Sensory evidence accumulation is considered a hallmark of decision-making in noisy environments. Integration of sensory inputs has been traditionally studied using passive stimuli, segregating perception from action. Lessons learned from this approach, however, may not generalize to ethological behaviors like navigation, where there is an active interplay between perception and action. We designed a sensory-based sequential decision task in virtual reality in which humans and monkeys navigated to a memorized location by integrating optic flow generated by their own joystick movements. A major challenge in such closed-loop tasks is that subjects' actions will determine future sensory input, causing ambiguity about whether they rely on sensory input rather than expectations based solely on a learned model of the dynamics. To test whether subjects integrated optic flow over time, we used three independent experimental manipulations, unpredictable optic flow perturbations, which pushed subjects off their trajectory; gain manipulation of the joystick controller, which changed the consequences of actions; and manipulation of the optic flow density, which changed the information borne by sensory evidence. Our results suggest that both macaques (male) and humans (female/male) relied heavily on optic flow, thereby demonstrating a critical role for sensory evidence accumulation during naturalistic action-perception closed-loop tasks.

SIGNIFICANCE STATEMENT The temporal integration of evidence is a fundamental component of mammalian intelligence. Yet, it has traditionally been studied using experimental paradigms that fail to capture the closed-loop interaction between actions and sensations inherent in real-world continuous behaviors. These conventional paradigms use binary decision tasks and passive stimuli with statistics that remain stationary over time. Instead, we developed a naturalistic visuomotor visual navigation paradigm that mimics the causal structure of real-world sensorimotor interactions and probed the extent to which participants integrate sensory evidence by adding task manipulations that reveal complementary aspects of the computation.

感官证据积累被认为是在嘈杂环境中做出决策的标志。传统上使用被动刺激来研究感觉输入的整合，将感知与行动分开。然而，从这种方法中汲取的经验教训可能无法推广到像导航这样的行为学行为，因为感知和行动之间存在积极的相互作用。我们在虚拟现实中设计了一个基于感觉的顺序决策任务，其中人类和猴子通过整合自己的操纵杆运动产生的光流导航到记忆的位置。这种闭环任务的一个主要挑战是，受试者的行为将决定未来的感官输入，从而导致他们是否依赖感官输入而不是仅基于学习的动态模型的期望变得模糊。为了测试受试者是否随着时间的推移整合光流，我们使用了三种独立的实验操作，即不可预测的光流扰动，这使受试者偏离了他们的轨迹；获得对操纵杆控制器的操纵，从而改变动作的后果；以及光流密度的操纵，这改变了感官证据所承载的信息。我们的结果表明，猕猴（雄性）和人类（雌性/雄性）都严重依赖光流，从而证明了在自然动作感知闭环任务中感官证据积累的关键作用。

意义陈述证据的时间整合是哺乳动物智力的基本组成部分。然而，传统上是使用实验范式来研究它，但无法捕捉现实世界连续行为中固有的动作和感觉之间的闭环相互作用。这些传统范例使用二元决策任务和被动刺激，并具有随时间推移保持稳定的统计数据。相反，我们开发了一种自然主义的视觉运动视觉导航范式，它模仿现实世界感觉运动相互作用的因果结构，并通过添加揭示计算互补方面的任务操作来探讨参与者整合感官证据的程度。