Detecting stable individual differences in the functional organization of the human basal ganglia.
Detecting stable individual differences in the functional organization of the human basal ganglia.
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DOI：
10.1016/j.neuroimage.2017.07.029
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发表时间：
2018-04-15
期刊：
影响因子：
5.7
通讯作者：
Milham MP
中科院分区：
文献类型：
--
作者：
Garcia-Garcia M;Nikolaidis A;Bellec P;Craddock RC;Cheung B;Castellanos FX;Milham MP
从群体水平到个人水平的功能分割图是丰富理解功能网络结构中个体差异与认知和临床表型之间联系的关键一步。尽管如此，基于受试者之间和受试者之间的内在功能连接及其动态变化来识别大脑中的功能单位仍然具有挑战性。最近，稳定簇的Bootstrap分析(BASC)框架被开发用于量化受试者之间和受试者内部的功能脑网络的稳定性。这种多层次方法利用引导重新采样用于个人和组级别的聚类，以基于其跨对象和在对象内的一致性来描绘功能单元，同时提供对其稳定性的测量。在这里，我们通过研究各种聚类算法和相似性度量来优化BASC框架以进行基底节的功能分割。计算了重复性和重测信度，以验证该分析框架作为描述功能网络稳定性的个体间差异的工具。稳定的簇揭示的功能分割复制了先前在基底节中发现的基于内在功能连接的分裂。虽然我们发现了中等到高度的重复性，但重测的可靠性在功能单元的边界和核心内都很高。这很有趣，因为功能网络之间的边界已经被证明可以解释大多数个体的表型差异。目前的研究为基底节的分割的一致性提供了证据，并提供了第一个从个体水平的簇解决方案建立的组水平的分割。这些新的结果证明了BASC在量化大脑区域功能组织的个体间差异方面的实用性，并鼓励在未来的研究中使用。
Moving from group level to individual level functional parcellation maps is a critical step for developing a rich understanding of the links between individual variation in functional network architecture and cognitive and clinical phenotypes. Still, the identification of functional units in the brain based on intrinsic functional connectivity and its dynamic variations between and within subjects remains challenging. Recently, the bootstrap analysis of stable clusters (BASC) framework was developed to quantify the stability of functional brain networks both across and within subjects. This multi-level approach utilizes bootstrap resampling for both individual and group-level clustering to delineate functional units based on their consistency across and within subjects, while providing a measure of their stability. Here, we optimized the BASC framework for functional parcellation of the basal ganglia by investigating a variety of clustering algorithms and similarity measures. Reproducibility and test-retest reliability were computed to validate this analytic framework as a tool to describe inter-individual differences in the stability of functional networks. The functional parcellation revealed by stable clusters replicated previous divisions found in the basal ganglia based on intrinsic functional connectivity. While we found moderate to high reproducibility, test-retest reliability was high at the boundaries of the functional units as well as within their cores. This is interesting because the boundaries between functional networks have been shown to explain most individual phenotypic variability. The current study provides evidence for the consistency of the parcellation of the basal ganglia, and provides the first group level parcellation built from individual-level cluster solutions. These novel results demonstrate the utility of BASC for quantifying inter-individual differences in the functional organization of brain regions, and encourage usage in future studies.
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影响因子：
19.9
作者：
Byrge, Lisa;Sporns, Olaf;Smith, Linda B.
通讯作者：
Smith, Linda B.
DOI：
10.1176/appi.ajp.2009.08121894
发表时间：
2009-08
期刊：
The American journal of psychiatry
影响因子：
--
作者：
Di Martino A;Shehzad Z;Kelly C;Roy AK;Gee DG;Uddin LQ;Gotimer K;Klein DF;Castellanos FX;Milham MP
通讯作者：
Milham MP
影响因子：
48
作者：
Craddock, R. Cameron;Jbabdi, Saad;Yan, Chao-Gan;Vogelstein, Joshua T.;Castellanos, F. Xavier;Di Martino, Adriana;Kelly, Clare;Heberlein, Keith;Colcombe, Stan;Milham, Michael P.
通讯作者：
Milham, Michael P.
影响因子：
5.7
作者：
Curtis, Andrew T.;Hutchison, R. Matthew;Menon, Ravi S.
通讯作者：
Menon, Ravi S.
影响因子：
10.6
作者：
Chabernaud, Camille;Mennes, Maarten;Kelly, Clare;Nooner, Kate;Di Martino, Adriana;Castellanos, F. Xavier;Milham, Michael P.
通讯作者：
Milham, Michael P.