Bioengineering Department and Computer Science and Engineering Department, University of Louisville, Louisville, KY, USA.
Bioengineering Dept., University of Louisville, Louisville, KY, USA.
Med Image Anal. 2021 Feb;68:101899. doi: 10.1016/j.media.2020.101899. Epub 2020 Nov 12.
Altered functional connectivity patterns play an important role in explaining autism spectrum disorder related impairments. In order to examine such connectivity, resting state functional MRI is the most commonly used technique. To date, the majority of works in this area examine a whole time series of brain activation as a discrete stationary process. This study proposes a more detailed analysis of how functional connectivity fluctuates over time and how it is used to quantify instances demonstrating overconnectivity or underconnectivity. Non-parametric surrogates test identifies the areas where underconnectivity or overconnectivity correlate with the Autism Diagnosis Observation Schedule. In addition, this study shows how the areas identified affect the subjects behaviors. Our ultimate goal is a personalized autism diagnosis and treatment CAD system, where each subject impairments are distinctly mapped so they can be addressed with targeted treatments.
功能连接模式的改变在解释自闭症谱系障碍相关损伤方面起着重要作用。为了研究这种连接，静息态功能磁共振成像（fMRI）是最常用的技术。迄今为止，该领域的大多数研究都将整个脑激活时间序列作为离散的平稳过程进行研究。本研究提出了一种更详细的分析方法，研究功能连接如何随时间波动，以及如何利用它来量化表现出过度连接或连接不足的实例。非参数替代检验确定了与自闭症诊断观察量表（Autism Diagnosis Observation Schedule）相关的连接不足或过度连接的区域。此外，本研究还展示了所确定的区域如何影响被试的行为。我们的最终目标是建立一个个性化的自闭症诊断和治疗 CAD 系统，其中每个被试的损伤都被明确地映射出来，以便可以针对这些损伤进行靶向治疗。
