Developing deep learning algorithms for studying infant brain and behavior relationships

开发深度学习算法来研究婴儿大脑和行为关系

基本信息

  • 批准号:
    10263607
  • 负责人:
  • 金额:
    $ 8.65万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-01-01 至 2021-12-31
  • 项目状态:
    已结题

项目摘要

Project Summary Infants communicate to their caregivers that they need food by crying. This represents our very first social interaction that lays the foundation for a healthy life by acquiring nutrition for growth and establishing a strong social bond with caregivers. Infants that cannot regulate their nutrition are at risk for malnourishment or obesity, whose deleterious effects will negatively impact the wellness of these individuals for their lifetime. Abnormalities in social recognition and communication, like those found in autism spectrum disorders, also become apparent during infancy. Despite the critical importance of infants communicating nutritional need to caregivers, the neuronal basis remains unknown. To address this deficit, I propose to study social tadpoles that beg their parents for food by dancing. Tadpoles use this begging display to encode nutritional state, enabling us to quantify hunger- based communication. These tadpoles are translucent, allowing us to visualize the development and activity of neurons in the brain. I am combining this novel model system and behavioral paradigm with advanced neurogenetic tools to interrogate the neuronal substrates of hunger-based communication. I will examine whether nutritional quality influences the development of neurons that regulating feeding and communication with in vivo brain imaging. I will also test for a functional role of these neuronal cell-types in begging behavior using a high throughput behavior assay, whole brain clearing and immunohistochemistry, and cell-specific manipulations of neuronal activity. As social recognition is important for establishing parent-offspring bonds, I will then use in vivo neural activity imaging to determine how tadpoles recognize their parents using multi-modal sensory integration. Completion of these experiments will transform our understanding of a social behavior critical for infant survival and life-long wellbeing. There is a pressing need for this research because there are currently no established models for studying the neural mechanisms of infant communication of hunger. This work is important to public health because some of the most prevalent disorders afflicting children in the United States are eating related disorders and conditions involving abnormalities in social recognition and communication, such as autism spectrum disorders. More research on infant feeding and communication is needed to better understand these pathologies in the youngest members of our society.
项目摘要 婴儿通过哭泣向他们的照顾者传达他们需要食物的信息。这是我们第一次 互动,通过获取生长营养和建立强大的 与照顾者的社会关系不能调节营养的婴儿有营养不良或肥胖的风险, 其有害影响将对这些个体的健康产生负面影响。异常 在社会认知和交流方面,就像在自闭症谱系障碍中发现的那样, 在婴儿时期。尽管婴儿向照顾者传达营养需求至关重要, 神经基础仍然未知。为了解决这一缺陷,我建议研究乞求父母的社会性蝌蚪 通过跳舞来获得食物。蝌蚪用这种乞讨的方式来编码营养状态,使我们能够量化饥饿- 基于沟通。这些蝌蚪是半透明的,使我们能够可视化的发展和活动, 大脑中的神经元。我将这个新颖的模型系统和行为范例与先进的 神经遗传学工具来询问基于饥饿的通信的神经元基底。我将研究 营养质量是否影响调节摄食和通讯的神经元的发育 进行活体脑成像我还将测试这些神经元细胞类型在乞讨行为中的功能作用 使用高通量行为测定、全脑清除和免疫组织化学,以及细胞特异性 操纵神经元活动。由于社会认可对建立亲子关系很重要, 然后将使用体内神经活动成像来确定蝌蚪如何使用多模态识别它们的父母, 感觉统合这些实验的完成将改变我们对社会行为的理解 这对婴儿的存活和终身幸福至关重要。这项研究是迫切需要的,因为有 目前还没有建立模型来研究婴儿饥饿沟通的神经机制。这 工作对公共健康很重要,因为在美国, 国家是饮食有关的疾病和条件,涉及异常的社会承认, 沟通,如自闭症谱系障碍。更多关于婴儿喂养和沟通的研究 需要更好地了解我们社会中最年轻成员的这些病理。

项目成果

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Lauren A O'Connell其他文献

Lauren A O'Connell的其他文献

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{{ truncateString('Lauren A O'Connell', 18)}}的其他基金

Dopamine regulation of infant perceptual motor development and communication
多巴胺对婴儿知觉运动发育和交流的调节
  • 批准号:
    10735199
  • 财政年份:
    2023
  • 资助金额:
    $ 8.65万
  • 项目类别:
microRNA tuning of gregarious versus antisocial behavior in juveniles
microRNA 调节青少年群居与反社会行为
  • 批准号:
    10839665
  • 财政年份:
    2023
  • 资助金额:
    $ 8.65万
  • 项目类别:

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