1] Howard Hughes Medical Institute and Department of Neurobiology, Stanford University, Stanford, California 94305, USA [2] Institute of Neuroinformatics, University of Zurich/ETH Zurich, CH-8057 Zurich, Switzerland. [3].
Nature. 2013 Nov 7;503(7474):78-84. doi: 10.1038/nature12742.
Prefrontal cortex is thought to have a fundamental role in flexible, context-dependent behaviour, but the exact nature of the computations underlying this role remains largely unknown. In particular, individual prefrontal neurons often generate remarkably complex responses that defy deep understanding of their contribution to behaviour. Here we study prefrontal cortex activity in macaque monkeys trained to flexibly select and integrate noisy sensory inputs towards a choice. We find that the observed complexity and functional roles of single neurons are readily understood in the framework of a dynamical process unfolding at the level of the population. The population dynamics can be reproduced by a trained recurrent neural network, which suggests a previously unknown mechanism for selection and integration of task-relevant inputs. This mechanism indicates that selection and integration are two aspects of a single dynamical process unfolding within the same prefrontal circuits, and potentially provides a novel, general framework for understanding context-dependent computations.
前额皮质被认为在灵活的、依赖于上下文的行为中具有基础性作用，但支撑这一作用的计算的确切性质在很大程度上仍然未知。特别是，单个前额皮质神经元通常会产生非常复杂的反应，这使得我们很难深入了解它们对行为的贡献。在这里，我们研究了猕猴前额皮质的活动，这些猕猴经过训练可以灵活地选择和整合嘈杂的感官输入以做出选择。我们发现，在群体层面上展开的动态过程框架内，很容易理解单个神经元的观察到的复杂性和功能作用。群体动态可以通过经过训练的递归神经网络来再现，这表明了一种用于选择和整合与任务相关输入的先前未知的机制。这种机制表明，选择和整合是在相同前额皮质回路内展开的单一动态过程的两个方面，并且可能为理解依赖于上下文的计算提供了一个新颖的、通用的框架。
