The brain exhibits a remarkable ability to learn and execute context-appropriate behaviors. How it achieves such flexibility, without sacrificing learning efficiency, is an important open question. Neuroscience, psychology, and engineering suggest that reusing and repurposing computations are part of the answer. Here, we review evidence that thalamocortical architectures may have evolved to facilitate these objectives of flexibility and efficiency by coordinating distributed computations. Recent work suggests that distributed prefrontal cortical networks compute with flexible codes, and that the mediodorsal thalamus provides regularization to promote efficient reuse. Thalamocortical interactions resemble hierarchical Bayesian computations, and their network implementation can be related to existing gating, synchronization, and hub theories of thalamic function. By reviewing recent findings and providing a novel synthesis, we highlight key research horizons integrating computation, cognition, and systems neuroscience.

中文翻译：

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用于灵活认知和高效学习的丘脑皮质架构


大脑表现出非凡的学习和执行适合情境的行为的能力。如何在不牺牲学习效率的情况下实现这种灵活性，是一个重要的悬而未决的问题。神经科学、心理学和工程学表明，重用和重新利用计算是答案的一部分。在这里，我们回顾了丘脑皮质架构可能已经进化到通过协调分布式计算来促进灵活性和效率的这些目标的证据。最近的研究表明，分布式前额皮质网络使用灵活的代码进行计算，而内侧丘脑提供正则化以促进有效的重用。丘脑皮质相互作用类似于分层贝叶斯计算，其网络实现可以与丘脑功能的现有门控、同步和中枢理论相关。通过回顾最近的发现并提供新颖的综合，我们强调了整合计算、认知和系统神经科学的关键研究视野。