Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom, and Ageing Research Centre, Karolinska Institute, SE-11330 Stockholm, Sweden.
J Neurosci. 2014 Feb 26;34(9):3340-9. doi: 10.1523/JNEUROSCI.4313-13.2014.
Actions can lead to an immediate reward or punishment and a complex set of delayed outcomes. Adaptive choice necessitates the brain track and integrate both of these potential consequences. Here, we designed a sequential task whereby the decision to exploit or forego an available offer was contingent on comparing immediate value and a state-dependent future cost of expending a limited resource. Crucially, the dynamics of the task demanded frequent switches in policy based on an online computation of changing delayed consequences. We found that human subjects choose on the basis of a near-optimal integration of immediate reward and delayed consequences, with the latter computed in a prefrontal network. Within this network, anterior cingulate cortex (ACC) was dynamically coupled to ventromedial prefrontal cortex (vmPFC) when adaptive switches in choice were required. Our results suggest a choice architecture whereby interactions between ACC and vmPFC underpin an integration of immediate and delayed components of value to support flexible policy switching that accommodates the potential delayed consequences of an action.
行动可能会立即带来奖励或惩罚，也可能会带来一系列复杂的延迟结果。适应性选择需要大脑跟踪和整合这两种潜在的结果。在这里，我们设计了一个序列任务，其中利用或放弃可用选项的决定取决于比较即时价值和消耗有限资源的未来状态相关成本。至关重要的是，任务的动态要求根据不断变化的延迟结果进行在线计算，频繁切换策略。我们发现，人类受试者根据即时奖励和延迟结果的近乎最优整合进行选择，而后者是在前额叶网络中计算的。在这个网络中，当需要适应性选择切换时，前扣带皮层（ACC）与腹内侧前额叶皮层（vmPFC）动态耦合。我们的结果表明，一种选择架构，其中 ACC 和 vmPFC 之间的相互作用支持即时和延迟价值成分的整合，以支持灵活的策略切换，从而适应行动的潜在延迟结果。
