Collaborative Research: Dynamic interactions of individual neurons in supporting hippocampal network oscillations during behavior

合作研究:行为过程中单个神经元的动态相互作用支持海马网络振荡

基本信息

  • 批准号:
    2002971
  • 负责人:
  • 金额:
    $ 69.83万
  • 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:
    2020-10-01 至 2025-09-30
  • 项目状态:
    未结题

项目摘要

Cognitive and motor behavior in the brain is controlled by networks of highly interconnected neurons. Neurons communicate via signals called spikes, which are generated by complex biological mechanisms. These mechanisms crucially depend on the subthreshold membrane potential activity, which is controlled by the complex interaction of ionic currents among other factors. Although the spiking patterns of the individual neurons are typically not regular, certain neuronal networks produce periodic oscillatory patterns. Important among them is the theta rhythm (4-10 Hz), which has been recorded in various brain areas by global activity measures, such as electroencephalography (EEG) or extracellular local field potentials (LFPs). Theta oscillations have been observed during motor activity and REM sleep, and are thought to play important roles in navigation, episodic memory and learning. Theta oscillations have also been observed at the subthreshold membrane potential level in brain slice preparations, and in behaving animals in the hippocampal CA1 area. However, how the oscillatory activity at the network level is linked to the biophysical properties of individual neurons remains largely unknown. In this project, the investigators will address this question using a combined experimental/theoretical approach. The Boston University team will perform experiments in behaving animals in CA1, and the NJIT team will carry out detailed computational modeling. This research is expected to generate a framework for describing and understanding how high-level neuronal oscillations depend on the oscillatory activity of individual neurons through complex network interactions. The PIs will also work to disseminate their imaging technology to the scientific community. This project will contribute to the cross-disciplinary training of students and postdoctoral trainees in both experimental and computational neuroscience. The central hypothesis of this project is that theta oscillations in the hippocampus are generated by resonant mechanisms involving the intrinsic properties of individual neurons, and circuit interactions that are tuned to amplify theta frequency inputs from the medial septum and possibly other external sources. We will address this hypothesis from an interdisciplinary perspective involving in vivo experiments, computational modeling, and dynamical systems analysis. We aim to understand the cellular and circuit mechanisms of hippocampal theta oscillations in vivo, and to create a theoretical framework to describe the biophysical and dynamic links between the oscillatory properties of individual neurons and network oscillations. The Boston University team will deploy a novel voltage imaging technique to measure subthreshold voltage dynamics and spiking activity from individual hippocampal neurons of defined cell types, including pyramidal cells and local interneurons (e.g. parvalbumim (PV)- and somatostatin (SOM)- positive ones) during behavioral states with varying levels of LFP theta oscillations. Additionally, to test the causal role of these interneurons in supporting theta oscillations, precision optogenetic activation and silencing will be used. The NJIT team will build biophysical models of the hippocampal network that include the intrinsic subthreshold oscillatory properties of the participating neurons and inputs from other areas (e.g., medial septum) to produce theta LFP oscillations. The results of the proposed research will provide mechanistic insights on the formation of hippocampal CA1 network oscillations with implications to learning, memory and other cognitive functions.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.
大脑中的认知和运动行为由高度相互连接的神经元网络控制。神经元通过称为棘波的信号进行交流,这种信号是由复杂的生物机制产生的。这些机制关键地依赖于阈值以下的膜电位活性,该活性受离子电流等因素的复杂相互作用控制。虽然单个神经元的尖峰模式通常不是规则的,但某些神经元网络会产生周期性的振荡模式。其中重要的是theta节律(4-10赫兹),通过脑电(EEG)或细胞外局部场电位(LFP)等全局活动测量方法在不同的脑区记录到这种节律。在运动活动和快速眼动睡眠中观察到了Theta振荡,并被认为在导航、情景记忆和学习中发挥着重要作用。在脑片制备中的阈值下膜电位水平以及在海马区CA1区的行为动物中也观察到了Theta振荡。然而,网络水平上的振荡活动如何与单个神经元的生物物理属性联系在一起,在很大程度上仍不清楚。在这个项目中,研究人员将使用实验和理论相结合的方法来解决这个问题。波士顿大学团队将在CA1中进行动物行为实验,NJIT团队将进行详细的计算建模。这项研究有望产生一个框架,用于描述和理解高水平神经元振荡如何依赖于单个神经元通过复杂网络相互作用的振荡活动。PIS还将致力于向科学界传播他们的成像技术。该项目将有助于对学生和博士后学员进行实验神经科学和计算神经科学方面的跨学科培训。该项目的中心假设是,海马区的theta振荡是由涉及单个神经元的内在属性的共振机制和电路相互作用产生的,这些电路相互作用被调节以放大来自内侧隔区和可能的其他外部来源的theta频率输入。我们将从跨学科的角度解决这一假设,包括活体实验、计算建模和动力系统分析。我们的目标是了解活体海马theta振荡的细胞和电路机制,并创建一个理论框架来描述单个神经元的振荡特性和网络振荡之间的生物物理和动力学联系。波士顿大学研究小组将部署一种新的电压成像技术,以测量特定细胞类型的单个海马神经元(包括锥体细胞和局部中间神经元(例如,小白蛋白(PV)和生长抑素(SOM)阳性神经元)在不同水平的LFP theta振荡的行为状态下的亚阈值电压动态和尖峰活动。此外,为了测试这些中间神经元在支持theta振荡中的因果作用,将使用精确的光遗传激活和沉默。NJIT团队将建立海马网络的生物物理模型,其中包括参与神经元的固有阈值下振荡特性和来自其他区域(例如内侧隔区)的输入,以产生theta LFP振荡。这项拟议的研究结果将提供对学习、记忆和其他认知功能影响的海马区CA1网络振荡形成的机械性见解。这一奖项反映了NSF的法定使命,并通过使用基金会的智力优势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(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Single and complex spikes relay distinct frequency-dependent circuit information in the hippocampus
单个和复杂的尖峰在海马体中传递不同的频率相关电路信息
  • DOI:
    10.1101/2022.04.06.487256
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Eric Lowet, Daniel J.
  • 通讯作者:
    Eric Lowet, Daniel J.
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Xue Han其他文献

