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: 10011856
• 负责人: STEPHEN J SHEINKOPF
• 金额: $ 86.24万
• 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 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10011856
• 关键词: 2 year old; 3 year old; Acoustics; Address; Affect; Age-Months; Arousal; Birth; Characteristics; Child; Child Development; Childhood; Classification; Complex; Data; Detection; 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; 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）对儿童及其生活的生活有重大和长期影响 家庭。直到2岁或以后才能可靠诊断自闭症，目前尚无 可用的方法来筛选婴儿早期的自闭症。初步证据表明 自闭症的特征是婴儿早期哭泣和神经行为的非典型特征。以前的 研究确定了自闭症儿童的声带生产非典型性，异常声音 婴儿哭泣的特征将与幼儿时期的这种发现一致。声学的一个障碍 新生儿哭泣的分析是缺乏基于现代的计算机化哭泣分析系统 技术。我们的实验室已经建立了一种基于最新信号处理的新的哭泣分析系统 可用于研究可能与自闭症风险有关的哭声的声学特征。我们的小组也有 开发了NNNS，这是一种广泛使用且经过良好验证的新生儿的神经行为检查 时期。初步发现指出了这些措施的一组哭泣和神经行为特征 能够区分后来被诊断为自闭症的婴儿与A中包括的非自闭症婴儿 纵向，异质，儿童发展研究。其他初步发现支持以下假设 婴儿哭泣和神经行为在患有后来自闭症诊断的婴儿中受到影响。在拟议的项目中，我们 将利用作为独特怀孕和出生的一部分收集的哭泣和神经行为评估 在大型地区医院的队列。预计最多将注册多达5,000名婴儿并遵循 纵向。 2阶段筛查和评估过程将确定自闭症儿童24至36个月 年龄。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风险有关。 该项目具有很高的意义，并有可能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对 开发有自闭症风险的婴儿的早期筛查和早期干预措施。