Integrative computational models of latent behavioral and neural constructs in children: a longitudinal developmental big-data approach

儿童潜在行为和神经结构的综合计算模型:纵向发展大数据方法

基本信息

  • 批准号:
    10425350
  • 负责人:
  • 金额:
    $ 78.31万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-07-26 至 2024-05-31
  • 项目状态:
    已结题

项目摘要

Project Abstract Impairments in cognitive systems that regulate the ability to adaptively engage with and respond to changing stimuli and goals are a hallmark of psychopathology. Identifying the underlying cognitive and neural factors that drive dysfunctional behavioral dynamics is a primary goal for psychiatric research. However conventional methods are unable to reveal latent constructs that govern these dynamic processes. Novel computational approaches are required to reveal latent behavioral dynamics and traits associated with psychopathology, and their neural circuit basis, within the Research Domain Criteria (RDoC) framework. Most, if not all, psychiatric disorders have a neurodevelopmental origin and are associated with atypical maturation of cognitive brain networks. Cognition is a dynamic process, which relies on flexible inhibitory control, goal-directed beliefs that impact moment-to-moment expectation, and the capacity to learn and adapt from prior decisions. Developing dynamic latent behavioral models of cognition is significant in the context of psychopathology, because deficits in inhibitory control, performance monitoring and belief updating are implicated in multiple psychiatric disorders including ADHD, autism, and schizophrenia. Our overarching goal is to develop and validate Hierarchical Latent Variable Dynamics (HLVD), a novel integrative computational approach for discovering robust latent behavioral constructs and their neural circuit bases. The proposed studies will leverage the longitudinal Adolescent Behavioral and Cognitive Development (ABCD) study, which has generated unprecedented amounts of “Big Data” (N>5,000) for charting cognitive and brain development in children and adolescents over time. Crucially, HLVD will be used to identify and validate novel latent constructs of behavioral dynamics that are expected to be significant dimensional predictors of externalizing symptoms and developmental psychopathology. The proposed studies will significantly enhance our understanding of RDoC constructs and provide new insights into latent behavioral dynamics and traits associated with psychopathology in the developing brain. Our studies are highly relevant to the mission of the NIMH initiative RFA-MH-19-242, which seeks to accelerate research on neurodevelopment and trajectories of risk for mental illness. Our innovative approach will ultimately aid in the development of biomarkers for early detection and treatment of psychiatric disorders.
项目摘要 认知系统中调节适应和应对变化的能力的损害 刺激和目标是精神病理学的一个标志。确定潜在的认知和神经因素, 驾驶功能障碍的行为动力学是精神病学研究的主要目标。无论多么传统 方法无法揭示控制这些动态过程的潜在构造。新颖的计算方式 需要方法来揭示潜在的行为动力学和与精神病理学相关的特征,以及 他们的神经回路基础,在研究领域标准(RDoC)框架内。大多数,如果不是全部的话,精神病 障碍源于神经发育,并与认知大脑的非典型成熟有关 网络。认知是一个动态的过程,它依赖于灵活的抑制控制和目标导向的信念 这种影响时时刻刻的预期,以及从先前的决定中学习和适应的能力。 在精神病理学的背景下,开发认知的动态潜在行为模型是重要的, 由于抑制控制、绩效监控和信念更新方面的缺陷与多个 精神障碍包括多动症、自闭症和精神分裂症。我们的首要目标是发展和 一种新的一体化计算方法--分层潜变量动力学(HLVD)的验证 发现健壮的潜在行为结构及其神经回路基础。拟议的研究将 利用纵向青少年行为和认知发展(ABCD)研究,该研究具有 产生了空前数量的“大数据”(N>5,000),用于绘制认知和大脑发展图表 随着时间的推移,儿童和青少年。至关重要的是,HLVD将用于识别和验证新的潜在结构 被认为是外化症状的重要维度预测因素的行为动力学 和发育性精神病理学。建议的研究将大大加深我们对 RDoC构建并提供对潜在行为动力学和与以下各项相关的特征的新见解 发育中的大脑中的精神病理学。我们的研究与NIMH倡议的使命高度相关 RFA-MH-19-242,旨在加快对神经发育和精神疾病风险轨迹的研究 生病了。我们的创新方法最终将有助于开发生物标记物,用于早期检测和 治疗精神疾病。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

VINOD MENON其他文献

VINOD MENON的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('VINOD MENON', 18)}}的其他基金

