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Development of the Large-Scale Neural Networks in Infancy

Development of the Large-Scale Neural Networks in Infancy
婴儿期大规模神经网络的发展
批准号:
RGPIN-2022-03655
负责人:
Emberson, Lauren
金额:
$3.21万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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中文摘要
翻译
发展认知神经科学对我们进一步了解婴儿期建立的基本神经和心理机制有着巨大的希望。然而,尽管许多研究表明,由于短期的学习经历,婴儿的大脑和行为都会发生快速变化,但很少有研究探讨这些短期变化与婴儿大脑功能或基于任务的连通性的发展以及其他长期发展变化之间的关系。重要的是,神经相互作用理论方法(发育认知神经科学的核心原则)的关键预测在很大程度上仍未经检验。为了实现理解婴儿大脑和行为的短期和长期变化是如何相互关联和相互促进的长期研究目标,我的研究计划将利用婴儿基于任务的功能连接方面的最新进展,调查尚未经过测试的神经相互作用学家的预测,即长期发育变化可能通过短期经历中高级神经区域的参与而发生。我将结合功能近红外光谱(fNIRS)、敏感行为方法和计算分析方法,在三个相互关联的研究流中测试这些预测。研究流1将研究功能性神经网络在基于短期学习的感知变化中的作用,整合眼动追踪和近红外光谱方法。我们假设额叶在短期的认知学习变化中起着至关重要的作用。研究流2将探讨如何短期变化的感知,作为衡量行为,引起表征的长期变化。计划了三个理论激励的培训方案。然后,我们将使用近红外光谱来观察这些短期变化是否独立于额叶。研究流3将研究婴儿大脑的短期神经参与(例如,在远程神经网络中)如何支持关键神经网络的长期发育出现。研究流3将检查来自高收入和低收入家庭的3个数据集——两个先前从撒哈拉以南非洲和英国收集的样本,第三个提议的数据集将从150多名加拿大婴儿纵向收集,研究在主动序列学习和预测任务中的表现与生命最初两年的神经网络激活之间的关系。总之,这项研究将深入了解婴儿在短期学习经历中的任务参与如何引起长期的发展变化。我们将检验关键理论预测;这项工作有望深入了解支持大脑如何通过经验构建的基本机制。
英文摘要
Developmental cognitive neuroscience holds great promise for furthering our understanding of fundamental neural and psychological mechanisms are established in infancy. Yet while much work has demonstrated that infants show rapid changes in both their brain and behaviour as a result of short-term learning experiences, very little work has explored how these short-term changes relate to the development of functional, or task-based, connectivity in the infant brain, and to other long-term developmental changes. Importantly, key predictions of the neural-interactionist theoretical approach (a central tenet in developmental cognitive neuroscience) remain largely untested. Towards the long-term research goal of understanding how short and long-term changes in the infant brain and behaviour interrelate and give rise to one another, my research program will leverage recent advances in infant task-based functional connectivity to investigate the still-untested neural-interactionist prediction that longer-term developmental changes can occur through the involvement of higher-level neural regions during short-term experiences. I will use a combination of functional Near-Infrared Spectroscopy (fNIRS), sensitive behavioural methods and computational analytic approaches to test these predictions in three inter-related research streams. Research Stream 1 will examine the role of functional neural networks in short-term learning-based changes in perception, integrating eye-tracking and fNIRS approaches. We hypothesize that the frontal lobe is crucially involved in short-term, learning changes in perception. Research Stream 2 will explore how short-term changes in perception, as measured in behaviour, give rise to longer-term changes in representations. Three theoretically-motivated training protocols are planned. Then, we will use fNIRS to see whether these short-term changes become independent of the frontal lobe. Research Stream 3 will investigate how short-term neural engagement of the infant brain (for example, in long-range neural networks) support longer-term, developmental emergence of key neural networks. Research Stream 3 will examine 3 data sets from high- and low-income families - two previously collected samples from sub-Saharan Africa and the United Kingdom, and a third proposed data set to be gathered from 150+ Canadian infants longitudinally, examining how performance during active sequence learning and prediction tasks relates to neural network activation across the first two years of life. Together, this research will provide insight into how infants' task engagement during short-term learning experiences gives rise to long-term, developmental changes. We will test key theoretical prediction; this work is expected to give insights into fundamental mechanisms supporting how the brain is built through experience.
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Development of the Large-Scale Neural Networks in Infancy
  • 批准号:
    DGECR-2022-00262
  • 项目类别:
    Discovery Launch Supplement
  • 资助金额:
    $0.91万
  • 财政年份:
    2022
  • 负责人:
    Emberson, Lauren
  • 依托单位:
Interactions of perceptual cortices and domain-general learning regions in implicit statistical learning
  • 批准号:
    374185-2009
  • 项目类别:
    Postgraduate Scholarships - Doctoral
  • 资助金额:
    $1.53万
  • 财政年份:
    2010
  • 负责人:
    Emberson, Lauren
  • 依托单位:
Interactions of perceptual cortices and domain-general learning regions in implicit statistical learning
  • 批准号:
    374185-2009
  • 项目类别:
    Postgraduate Scholarships - Doctoral
  • 资助金额:
    $1.53万
  • 财政年份:
    2009
  • 负责人:
    Emberson, Lauren
  • 依托单位:
国内基金
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  • 资助金额:
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  • 批准号:
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  • 项目类别:
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  • 资助金额:
    30万元
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    2022
  • 负责人:
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  • 依托单位:
量子自旋液体中拓扑拟粒子的性质:量子蒙特卡罗和新的large-N理论
  • 批准号:
    12074246
  • 项目类别:
    面上项目
  • 资助金额:
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  • 批准年份:
    2020
  • 负责人:
    Yoshitomo Kamiya
  • 依托单位:
甘蓝型油菜Large Grain基因调控粒重的分子机制研究
  • 批准号:
    31972875
  • 项目类别:
    面上项目
  • 资助金额:
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  • 批准年份:
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