• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

SMART-BARN:可扩展的多模态动物行为实时追踪平台,适用于大规模动物群体。

SMART-BARN: Scalable multimodal arena for real-time tracking behavior of animals in large numbers.

机构信息

Department of Collective Behavior, Max-Planck Institute of Animal Behavior, Konstanz, Germany.

Centre for the Advanced Study of Collective Behavior, University of Konstanz, Konstanz, Germany.

出版信息

Sci Adv. 2023 Sep;9(35):eadf8068. doi: 10.1126/sciadv.adf8068. Epub 2023 Sep 1.

DOI:10.1126/sciadv.adf8068
PMID:37656798
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10854427/
Abstract

The SMART-BARN (scalable multimodal arena for real-time tracking behavior of animals in large numbers) achieves fast, robust acquisition of movement, behavior, communication, and interactions of animals in groups, within a large (14.7 meters by 6.6 meters by 3.8 meters), three-dimensional environment using multiple information channels. Behavior is measured from a wide range of taxa (insects, birds, mammals, etc.) and body size (from moths to humans) simultaneously. This system integrates multiple, concurrent measurement techniques including submillimeter precision and high-speed (300 hertz) motion capture, acoustic recording and localization, automated behavioral recognition (computer vision), and remote computer-controlled interactive units (e.g., automated feeders and animal-borne devices). The data streams are available in real time allowing highly controlled and behavior-dependent closed-loop experiments, while producing comprehensive datasets for offline analysis. The diverse capabilities of SMART-BARN are demonstrated through three challenging avian case studies, while highlighting its broad applicability to the fine-scale analysis of collective animal behavior across species.

摘要

SMART-BARN(用于实时跟踪大量动物行为的可扩展多模态竞技场)可在一个大型(14.7 米×6.6 米×3.8 米)三维环境中,使用多个信息通道,快速、稳健地获取动物群体的运动、行为、交流和相互作用。该系统可同时测量来自多个分类群(昆虫、鸟类、哺乳动物等)和不同体型(从飞蛾到人类)的行为。该系统集成了多种并发测量技术,包括亚毫米级精度和高速(300 赫兹)运动捕捉、声记录和定位、自动行为识别(计算机视觉)以及远程计算机控制的交互式单元(例如自动喂食器和动物携带设备)。数据流可实时获取,允许进行高度受控和行为依赖的闭环实验,同时生成全面的数据集供离线分析。通过三个具有挑战性的鸟类案例研究展示了 SMART-BARN 的多样化功能,同时强调了其在跨物种的集体动物行为的精细分析中的广泛适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/cd94a4fcd317/sciadv.adf8068-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/e9ab7fbae634/sciadv.adf8068-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/6d598acfe7d6/sciadv.adf8068-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/9c20a52a1a60/sciadv.adf8068-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/81ce33bad02b/sciadv.adf8068-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/dc9743c7c1eb/sciadv.adf8068-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/9bf9d4e048a5/sciadv.adf8068-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/305e202147f5/sciadv.adf8068-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/a04fda2145cc/sciadv.adf8068-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/cd94a4fcd317/sciadv.adf8068-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/e9ab7fbae634/sciadv.adf8068-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/6d598acfe7d6/sciadv.adf8068-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/9c20a52a1a60/sciadv.adf8068-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/81ce33bad02b/sciadv.adf8068-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/dc9743c7c1eb/sciadv.adf8068-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/9bf9d4e048a5/sciadv.adf8068-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/305e202147f5/sciadv.adf8068-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/a04fda2145cc/sciadv.adf8068-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d80/10854427/cd94a4fcd317/sciadv.adf8068-f9.jpg

