无对称可塑性的前向与反向延迟驱动海马重放
Forward and reverse delay-driven hippocampal replay without symmetric plasticity
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中文总结 AI 辅助
提出延迟耦合的CA3神经场模型，证明无论对称或不对称可塑性均可实现双向海马重放，推导动力学低维描述并分析重放速度稳定性，为双向重放的机制提供新解释。
中文摘要 AI 辅助
海马重放是在哺乳动物和鸣禽中观察到的现象，清醒期经历的神经激活序列会在休息或睡眠期间重复，该机制被认为在情景记忆巩固、检索和规划中发挥关键作用。有趣的是，重放可以按前向和反向时间顺序发生，且跨越广泛的加速范围。激活序列的学习传统上由时间不对称的赫布可塑性规则建模，该规则将重放解释为活动链。这类规则无法强化反向连接，导致人们普遍认为它们无法解释双向重放。因此，现有理论工作通过对称连接解释反向重放，这类连接通过对称可塑性规则形成。我们提出了一个延迟耦合的CA3神经场模型，其中活动以波的形式在环中传播，重放以不同速度前向和反向发生。我们的模型在单次暴露于含噪声的刺激后，无论使用对称还是不对称可塑性，都能学习双向重放。我们推导了动力学的低维描述，并分析了可能的重放速度的稳定性。
英文摘要
Hippocampal replay is a phenomenon observed in mammals and songbirds where neural activation sequences experienced during wakeful periods are repeated during rest or sleep. This mechanism is believed to play a crucial role in episodic memory consolidation, retrieval, and planning. Interestingly, replay can occur in both forward and reverse temporal orders and across a wide range of increased speeds. The learning of activation sequences has traditionally been modeled by temporally asymmetric Hebbian plasticity rules, which explain replay as a chain of activity. The inability of such rules to strengthen backward connections has led to the widespread belief that they cannot account for bidirectional replay. Existing theoretical work therefore explains reverse replay through symmetric connections, which would be formed through symmetric plasticity rules. We propose a delay-coupled neural field model of CA3, where activity propagates as a wave in a ring, and replays occur both forwards and backwards at different speeds. Our model can learn bidirectional replay after a single noisy exposure to a stimulus with either symmetric or asymmetric plasticity. We derive a low-dimensional description of the dynamics and analyze the stability of possible replay speeds.
