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中文摘要
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项目概要/摘要 数学认知提供了一个基础,为定量技能的发展至关重要的运作, 21世纪。然而,数学困难在儿童、青少年和大学生中普遍存在, 在美国,五个成年人中有一个是功能性的不识数。计算能力低与健康状况较差有关 结果,健康知识普及率降低,卫生资源使用不当。表征神经认知 发展轨迹和风险因素的数学残疾(MD)是至关重要的,以解决公众 不识数的健康负担。在创新和高影响力的研究基础上,我们建议 研究MD的神经认知纵向轨迹和结果。我们专注于两个关键的认知 MD受损的领域:(1)数感,包括数量,数字及其 心理操作,以及(2)算术技能,包括解决数字问题和流畅的数学检索 记忆中的事实我们的中心假设是,相对于典型发展(TD)控制,个体 患有MD的人将表现出非典型的大脑反应、表征和连接的发展轨迹, 两个脑功能系统:(1)顶叶视觉空间注意系统,支持数量 陈述,以及(2)中间时间(MTL)声明性记忆系统,它支持算术 事实检索我们将测试(1)非典型数感发展的核心和接近缺陷模型,以及(2) 一个记忆缺陷模型的弱事实检索。使用最先进的多模式脑成像和三个 创新的纵向设计,我们将测试这些模型(1)特征的发展轨迹, 儿童和青少年,跨越小学,初中和高中年龄(7至16岁), 加速纵向设计;(2)确定预测纵向2年早期数学的大脑措施 在正式指导或MD诊断之前的幼儿(5-7岁)的轨迹和结果;以及(3) 确定预测青少年(17岁)纵向10年长期数学结果的大脑测量 这些人在童年时就有特征。三种创新的纵向设计将解决关键差距 我们对神经认知系统的理解影响了MD的发展。调查结果将告知我们 了解MD的病因和有针对性的认知干预措施的发展, 最终减轻低计算能力的公共卫生负担。
英文摘要
Project Summary/Abstract Mathematical cognition provides a foundation for the development of quantitative skills critical for functioning in the 21st century. Yet, math difficulties are widespread in children, adolescents, and college students, and one in five adults in the USA is functionally innumerate. Low numeracy is associated with poorer health outcomes, reduced health literacy, and improper use of health resources. Characterizing neurocognitive developmental trajectories and risk factors of mathematical disabilities (MD) is critical for addressing the public health burdens of innumeracy. Building on an innovative and high-impact line of research, we propose to investigate neurocognitive longitudinal trajectories and outcomes in MD. We focus on two key cognitive domains impaired in MD: (1) number sense, including representations of quantities, numbers, and their mental manipulation, and (2) arithmetic skills, including numerical problem solving and fluent retrieval of math facts from memory. Our central hypothesis is that, relative to typically developing (TD) controls, individuals with MD will exhibit atypical developmental trajectories of brain response, representations, and connectivity in two functional brain systems: (1) the parietal visuo-spatial attention system, which supports quantity representations, and (2) the medial temporal (MTL) declarative memory system, which supports arithmetic fact retrieval. We will test (1) core and access deficit models of atypical number sense development and (2) a memory deficit model of weak fact retrieval. Using state-of-the-art multimodal brain imaging and three innovative longitudinal designs, we will test these models by (1) characterizing developmental trajectories in children and adolescents, spanning elementary, middle, and high school years (ages 7 to 16), with an accelerated longitudinal design; (2) identify brain measures that predict longitudinal 2-year early math trajectories and outcomes in young children prior to formal instruction or MD diagnosis (ages 5-7); and (3) identify brain measures that predict longitudinal 10-year long-term math outcomes in adolescents (age 17) who were previously characterized in childhood. Three innovative longitudinal designs will address critical gaps in our understanding of neurocognitive systems impacted over development in MD. Findings will inform our understanding of the etiology of MD and the development of targeted cognitive interventions that may ultimately reduce the public health burden of low numeracy.
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Circuit Mechanisms Governing the Default Mode Network
Circuit Mechanisms Governing the Default Mode Network
Integrative computational models of latent behavioral and neural constructs in children: a longitudinal developmental big-data approach
  • 批准号:
    10200653
  • 项目类别:
  • 资助金额:
    $78.31万
  • 财政年份:
    2019
  • 负责人:
    VINOD MENON
  • 依托单位:
Integrative computational models of latent behavioral and neural constructs in children: a longitudinal developmental big-data approach
  • 批准号:
    10631143
  • 项目类别:
  • 资助金额:
    $78.31万
  • 财政年份:
    2019
  • 负责人:
    VINOD MENON
  • 依托单位:
海外基金