Solomon H. Snyder Department of Neuroscience, Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218, USA.
Center for Neuroscience and Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Philos Trans R Soc Lond B Biol Sci. 2023 Sep 25;378(1886):20220333. doi: 10.1098/rstb.2022.0333. Epub 2023 Aug 7.
To navigate and guide adaptive behaviour in a dynamic environment, animals must accurately estimate their own motion relative to the external world. This is a fundamentally multisensory process involving integration of visual, vestibular and kinesthetic inputs. Ideal observer models, paired with careful neurophysiological investigation, helped to reveal how visual and vestibular signals are combined to support perception of linear self-motion direction, or heading. Recent work has extended these findings by emphasizing the dimension of time, both with regard to stimulus dynamics and the trade-off between speed and accuracy. Both time and certainty-i.e. the degree of confidence in a multisensory decision-are essential to the ecological goals of the system: terminating a decision process is necessary for timely action, and predicting one's accuracy is critical for making multiple decisions in a sequence, as in navigation. Here, we summarize a leading model for multisensory decision-making, then show how the model can be extended to study confidence in heading discrimination. Lastly, we preview ongoing efforts to bridge self-motion perception and navigation , including closed-loop virtual reality and active self-motion. The design of unconstrained, ethologically inspired tasks, accompanied by large-scale neural recordings, raise promise for a deeper understanding of spatial perception and decision-making in the behaving animal. This article is part of the theme issue 'Decision and control processes in multisensory perception'.
为了在动态环境中导航和指导适应性行为，动物必须准确估计自己相对于外部世界的运动。这是一个基本的多感官过程，涉及视觉、前庭和运动感觉输入的整合。理想观察者模型与仔细的神经生理学研究相结合，有助于揭示视觉和前庭信号如何结合以支持对线性自我运动方向或航向的感知。最近的工作通过强调时间的维度，无论是在刺激动态方面，还是在速度和准确性之间的权衡方面，扩展了这些发现。时间和确定性——即多感官决策的置信度程度——对于系统的生态目标都是至关重要的：及时终止决策过程对于及时采取行动是必要的，而预测自己的准确性对于在序列中做出多个决策至关重要，就像在导航中一样。在这里，我们总结了一个用于多感官决策的主导模型，然后展示了如何扩展该模型来研究航向辨别中的置信度。最后，我们预览了正在进行的努力，以弥合自我运动感知和导航之间的差距，包括闭环虚拟现实和主动自我运动。不受约束的、受生态学启发的任务的设计，伴随着大规模的神经记录，为更深入地了解行为动物的空间感知和决策提供了希望。本文是主题为“多感官感知中的决策和控制过程”的特刊的一部分。
