five

Visuo-motor biases in buff-tailed bumblebees (Bombus terrestris)

收藏
DataCite Commons2024-03-22 更新2024-07-13 收录
下载链接:
https://repository.lincoln.ac.uk/articles/dataset/Visuo-motor_biases_in_buff-tailed_bumblebees_Bombus_terrestris_/24325411/2
下载链接
链接失效反馈
官方服务:
资源简介:
Bees provide a good model to investigate the evolution of lateralisation. So far, most studies focused on olfactory learning and recall of olfactory memories in tethered bees. This study investigated possible behavioural biases in free-flying buff-tailed bumblebees (Bombus terrestris) by analysing their turning decisions in a T-maze. Bees of various size were trained to associate a syrup reward with a blue target placed at the centre of the T-maze. The bees were then tested over 16 trials by presenting them with blue targets at the end of the maze’s arms. The maze was rotated 180? after the first 8 trials to control for the effect of environmental factors. The number of turnings to the left and right arms were analysed. The bees sampled exhibited a population-level rightward turning bias. The width of the bee’s thorax was also measured to identify a possible relationship between size and the bias. A positive, although not significant, correlation was identified, suggesting that large bees may be more strongly lateralised. This study shows that bees present lateralisation in a visuo-motor task that mimic their foraging behaviour, indicating a possible specialisation of the right side of the nervous system in routine tasks.

蜜蜂是研究偏侧化(lateralisation)演化的优质模型。迄今多数研究均围绕拴缚式蜜蜂的嗅觉学习与嗅觉记忆提取展开。本研究通过分析自由飞行的黄尾熊蜂(Bombus terrestris)在T型迷宫中的转向决策,探究其行为偏侧化倾向。研究人员将不同体型的蜜蜂训练至将糖浆奖励与放置于T型迷宫中央的蓝色目标刺激建立关联,随后通过16轮测试,在迷宫臂末端呈现蓝色目标刺激以检验蜜蜂的选择偏好。为控制环境因素的影响,在前8轮测试结束后将迷宫旋转180°,并对蜜蜂转向左右臂的次数进行统计分析。受试样本整体表现出群体水平的右转偏向。此外,研究人员还测量了蜜蜂的胸部宽度,以探究体型与转向偏侧化之间的潜在关联。研究发现二者存在正向相关关系(虽未达到统计学显著性),提示体型更大的蜜蜂其偏侧化程度可能更强。本研究表明,蜜蜂在模拟觅食行为的视运动任务中存在偏侧化现象,提示其神经系统右侧或许在日常任务中存在功能特化。
提供机构:
University of Lincoln
创建时间:
2023-10-30
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作