The hippocampus plays a critical role in the compression and retrieval of sequential information. During wakefulness, it achieves this through theta phase precession and theta sequences. Subsequently, during periods of sleep or rest, the compressed information reactivates through sharp-wave ripple events, manifesting as memory replay. However, how these sequential neuronal activities are generated and how they store information about the external environment remain unknown. We developed a hippocampal cornu ammonis 3 (CA3) computational model based on anatomical and electrophysiological evidence from the biological CA3 circuit to address these questions. The model comprises theta rhythm inhibition, place input, and CA3-CA3 plastic recurrent connection. The model can compress the sequence of the external inputs, reproduce theta phase precession and replay, learn additional sequences, and reorganize previously learned sequences. A gradual increase in synaptic inputs, controlled by interactions between theta-paced inhibition and place inputs, explained the mechanism of sequence acquisition. This model highlights the crucial role of plasticity in the CA3 recurrent connection and theta oscillational dynamics and hypothesizes how the CA3 circuit acquires, compresses, and replays sequential information.

中文翻译：

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CA3 电路模型压缩 Theta 振荡和重放中的顺序信息

海马体在顺序信息的压缩和检索中起着至关重要的作用。在清醒期间，它通过 θ 相位进动和 θ 序列来实现这一点。随后，在睡眠或休息期间，压缩的信息通过尖波波纹事件重新激活，表现为记忆重放。然而，这些连续的神经元活动是如何产生的以及它们如何存储有关外部环境的信息仍然未知。我们基于生物 CA3 回路的解剖学和电生理学证据开发了海马角 3 (CA3) 计算模型来解决这些问题。该模型包括theta节律抑制、位置输入和CA3-CA3可塑性循环连接。该模型可以压缩外部输入的序列、再现 theta 相位进动和重放、学习附加序列以及重新组织先前学习的序列。突触输入的逐渐增加（由 theta 节奏抑制和位置输入之间的相互作用控制）解释了序列获取的机制。该模型强调了可塑性在 CA3 循环连接和 theta 振荡动力学中的关键作用，并假设了 CA3 电路如何获取、压缩和重放顺序信息。