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

BRAIN EAGER:生命前 3 年大脑振荡的稳健纵向特征

基本信息

  • 批准号:
    1451480
  • 负责人:
  • 金额:
    $ 30万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-09-01 至 2018-08-31
  • 项目状态:
    已结题

项目摘要

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.
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。 随着最近的技术和计算的进步,已经有可能克服这些技术障碍,并获得直接测量的脑电活动的行为婴儿。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。

项目成果

期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Neuronal networks in the developing brain are adversely modulated by early psychosocial neglect
  • DOI:
    10.1152/jn.00014.2017
  • 发表时间:
    2017-10-01
  • 期刊:
  • 影响因子:
    2.5
  • 作者:
    Stamoulis,Catherine;Vanderwert,Ross E.;Nelson,Charles A.
  • 通讯作者:
    Nelson,Charles A.
Widespread Positive Direct and Indirect Effects of Regular Physical Activity on the Developing Functional Connectome in Early Adolescence
  • DOI:
    10.1093/cercor/bhab126
  • 发表时间:
    2021-05-14
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Brooks, Skylar J.;Parks, Sean M.;Stamoulis, Catherine
  • 通讯作者:
    Stamoulis, Catherine
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Catherine Stamoulis其他文献

Pediatric CT dose reduction for suspected appendicitis: a practice quality improvement project using artificial gaussian noise--part 2, clinical outcomes.
疑似阑尾炎的儿童 CT 剂量减少:使用人工高斯噪声的实践质量改进项目 - 第 2 部分,临床结果。
  • DOI:
  • 发表时间:
    2015
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Michael J. Callahan;Seema P. Anandalwar;Robert D MacDougall;Catherine Stamoulis;P. Kleinman;Shawn J Rangel;R. Bachur;George A. Taylor
  • 通讯作者:
    George A. Taylor
Non-invasively recorded transient pathological high-frequency oscillations in the epileptic brain: a novel signature of seizure evolution
  • DOI:
    10.1186/1471-2202-16-s1-p32
  • 发表时间:
    2015-12-18
  • 期刊:
  • 影响因子:
    2.300
  • 作者:
    Catherine Stamoulis;Bernard Chang
  • 通讯作者:
    Bernard Chang
2. Depression in Adolescent and Adult Women with Endometriosis
  • DOI:
    10.1016/j.jpag.2024.01.147
  • 发表时间:
    2024-04-01
  • 期刊:
  • 影响因子:
  • 作者:
    Sinah Esther Kim;Catherine Stamoulis;Jenny Gallagher;Emma Draisin;Marc Laufer;Amy DiVasta
  • 通讯作者:
    Amy DiVasta
97. Pain Interference in Adolescents and Adults with Chronic Pelvic Pain Due to Endometriosis
  • DOI:
    10.1016/j.jpag.2024.01.104
  • 发表时间:
    2024-04-01
  • 期刊:
  • 影响因子:
  • 作者:
    Emma Draisin;Catherine Stamoulis;Jenny Gallagher;Sinah Esther Kim;Marc Laufer;Amy DiVasta
  • 通讯作者:
    Amy DiVasta
Guatemala City Youth: A Descriptive Study of Health Indicators Through the Lens of a Clinical Registry
  • DOI:
    10.1016/j.jadohealth.2016.10.083
  • 发表时间:
    2017-02-01
  • 期刊:
  • 影响因子:
  • 作者:
    Sarah A. Golub;Juan Carlos Maza;Catherine Stamoulis;Hayley Teich;Erwin Humberto Calgua;Areej Hassan
  • 通讯作者:
    Areej Hassan

Catherine Stamoulis的其他文献

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{{ truncateString('Catherine Stamoulis', 18)}}的其他基金

CRCNS Research Proposal: Modeling Human Brain Development as a Dynamic Multi-Scale Network Optimization Process
CRCNS 研究提案:将人脑发育建模为动态多尺度网络优化过程
  • 批准号:
    2207733
  • 财政年份:
    2022
  • 资助金额:
    $ 30万
  • 项目类别:
    Continuing Grant
Resilience and Vulnerability of the Developing Brain's Connectome during the COVID-19 Pandemic
COVID-19 大流行期间发育中的大脑连接组的弹性和脆弱性
  • 批准号:
    2116707
  • 财政年份:
    2021
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
Collaborative Research: From Brains to Society: Neural Underpinnings of Collective Behaviors Via Massive Data and Experiments
合作研究:从大脑到社会:通过大量数据和实验研究集体行为的神经基础
  • 批准号:
    1940096
  • 财政年份:
    2019
  • 资助金额:
    $ 30万
  • 项目类别:
    Continuing Grant
Dynamic changes in neural circuitry underlying emotional face processing in early life: network re-organization and functional interactions
早期生活中情绪面孔处理背后的神经回路的动态变化:网络重组和功能相互作用
  • 批准号:
    1658414
  • 财政年份:
    2017
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
Computational Infrastructure for Brain Research: EAGER: Next-Generation Neural Data Analysis (NGNDA) Platform: Massive Parallel Analysis of Multi-Modal Brain Networks
脑研究计算基础设施:EAGER:下一代神经数据分析(NGNDA)平台:多模态脑网络的大规模并行分析
  • 批准号:
    1649865
  • 财政年份:
    2016
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant

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