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: University of British Columbia
• 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
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=764007
• 关键词: Development; Large; Scale; Neural; Networks

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.

发展认知神经科学为我们进一步理解婴儿期建立的基本神经和心理机制提供了巨大的希望。然而，虽然许多研究表明，婴儿的大脑和行为都表现出快速的变化，作为短期学习经验的结果，很少有研究探讨这些短期变化如何与婴儿大脑中功能性或基于任务的连接性的发展以及其他长期发展变化有关。重要的是，神经互动理论方法（发展认知神经科学的核心原则）的关键预测在很大程度上尚未得到验证。 为了了解婴儿大脑和行为的短期和长期变化如何相互关联并相互产生的长期研究目标，我的研究计划将利用婴儿基于任务的功能连接的最新进展来调查尚未经过测试的神经互动预测，即长期发展变化可以通过参与短期经验期间的高级神经区域发生。我将使用功能近红外光谱（fNIRS），敏感的行为方法和计算分析方法的组合，以测试这些预测在三个相互关联的研究流。研究流1将研究功能性神经网络在感知短期学习变化中的作用，整合眼动跟踪和fNIRS方法。我们假设，额叶是至关重要的参与在短期内，学习变化的看法。研究流2将探讨如何感知的短期变化，如行为测量，引起表征的长期变化。三个理论激励的培训协议计划。然后，我们将使用fNIRS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，在长距离神经网络中）如何支持关键神经网络的长期发展。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，第三个拟议的数据集将从150多名加拿大婴儿纵向收集，研究主动序列学习和预测任务期间的表现如何与生命头两年的神经网络激活相关。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。我们将测试关键的理论预测;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。