相似文献

1
SMART-BARN: Scalable multimodal arena for real-time tracking behavior of animals in large numbers.SMART-BARN:可扩展的多模态动物行为实时追踪平台,适用于大规模动物群体。
Sci Adv. 2023 Sep;9(35):eadf8068. doi: 10.1126/sciadv.adf8068. Epub 2023 Sep 1.
2
Real-Time Closed-Loop Feedback in Behavioral Time Scales Using DeepLabCut.使用DeepLabCut在行为时间尺度上进行实时闭环反馈。
eNeuro. 2021 Apr 16;8(2). doi: 10.1523/ENEURO.0415-20.2021. Print 2021 Mar-Apr.
3
MARGO (Massively Automated Real-time GUI for Object-tracking), a platform for high-throughput ethology.Margo(用于目标跟踪的大规模自动化实时图形用户界面),一个高通量行为学的平台。
PLoS One. 2019 Nov 25;14(11):e0224243. doi: 10.1371/journal.pone.0224243. eCollection 2019.
4
A novel low-noise movement tracking system with real-time analog output for closed-loop experiments.一种具有实时模拟输出的新型低噪声运动跟踪系统,用于闭环实验。
J Neurosci Methods. 2019 Apr 15;318:69-77. doi: 10.1016/j.jneumeth.2018.12.016. Epub 2019 Jan 14.
5
Closed-loop automated reaching apparatus (CLARA) for interrogating complex motor behaviors.闭环自动到达装置(CLARA)用于探究复杂的运动行为。
J Neural Eng. 2021 Aug 31;18(4). doi: 10.1088/1741-2552/ac1ed1.
6
A system for the real-time tracking of operant behavior as an application of 3D camera.一种作为3D相机应用的操作性行为实时跟踪系统。
J Exp Anal Behav. 2018 Nov;110(3):522-544. doi: 10.1002/jeab.471. Epub 2018 Sep 19.
7
EthoVision: a versatile video tracking system for automation of behavioral experiments.EthoVision:一款用于行为实验自动化的多功能视频跟踪系统。
Behav Res Methods Instrum Comput. 2001 Aug;33(3):398-414. doi: 10.3758/bf03195394.
8
The Synthetic Moth: A Neuromorphic Approach toward Artificial Olfaction in Robots合成蛾:一种用于机器人人工嗅觉的神经形态方法
9
Classification of Animal Movement Behavior through Residence in Space and Time.通过空间和时间中的栖息地对动物运动行为进行分类。
PLoS One. 2017 Jan 3;12(1):e0168513. doi: 10.1371/journal.pone.0168513. eCollection 2017.
10
Examination of an averaging method for estimating repulsion and attraction interactions in moving groups.检验一种用于估计移动星团中斥力和引力相互作用的平均方法。
PLoS One. 2020 Dec 9;15(12):e0243631. doi: 10.1371/journal.pone.0243631. eCollection 2020.

引用本文的文献

1
The lab-field continuum in conservation physiology research: leveraging multiple approaches to inform policy and practice.保护生理学研究中的实验室-野外连续体:利用多种方法为政策和实践提供信息。
Conserv Physiol. 2025 Sep 2;13(1):coaf063. doi: 10.1093/conphys/coaf063. eCollection 2025.
2
Gaze following in pigeons increases with the number of demonstrators.鸽子的注视跟随行为会随着示范者数量的增加而增强。
iScience. 2025 Jun 9;28(7):112857. doi: 10.1016/j.isci.2025.112857. eCollection 2025 Jul 18.
3
Mapping the landscape of social behavior.

