BRAIN EAGER: Robust longitudinal characterization of brain oscillations in the first 3 years of life

人类大脑在生命的前3年经历了快速而深刻的变化，伴随着新的认知技能的出现，包括记住和识别面孔和物体，获取词汇，以及将注意力集中在手头的任务上。 虽然如此丰富的功能需要多个大脑区域的协调，但人们对不同大脑区域的脑电活动变化如何与行为变化相关知之甚少。这种知识差距部分是由于主要的脑成像方法，功能性磁共振成像（fMRI）所施加的方法限制。fMRI不仅要求婴儿或幼儿在观察期间保持静止或睡眠，而且不能以高时间分辨率（毫秒）直接测量神经元活动的快速变化。 随着最近技术和计算的进步，克服这些技术障碍并直接测量行为良好的婴儿的脑电活动已成为可能。在美国国家科学基金会的支持下，Stamoulis博士和他在波士顿儿童医院/哈佛医学院认知神经科学实验室的同事们将有难得的机会系统地描述神经信号中与发育相关的变化，这些神经信号来自于使用许多先进的计算方法在3到36个月大的婴儿和幼儿中反复获得的纵向hdEEG数据。这项研究将提供有关大脑在早期发育过程中如何变化的基本信息。该项目的研究结果还有望帮助教育家庭了解早期经历如何塑造大脑和促进认知功能，并将激发新课程和教学材料的开发，以教育学生，研究人员和临床医生之间的关系认知发展的行为和神经机制。该项目是一个雄心勃勃的尝试，通过分析高，使用源定位和不同功能脑区域内和之间的神经振荡的频率分析，从相同婴儿在生命的前三年收集的密度脑电图（hdEEG）数据。 该研究将重点关注早期发育过程中来自不同空间位置的多个时间点的脑电信号的振荡波形。 已知这些波形在不同频带中的功率，例如θ、α、β和γ功率，在早期发育期间的不同时间点出现，并且与外部刺激、信息处理需求和行为的变化相关联。 然而，年龄相关的变化，在主导振荡频率，功率和空间分布之间的大脑区域还没有系统的特点，在这个年龄范围内。 在相同类型的任务和无任务条件下，将分析约200名3、6、9、12、18、24和36个月龄的典型发育婴儿的纵向高密度EEG数据。 新的源分析方法将被应用到hdEEG，提取和定位主导源，并将源信号分解为单独的振荡分量，并在不同年龄段进行比较。已确定的来源之间的休息和功能网络以及方向性连接也将系统地量化和跨年龄比较。该项目预计将为使用EEG研究人类大脑发育提供一种新的基于源代码的语言，并揭示神经信号如何在时间，频率和大脑空间中变化，以使婴儿能够与世界交流并获得新技能。

The human brain undergoes rapid and profound changes during the first 3 years of life, which accompany the emergence of new cognitive skills, including remembering and recognizing faces and objects, acquiring vocabularies, and focusing attention on the task at hand, among others. While such a rich repertoire of functions requires the coordination of multiple brain regions, little is known about how changes in the brain's electrical activity across different brain regions correlate with changes in behavior. This knowledge gap is in part due to methodological limitations imposed by the predominant brain imaging method, functional magnetic resonance imaging (fMRI). fMRI not only requires infants or toddlers to remain still or asleep during the observation, but also cannot directly measure rapid changes in neuronal activity at a high temporal resolutions (millisecond). With recent technological and computational advances, it has become possible to overcome these technical barriers and obtain direct measurements of brain electrical activity in behaving infants. With the support of the National Science foundation, Dr Stamoulis and colleagues at the Laboratory of Cognitive Neuroscience at Boston Children's Hospital/Harvard Medical School, will have the rare opportunity to systematically characterize development-related changes in neural signals derived from longitudinal hdEEG data acquired in infants and toddlers repeatedly across 3 to 36 months of age using a number of advanced computational approaches. This study will provide fundamental information regarding how the brain changes across early development. Findings from this project are also expected to help educate families on how early experiences shape the brain and facilitate cognitive functions, and will inspire the development of new courses and instructional materials to educate students, researchers and clinicians on the relationships between behavioral and neural mechanisms of cognitive development.The project is an ambitious attempt at characterizing changes in the developing human brain by analysing high-density electroencephalography (hdEEG) data collected from the same infants across the first three years of life using source localization and frequency analysis of neural oscillations within and between different functional brain regions. The investigation will focus on characterizing oscillatory waveforms of brain electrical signals originating from different spatial locations across multiple time points during early development. The power of these waveforms in different frequency bands, e.g. theta, alpha, beta, and gamma power, are known to emerge at different time points during early development and to be associated with variations in external stimuli, information processing demands, and behaviors. However, age-related changes in the dominant oscillation frequency, power and spatial distribution among brain regions have not been systematically characterized during this age range. Longitudinal high-density EEG data from about 200 typically developing infants at 3, 6, 9, 12, 18, 24, and 36 months of age will be analyzed under the same type of tasks and no-task conditions. Novel source analysis methods will be applied to hdEEGs, to extract and localize dominant sources and to decompose source signals into individual oscillation components and compare them across ages. Resting and functional networks and directional connectivities between identified sources will also be systematically quantified and compared across ages. This project is expected to provide a new source-based language for investigating human brain development using EEG and to reveal how neural signals change in time, frequency and brain spaces to enable infants to communicate with the world and to acquire new skills.