当前位置: X-MOL 学术Mol. Autism › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Generalizability and reproducibility of functional connectivity in autism.
Molecular Autism ( IF 6.2 ) Pub Date : 2019-06-24 , DOI: 10.1186/s13229-019-0273-5
Jace B King 1, 2 , Molly B D Prigge 3, 4 , Carolyn K King 1, 3 , Jubel Morgan 1, 3, 4 , Fiona Weathersby 1, 5 , J Chancellor Fox 1 , Douglas C Dean 4 , Abigail Freeman 4, 6 , Joaquin Alfonso M Villaruz 4 , Karen L Kane 4 , Erin D Bigler 7 , Andrew L Alexander 4, 6, 8 , Nicholas Lange 9 , Brandon Zielinski 3, 10 , Janet E Lainhart 4, 6 , Jeffrey S Anderson 1, 2, 5
Affiliation  

Background Autism is hypothesized to represent a disorder of brain connectivity, yet patterns of atypical functional connectivity show marked heterogeneity across individuals. Methods We used a large multi-site dataset comprised of a heterogeneous population of individuals with autism and typically developing individuals to compare a number of resting-state functional connectivity features of autism. These features were also tested in a single site sample that utilized a high-temporal resolution, long-duration resting-state acquisition technique. Results No one method of analysis provided reproducible results across research sites, combined samples, and the high-resolution dataset. Distinct categories of functional connectivity features that differed in autism such as homotopic, default network, salience network, long-range connections, and corticostriatal connectivity, did not align with differences in clinical and behavioral traits in individuals with autism. One method, lag-based functional connectivity, was not correlated to other methods in describing patterns of resting-state functional connectivity and their relationship to autism traits. Conclusion Overall, functional connectivity features predictive of autism demonstrated limited generalizability across sites, with consistent results only for large samples. Different types of functional connectivity features do not consistently predict different symptoms of autism. Rather, specific features that predict autism symptoms are distributed across feature types.

中文翻译:

自闭症中功能连接的普遍性和可复制性。

背景自闭症被认为代表一种大脑连接障碍,但是非典型功能连接的模式在个体之间显示出明显的异质性。方法我们使用了一个大型的多站点数据集,该数据集包含自闭症个体的异质群体,通常是发展中的个体,以比较自闭症的许多静息状态功能连接特征。这些特征还通过使用高温分辨率,长时间静止状态采集技术的单个站点样本进行了测试。结果没有一种分析方法可以在研究地点,组合样品和高分辨率数据集之间提供可重复的结果。自闭症不同的功能连接功能的不同类别,例如同位,默认网络,显着网络,远程连接,自闭症患者的皮质和骨皮质连接性与临床和行为特征的差异不符。一种方法,基于滞后的功能连通性,在描述静止状态功能连通性及其与自闭症特征之间的关系时,与其他方法不相关。结论总体而言,可预测自闭症的功能连接性特征证明了跨站点的通用性有限,仅大型样本具有一致的结果。不同类型的功能连接功能不能始终如一地预测自闭症的不同症状。而是,预测自闭症症状的特定特征分布在各个特征类型中。与描述静止状态功能连接模式及其与自闭症特征的关系方面的其他方法无关。结论总体而言,可预测自闭症的功能连接性特征证明了跨站点的通用性有限,仅大型样本具有一致的结果。不同类型的功能连接功能不能始终如一地预测自闭症的不同症状。而是,预测自闭症症状的特定特征分布在各个特征类型中。与描述静止状态功能连接模式及其与自闭症特征的关系方面的其他方法无关。结论总体而言,可预测自闭症的功能连接性特征证明了跨站点的通用性有限,仅大型样本具有一致的结果。不同类型的功能连接功能不能始终如一地预测自闭症的不同症状。而是,预测自闭症症状的特定特征分布在各个特征类型中。不同类型的功能连接功能不能始终如一地预测自闭症的不同症状。而是,预测自闭症症状的特定特征分布在各个特征类型中。不同类型的功能连接功能不能始终如一地预测自闭症的不同症状。而是,预测自闭症症状的特定特征分布在各个特征类型中。
更新日期:2019-06-24
down
wechat
bug