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A hippocampal model for episodic memory using neurogenesis and asymmetric STDP

机译:使用神经发生和不对称STDP的海马情景记忆模型

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Our memory is first acquired as memory of a personal event (episodic memory). Then, its temporal context is removed and the resultant memory is used in higher-order information processing, such as thinking, reasoning and so on. Therefore, episodic memory is the basis of our memories. In this paper, we propose an episodic memory model which adopts the physiological findings of the hippocampus. Episodic memory can be regarded as a temporal sequence of patterns. In general, such a sequence may have some patterns which appear several times in it, or plural temporal sequences may share some same patterns with each other. That is, it is indispensable for the episodic memory model to handle one-to-many association and context. In the proposed model, the neurogenesis in dentate gyrus (DG) contributes to build different representations in CA3 for the same input patterns, and facilitates one-to-many association. Moreover, the asymmetric spike timing dependent synaptic plasticity introduced to the learning of recurrent collateral in CA3 enables memory of context. Computer simulation results show that the proposed model can deal with complex temporal sequences.
机译:我们的存储器首先被获取为个人事件的内存(epiSodic存储器)。然后,删除其时间上下文,并在高阶信息处理中使用结果存储器,例如思维,推理等。因此,情节记忆是我们记忆的基础。在本文中,我们提出了一种具有海马的生理结果的情节记忆模型。插曲记忆可以被视为模式的时间序列。通常,这种序列可以具有一些在其中出现几次的图案,或者多个时间序列可以彼此共享一些相同的模式。也就是说,扩展内存模型是处理一对多关联和上下文是必不可少的。在所提出的模型中,牙齿转座(DG)中的神经发生有助于为相同的输入模式构建CA3中的不同表示,并促进一对多协会。此外,引入到CA3中反复抵押品的学习的非对称尖峰定时依赖性突触塑性使得能够记忆上下文。计算机仿真结果表明,所提出的模型可以处理复杂的时间序列。

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