Neonatal Cry Acoustics and Neurobehavioral Characteristics as Early Markers of Risk for Autism Spectrum Disorder

新生儿哭声和神经行为特征作为自闭症谱系障碍风险的早期标志

• 批准号: 10213595
• 负责人: STEPHEN J SHEINKOPF
• 金额: --
• 依托单位: WOMEN AND INFANTS HOSPITAL-RHODE ISLAND
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-09 至 2021-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10213595
• 关键词: 2 year old; 3 year old; Acoustics; Address; Affect; Age-Months; Arousal; Birth; Characteristics; Child; Child Development; Childhood; Classification; Complex; Data; Development; Developmental Course; Diagnosis; Diagnostic; Disease Progression; Early Intervention; Early identification; Enrollment; Evaluation; Family; Family member; Functional disorder; Genetic; Hospitals; Impairment; Infant; Life; Link; Logistics; Long-Term Effects; Measures; Methods; Modeling; Modernization; Movement; Neonatal; Neurodevelopmental Deficit; Newborn Infant; Outcome; Parents; Population; Predictive Value; Pregnancy; Prevention; Procedures; Process; Production; Property; Public Health; Publishing; Recording of previous events; Registries; Regulation; Research; Rhode Island; Risk; Risk Marker; Sampling; Screening procedure; Series; Siblings; Signal Transduction; Statistical Models; Stress; Systems Analysis; Technology; Testing; Validation; Woman; Work; autism spectrum disorder; autistic children; base; biobehavior; cohort; computerized; detection method; early childhood; early screening; follow-up; high risk infant; improved; infancy; model building; model development; neonatal period; neurobehavior; neurobehavioral; novel; predictive modeling; recruit; response; screening; signal processing; success; tool development

PROJECT SUMMARY/ABSTRACT Autism Spectrum Disorders (autism) has significant and long term effects on the lives of children and their families. Reliable diagnosis of autism is not possible until 2 years of age or later, and there are no currently available methods to screen for autism in early infancy. Preliminary evidence suggests that children with autism may be characterized by atypical features of cry and neurobehavior during early infancy. Previous research has identified atypicalities in vocal production in older children with autism, and unusual acoustic features of infant cry would be consistent with such findings from early childhood. One barrier to the acoustic analysis of newborn cry has been the lack of a computerized cry analysis system based on modern technology. Our lab has developed a new cry analysis system based on state-of-the-art signal processing that can be used to study acoustic characteristics of cry that could relate to risk for autism. Our group has also developed the NNNS, a widely used and well validated neurobehavioral exam for infants in the newborn period. Preliminary findings point to a set of cry and neurobehavioral features from these measures that was able to differentiate a sample of infants later diagnosed with autism from non-autistic infants included in a longitudinal, heterogeneous, child development study. Other preliminary findings support the hypothesis that infant cry and neurobehavior are affected in infants with later autism diagnoses. In the proposed project, we will utilize cry and neurobehavioral assessments that are being collected as part of unique pregnancy and birth cohort at a large regional hospital. It is anticipated that up to up to 5,000 infants will be enrolled and followed longitudinally. A 2-stage screening and evaluation process will identify children with autism by 24 to 36 months of age. Ongoing analyses will be conducted to identify neonatal cry and neurobehavioral characteristics that are associated with risk for autism using signal detection methods and complex conditional statistical models. This project is of high significance and has the potential to have substantial impact on public health by identifying potential indicators of risk for autism. The long term impact of this research would be on the development of early screening and early interventions for infants at risk for autism.

项目摘要/摘要 自闭症谱系障碍(自闭症)对儿童的生活和他们的 家人。自闭症的可靠诊断直到两岁或更晚是不可能的，目前还没有 在婴儿早期筛查自闭症的有效方法。初步证据表明，患有 自闭症的特征可能是婴儿早期哭闹和神经行为的不典型特征。上一首 研究发现，患有自闭症的年龄较大的儿童在发声方面存在非典型性，而且声音异常 婴儿哭闹的特征与儿童早期的发现是一致的。声学的一个障碍 新生儿哭声分析一直缺乏一套基于现代计算机的哭声分析系统 技术我们实验室基于最先进的信号处理技术开发了一种新的哭声分析系统 可以用来研究哭声的声学特征，这可能与自闭症的风险有关。我们组也有 开发了NNNS，这是一种广泛使用且经过良好验证的新生儿神经行为测试 句号。初步的发现表明，这些测量方法中的一系列哭声和神经行为特征 能够区分后来被诊断为自闭症的婴儿样本和包括在 纵向的、异质性的、儿童发展研究。其他初步发现支持这样的假设 自闭症确诊较晚的婴儿会受到哭闹和神经行为的影响。在建议的项目中，我们 将利用作为独特怀孕和分娩一部分收集的哭声和神经行为评估 一家大型地区性医院的队列。预计将有多达5,000名婴儿参加登记和跟踪 纵向的。一个两阶段的筛查和评估过程将在24到36个月内确定患有自闭症的儿童。 年纪大了。将进行持续的分析，以确定新生儿哭泣和神经行为特征 使用信号检测方法和复杂的条件统计模型，与自闭症的风险有关。 该项目意义重大，有可能通过以下方式对公共卫生产生重大影响 确定自闭症风险的潜在指标。这项研究的长期影响将是 发展对有自闭症风险的婴儿的早期筛查和早期干预。