Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA, USA.
Nat Neurosci. 2018 Apr;21(4):607-616. doi: 10.1038/s41593-018-0095-3. Epub 2018 Mar 12.
Behavior is driven by coordinated activity across a population of neurons. Learning requires the brain to change the neural population activity produced to achieve a given behavioral goal. How does population activity reorganize during learning? We studied intracortical population activity in the primary motor cortex of rhesus macaques during short-term learning in a brain-computer interface (BCI) task. In a BCI, the mapping between neural activity and behavior is exactly known, enabling us to rigorously define hypotheses about neural reorganization during learning. We found that changes in population activity followed a suboptimal neural strategy of reassociation: animals relied on a fixed repertoire of activity patterns and associated those patterns with different movements after learning. These results indicate that the activity patterns that a neural population can generate are even more constrained than previously thought and might explain why it is often difficult to quickly learn to a high level of proficiency.
行为是由神经元群体的协调活动驱动的。学习需要大脑改变产生的神经群体活动，以实现给定的行为目标。在学习过程中，群体活动如何重新组织？我们在灵长类动物恒河猴的初级运动皮层中研究了脑机接口 (BCI) 任务中的短期学习期间的皮质内群体活动。在 BCI 中，神经活动和行为之间的映射是完全已知的，这使我们能够严格定义关于学习过程中神经重组的假设。我们发现，群体活动的变化遵循一种次优的神经再关联策略：动物依赖于固定的活动模式库，并在学习后将这些模式与不同的运动相关联。这些结果表明，神经群体可以产生的活动模式比以前想象的更加受限，这可能解释了为什么通常很难快速学习到很高的熟练程度。