本文引用的文献

1
Head-tracking of freely-behaving pigeons in a motion-capture system reveals the selective use of visual field regions.在运动捕捉系统中对自由活动的鸽子进行头部跟踪,揭示了视觉区域的选择性使用。
Sci Rep. 2022 Nov 9;12(1):19113. doi: 10.1038/s41598-022-21931-9.
2
Empirical test of the many-wrongs hypothesis reveals weighted averaging of individual routes in pigeon flocks.对“诸多错误”假说的实证检验揭示了鸽群中个体路线的加权平均情况。
iScience. 2022 Sep 5;25(10):105076. doi: 10.1016/j.isci.2022.105076. eCollection 2022 Oct 21.
3
Natural switches in behaviour rapidly modulate hippocampal coding.
描绘社会行为的全貌。
Cell. 2025 Apr 17;188(8):2249-2266.e23. doi: 10.1016/j.cell.2025.01.044. Epub 2025 Mar 4.
4
Mapping the landscape of social behavior.描绘社会行为的全貌。
bioRxiv. 2024 Sep 27:2024.09.27.615451. doi: 10.1101/2024.09.27.615451.
5
Fine-scale tracking reveals visual field use for predator detection and escape in collective foraging of pigeon flocks.精细追踪揭示了鸽群集体觅食中用于探测和逃避捕食者的视野利用。
Elife. 2024 Sep 12;13:RP95549. doi: 10.7554/eLife.95549.
6
A behavioral analysis system MCFBM enables objective inference of songbirds' attention during social interactions.一种行为分析系统 MCFBM 能够客观推断出鸣禽在社交互动期间的注意力。
Cell Rep Methods. 2024 Sep 16;4(9):100844. doi: 10.1016/j.crmeth.2024.100844. Epub 2024 Sep 3.
7
Understanding collective behavior through neurobiology.通过神经生物学理解集体行为。
Curr Opin Neurobiol. 2024 Jun;86:102866. doi: 10.1016/j.conb.2024.102866.
8
A perspective on neuroethology: what the past teaches us about the future of neuroethology.神经行为学视角:过去对神经行为学未来的启示。
J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 2024 Mar;210(2):325-346. doi: 10.1007/s00359-024-01695-5. Epub 2024 Feb 27.
9
Gaze tracking of large-billed crows (Corvus macrorhynchos) in a motion capture system.大头乌鸦在运动捕捉系统中的注视追踪。
J Exp Biol. 2024 Mar 15;227(6). doi: 10.1242/jeb.246514. Epub 2024 Mar 22.
10
Head-tracking of freely-behaving pigeons in a motion-capture system reveals the selective use of visual field regions.在运动捕捉系统中对自由活动的鸽子进行头部跟踪,揭示了视觉区域的选择性使用。
Sci Rep. 2022 Nov 9;12(1):19113. doi: 10.1038/s41598-022-21931-9.
行为中的自然转变能快速调节海马体的编码。
Nature. 2022 Sep;609(7925):119-127. doi: 10.1038/s41586-022-05112-2. Epub 2022 Aug 24.
4
Individual tracking reveals long-distance flight-path control in a nocturnally migrating moth.个体追踪揭示了一种夜间迁徙蛾类的长途飞行路径控制。
Science. 2022 Aug 12;377(6607):764-768. doi: 10.1126/science.abn1663. Epub 2022 Aug 11.
5
Multimodal cues displayed by submissive rats promote prosocial choices by dominants.顺从的老鼠表现出的多种模态线索促进了优势个体的亲社会选择。
Curr Biol. 2022 Aug 8;32(15):3288-3301.e8. doi: 10.1016/j.cub.2022.06.026. Epub 2022 Jul 7.
6
SLEAP: A deep learning system for multi-animal pose tracking.SLEAP:一个用于多动物姿态跟踪的深度学习系统。
Nat Methods. 2022 Apr;19(4):486-495. doi: 10.1038/s41592-022-01426-1. Epub 2022 Apr 4.
7
Biological Earth observation with animal sensors.动物传感器的生物地球观测。
Trends Ecol Evol. 2022 Apr;37(4):293-298. doi: 10.1016/j.tree.2021.11.011.
8
Emergence of splits and collective turns in pigeon flocks under predation.鸽群在捕食情况下出现分裂和集体转向。
R Soc Open Sci. 2022 Feb 23;9(2):211898. doi: 10.1098/rsos.211898. eCollection 2022 Feb.
9
Perspectives in machine learning for wildlife conservation.机器学习在野生动物保护中的应用展望。
Nat Commun. 2022 Feb 9;13(1):792. doi: 10.1038/s41467-022-27980-y.
10
Spatiotemporal dynamics of animal contests arise from effective forces between contestants.动物竞争的时空动态源于参赛者之间的有效力量。
Proc Natl Acad Sci U S A. 2021 Dec 7;118(49). doi: 10.1073/pnas.2106269118.