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

人脑在生命的前三年经历了快速而深刻的变化，这些变化伴随着新的认知技能的出现，包括记忆和识别人脸和物体，习得词汇，以及将注意力集中在手头的任务上等。虽然如此丰富的功能需要多个大脑区域的协调，但人们对大脑不同区域的电活动变化与行为变化的相关性知之甚少。这种知识差距的部分原因是主要的脑成像方法--功能磁共振成像(FMRI)施加的方法学限制。功能磁共振成像不仅要求婴儿或蹒跚学步的儿童在观察过程中保持静止或睡眠，而且不能直接测量高时间分辨率(毫秒)下神经元活动的快速变化。随着最近的技术和计算技术的进步，克服这些技术障碍并直接测量行为正常婴儿的脑电活动已经成为可能。在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获得难得的机会，利用许多先进的计算方法，系统地表征从3到36个月大的婴儿和幼儿身上重复获取的纵向hdEEG数据得出的神经信号与发育相关的变化。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。该项目的发现还有望帮助家庭了解早期经历如何塑造大脑和促进认知功能，并将激励开发新课程和教材，教育学生、研究人员和临床医生认知发展的行为和神经机制之间的关系。该项目是一项雄心勃勃的尝试，通过分析同一婴儿出生后三年的高密度脑电数据，利用不同脑区内和不同功能脑区之间神经振荡的来源定位和频率分析，来表征人类大脑发育中的变化。这项研究将集中于表征早期发育过程中来自不同空间位置的跨多个时间点的脑电信号的振荡波形。这些波形在不同频段的功率，例如，θ、α、β和伽马功率，已知在早期发育的不同时间点出现，并与外部刺激、信息处理需求和行为的变化有关。然而，在这个年龄范围内，与年龄相关的主要振荡频率、功率和大脑区域之间的空间分布的变化还没有得到系统的表征。在相同类型的任务和非任务条件下，对大约200名3、6、9、12、18、24和36个月大的典型发育婴儿的纵向高密度脑电数据进行分析。新的源分析方法将被应用于hdEGs，以提取和定位主要源，并将源信号分解为单独的振荡分量，并跨年龄进行比较。还将系统量化和比较不同年龄段的静息和功能网络以及已确定来源之间的方向连接性。该项目有望为使用脑电研究人类大脑发育提供一种新的基于来源的语言，并揭示神经信号如何在时间、频率和脑空间中变化，使婴儿能够与世界交流并获得新的技能。

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.