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 2 years. 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.

动物很容易在很长一段时间内以一致的方式执行习得的行为，但尚未证明同样稳定的神经相关性。皮层如何实现这种稳定的控制？使用感觉运动系统作为皮质处理的模型，我们研究了这样的假设：神经潜在活动的动态（捕获神经群体内的主要共变模式）必须随着时间的推移而保留。我们记录了猴子执行伸手任务长达两年的前运动皮层、初级运动皮层和体感皮层的神经元群。有趣的是，尽管记录的神经元的更新稳定，但低维潜在动态保持稳定。稳定性允许对整个时间跨度的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器则大幅退化。我们假设流形内稳定的潜在皮质动力学是一致行为执行的基本构建块。