arrow
返回

Individual learning phenotypes drive collective behavior

delete2020-07-15
delete39
delete
OA
AI
C
Chelsea N. Cook *
N
Natalie J. Lemanski
T
Thiago Mosqueiro
C
Cahit Öztürk
J
Jürgen Gadau
N
Noa Pinter‐Wollman
B
Brian H. Smith
DOI:10.1073/pnas.1920554117delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
Individual differences in learning can influence how animals respond to and communicate about their environment, which may nonlinearly shape how a social group accomplishes a collective task. There are few empirical examples of how differences in collective dynamics emerge from variation among individuals in cognition. Here, we use a naturally variable and heritable learning behavior called latent inhibition (LI) to show that interactions among individuals that differ in this cognitive ability drive collective foraging behavior in honey bee colonies. We artificially selected two distinct phenotypes: high-LI bees that ignore previously familiar stimuli in favor of novel ones and low-LI bees that learn familiar and novel stimuli equally well. We then provided colonies differentially composed of different ratios of these phenotypes with a choice between familiar and novel feeders. Colonies of predominantly high-LI individuals preferred to visit familiar food locations, while low-LI colonies visited novel and familiar food locations equally. Interestingly, in colonies of mixed learning phenotypes, the low-LI individuals showed a preference to visiting familiar feeders, which contrasts with their behavior when in a uniform low-LI group. We show that the shift in feeder preference of low-LI bees is driven by foragers of the high-LI phenotype dancing more intensely and attracting more followers. Our results reveal that cognitive abilities of individuals and their social interactions, which we argue relate to differences in attention, drive emergent collective outcomes.
Keyword:
collective behavior
cognition
learning
latent inhibition
honey bee
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

P
Proceedings of the National Academy of Sciences of the United States of America
IF:
9.1
论文数:
10.8W
被引数:
73.5W

机构

A
Arizona State University
学者数:
2.7W
论文数: 2.5W
被引数: 4.2W
M
Marquette University
学者数:
3.3K
论文数: 2.9K
被引数: 3.2K
University of California System 封面图
University of California System
学者数:
37.7W
论文数: 33.8W
被引数: 6.6K
学者 查看更多机构
引用论文

引用论文

Context, Learning, and Extinction
err2010-01-01
err278
PREAI
errGershman, Samuel J.; Blei, David M.; Niv, Yael
err分享
err收藏
Individual differences in learning and biogenic amine levels influence the behavioural division between foraging honeybee scouts and recruits
err2018-11-02
err40
errOAAI
errCook, Chelsea N.; Mosqueiro, Thiago; Brent, Colin S.; Ozturk, Cahit; Gadau, Juergen; Pinter-Wollman, Noa; Smith, Brian H.
err分享
err收藏
Numerical Prediction of Car Tire Wear
err2004-07-01
err0
PREAI
errH. Lupker; F. Cheli; F. Braghin; E. Gelosa; A. Keckman
err分享
err收藏
The frontiers of insect cognition
err2017-08-01
err72
PREAI
errPerry, Clint J.; Barron, Andrew B.; Chittka, Lars
err分享
err收藏
err分享
err收藏
Supercapacitors Based on Mixed Nickel/Cobalt 2D MOF Coordination Nanosheets for Energy Storage
err2024-02-14
err0
PREAI
errYi-Fan Zhang; Chen-Min Han; Chao Bai; Jing-Jing Ma; Le Yu; Li-Juan Sun; Xiao-Yue Zhang; Huai-Ming Hu
err分享
err收藏
学者 查看更多内容