Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), Seika-cho, Kyoto, Japan.
Research Fellow of Japan Society for the Promotion of Science, Chiyoda-ku, Tokyo, Japan.
PLoS One. 2021 May 5;16(5):e0250517. doi: 10.1371/journal.pone.0250517. eCollection 2021.
Bats use echolocation through flexible active sensing via ultrasounds to identify environments suitable for their habitat and foraging. Mimicking the sensing strategies of bats for echolocation, this study examined how humans acquire new acoustic-sensing abilities, and proposes effective strategies for humans. A target geometry identification experiment-involving 15 sighted people without experience of echolocation-was conducted using two targets with different geometries, based on a new sensing system. Broadband frequency-modulated pulses with short inter-pulse intervals (16 ms) were used as a synthetic echolocation signal. Such pulses mimic buzz signals emitted by bats for echolocation prior to capturing their prey. The study participants emitted the signal from a loudspeaker by tapping on Android devices. Because the signal included high-frequency signals up to 41 kHz, the emitted signal and echoes from a stationary or rotating target were recorded using a 1/7-scaled miniature dummy head. Binaural sounds, whose pitch was down-converted, were presented through headphones. This way, time-varying echo information was made available as an acoustic cue for target geometry identification under a rotating condition, as opposed to a stationary one. In both trials, with (i.e., training trials) and without (i.e., test trials) answer feedback immediately after the participants answered, the participants identified the geometries under the rotating condition. Majority of the participants reported using time-varying patterns in terms of echo intensity, timbre, and/or pitch under the rotating condition. The results suggest that using time-varying patterns in echo intensity, timbre, and/or pitch enables humans to identify target geometries. However, performance significantly differed by condition (i.e., stationary vs. rotating) only in the test trials. This difference suggests that time-varying echo information is effective for identifying target geometry through human echolocation especially when echolocators are unable to obtain answer feedback during sensing.
蝙蝠通过灵活的主动感知,利用超声波来识别适合其栖息地和觅食的环境。本研究通过模拟蝙蝠回声定位的感知策略,研究了人类如何获得新的声感知能力,并提出了有效的人类策略。基于一种新的感知系统,进行了一项涉及 15 名没有回声定位经验的明眼人的目标几何识别实验。该实验使用两个具有不同几何形状的目标,使用宽带调频脉冲(脉冲间隔 16 毫秒)作为合成回声定位信号。这些脉冲模拟了蝙蝠在捕捉猎物前发出的嗡嗡声信号。研究参与者通过敲击安卓设备上的扬声器来发出信号。由于信号包含高达 41 kHz 的高频信号,因此通过使用 1/7 比例的微型假人头来记录来自静止或旋转目标的发出信号和回波。经过下变频的双耳声音通过耳机呈现。这样,在旋转条件下,而不是在静止条件下,作为时间变化的回声信息的声线索可用于目标几何识别。在两种情况下(即训练试验和无答案反馈的测试试验),参与者都在旋转条件下识别出了目标的几何形状。大多数参与者报告说,在旋转条件下,他们根据回声强度、音色和/或音高的时间变化模式来识别目标的几何形状。结果表明,利用回声强度、音色和/或音高的时间变化模式可以使人类识别目标的几何形状。然而,只有在测试试验中,性能才会因条件(即静止与旋转)的不同而显著不同。这种差异表明,时间变化的回声信息对于通过人类回声定位来识别目标几何形状是有效的,尤其是当回声定位器在感知过程中无法获得答案反馈时。