Biomedical Engineering, University of Rochester, Rochester, New York, United States of America.
Del Monte Institute for Neuroscience, University of Rochester, Rochester, New York, United States of America.
PLoS One. 2019 Sep 9;14(9):e0215417. doi: 10.1371/journal.pone.0215417. eCollection 2019.
In order to survive and function in the world, we must understand the content of our environment. This requires us to gather and parse complex, sometimes conflicting, information. Yet, the brain is capable of translating sensory stimuli from disparate modalities into a cohesive and accurate percept with little conscious effort. Previous studies of multisensory integration have suggested that the brain's integration of cues is well-approximated by an ideal observer implementing Bayesian causal inference. However, behavioral data from tasks that include only one stimulus in each modality fail to capture what is in nature a complex process. Here we employed an auditory spatial discrimination task in which listeners were asked to determine on which side they heard one of two concurrently presented sounds. We compared two visual conditions in which task-uninformative shapes were presented in the center of the screen, or spatially aligned with the auditory stimuli. We found that performance on the auditory task improved when the visual stimuli were spatially aligned with the auditory stimuli-even though the shapes provided no information about which side the auditory target was on. We also demonstrate that a model of a Bayesian ideal observer performing causal inference cannot explain this improvement, demonstrating that humans deviate systematically from the ideal observer model.
为了在这个世界上生存和运作，我们必须理解我们所处环境的内容。这需要我们收集和解析复杂的、有时甚至相互冲突的信息。然而，大脑能够以很少的意识努力将来自不同感觉模式的感觉刺激转化为一个连贯而准确的感知。先前关于多感觉整合的研究表明，大脑对线索的整合可以很好地用实施贝叶斯因果推理的理想观察者来近似。然而，仅在每种感觉模式中包含一个刺激的任务中的行为数据未能捕捉到本质上是一个复杂的过程。在这里，我们采用了一个听觉空间辨别任务，要求听众确定他们听到两个同时呈现的声音中的哪一个在哪个侧。我们比较了两种视觉条件，其中在屏幕中央或与听觉刺激空间对齐呈现与任务无关的形状。我们发现，当视觉刺激与听觉刺激空间对齐时，听觉任务的表现会提高——尽管这些形状没有提供关于听觉目标在哪个侧的信息。我们还证明，执行因果推理的贝叶斯理想观察者模型不能解释这种提高，表明人类系统地偏离了理想观察者模型。
