Neuroscience Institute, New York University, New York, NY, USA.
Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
Philos Trans R Soc Lond B Biol Sci. 2020 May 25;375(1799):20190231. doi: 10.1098/rstb.2019.0231. Epub 2020 Apr 6.
A major task in the history of neurophysiology has been to relate patterns of neural activity to ongoing external stimuli. More recently, this approach has branched out to relating current neural activity patterns to external stimuli or experiences that occurred in the past or future. Here, we aim to review the large body of methodological approaches used towards this goal, and to assess the assumptions each makes with reference to the statistics of neural data that are commonly observed. These methods primarily fall into two categories, those that quantify zero-lag relationships without examining temporal evolution, termed , and those that quantify the temporal structure of changing activity patterns, termed . However, no two studies use the exact same approach, which prevents an unbiased comparison between findings. These observations should instead be validated by multiple and, if possible, previously established tests. This will help the community to speak a common language and will eventually provide tools to study, more generally, the organization of neuronal patterns in the brain. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.
神经生理学历史上的一个主要任务是将神经活动模式与当前的外部刺激联系起来。最近，这种方法已经扩展到将当前的神经活动模式与过去或未来发生的外部刺激或经验联系起来。在这里，我们旨在回顾为实现这一目标而采用的大量方法，并评估每种方法在参考常见观察到的神经数据统计时所做的假设。这些方法主要分为两类，一类是不考虑时间演化而量化零延迟关系的方法，称为 ，另一类是量化不断变化的活动模式的时间结构的方法，称为 。然而，没有两项研究使用完全相同的方法，这使得在研究结果之间无法进行无偏比较。这些观察结果应该通过多个（如果可能的话，以前建立的）测试来验证。这将有助于科学界使用共同的语言，并最终提供工具来更广泛地研究大脑中神经元模式的组织。本文是“记忆再激活：回放过去、现在和未来的事件”主题会议的一部分。
