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Neuronal dynamics during the learning of trace conditioning in a CA3 model of hippocampal function

机译:海马功能CA3模型中的微量条件学习过程中的神经元动力学

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The present article develops quantitative behavioral and neurophysiological predictions for rabbits trained on an air-puff version of the trace-interval classical conditioning paradigm. Using a minimal hippocampal model, consisting of 8,000 primary cells sparsely and randomly interconnected as a model of hippocampal region CA-3, the simulations identify conditions which produce a clear split in the number of trials individual animals should need to learn a criterion response. A trace interval that is difficult to learn, but still learnable by half the experimental population, produces a bimodal population of learners:an early learner group and a late learner group. The model predicts that late learners are characterized by two kinds of CA-3 neuronal activity fluctuations that are not seen in the early learners. As is typical in our minimal hippocampal models, the off-rate constant of the N-methyl-D-aspartate receptor receptor gives a timescale to the model that leads to a temporally quantifiable behavior, the learnable trace interval.
机译:本文为跟踪间隔经典条件范式的吹气式训练的兔子开发了定量的行为和神经生理预测。使用最小的海马模型,该模型由稀疏且随机互连的8,000个原代细胞组成,作为海马CA-3区模型,该模拟确定了条件,这些条件在个体动物学习标准反应所需的试验数量中产生了明显的分歧。一个很难学习但仍可被一半实验人群学习的跟踪间隔会产生一个双峰学习者群体:一个早期学习者组和一个晚期学习者组。该模型预测,晚期学习者的特征是两种CA-3神经元活动性波动,这在早期学习者中是不可见的。正如我们最小的海马模型中的典型情况一样,N-甲基-D-天冬氨酸受体受体的失速常数为该模型提供了一个时间尺度,从而导致了时间上可量化的行为,即可学习的示踪间隔。

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