Aluminate Green Phosphor with Small Particle Size Used for PDP via Co-Precipitation Method
共沉淀法用于PDP的小粒径铝酸盐绿色荧光粉
  • DOI:
    10.4028/www.scientific.net/amr.295-297.890
  • 发表时间:
    2011
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yan Dong;Yang Zhou;Xue Han;W. Gu
  • 通讯作者:
    W. Gu
Rates and predictors of one-year antipsychotic treatment discontinuation in first-episode schizophrenia: Results from an open-label, randomized, “real world” clinical trial
首发精神分裂症一年抗精神病药物治疗中断的比率和预测因素:开放标签、随机、“真实世界”临床试验的结果
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    11.3
  • 作者:
    Zhang Cheng;Yan;Xue Han;Lei Yang;Xin Zeng;Fude Yang;Zheng Lu;Chuanyue Wang;H. Deng;Jingping Zhao;Yu;C. Correll;Xin Yu
  • 通讯作者:
    Xin Yu
DNA tetrahedron-based nanogels for siRNA delivery and gene silencing
用于 siRNA 递送和基因沉默的 DNA 四面体纳米凝胶
  • DOI:
    10.1039/c9cc00175a
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    4.9
  • 作者:
    Xue Han;Ding Fei;Zhang Jiao;Guo Yuanyuan;Gao Xihui;Feng Jing;Zhu Xinyuan;Zhang Chuan
  • 通讯作者:
    Zhang Chuan
The various structures and photocatalysis properties constructed by nitrogen heterocycle carboxylate ligand
含氮杂环羧酸酯配体构建的各种结构及光催化性能
  • DOI:
    10.1016/j.poly.2018.05.026
  • 发表时间:
    2018-09
  • 期刊:
  • 影响因子:
    2.6
  • 作者:
    Xiao-Xin Han;Xue Han;Ying Wang;Di Shang;Yong-Heng Xing;Feng-Ying Bai
  • 通讯作者:
    Feng-Ying Bai
Formation of bimetallic metal-organic frameworks nanosheets and their derived porous nickel-cobalt sulfides for supercapacitors
用于超级电容器的双金属金属有机框架纳米片及其衍生的多孔镍钴硫化物的形成
  • DOI:
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    4
  • 作者:
    Chen Chen;Meng-Ke Wu;Kai Tao;Jiao-Jiao Zhou;Yan-Li Li;Xue Han;Lei Han
  • 通讯作者:
    Lei Han

Xue Han的其他文献

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{{ truncateString('Xue Han', 18)}}的其他基金

Convergence: RAISE Integrating machine learning and biological neural networks
融合:RAISE 集成机器学习和生物神经网络
  • 批准号:
    1848029
  • 财政年份:
    2018
  • 资助金额:
    $ 69.83万
  • 项目类别:
    Standard Grant

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