State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Chinese Institute for Brain Research, Beijing, China.
Science. 2021 May 21;372(6544). doi: 10.1126/science.abf1357.
To make effective decisions, people need to consider the relationship between actions and outcomes. These are often separated by time and space. The neural mechanisms by which disjoint actions and outcomes are linked remain unknown. One promising hypothesis involves neural replay of nonlocal experience. Using a task that segregates direct from indirect value learning, combined with magnetoencephalography, we examined the role of neural replay in human nonlocal learning. After receipt of a reward, we found significant backward replay of nonlocal experience, with a 160-millisecond state-to-state time lag, which was linked to efficient learning of action values. Backward replay and behavioral evidence of nonlocal learning were more pronounced for experiences of greater benefit for future behavior. These findings support nonlocal replay as a neural mechanism for solving complex credit assignment problems during learning.
为了做出有效的决策，人们需要考虑行为和结果之间的关系。这些通常是时间和空间上分离的。将不相关的行为和结果联系起来的神经机制尚不清楚。一个有希望的假设涉及非局部经验的神经重放。我们使用一种将直接价值学习和间接价值学习分开的任务，结合脑磁图，研究了神经重放在人类非局部学习中的作用。在收到奖励后，我们发现了非局部经验的显著回溯重放，状态到状态的时间滞后为 160 毫秒，这与行为值的有效学习有关。对于未来行为更有利的经验，回溯重放和非局部学习的行为证据更为明显。这些发现支持非局部重放作为学习过程中解决复杂信用分配问题的神经机制。
