Adaptive Sampling of Information in Perceptual Decision-Making

In many perceptual and cognitive decision-making problems, humans sample multiple noisy information sources serially, and integrate the sampled information to make an overall decision. We derive the optimal decision procedure for two-alternative choice tasks in which the different options are sampled one at a time, sources vary in the quality of the information they provide, and the available time is fixed. To maximize accuracy, the optimal observer allocates time to sampling different information sources in proportion to their noise levels. We tested human observers in a corresponding perceptual decision-making task. Observers compared the direction of two random dot motion patterns that were triggered only when fixated. Observers allocated more time to the noisier pattern, in a manner that correlated with their sensory uncertainty about the direction of the patterns. There were several differences between the optimal observer predictions and human behaviour. These differences point to a number of other factors, beyond the quality of the currently available sources of information, that influences the sampling strategy.

在诸多感知与认知决策任务中，人类会串行采样多个带噪声的信息源，并整合所采集到的信息以做出最终决策。本研究针对二选一抉择任务推导了最优决策流程：此类任务要求对不同选项逐一进行采样，各信息源提供的信息质量存在差异，且可用采样总时长固定。为最大化决策准确率，最优观察者会根据各信息源的噪声水平，按比例分配用于采样的时长。我们通过对应的感知决策任务对人类观察者进行了测试。受试者需比对两组仅在被注视时才会触发的随机点运动图（random dot motion pattern）的运动方向。人类观察者会为噪声更高的运动图分配更多采样时长，且该时长分配模式与他们对运动图方向的感知不确定性相关。最优观察者的预测结果与人类实际行为之间存在多处差异。这些差异表明，除当前可用信息源的质量外，尚有诸多其他因素会影响人类的采样策略。