FMRI and EEG approaches to the resting state in ASD

FMRI 和 EEG 方法探讨自闭症谱系障碍 (ASD) 的静息状态

• 批准号: 8852190
• 负责人: THOMAS T LIU
• 金额: $ 19.04万
• 依托单位: SAN DIEGO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8852190
• 关键词: Adolescent; Adult; Affect; Arousal; Attention; Autistic Disorder; Base of the Brain; Behavioral; Biological Markers; Brain; Brain Diseases; Brain imaging; Child; Cognitive; Cognitive Science; Consensus; Control Groups; Data; Data Set; Databases; Diagnostic; Disease; Dorsal; Electroencephalography; Excision; Frequencies; Fright; Functional Magnetic Resonance Imaging; Future; Gray unit of radiation dose; Growth; Health; Investigation; Knowledge; Literature; MRI Scans; Magnetic Resonance Imaging; Measures; Methods; Mind; Monitor; Nature; Neurologic; Participant; Pattern; Prevalence; Probability; Procedures; Public Health; Publications; Publishing; Relative (related person); Research; Rest; Risk; Sample Size; Sampling; Scanning; Signal Transduction; Site; Sleep; Slide; Testing; Time; Uncertainty; Variant; autism spectrum disorder; autonomic conditioning; blood oxygen level dependent; cognitive process; cohort; data acquisition; data exchange; data sharing; early onset; foot; interest; neglect; network dysfunction; optimism; response; temporal measurement; time use; trait; vigilance

DESCRIPTION (provided by applicant): In the context of increasing prevalence the brain bases of autism spectrum disorder (ASD) remain incompletely understood. There is growing consensus that ASD is a disorder of brain connectivity, but functional connectivity findings are inconsistent. Resting state functional MRI (rs-fMRI) data, considered ideal for the study of intrinsic functional connectivity, are being acquired by numerous groups and are now available in a large public database. However, known differences in behavioral and cognitive traits may significantly affect fMRI data collected in the 'resting state' and little is known about potential confounds that may result. This lack of knowledge is troubling in view of the ill-defined nature of the 'resting state', which largely eludes experimental control. Specifically, rs-fMRI connectivity has been solely examined using static approaches. The current proposal will use dynamic fMRI sliding window analyses in combination with EEG to investigate the dynamic variability of functional connectivity during the resting state. Samples of adolescents with ASD and matched typically developing (TD) participants from existing cohorts will be scanned using rs-fMRI with concurrent EEG. In two aims we will (1) test dynamic changes in connectivity across time, using a sliding window rs-fMRI analysis; and (2) use EEG data to examine dynamic changes in high temporal frequency bands and characterize temporal patterns observed in Aim 1 with respect to electrophysiological changes. We hypothesize that ASD participants will show greater variability of connectivity across time in and between several networks of interest (default mode, dorsal attention, saliency), accompanied by variability in electrophysiological states. The proposed project will be the first to combine fMRI and EEG for an in-depth investigation of dynamic changes during the 'resting state' in ASD. A better understanding of potentially systematic differences between ASD and TD participants in response to the resting state is a prerequisite for the adequate interpretation of group differences detected in rs-fMRI functional connectivity studies and is therefore urgently needed.

描述（由申请人提供）：在增加患病率的背景下，自闭症谱系障碍（ASD）的大脑基础尚未完全理解。越来越多的共识是ASD是一种大脑连通性的疾病，但功能连通性发现并不一致。静止状态功能性MRI（RS-FMRI）数据被认为是内在功能连接性研究的理想选择，已被许多组获取，现在可以在大型公共数据库中获得。但是，行为和认知特征的已知差异可能会显着影响“静止状态”中收集的fMRI数据，而对潜在的差异知之甚少 可能导致的混杂。考虑到这种缺乏知识，鉴于明确的性质， “静止状态”，这在很大程度上避开了实验控制。具体而言，仅使用静态方法对RS-FMRI连接进行了检查。当前的建议将使用动态fMRI滑动窗口分析与EEG结合使用，以研究静止状态期间功能连接性的动态变异性。 使用与并发脑电图的RS-FMRI一起扫描具有ASD和匹配通常开发的ASD和匹配的青少年（TD）参与者的样本。在两个目标中，我们将使用滑动窗口RS-FMRI分析来测试跨时间的连接性变化； （2）使用脑电图数据检查高时间频带的动态变化，并表征AIM 1在电生理变化中观察到的时间模式。我们假设ASD参与者将在几个感兴趣的网络（默认模式，背注意，显着性）之间以及在电位生理状态的差异中显示出跨时间和时间之间的连通性差异。 拟议的项目将是第一个将fMRI和EEG结合起来的项目，以深入研究ASD中“静止状态”期间动态变化。更好地理解ASD和TD参与者对静止状态的潜在系统差异是对RS-FMRI功能连通性研究中检测到的群体差异的充分解释的先决条件，因此迫切需要。