运动系统中单神经元活动的长期稳定性。
Long-term stability of single neuron activity in the motor system.
机构信息
Department of Organismic and Evolutionary Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA.
Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK.
出版信息
Nat Neurosci. 2022 Dec;25(12):1664-1674. doi: 10.1038/s41593-022-01194-3. Epub 2022 Nov 10.
How an established behavior is retained and consistently produced by a nervous system in constant flux remains a mystery. One possible solution to ensure long-term stability in motor output is to fix the activity patterns of single neurons in the relevant circuits. Alternatively, activity in single cells could drift over time provided that the population dynamics are constrained to produce the same behavior. To arbitrate between these possibilities, we recorded single-unit activity in motor cortex and striatum continuously for several weeks as rats performed stereotyped motor behaviors-both learned and innate. We found long-term stability in single neuron activity patterns across both brain regions. A small amount of drift in neural activity, observed over weeks of recording, could be explained by concomitant changes in task-irrelevant aspects of the behavior. These results suggest that long-term stable behaviors are generated by single neuron activity patterns that are themselves highly stable.
神经系统在不断变化的情况下如何保持和持续产生既定的行为仍然是一个谜。确保运动输出长期稳定的一种可能方法是固定相关回路中单神经元的活动模式。或者，只要群体动力学被约束产生相同的行为，单个细胞的活动就可以随时间漂移。为了解决这些可能性，我们在大鼠执行刻板的运动行为（包括学习和本能行为）时，连续数周记录运动皮层和纹状体的单个单位活动。我们发现，两个脑区的单个神经元活动模式都具有长期稳定性。在数周的记录过程中观察到的神经活动的少量漂移，可以用行为中与任务无关的方面的伴随变化来解释。这些结果表明，长期稳定的行为是由自身高度稳定的单个神经元活动模式产生的。
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