[论文解读] A computational account of dreaming: learning and memory consolidation

Zhang, Qi|arXiv (Cornell University)|Feb 4, 2026

Sleep and Wakefulness Research被引用 0

一句话总结

论文提出一个认知与计算模型，在梦眠期间随机的内部信号有助于学习和记忆巩固，使梦境与清醒时的大脑活动保持一致，而不是无意义的噪声。

ABSTRACT

A number of studies have concluded that dreaming is mostly caused by randomly arriving internal signals because "dream contents are random impulses", and argued that dream sleep is unlikely to play an important part in our intellectual capacity. On the contrary, numerous functional studies have revealed that dream sleep does play an important role in our learning and other intellectual functions. Specifically, recent studies have suggested the importance of dream sleep in memory consolidation, following the findings of neural replaying of recent waking patterns in the hippocampus. The randomness has been the hurdle that divides dream theories into either functional or functionless. This study presents a cognitive and computational model of dream process. This model is simulated to perform the functions of learning and memory consolidation, which are two most popular dream functions that have been proposed. The simulations demonstrate that random signals may result in learning and memory consolidation. Thus, dreaming is proposed as a continuation of brain's waking activities that processes signals activated spontaneously and randomly from the hippocampus. The characteristics of the model are discussed and found in agreement with many characteristics concluded from various empirical studies.

研究动机与目标

• 促使辩论：梦境是否具有功能性重要性还是随机性？
• 提出用于梦境处理的认知与计算框架。
• 通过仿真演示随机内部信号可以支持学习和记忆巩固。
• 将模型预测与关于海马重放和梦境报告的实证发现联系起来。

提出的方法

• 将梦境过程视为清醒时脑活动的延续，开发一个计算模型。
• 使用来自海马活动的随机信号驱动学习动力学。
• 对模型进行仿真以测试学习与记忆巩固的结果。
• 讨论模型的特征并将其与实证梦研究进行比较。
• 分析自发信号如何在睡眠中类似于神经重放的现象。

实验结果

研究问题

• RQ1 睡眠中随机生成的信号是否可以按照清醒时的活动来驱动学习和记忆巩固？
• RQ2 梦境般的过程是否为记忆巩固等认知功能做出贡献，而不仅仅是随机冲动？
• RQ3 模拟的梦境动态与海马重放和梦境内容的实证发现如何吻合？
• RQ4 提出的模型具备哪些特征能够再现梦境与睡眠研究的实证观察？

主要发现

• 仿真表明随机信号可以导致学习的产生。
• 该模型支持记忆巩固作为梦境式处理的一个功能。
• 梦境被提出为清醒大脑活动的延续，由自发激活的海马信号驱动。
• 模型特征与梦境与睡眠研究中的若干实证发现相吻合。