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主动头部转动可提高基于声纳的听觉定位性能。

Active head rolls enhance sonar-based auditory localization performance.

机构信息

Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong.

Department of Neuroscience, University of Arizona, Tucson, Arizona, United States.

出版信息

PLoS Comput Biol. 2021 May 10;17(5):e1008973. doi: 10.1371/journal.pcbi.1008973. eCollection 2021 May.

Abstract

Animals utilize a variety of active sensing mechanisms to perceive the world around them. Echolocating bats are an excellent model for the study of active auditory localization. The big brown bat (Eptesicus fuscus), for instance, employs active head roll movements during sonar prey tracking. The function of head rolls in sound source localization is not well understood. Here, we propose an echolocation model with multi-axis head rotation to investigate the effect of active head roll movements on sound localization performance. The model autonomously learns to align the bat's head direction towards the target. We show that a model with active head roll movements better localizes targets than a model without head rolls. Furthermore, we demonstrate that active head rolls also reduce the time required for localization in elevation. Finally, our model offers key insights to sound localization cues used by echolocating bats employing active head movements during echolocation.

摘要

动物利用各种主动感知机制来感知周围的世界。回声定位蝙蝠是研究主动听觉定位的极佳模型。例如,大棕蝠(Eptesicus fuscus)在声纳追踪猎物时会主动进行头部滚动运动。然而,人们对头部滚动在声源定位中的作用还不太了解。在这里,我们提出了一个具有多轴头部旋转的回声定位模型,以研究主动头部滚动运动对声音定位性能的影响。该模型可以自主学习将蝙蝠的头部方向对准目标。我们发现,具有主动头部滚动运动的模型比没有头部滚动的模型能更好地定位目标。此外,我们还证明,主动头部滚动还可以减少在垂直方向上进行定位所需的时间。最后,我们的模型为使用主动头部运动进行回声定位的回声定位蝙蝠提供了有关声音定位线索的关键见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90e7/8136848/d1b9a8e5dcb0/pcbi.1008973.g003.jpg

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