Humans can draw insight from previous experiences to quickly adapt to novel environments that share a common underlying structure. Here we combine functional imaging and computational modeling to identify the neural systems that support the discovery and transfer of hierarchical task structure. Human subjects (male and female) completed multiple blocks of a reinforcement learning task that contained a global hierarchical structure governing stimulus–response action mapping. First, behavioral and computational evidence showed that humans successfully discover and transfer the hierarchical rule structure embedded within the task. Next, analysis of fMRI BOLD data revealed activity across a frontoparietal network that was specifically associated with the discovery of this embedded structure. Finally, activity throughout a cingulo-opercular network supported the transfer and implementation of this discovered structure. Together, these results reveal a division of labor in which dissociable neural systems support the learning and transfer of abstract control structures.

SIGNIFICANCE STATEMENT A fundamental and defining feature of human behavior is the ability to generalize knowledge from the past to support future action. Although the neural circuits underlying more direct forms of learning have been well established over the last century, we still lack a solid framework from which to investigate more abstract, higher-order human learning and knowledge generalization. We designed a novel behavioral paradigm to specifically isolate a learning process in which previous knowledge, rather than directly indicating the correct action, instead guides the search for the correct action. Moreover, we identify that this learning process is achieved via the coordinated and temporally specific activity of two prominent cognitive control brain networks.

人类可以从以前的经验中汲取见识，以快速适应具有共同基础结构的新颖环境。在这里，我们结合功能成像和计算模型来识别支持分层任务结构的发现和传递的神经系统。人类受试者（男性和女性）完成了强化学习任务的多个模块，其中包含控制刺激－反应动作映射的全局分层结构。首先，行为和计算证据表明，人类成功发现并转移了嵌入任务中的分层规则结构。接下来，对fMRI BOLD数据的分析揭示了跨额叶网络的活动，该活动与发现该嵌入式结构特别相关。最后，整个耳鞘-神经网络的活动支持了这一发现结构的转移和实施。总之，这些结果揭示了一种分工，其中可分离的神经系统支持抽象控制结构的学习和转移。

意义声明人类行为的基本特征是能够概括过去的知识以支持未来行动的能力。尽管在上个世纪已经建立了建立更直接的学习形式的神经回路，但我们仍然缺乏一个可靠的框架来研究更抽象，更高阶的人类学习和知识概括。我们设计了一种新颖的行为范式，专门隔离了学习过程，在该过程中，先前的知识而不是直接指示正确的动作，而是指导了对正确动作的搜索。此外，我们确定该学习过程是通过两个突出的认知控制脑网络的协调和在时间上特定的活动来实现的。