Circuit Mechanisms Governing the Default Mode Network
管理默认模式网络的电路机制
  • 批准号:
    10380898
  • 财政年份:
    2021
  • 资助金额:
    $ 78.31万
  • 项目类别:
Circuit Mechanisms Governing the Default Mode Network
管理默认模式网络的电路机制
  • 批准号:
    10576946
  • 财政年份:
    2021
  • 资助金额:
    $ 78.31万
  • 项目类别:
Integrative computational models of latent behavioral and neural constructs in children: a longitudinal developmental big-data approach
儿童潜在行为和神经结构的综合计算模型:纵向发展大数据方法
  • 批准号:
    10200653
  • 财政年份:
    2019
  • 资助金额:
    $ 78.31万
  • 项目类别:
Integrative computational models of latent behavioral and neural constructs in children: a longitudinal developmental big-data approach
儿童潜在行为和神经结构的综合计算模型:纵向发展大数据方法
  • 批准号:
    10631143
  • 财政年份:
    2019
  • 资助金额:
    $ 78.31万
  • 项目类别:
Longitudinal Neurocognitive Studies of Mathematical Disabilities: trajectories and outcomes
数学障碍的纵向神经认知研究:轨迹和结果
  • 批准号:
    10468844
  • 财政年份:
    2018
  • 资助金额:
    $ 78.31万
  • 项目类别:
Longitudinal Neurocognitive Studies of Mathematical Disabilities: trajectories and outcomes
数学障碍的纵向神经认知研究:轨迹和结果
  • 批准号:
    9769805
  • 财政年份:
    2018
  • 资助金额:
    $ 78.31万
  • 项目类别:
Longitudinal Neurocognitive Studies of Mathematical Disabilities: Outcomes and Trajectories
数学障碍的纵向神经认知研究:结果和轨迹
  • 批准号:
    10842461
  • 财政年份:
    2018
  • 资助金额:
    $ 78.31万
  • 项目类别:
Longitudinal Neurocognitive Studies of Mathematical Disabilities: trajectories and outcomes
数学障碍的纵向神经认知研究:轨迹和结果
  • 批准号:
    10259850
  • 财政年份:
    2018
  • 资助金额:
    $ 78.31万
  • 项目类别:
Novel Bayesian linear dynamical systems-based methods for discovering human brain circuit dynamics in health and disease
新颖的——贝叶斯——线性——动态——基于系统的——方法——用于发现——人类——大脑——电路——健康和疾病的动力学
  • 批准号:
    9170593
  • 财政年份:
    2016
  • 资助金额:
    $ 78.31万
  • 项目类别:
Computational modeling of dynamic causal brain circuits underlying cognitive dysfunction in Alzheimer's disease
阿尔茨海默病认知功能障碍的动态因果脑回路的计算模型
  • 批准号:
    10301331
  • 财政年份:
    2014
  • 资助金额:
    $ 78.31万
  • 项目类别:

相似海外基金

Understanding the relationship between cannabis use and attention-deficit/hyperactivity disorder
了解大麻使用与注意力缺陷/多动症之间的关系
  • 批准号:
    2874883
  • 财政年份:
    2023
  • 资助金额:
    $ 78.31万
  • 项目类别:
    Studentship
RestEaze: A Novel Wearable Device and Mobile Application to Improve the Diagnosis and Management of Restless Legs Syndrome in Pediatric Patients with Attention Deficit/Hyperactivity Disorder
RestEaze:一种新型可穿戴设备和移动应用程序,可改善注意力缺陷/多动症儿科患者不宁腿综合症的诊断和管理
  • 批准号:
    10760442
  • 财政年份:
    2023
  • 资助金额:
    $ 78.31万
  • 项目类别:
Diagnosis and Treatment of Adult Attention-Deficit/Hyperactivity Disorder: A Workshop
成人注意力缺陷/多动症的诊断和治疗:研讨会
  • 批准号:
    10825708
  • 财政年份:
    2023
  • 资助金额:
    $ 78.31万
  • 项目类别:
Maternal Attention Deficit Hyperactivity Disorder (m-ADHD): Mental Health, Pregnancy and Infant Outcomes
母亲注意力缺陷多动障碍 (m-ADHD):心理健康、妊娠和婴儿结局
  • 批准号:
    488888
  • 财政年份:
    2023
  • 资助金额:
    $ 78.31万
  • 项目类别:
    Operating Grants
SBIR Phase I: A novel caregiver-centered mobile app and artificial intelligence (AI) coaching intervention for pediatric Attention Deficit Hyperactivity Disorder (ADHD)
SBIR 第一阶段:一款新颖的以护理人员为中心的移动应用程序和人工智能 (AI) 辅导干预儿童注意力缺陷多动障碍 (ADHD)
  • 批准号:
    2335539
  • 财政年份:
    2023
  • 资助金额:
    $ 78.31万
  • 项目类别:
    Standard Grant
Machine Learning Methods to Develop and Deploy Real-Time Risk Surveillance for Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder from the Electronic Health Record
用于开发和部署电子健康记录中自闭症谱系障碍和注意力缺陷多动障碍实时风险监测的机器学习方法
  • 批准号:
    10449468
  • 财政年份:
    2022
  • 资助金额:
    $ 78.31万
  • 项目类别:
Do Cerebrovascular Factors mediate the possible link between later-life Attention-Deficit/Hyperactivity Disorder and the development of Lewy Body Diseases?
脑血管因素是否介导晚年注意力缺陷/多动障碍与路易体疾病发展之间的可能联系?
  • 批准号:
    460431
  • 财政年份:
    2022
  • 资助金额:
    $ 78.31万
  • 项目类别:
Defining Embodied Characteristics of Decision Making in Attention Deficit Hyperactivity Disorder
定义注意力缺陷多动障碍决策的具体特征
  • 批准号:
    10316100
  • 财政年份:
    2022
  • 资助金额:
    $ 78.31万
  • 项目类别:
The biological connection between educational attainment and attention-deficit/hyperactivity disorder in contrasting environments
对比环境中教育程度与注意力缺陷/多动症之间的生物学联系
  • 批准号:
    10677008
  • 财政年份:
    2022
  • 资助金额:
    $ 78.31万
  • 项目类别:
Conceptualising and Measuring Attention-Deficit Hyperactivity Disorder (ADHD) Across the Lifespan
在整个生命周期中概念化和测量注意力缺陷多动障碍 (ADHD)
  • 批准号:
    2689864
  • 财政年份:
    2022
  • 资助金额:
    $ 78.31万
  • 项目类别:
    Studentship
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了