CAREER:Single-neuron mechanisms of social attention in humans

职业:人类社会注意力的单神经元机制

基本信息

  • 批准号:
    1945230
  • 负责人:
  • 金额:
    $ 63.33万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-04-01 至 2024-03-31
  • 项目状态:
    已结题

项目摘要

The ability of people to focus visual attention on salient objects or people in our visual field is one of the most fundamental cognitive functions in humans. This ability is critically important in order to learn and interact socially with others. In particular, visual attention to social stimuli (i.e., social attention) plays a vital role in guiding social behaviors. Impaired social attention underlies many psychiatric and neurological disorders, such as autism and ADHD. However, very little is known about human visual attention at the single-neuron level. The goal of this CAREER project is to understand the underlying neural processes involved in human social attention using technology that provides the highest degree of spatial resolution (location of brain activity) and temporal resolution (timing of brain activity) currently available. The investigators will collaborate with neurosurgeons and record directly from neurons in the human brain, as patients undergo treatment of epilepsy. These neurons reside in brain regions involved in attention, decision making, or processing of socially relevant images. The research will elucidate how single neurons, within specific brain regions, contribute to visual attention. Results will provide novel insight into how these processes differ in psychiatric and neurological disorders. This study will contribute to teaching materials and outreach to clinical communities. The data acquired and analysis tools developed will be made freely available to other researchers in order to advance science in the field of cognitive neuroscience research and human neural recordings.The research team will investigate the neural circuits of social attention in humans for both goal-driven attention (Aim 1) and stimulus-driven attention (Aim 2). The research will: (1) characterize social attention signals in the medial temporal lobe (amygdala and hippocampus) and prefrontal cortex (in particular the orbitofrontal cortex); (2) analyze attention signals from different brain regions using comprehensive functional connectivity analysis; and (3) compare neural mechanisms for goal-driven vs. stimulus-driven attention. Together, with the unique human single-neuron recordings, the research will address important fundamental neuroscience questions by providing comprehensive analysis of the neural circuits underlying social attention in humans. The outcomes of this research are important to understand the neural mechanisms of impaired visual attention in patients with psychiatric and neurological disorders and will be informative for development of future targeted intervention strategies. This research will also integrate undergraduate education and generate tools and methods to enable new research groups to conduct state-of-the-art human single-neuron recordings.This project is jointly funded by the Cognitive Neuroscience Program and by the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
人们将视觉注意力集中在视野中突出的物体或人的能力是人类最基本的认知功能之一。这种能力对于学习和与他人交往至关重要。特别是对社会刺激的视觉注意(即社会注意)在指导社会行为中起着至关重要的作用。社会注意力受损是许多精神和神经疾病的基础,如自闭症和多动症。然而,在单个神经元水平上对人类视觉注意的了解甚少。这个CAREER项目的目标是通过提供目前可用的最高程度的空间分辨率(大脑活动的位置)和时间分辨率(大脑活动的时间)的技术来了解涉及人类社会注意力的潜在神经过程。研究人员将与神经外科医生合作,在患者接受癫痫治疗时直接记录人类大脑中的神经元。这些神经元位于大脑中涉及注意力、决策或处理社会相关图像的区域。这项研究将阐明特定大脑区域内的单个神经元是如何影响视觉注意力的。结果将为这些过程在精神疾病和神经疾病中的不同提供新的见解。这项研究将有助于教学材料和推广到临床社区。获取的数据和开发的分析工具将免费提供给其他研究人员,以推进认知神经科学研究和人类神经记录领域的科学。研究小组将研究人类社会注意的神经回路,包括目标驱动注意(目标1)和刺激驱动注意(目标2)。研究将:(1)表征内侧颞叶(杏仁核和海马)和前额叶皮层(特别是眶额皮质)的社会注意信号;(2)利用综合功能连通性分析分析不同脑区注意信号;(3)比较目标驱动和刺激驱动注意的神经机制。与独特的人类单神经元记录一起,该研究将通过提供对人类社会注意力背后的神经回路的全面分析,解决重要的基础神经科学问题。本研究结果对于理解精神和神经疾病患者视觉注意受损的神经机制具有重要意义,并将为未来有针对性的干预策略的制定提供信息。这项研究还将整合本科教育,并产生工具和方法,使新的研究小组能够进行最先进的人类单神经元记录。本项目由认知神经科学项目和刺激竞争研究既定项目(EPSCoR)共同资助。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(16)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Task Modulation of Single-Neuron Activity in the Human Amygdala and Hippocampus
  • DOI:
    10.1523/eneuro.0398-21.2021
  • 发表时间:
    2022-01-01
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
    Cao, Runnan;Todorov, Alexander;Wang, Shuo
  • 通讯作者:
    Wang, Shuo
Deep Neural Network Reveals the World of Autism From a First‐Person Perspective
深度神经网络从第一人称视角揭示自闭症世界
  • DOI:
    10.1002/aur.2376
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    4.7
  • 作者:
    Ruan, Mindi;Webster, Paula J.;Li, Xin;Wang, Shuo
  • 通讯作者:
    Wang, Shuo
Comprehensive Social Trait Judgments From Faces in Autism Spectrum Disorder
  • DOI:
    10.1177/09567976231192236
  • 发表时间:
    2023-09-06
  • 期刊:
  • 影响因子:
    8.2
  • 作者:
    Cao,Runnan;Zhang,Na;Wang,Shuo
  • 通讯作者:
    Wang,Shuo
Reduced Pupil Oscillation During Facial Emotion Judgment in People with Autism Spectrum Disorder
自闭症谱系障碍患者面部情绪判断过程中瞳孔振荡减少
Outcome saliency modulates behavioral decision switching
  • DOI:
    10.1038/s41598-020-71182-9
  • 发表时间:
    2020-08
  • 期刊:
  • 影响因子:
    4.6
  • 作者:
    Sai Sun;Rongjun Yu;Shuo Wang
  • 通讯作者:
    Sai Sun;Rongjun Yu;Shuo Wang
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Xin Li其他文献

