Parrini Martina, Tricot Guillaume, Caroni Pico, Spolidoro Maria
Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland.
Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland.
Curr Biol. 2024 Jan 8;34(1):79-91.e4. doi: 10.1016/j.cub.2023.11.047. Epub 2023 Dec 14.
Navigation tasks involve the gradual selection and deployment of increasingly effective searching procedures to reach targets. The brain mechanisms underlying such complex behavior are poorly understood, but their elucidation might provide insights into the systems linking exploration and decision making in complex learning. Here, we developed a trial-by-trial goal-related search strategy analysis as mice learned to navigate identical water mazes encompassing distinct goal-related rules and monitored the strategy deployment process throughout learning. We found that navigation learning involved the following three distinct phases: an early phase during which maze-specific search strategies are deployed in a minority of trials, a second phase of preferential increasing deployment of one search strategy, and a final phase of increasing commitment to this strategy only. The three maze learning phases were affected differently by inhibition of retrosplenial cortex (RSC), dorsomedial striatum (DMS), or dorsolateral striatum (DLS). Through brain region-specific inactivation experiments and gain-of-function experiments involving activation of learning-related cFos+ ensembles, we unraveled how goal-related strategy selection relates to deployment throughout these sequential processes. We found that RSC is critically important for search strategy selection, DMS mediates strategy deployment, and DLS ensures searching consistency throughout maze learning. Notably, activation of specific learning-related ensembles was sufficient to direct strategy selection (RSC) or strategy deployment (DMS) in a different maze. Our results establish a goal-related search strategy deployment approach to dissect unsupervised navigation learning processes and suggest that effective searching in navigation involves evidence-based goal-related strategy direction by RSC, reinforcement-modulated strategy deployment through DMS, and online guidance through DLS.
导航任务涉及逐步选择和部署越来越有效的搜索程序以到达目标。这种复杂行为背后的大脑机制尚不清楚，但其阐明可能为深入了解复杂学习中连接探索与决策的系统提供线索。在这里，我们开发了一种逐次试验的与目标相关的搜索策略分析方法，当小鼠学习在包含不同目标相关规则的相同水迷宫中导航时，我们在整个学习过程中监测策略部署过程。我们发现导航学习涉及以下三个不同阶段：一个早期阶段，在此阶段少数试验中会部署特定于迷宫的搜索策略；第二个阶段，一种搜索策略的优先增加部署阶段；以及最后一个阶段，仅对该策略的增加投入阶段。扣带回后皮质（RSC）、背内侧纹状体（DMS）或背外侧纹状体（DLS）的抑制对这三个迷宫学习阶段的影响各不相同。通过脑区特异性失活实验和涉及激活与学习相关的cFos+神经元群的功能获得实验，我们揭示了在这些连续过程中与目标相关的策略选择如何与部署相关。我们发现RSC对搜索策略选择至关重要，DMS介导策略部署，而DLS确保在整个迷宫学习过程中的搜索一致性。值得注意的是，激活特定的与学习相关的神经元群足以在不同的迷宫中指导策略选择（RSC）或策略部署（DMS）。我们的研究结果建立了一种与目标相关的搜索策略部署方法来剖析无监督的导航学习过程，并表明导航中的有效搜索涉及由RSC进行基于证据的与目标相关的策略指导、通过DMS进行强化调制的策略部署以及通过DLS进行在线指导。
