Soh Zu, Matsuno Motoki, Yoshida Masayuki, Tsuji Toshio
1 Graduate School of Engineering, Hiroshima University , Higashi-Hiroshima, Hiroshima, Japan .
2 Graduate School of Biosphere Science, Hiroshima University , Higashi-Hiroshima, Hiroshima, Japan .
Zebrafish. 2018 Apr;15(2):133-144. doi: 10.1089/zeb.2017.1491. Epub 2018 Jan 30.
Fear and anxiety in fish are generally evaluated by video-based behavioral analysis. However, it is difficult to distinguish the psychological state of fish exclusively through video analysis, particularly whether the fish are freezing, which represents typical fear behavior, or merely resting. We propose a system that can measure bioelectrical signals called ventilatory signals and simultaneously analyze swimming behavior in real time. Experimental results comparing the behavioral analysis of the proposed system and the camera system showed a low error level with an average absolute position error of 9.75 ± 3.12 mm (about one-third of the body length) and a correlation between swimming speeds of r = 0.93 ± 0.07 (p < 0.01). We also exposed the fish to zebrafish skin extracts containing alarm substances that induce fear and anxiety responses to evaluate their emotional changes. The results confirmed that this solution significantly changed all behavioral and ventilatory signal indices obtained by the proposed system (p < 0.01). By combining the behavioral and ventilatory signal indices, we could detect fear and anxiety with a discrimination rate of 83.3% ± 16.7%. Furthermore, we found that the decreasing fear and anxiety over time could be detected according to the peak frequency of the ventilatory signals, which cannot be measured through video analysis.
鱼类的恐惧和焦虑通常通过基于视频的行为分析来评估。然而,仅通过视频分析很难区分鱼类的心理状态,特别是鱼类是处于静止状态(这代表典型的恐惧行为)还是仅仅在休息。我们提出了一种系统,该系统可以测量称为呼吸信号的生物电信号,并同时实时分析游泳行为。将该系统与摄像头系统的行为分析结果进行比较的实验表明,误差水平较低,平均绝对位置误差为9.75±3.12毫米(约为鱼体长度的三分之一),游泳速度之间的相关性为r = 0.93±0.07(p <0.01)。我们还将鱼暴露于含有警报物质的斑马鱼皮肤提取物中,这些物质会引发恐惧和焦虑反应,以评估它们的情绪变化。结果证实,这种溶液显著改变了该系统获得的所有行为和呼吸信号指标(p <0.01)。通过结合行为和呼吸信号指标,我们能够以83.3%±16.7%的辨别率检测到恐惧和焦虑。此外,我们发现可以根据呼吸信号的峰值频率检测到随着时间推移恐惧和焦虑的减轻,而这是无法通过视频分析来测量的。