Collective semantic behavior extraction in social networks
社交网络中的集体语义行为提取
  • DOI:
    10.1016/j.jocs.2017.11.003
  • 发表时间:
    2017-11
  • 期刊:
  • 影响因子:
    3.3
  • 作者:
    Lei Li;Chuan Zhou;Jianping He;Jiamiao Wang;Xin Li;Xindong Wu
  • 通讯作者:
    Xindong Wu
Pressure Dependence of Structural Behavior and Electronic Properties in Double Perovskite Ba2SmSbO6
双钙钛矿 Ba2SmSbO6 结构行为和电子性能的压力依赖性
  • DOI:
    10.1021/acs.jpcc.1c07153.s001
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Yanju Wang;Yongsheng Zhao;Shuailing Ma;Xin Li;D. Tan;Jiajia Feng;Junxiu Liu;Bin Chen
  • 通讯作者:
    Bin Chen
Observations of pores and surrounding regions with CO 4.66 micron lines by BBSO/CYRA
通过 BBSO/CYRA 用 CO 4.66 微米线观察孔隙和周围区域
  • DOI:
    10.1051/0004-6361/202244600
  • 发表时间:
    2022-11
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yongliang Song;Xianyong Bai;Xu Yang;Wenda Cao;Han Uitenbroek;Yuanyong Deng;Xin Li;Xiao Yang;Mei Zhang
  • 通讯作者:
    Mei Zhang
A tumor map generated from three-dimensional visualization of image fusion for the assessment of microwave ablation of hepatocellular carcinoma: a preliminary study
图像融合三维可视化生成的肿瘤图用于评估肝细胞癌微波消融:初步研究
  • DOI:
    10.2147/cmar.s195354
  • 发表时间:
    2019-02
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chao An;Xin Li;Ping liang;Jie Yu;Zhigang Cheng;Zhiyu Han;Fangyi Liu;Linan Dong
  • 通讯作者:
    Linan Dong
Effects of modulation periodicity on microstructure, mechanical andbr / tribological properties of NbN/AlN nanostructured multilayer films
调制周期对 NbN/AlN 纳米结构多层薄膜微观结构、机械和摩擦学性能的影响
  • DOI:
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    6.7
  • 作者:
    Mao Wen;Hao Huang;Kan Zhang;Qingnan Meng;Xin Li;Xiaoming Zhang;Lingwei Kong;Weitao Zheng
  • 通讯作者:
    Weitao Zheng

