Brain-wide neural recordings in mice navigating physical spaces enabled by robotic neural recording headstages

IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Nature Methods Pub Date : 2024-10-07 DOI:10.1038/s41592-024-02434-z
James Hope, Travis M. Beckerle, Pin-Hao Cheng, Zoey Viavattine, Michael Feldkamp, Skylar M. L. Fausner, Kapil Saxena, Eunsong Ko, Ihor Hryb, Russell E. Carter, Timothy J. Ebner, Suhasa B. Kodandaramaiah
{"title":"Brain-wide neural recordings in mice navigating physical spaces enabled by robotic neural recording headstages","authors":"James Hope, Travis M. Beckerle, Pin-Hao Cheng, Zoey Viavattine, Michael Feldkamp, Skylar M. L. Fausner, Kapil Saxena, Eunsong Ko, Ihor Hryb, Russell E. Carter, Timothy J. Ebner, Suhasa B. Kodandaramaiah","doi":"10.1038/s41592-024-02434-z","DOIUrl":null,"url":null,"abstract":"Technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales are typically much larger than the animals that are being recorded from and are thus limited to recording from head-fixed subjects. Here we have engineered robotic neural recording devices—‘cranial exoskeletons’—that assist mice in maneuvering recording headstages that are orders of magnitude larger and heavier than the mice, while they navigate physical behavioral environments. We discovered optimal controller parameters that enable mice to locomote at physiologically realistic velocities while maintaining natural walking gaits. We show that mice learn to work with the robot to make turns and perform decision-making tasks. Robotic imaging and electrophysiology headstages were used to record recordings of Ca2+ activity of thousands of neurons distributed across the dorsal cortex and spiking activity of hundreds of neurons across multiple brain regions and multiple days, respectively. To avoid head fixation or drawbacks of miniaturized devices for freely moving rodents, a robotic device can move a headstage for microscopy or electrophysiology with the animal, thereby enabling naturalistic behavior.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"21 11","pages":"2171-2181"},"PeriodicalIF":36.1000,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Methods","FirstCategoryId":"99","ListUrlMain":"https://www.nature.com/articles/s41592-024-02434-z","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales are typically much larger than the animals that are being recorded from and are thus limited to recording from head-fixed subjects. Here we have engineered robotic neural recording devices—‘cranial exoskeletons’—that assist mice in maneuvering recording headstages that are orders of magnitude larger and heavier than the mice, while they navigate physical behavioral environments. We discovered optimal controller parameters that enable mice to locomote at physiologically realistic velocities while maintaining natural walking gaits. We show that mice learn to work with the robot to make turns and perform decision-making tasks. Robotic imaging and electrophysiology headstages were used to record recordings of Ca2+ activity of thousands of neurons distributed across the dorsal cortex and spiking activity of hundreds of neurons across multiple brain regions and multiple days, respectively. To avoid head fixation or drawbacks of miniaturized devices for freely moving rodents, a robotic device can move a headstage for microscopy or electrophysiology with the animal, thereby enabling naturalistic behavior.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用机器人神经记录头架对小鼠在物理空间中的导航进行全脑神经记录。
能够在多个空间和时间尺度上以细胞分辨率记录神经活动的技术通常比被记录的动物大得多,因此仅限于记录头部固定的实验对象。在这里,我们设计了机器人神经记录装置--"颅骨外骨骼"--它可以帮助小鼠操纵比小鼠大得多、重得多的记录头架,同时帮助小鼠在物理行为环境中导航。我们发现了最佳控制器参数,使小鼠能够以符合生理实际的速度运动,同时保持自然的行走步态。我们的研究表明,小鼠学会了与机器人合作转弯和执行决策任务。我们利用机器人成像和电生理学头台分别记录了分布在背侧皮层的数千个神经元的 Ca2+ 活动以及多个脑区和多天内数百个神经元的尖峰活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Nature Methods
Nature Methods 生物-生化研究方法
CiteScore
58.70
自引率
1.70%
发文量
326
审稿时长
1 months
期刊介绍: Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.
期刊最新文献
CelloType: a unified model for segmentation and classification of tissue images. Super-resolution imaging of fast morphological dynamics of neurons in behaving animals. Accurate RNA 3D structure prediction using a language model-based deep learning approach. Large language modeling and deep learning shed light on RNA structure prediction. A benchmarked, high-efficiency prime editing platform for multiplexed dropout screening.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1