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Modeling Acquisition and Extinction of Conditioned Fear in LA Neurons using Learning Algorithm

机译:使用学习算法对LA神经元中条件恐惧的获取和消灭建模

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We develop a biophysical network model of the lateral amygdala (LA) neurons to investigate the underlying mechanisms for acquisition and extinction of conditioned fear. A Hodgkin-Huxley formalism is used to model two main types of LA neurons: pyramidal cells and GABAergic interneurons, which are connected based on biological evidence. Hebbian type synaptic plasticity is implemented into the excitatory NMDA/AMPA receptor mediated synapses to model the learning process. We constrained our models on both the single cell and the network levels by matching the experimental recording. The network model is used to simulate the classical auditory fear conditioning experiment and the results show the model can replicate the neuronal behaviors well during three training process. Our major finding is that expression of conditioned fear and extinction in LA is controlled by the balance between pyramidal cell and interneuron activations. Extinction does not erase the fear memory, but instead further activates the local interneurons which inhibit the responses of pyramidal cells.
机译:我们开发了横向Amygdala(LA)神经元的生物物理网络模型,以研究收购和灭绝条件恐惧的潜在机制。 Hodgkin-Huxley形式主义用于模拟两种主要类型的La神经元:锥体细胞和加布性型在一起,基于生物学证据连接。 Hebbian型突触可塑性被实施为兴奋性NMDA / AMPA受体介导的突触,以建模学习过程。我们通过匹配实验记录来限制我们在单个电池和网络水平上的模型。网络模型用于模拟经典听觉恐惧调理实验,结果表明该模型可以在三个训练过程中复制神经元行为。我们的重大发现是,在LA中的条件恐惧和灭绝的表达是由金字塔细胞和中间核激活之间的平衡来控制。灭绝不会抹去恐惧记忆,而是进一步激活局部的局部核心,抑制金字塔细胞的反应。

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