2012-02-01
期刊：
影响因子：
5.7
通讯作者：
Lim, Kelvin O.
中科院分区：
文献类型：
--
作者：
Bassett, Danielle S.;Nelson, Brent G.;Mueller, Bryon A.;Camchong, Jazmin;Lim, Kelvin O.
人类大脑活动和连接的复杂性随时间尺度而变化，并在精神分裂症等疾病状态下发生变化。使用多层次的分析自发低频fMRI数据拉伸从个别脑区的活动，以协调连接模式的整个大脑，我们调查的作用，脑信号的复杂性在精神分裂症。具体而言，我们定量表征区域活动的单变量小波熵，区域之间的二元成对功能连接，以及连接模式的多元网络组织。我们的研究结果表明，单变量的复杂性措施是不太敏感的疾病状态比更高级别的双变量和多变量措施。虽然小波熵不受疾病状态的影响，成对的功能连接的幅度显着降低精神分裂症和方差增加。此外，通过考虑网络结构作为相关强度的函数，我们发现，网络组织特别是弱连接与注意力，记忆力和阴性症状评分密切相关，并显示出作为临床生物标志物的潜力，提供高达75%的分类准确度和85%的灵敏度。我们还开发了一个通用的统计框架，用于测试网络特性的组间差异，该框架广泛适用于网络组织变化对理解大脑功能至关重要的研究。
The complexity of the human brain’s activity and connectivity varies over temporal scales and is altered in disease states such as schizophrenia. Using a multi-level analysis of spontaneous low-frequency fMRI data stretching from the activity of individual brain regions to the coordinated connectivity pattern of the whole brain, we investigate the role of brain signal complexity in schizophrenia. Specifically, we quantitatively characterize the univariate wavelet entropy of regional activity, the bivariate pairwise functional connectivity between regions, and the multivariate network organization of connectivity patterns. Our results indicate that univariate measures of complexity are less sensitive to disease state than higher level bivariate and multivariate measures. While wavelet entropy is unaffected by disease state, the magnitude of pairwise functional connectivity is significantly decreased in schizophrenia and the variance is increased. Furthermore, by considering the network structure as a function of correlation strength, we find that network organization specifically of weak connections is strongly correlated with attention, memory, and negative symptom scores and displays potential as a clinical biomarker, providing up to 75% classification accuracy and 85% sensitivity. We also develop a general statistical framework for the testing of group differences in network properties, which is broadly applicable to studies where changes in network organization are crucial to the understanding of brain function.
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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：
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作者：
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通讯作者：
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影响因子：
5.3
作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
Auer, Dorothee P.
DOI：
10.1146/annurev-clinpsy-040510-143934
发表时间：
2011-01-01
影响因子：
18.4
作者：
Bullmore, Edward T.;Bassett, Danielle S.
通讯作者：
Bassett, Danielle S.