AI 中文总结
本研究提出信息论框架，揭示海马体有限神经资源导致情境竞争，决定印记细胞分配比例，并预测非单调关系及相变，为记忆分布提供可检验预测。
AI 中文摘要
海马体CA1区的印记细胞代表与动物经历事件相关的情境信息，构成情景记忆的细胞基础。近期实验表明，海马体位置细胞的一个子集被招募为特定情境的印记细胞。然而，控制跨情境印记细胞分配的机制仍不清楚。在此，我们开发了一个信息论框架，量化CA1神经元编码的空间与情境信息之间的权衡。我们的理论表明，有限的神经资源不可避免地导致情境之间竞争位置细胞作为印记细胞的招募。解决这一优化问题决定了分配给每个情境的印记细胞比例，作为其发生概率的函数。该理论预测情境概率与印记分配之间存在非单调关系，反映资源约束下空间与情境信息之间的竞争。因此，招募比例在临界概率处通过不连续转变出现，在中等概率处达到最大值，并在高频情境中下降。此外，我们解析推导了有限印记细胞分配出现的相边界，作为情境输入强度和情境信息相对重要性的函数。这些发现确定了有限神经资源的竞争是印记细胞分配的关键决定因素，并为资源约束下记忆表征如何跨情境分布提供了可实验验证的预测。
英文摘要
Engram cells in hippocampal CA1 represent contextual information associated with events experienced by animals and constitute a cellular substrate of episodic memory. Recent experiments have shown that a subset of hippocampal place cells is recruited as engram cells for individual contexts. However, the principle governing engram cell allocation across contexts remains unclear. Here, we develop an information-theoretic framework that quantifies the trade-off between spatial and contextual information encoded by CA1 neurons. Our theory shows that limited neural resources inevitably create competition among contexts for the recruitment of place cells as engram cells. Solving this optimization problem determines the fraction of engram cells allocated to each context as a function of its occurrence probability. The theory predicts a non-monotonic relationship between context probability and engram allocation, reflecting competition between spatial and contextual information under resource constraints. Consequently, the recruited fraction emerges through a discontinuous transition at a critical probability, reaches a maximum at intermediate probabilities, and decreases for highly frequent contexts. Furthermore, we analytically derive the phase boundary for the emergence of finite engram cell allocation as a function of contextual input strength and the relative importance of contextual information. These findings identify competition for limited neural resources as a key determinant of engram cell allocation and provide experimentally testable predictions for how memory representations are distributed across contexts under resource constraints.
Comments24 pages, 5 figures
