McDevitt Elizabeth A, Kim Ghootae, Turk-Browne Nicholas B, Norman Kenneth A
Princeton University.
Korea Brain Research Institute, Daegu, Republic of Korea.
J Cogn Neurosci. 2025 Jul 18:1-18. doi: 10.1162/jocn.a.82.
When faced with a familiar situation, we can use memory to make predictions about what will happen next. If such predictions turn out to be erroneous, the brain can adapt by differentiating the representations of the cue from the mispredicted item itself, reducing the likelihood of future prediction errors. Prior work by Kim, Norman, and Turk-Browne (2017) found that violating a sequential association in a statistical learning paradigm triggered differentiation of the neural representations of the associated items in the hippocampus. Here, we used fMRI to test the preregistered hypothesis that this hippocampal differentiation occurs only when violations are followed by rapid eye movement (REM) sleep. Participants first learned that some items predict others (e.g., A predicts B) and then encountered a violation in which a predicted item (B) failed to appear when expected after its associated item (A); the predicted item later appeared on its own after an unrelated item. Participants were then randomly assigned to one of three conditions: remain awake, take a nap containing non-REM sleep only, or take a nap with both non-REM and REM sleep. While the predicted results were not observed in the preregistered left CA2/3/dentate gyrus (DG) ROI, we did observe evidence for our hypothesis in closely related hippocampal ROIs, uncorrected for multiple comparisons: In right CA2/3/DG, differentiation in the group with REM sleep was greater than in the groups without REM sleep (wake and non-REM nap); this differentiation was item-specific and concentrated in right DG. REM-related differentiation effects were also greater in bilateral DG when the predicted item was more strongly reactivated during the violation. Overall, these results provide initial evidence linking REM sleep to changes in the hippocampal representations of memories in humans.
当面对熟悉的情境时，我们可以利用记忆来预测接下来会发生什么。如果这些预测被证明是错误的，大脑可以通过区分线索的表征与错误预测的项目本身来进行适应，从而降低未来预测错误的可能性。金、诺曼和特克-布朗（2017年）之前的研究发现，在统计学习范式中违反序列关联会引发海马体中相关项目神经表征的分化。在这里，我们使用功能磁共振成像来检验预先登记的假设，即这种海马体分化仅在违反之后紧接着快速眼动（REM）睡眠时才会发生。参与者首先了解到一些项目能预测其他项目（例如，A预测B），然后遇到一种违反情况，即当相关项目（A）出现后预期的预测项目（B）未出现；预测项目后来在一个不相关项目之后单独出现。然后，参与者被随机分配到三种条件之一：保持清醒、只进行包含非快速眼动睡眠的小睡或进行包含非快速眼动和快速眼动睡眠的小睡。虽然在预先登记的左侧CA2/3/齿状回（DG）感兴趣区域未观察到预测结果，但我们在密切相关的海马体感兴趣区域确实观察到了支持我们假设的证据，未进行多重比较校正：在右侧CA2/3/DG中，快速眼动睡眠组的分化大于无快速眼动睡眠组（清醒和非快速眼动小睡组）；这种分化是特定于项目的，且集中在右侧DG。当预测项目在违反过程中被更强烈地重新激活时，双侧DG中与快速眼动相关的分化效应也更大。总体而言，这些结果提供了初步证据，将快速眼动睡眠与人类记忆的海马体表征变化联系起来。
