Theta/gamma networks with slow NMDA channels learn sequences and encode episodic memory: Role of NMDA channels in recall
Theta/gamma networks with slow NMDA channels learn sequences and encode episodic memory: Role of NMDA channels in recall
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DOI：
10.1101/lm.3.2-3.264
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发表时间：
1996-09-01
影响因子：
2
通讯作者：
Lisman, JE
中科院分区：
文献类型：
--
作者：
Jensen, O;Lisman, JE
本文研究了慢n -甲基- d -天冬氨酸（NMDA）通道（失活时间类似于150毫秒）在低频θ振荡的不同伽马子周期中复用不同记忆的网络中的作用。NMDA通道位于循环侧支突触中，并根据已知的生理特性控制突触修饰。由于缓慢的NMDA通道具有跨越几个伽马周期的时间常数，因此代表不同记忆的细胞之间将形成突触连接。这使得具有缓慢NMDA通道的大脑结构能够在长期记忆中存储异相关序列信息。这些存储的序列信息可以通过显示序列的初始元素来唤起。其余序列然后回忆一段记忆的速度每伽马周期,NMDA通道的新角色建议由我们的发现是,召回al伽马频率工作如果缓慢NMDA通道提供的主要组件EPSP复发性突触的络脉:这些通道和长时间的缓慢发作期间允许解雇一个内存一个γ周期触发下一个内存在随后的伽马周期。读出机制的一个有趣特征是，给定记忆的激活是由于存储序列中多个先前记忆的累积输入，而不仅仅是前一个记忆。因此，神经网络以双重冗余的方式存储序列信息：记忆的激活取决于来自多个先前记忆的多个细胞的突触输入的强度。序列存储的累积特性得到了心理物理学文献的支持。累积学习还为不同序列有重叠区域时出现的消歧问题提供了解决方案。在最后一组模拟中，我展示了将自联想网络与异联想网络耦合如何允许情景记忆（一种短暂发生的已知项目的独特序列）的存储。自联想网络（皮层）捕获短期记忆中的序列，并提供精确的、时间压缩的重复，以驱动异联想网络（海马体）中的突触修改。这是第一个机制上详细的模型，展示了已知的大脑特性，包括网络振荡、循环分支、AMPA通道、NMDA通道亚型、ADP和AHP如何共同作用来完成记忆存储和零售。
This paper examines the role of slow N-methyl-D-aspartate (NMDA) channels (deactivation similar to 150 msec) in networks that multiplex different memories in different gamma subcycles of a low frequency theta oscillation. The NMDA channels are in the synapses of recurrent collaterals and govern synaptic modification in accord with known physiological properties. Because slow NMDA channels have a time constant that spans several gamma cycles, synaptic connections will form between cells that represent different memories. This enables brain structures that have slow NMDA channels to store heteroassociative sequence information Ln long-term memory. Recall of this stored sequence information can be initiated by presentation of initial elements of the sequence. The remaining sequence is then recalled at a rate of one memory every gamma cycle, A new role for the NMDA channel suggested by our finding is that recall al gamma frequency works well if slow NMDA channels provide the dominant component of the EPSP at the synapse of recurrent collaterals: The slow onset of these channels and their long duration allows the firing of one memory during one gamma cycle to trigger the next memory during the subsequent gamma cycle. An interesting feature of the readout mechanism is that the activation of a given memory is due to cumulative input from multiple previous memories in the stored sequence, not just the previous one. The network thus stores sequence information in a doubly redundant way: Activation of a memory depends on the strength of synaptic inputs from multiple cells of multiple previous memories. The cumulative property of sequence storage has support from the psychophysical literature. Cumulative learning also provides a solution to the disambiguation problem that occurs when different sequences have a region of overlap. in a final set of simulations, me show how coupling an autoassociative network to a heteroassociative network allows the storage of episodic memories (a unique sequence of briefly occuring known items), The autoassociative network (cortex) captures the sequence in short-term memory and provides the accurate, time-compressed repetition required to drive synaptic modification in the heteroassociative network (hippocampus). This is the first mechanistically detailed model showing how known brain properties, including network oscillations, recurrent collaterals, AMPA channels, NMDA channel subtypes, the ADP, and the AHP can act together to accomplish memory storage and retail.