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项目摘要/摘要 数学认知为数量技能的发展提供了基础,而数量技能对于 21世纪。然而,数学困难在儿童、青少年和大学生中普遍存在,还有一个 在美国,每五个成年人中就有五分之一的人功能不清。算术能力低与健康状况不佳有关 结果,健康素养下降,以及不适当地使用卫生资源。神经认知的特征 数学障碍(MD)的发展轨迹和危险因素是解决公众问题的关键 不会算数的健康负担。在创新和高影响力的研究基础上,我们建议 研究MD患者的神经认知纵向轨迹和结果。我们的重点是两个关键的认知 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,包括解决数值问题和流利地检索数学 记忆中的事实。我们的中心假设是,相对于典型的发展(TD)控制,个体 患有MD的患者将在大脑反应、表征和连接性方面呈现非典型的发育轨迹 两个脑功能系统:(1)顶叶视觉空间注意系统,支持数量 表示法,以及(2)支持算术运算的中间时态(MTL)声明性存储系统 事实检索。我们将检验(1)非典型数感发展的核心和通路缺陷模型和(2) 弱事实提取的记忆缺陷模型。使用最先进的多模式脑成像和三种 创新的纵向设计,我们将通过(1)描述以下方面的发展轨迹来测试这些模型 儿童和青少年,跨越小学、初中和高中(7至16岁),有 加速纵向设计;(2)确定预测纵向2年早期数学的大脑测量 幼儿在正式指导或MD诊断之前的轨迹和结果(5-7岁);和(3) 确定可预测青少年(17岁)纵向10年长期数学结果的大脑测量方法 他们以前的特点是童年时期的。三个创新的纵向设计将解决关键差距 在我们对影响MD发育的神经认知系统的理解中。调查结果将为我们的 了解MD的病因和开发有针对性的认知干预措施 最终减轻低数字带来的公共卫生负担。
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