Xin Li的其他文献

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{{ truncateString('Xin Li', 18)}}的其他基金

CCSS: Uncertainty-Aware Computational Imaging in the Wild: a Bayesian Deep Learning Approach in the Latent Space
CCSS:野外不确定性感知计算成像:潜在空间中的贝叶斯深度学习方法
  • 批准号:
    2318758
  • 财政年份:
    2023
  • 资助金额:
    $ 63.33万
  • 项目类别:
    Standard Grant
HCC: Small: Toward Computational Modeling of Autism Spectrum Disorder: Multimodal Data Collection, Fusion, and Phenotyping
HCC:小型:自闭症谱系障碍的计算模型:多模式数据收集、融合和表型分析
  • 批准号:
    2401748
  • 财政年份:
    2023
  • 资助金额:
    $ 63.33万
  • 项目类别:
    Standard Grant
CCSS: Uncertainty-Aware Computational Imaging in the Wild: a Bayesian Deep Learning Approach in the Latent Space
CCSS:野外不确定性感知计算成像:潜在空间中的贝叶斯深度学习方法
  • 批准号:
    2348046
  • 财政年份:
    2023
  • 资助金额:
    $ 63.33万
  • 项目类别:
    Standard Grant
CAREER:Single-neuron mechanisms of social attention in humans
职业:人类社会注意力的单神经元机制
  • 批准号:
    2401398
  • 财政年份:
    2023
  • 资助金额:
    $ 63.33万
  • 项目类别:
    Continuing Grant
AF: Small: Fundamental Questions in Communication and Computation Regarding Edit Type String Measures
AF:小:有关编辑类型字符串测量的通信和计算的基本问题
  • 批准号:
    2127575
  • 财政年份:
    2021
  • 资助金额:
    $ 63.33万
  • 项目类别:
    Standard Grant
HCC: Small: Toward Computational Modeling of Autism Spectrum Disorder: Multimodal Data Collection, Fusion, and Phenotyping
HCC:小型:自闭症谱系障碍的计算模型:多模式数据收集、融合和表型分析
  • 批准号:
    2114644
  • 财政年份:
    2021
  • 资助金额:
    $ 63.33万
  • 项目类别:
    Standard Grant
CAREER: Pseudorandom Objects and their Applications in Computer Science
职业:伪随机对象及其在计算机科学中的应用
  • 批准号:
    1845349
  • 财政年份:
    2019
  • 资助金额:
    $ 63.33万
  • 项目类别:
    Continuing Grant
SHF: Small: Re-thinking Polynomial Programming: Efficient Design and Optimization of Resilient Analog/RF Integrated Systems by Convexification
SHF:小:重新思考多项式编程:通过凸化实现弹性模拟/射频集成系统的高效设计和优化
  • 批准号:
    1720569
  • 财政年份:
    2017
  • 资助金额:
    $ 63.33万
  • 项目类别:
    Standard Grant
SHF: Small: Re-thinking Polynomial Programming: Efficient Design and Optimization of Resilient Analog/RF Integrated Systems by Convexification
SHF:小:重新思考多项式编程:通过凸化实现弹性模拟/射频集成系统的高效设计和优化
  • 批准号:
    1604150
  • 财政年份:
    2016
  • 资助金额:
    $ 63.33万
  • 项目类别:
    Standard Grant
AF: Small: Randomness in Computation - Old Problems and New Directions
AF:小:计算中的随机性 - 老问题和新方向
  • 批准号:
    1617713
  • 财政年份:
    2016
  • 资助金额:
    $ 63.33万
  • 项目类别:
    Standard Grant

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