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CRCNS: Modeling Acquisition and Extinction of Fear Memories in Amygdala Circuits

CRCNS：模拟杏仁核回路中恐惧记忆的获取和消除

基本信息

批准号：
8081062
负责人：
Satish S Nair
金额：
$ 24.03万
依托单位：
UNIVERSITY OF MISSOURI-COLUMBIA
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-08-31 至 2013-04-30
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): The overall objective of the proposed cross-disciplinary research is to use an integrated computational/experimental approach to study the acquisition and extinction of conditioned fear associations in the neural components of the fear circuit of mammals. We propose an interdependent series of experiments and biologically realistic simulations, using a 'from biology to model, to predictions, and back to biology' theme where experiments will constrain the design of the models ('from biology to model') and discrepancies between the models and expected outcomes will lead to the formulation of hypotheses ('to predictions') that will be tested experimentally ('back to biology'). The computational models will be developed using experimental data from laboratories of two neuroscience Co-PIs. Preliminary models, developed by our group over a period of 21/2 years demonstrate that they can provide significant insights into the intrinsic and synaptic mechanisms associated with learning and neuroplasticity in conditioned fear. The proposed research will expand this collaboration with the following specific aims: 1.To investigate the underlying mechanisms of learning and neuroplasticity in the amygdala related to the acquisition and extinction of conditioned fear using a biologically realistic computational model, and to test model predictions in experiments. From biology to model: Use published biology data (in vitro and in vivo), to investigate neurocomputational properties of single cell models of amygdala nuclei including lateral amygdala (LA), basal amygdala (BA), intercalated cells (ITC), and central nucleus (CeM and CeL). From biology to model and to predictions: Investigate how the key amygdala nuclei interact to acquire and extinguish conditioned fear memories using a biologically realistic network model that includes the single cell models. Make predictions to quantify the relative contributions of the various projections from LA to CeM, and about other mechanisms. From predictions to biology (and back): Assess the effects of fear conditioning and extinction on synaptic responses in the projections from LA to CeL, and CeL to CeM, in an in vitro slice preparation (to be performed in the Par¿ lab). Incorporate findings from experiments and refine the model. 2. To investigate the mechanisms involved in the regulation of amygdala-dependent conditioning and extinction fear memory by the ventro medial prefrontal cortex, using a biologically realistic computational model, and to test model predictions in experiments. From biology to model: Use published biology data (in vitro and in vivo), to investigate the neurocomputational properties of single cells and networks in the pre-limbic (PL) and infra-limbic (IL) regions of the ventral medial prefrontal cortex (vmPFC). From biology to model and to predictions: Determine how the vmPFC regulates amygdala-dependent fear and extinction memories by developing an overall biologically realistic model including the vmPFC and the amygdala (from specific aim 1). Make predictions about the possible connections between vmPFC and the amygdala that may regulate these memories, and the effect of vmPFC inactivation on the tone responses of BA and Ce neurons. From predictions to biology (and back): Assess the effects of vmPFC inactivation on tone responses of BA and Ce neurons during fear conditioning and extinction (to be performed in Quirk lab). Incorporate findings from experiments and refine the model of vmPFC regulation of the amygdala in a single context. Intellectual Merit. The proposed interdisciplinary research will be the first to develop a biologically realistic computational model of the fear circuit. It will facilitate discovery of the learning and neuroplasticity mechanisms that underlie acquisition and extinction of conditioned fear in mammals, and will lead to valuable predictions, and novel directions for experimental research. The approach proposed will also lead to a better understanding of the systems and design principles governing the fear circuit. Broader Impact. The proposed computational model will provide new insights and understanding of a spectrum of psychiatric disorders including PTSD and anxiety disorders, which are thought to arise from deficits in the fear circuit. It will also be a key tool for the development of novel agents and strategies for the treatment of such disorders. Finally, the collaboration will also contribute to the generation of new curricula and materials for undergraduate, graduate and medical student education, and for K-12students.

描述（由申请人提供）：所提议的跨学科研究的总体目标是使用综合计算/实验方法来研究哺乳动物恐惧回路的神经组件中条件性恐惧关联的获得和消失。我们提出了一系列相互依赖的实验和生物学现实模拟，使用“从生物学到模型，到预测，再回到生物学”主题，其中实验将限制模型的设计（“从生物学到模型”），模型和预期结果之间的差异将导致提出假设（“到预测”），并通过实验进行测试（“回到生物学”）。计算模型将利用两位神经科学联合首席研究员实验室的实验数据来开发。我们小组历时 21/2 年开发的初步模型表明，它们可以为与条件性恐惧中的学习和神经可塑性相关的内在和突触机制提供重要的见解。拟议的研究将扩大这种合作，以实现以下具体目标： 1.使用生物学上真实的计算模型来研究与条件性恐惧的获得和消除相关的杏仁核学习和神经可塑性的潜在机制，并在实验中测试模型预测。从生物学到模型：使用已发表的生物学数据（体外和体内），研究杏仁核单细胞模型的神经计算特性，包括外侧杏仁核 (LA)、基底杏仁核 (BA)、闰细胞 (ITC) 和中央核（CeM 和 CeL）。从生物学到模型再到预测：使用包括单细胞模型的生物学真实网络模型研究关键杏仁核如何相互作用以获取和消除条件恐惧记忆。进行预测以量化从 LA 到 CeM 以及其他机制的各种预测的相对贡献。从预测到生物学（反之）：在体外切片制备（将在 Par¿ 实验室进行）中，评估从 LA 到 CeL、从 CeL 到 CeM 的预测中恐惧调节和消退对突触反应的影响。结合实验结果并完善模型。 2. 使用生物学真实的计算模型，研究腹内侧前额叶皮层调节杏仁核依赖性调节和消退恐惧记忆的机制，并在实验中测试模型预测。从生物学到模型：使用已发表的生物学数据（体外和体内），研究腹侧内侧前额叶皮质 (vmPFC) 的前边缘 (PL) 和下边缘 (IL) 区域的单细胞和网络的神经计算特性。从生物学到模型再到预测：通过开发包括 vmPFC 和杏仁核（来自具体目标 1）的整体生物学现实模型，确定 vmPFC 如何调节杏仁核依赖性恐惧和灭绝记忆。预测 vmPFC 和杏仁核之间可能调节这些记忆的联系，以及 vmPFC 失活对 BA 和 Ce 神经元音调反应的影响。从预测到生物学（反之亦然）：评估 vmPFC 失活对恐惧调节和消退过程中 BA 和 Ce 神经元音调反应的影响（将在 Quirk 实验室进行）。结合实验结果并在单一环境中完善 vmPFC 调节杏仁核的模型。智力优点。拟议的跨学科研究将是第一个开发恐惧回路的生物学真实计算模型的研究。它将有助于发现哺乳动物条件性恐惧的获得和消除的学习和神经可塑性机制，并将带来有价值的预测和实验研究的新方向。所提出的方法还将有助于更好地理解控制恐惧电路的系统和设计原理。更广泛的影响。所提出的计算模型将为一系列精神疾病提供新的见解和理解，包括创伤后应激障碍和焦虑症，这些疾病被认为是由恐惧回路的缺陷引起的。它还将成为开发治疗此类疾病的新药物和策略的关键工具。最后，此次合作还将有助于为本科生、研究生、医学生教育以及 K-12 学生开发新课程和材料。