Data Science Institute, University of California, Irvine, CA, USA.
Department of Statistics, University of California, Irvine, CA, USA.
Nat Commun. 2022 Feb 8;13(1):787. doi: 10.1038/s41467-022-28057-6.
The hippocampus is critical to the temporal organization of our experiences. Although this fundamental capacity is conserved across modalities and species, its underlying neuronal mechanisms remain unclear. Here we recorded hippocampal activity as rats remembered an extended sequence of nonspatial events unfolding over several seconds, as in daily life episodes in humans. We then developed statistical machine learning methods to analyze the ensemble activity and discovered forms of sequential organization and coding important for order memory judgments. Specifically, we found that hippocampal ensembles provide significant temporal coding throughout nonspatial event sequences, differentiate distinct types of task-critical information sequentially within events, and exhibit theta-associated reactivation of the sequential relationships among events. We also demonstrate that nonspatial event representations are sequentially organized within individual theta cycles and precess across successive cycles. These findings suggest a fundamental function of the hippocampal network is to encode, preserve, and predict the sequential order of experiences.
海马体对于我们的经验的时间组织至关重要。尽管这种基本能力在不同的感觉模态和物种中都得到了保留,但它的潜在神经元机制仍不清楚。在这里,我们记录了大鼠在几秒钟内记忆一系列非空间事件的海马体活动,就像人类日常生活中的事件一样。然后,我们开发了统计机器学习方法来分析集合活动,并发现了对顺序记忆判断很重要的序列组织和编码形式。具体来说,我们发现海马体集合在整个非空间事件序列中提供了重要的时间编码,在事件中按顺序区分不同类型的任务关键信息,并表现出与事件之间的序列关系相关的θ 波再激活。我们还证明,非空间事件表示在单个θ 周期内按顺序组织,并在连续周期中进动。这些发现表明,海马网络的基本功能是对经验的顺序进行编码、保存和预测。