Behavioral control is not unitary. It comprises parallel systems, model based and model free, that respectively generate flexible and habitual behaviors. Model-based decisions use predictions of the specific consequences of actions, but how these are implemented in the brain is poorly understood. We used calcium imaging and optogenetics in a sequential decision task for mice to show that the anterior cingulate cortex (ACC) predicts the state that actions will lead to, not simply whether they are good or bad, and monitors whether outcomes match these predictions. ACC represents the complete state space of the task, with reward signals that depend strongly on the state where reward is obtained but minimally on the preceding choice. Accordingly, ACC is necessary only for updating model-based strategies, not for basic reward-driven action reinforcement. These results reveal that ACC is a critical node in model-based control, with a specific role in predicting future states given chosen actions.

行为控制不是单一的。它包括并行系统，基于模型的和无模型的，分别产生灵活的习惯性行为。基于模型的决策使用动作的特定后果的预测，但是人们对这些后果在大脑中的实现方式知之甚少。我们在对小鼠的顺序决策任务中使用了钙成像和光遗传学技术，以显示前扣带回皮质（ACC）不仅可以预测动作的好坏，还可以预测动作将导致的状态，并监视结果是否符合这些预测。ACC代表任务的完整状态空间，其奖励信号在很大程度上取决于获得奖励的状态，而在最小程度上取决于先前的选择。因此，ACC仅对于更新基于模型的策略是必要的，不适用于基本的奖励驱动的行动强化。这些结果表明，ACC是基于模型的控制中的关键节点，在指定选定动作的未来状态预测中具有特定作用。