Memory consolidation assimilates recent experiences into long-term memory. This process requires the replay of learned sequences, although the content of these sequences remains controversial. Recent work has shown that the statistics of replay deviate from those of experience: stimuli that are experientially salient may be either recruited or suppressed from sharp-wave ripples. In this study, we found that this phenomenon can be explained parsimoniously and biologically plausibly by a Hebbian spike-time-dependent plasticity rule at inhibitory synapses. Using models at three levels of abstraction—leaky integrate-and-fire, biophysically detailed and abstract binary—we show that this rule enables efficient generalization, and we make specific predictions about the consequences of intact and perturbed inhibitory dynamics for network dynamics and cognition. Finally, we use optogenetics to artificially implant non-generalizable representations into the network in awake behaving mice, and we find that these representations also accumulate inhibition during sharp-wave ripples, experimentally validating a major prediction of our model. Our work outlines a potential direct link between the synaptic and cognitive levels of memory consolidation, with implications for both normal learning and neurological disease.

记忆巩固将最近的经历同化到长期记忆中。这个过程需要重放学习到的序列，尽管这些序列的内容仍然存在争议。最近的研究表明，重放的统计数据与经验的统计数据不同：在经验上突出的刺激可能被尖锐的波纹招募或抑制。在这项研究中，我们发现这种现象可以用抑制性突触的 Hebbian 尖峰时间依赖性可塑性规则来简洁且生物学上合理地解释。使用三个抽象层次的模型——泄漏的整合和发射、生物物理学详细的和抽象的二元——我们表明这条规则可以实现有效的泛化，并且我们对完整和扰动的抑制动力学对网络动力学和认知的后果进行了具体预测。最后，我们使用光遗传学人为地将不可推广的表征植入清醒行为小鼠的网络中，我们发现这些表征在尖锐的波纹期间也会积累抑制，通过实验验证了我们模型的主要预测。我们的工作概述了记忆巩固的突触和认知水平之间的潜在直接联系，对正常学习和神经系统疾病都有影响。