美国西北大学Lee E. Miller、西班牙国家研究委员会Juan A. Gallego等研究人员合作发现，持续行为背后皮质种群动态的长期稳定性。相关论文于2020年1月6日在线发表于国际顶学术期刊《自然—神经科学》。

研究人员表示，动物很容易在很长一段时间内以一致的方式执行学习的行为，但是还没有证明同样稳定的神经相关性。皮质如何实现这种稳定的控制？

使用感觉运动系统作为皮层处理的模型，研究人员测试了以下假设：必须在整个时间范围内保留神经潜伏活动的动态，该捕获了神经种群内的主要协变模式。研究人员记录了运动前皮层、原发性运动皮层和体感皮层中神经元的数量，其中猴子完成了多达2年的任务。有趣的是，尽管记录的神经元有稳定的更新，但低维潜伏动态仍保持稳定。稳定性允许在整个时间范围内对行为特征进行可靠的解码，而直接基于记录的神经活动的固定解码神经元的性能则大大降低。研究人员认为，稳定的潜在皮层动态是持续行为执行的基础。

附：英文原文

Title: Long-term stability of cortical population dynamics underlying consistent behavior

Author: Juan A. Gallego, Matthew G. Perich, Raeed H. Chowdhury, Sara A. Solla, Lee E. Miller

Issue&Volume: 2020-01-06

Abstract: Animals readily execute learned behaviors in a consistent manner over long periods of time, and yet no equally stable neural correlate has been demonstrated. How does the cortex achieve this stable control Using the sensorimotor system as a model of cortical processing, we investigated the hypothesis that the dynamics of neural latent activity, which captures the dominant co-variation patterns within the neural population, must be preserved across time. We recorded from populations of neurons in premotor, primary motor and somatosensory cortices as monkeys performed a reaching task, for up to 2years. Intriguingly, despite a steady turnover in the recorded neurons, the low-dimensional latent dynamics remained stable. The stability allowed reliable decoding of behavioral features for the entire timespan, while fixed decoders based directly on the recorded neural activity degraded substantially. We posit that stable latent cortical dynamics within the manifold are the fundamental building blocks underlying consistent behavioral execution.

DOI: 10.1038/s41593-019-0555-4

Source: https://www.nature.com/articles/s41593-019-0555-4