Cognitive control allows us to think and behave flexibly based on our context and goals. At the heart of theories of cognitive control is a control representation that enables the same input to produce different outputs contingent on contextual factors. In this review, we focus on an important property of the control representation’s neural code: its representational dimensionality. Dimensionality of a neural representation balances a basic separability/generalizability trade-off in neural computation. We will discuss the implications of this trade-off for cognitive control. We will then briefly review current neuroscience findings regarding the dimensionality of control representations in the brain, particularly the prefrontal cortex. We conclude by highlighting open questions and crucial directions for future research.

认知控制使我们能够根据我们的环境和目标灵活地思考和行动。认知控制理论的核心是控制表示，它使相同的输入能够根据上下文因素产生不同的输出。在这篇评论中，我们关注控制表示的神经代码的一个重要属性：它的表示维度。神经表示的维数平衡了神经计算中基本的可分离性/泛化性权衡。我们将讨论这种权衡对认知控制的影响。然后，我们将简要回顾当前有关大脑中控制表征维度的神经科学发现，特别是前额叶皮层。最后，我们强调了未解决的问题和未来研究的关键方向。