Color discrimination thresholds in a cichlid fish: Metriaclima benetos

慈鲷鱼(Metriaclima benetos)的颜色辨别阈值

阅读:1

Abstract

Color vision is essential for animals as it allows them to detect, recognize and discriminate between colored objects. Studies analyzing color vision require an integrative approach, combining behavioral experiments, physiological models and quantitative analyses of photoreceptor stimulation. Here, we demonstrate, for the first time, the limits of chromatic discrimination in Metriaclima benetos, a rock-dwelling cichlid from Lake Malawi, using behavioral experiments and visual modeling. Fish were trained to discriminate between colored stimuli. Color discrimination thresholds were quantified by testing fish chromatic discrimination between the rewarded stimulus and distracter stimuli that varied in chromatic distance (ΔS). This was done under fluorescent lights alone and with additional violet lights. Our results provide two main outcomes. First, cichlid color discrimination thresholds correspond with predictions from the receptor noise limited (RNL) model but only if we assume a Weber fraction higher than the typical value of 5%. Second, cichlids may exhibit limited color constancy under certain lighting conditions as most individuals failed to discriminate colors when violet light was added. We further used the color discrimination thresholds obtained from these experiments to model color discrimination of actual fish colors and backgrounds under natural lighting for Lake Malawi. We found that, for M. benetos, blue is most chromatically contrasting against yellows and space-light, which might be important for discriminating male nuptial colorations and detecting males against the background. This study highlights the importance of lab-based behavioral experiments in understanding color vision and in parameterizing the assumptions of the RNL vision model for different species.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。