Until now, it has been difficult to examine the neural bases of foraging in naturalistic environments because previous approaches have relied on restrained animals performing trial-based foraging tasks. Here we allowed unrestrained monkeys to freely interact with concurrent reward options while we wirelessly recorded population activity in the dorsolateral prefrontal cortex. The animals decided when and where to forage based on whether their prediction of reward was fulfilled or violated. This prediction was not solely based on a history of reward delivery, but also on the understanding that waiting longer improves the chance of reward. The task variables were continuously represented in a subspace of the high-dimensional population activity, and this compressed representation predicted the animal’s subsequent choices better than the true task variables and as well as the raw neural activity. Our results indicate that monkeys’ foraging strategies are based on a cortical model of reward dynamics as animals freely explore their environment.

到目前为止，研究自然环境中觅食的神经基础一直很困难，因为以前的方法依赖于受约束的动物执行基于试验的觅食任务。在这里，我们允许不受约束的猴子自由地与并发奖励选项互动，同时我们无线记录背外侧前额叶皮层的群体活动。动物根据奖励的预测是否实现或违反来决定何时何地觅食。这一预测不仅基于奖励交付的历史，而且还基于这样的理解：等待更长时间可以提高获得奖励的机会。任务变量在高维群体活动的子空间中连续表示，这种压缩表示比真实任务变量和原始神经活动更好地预测动物的后续选择。我们的结果表明，当动物自由探索其环境时，猴子的觅食策略基于奖励动力学的皮层模型。