• 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

神经像素探针进行大规模电生理学研究的挑战与机遇。

Challenges and opportunities for large-scale electrophysiology with Neuropixels probes.

机构信息

University College London, London, UK.

Allen Institute for Brain Science, Seattle, WA, United States.

出版信息

Curr Opin Neurobiol. 2018 Jun;50:92-100. doi: 10.1016/j.conb.2018.01.009. Epub 2018 Feb 13.

DOI:10.1016/j.conb.2018.01.009
PMID:29444488
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5999351/
Abstract

Electrophysiological methods are the gold standard in neuroscience because they reveal the activity of individual neurons at high temporal resolution and in arbitrary brain locations. Microelectrode arrays based on complementary metal-oxide semiconductor (CMOS) technology, such as Neuropixels probes, look set to transform these methods. Neuropixels probes provide ∼1000 recording sites on an extremely narrow shank, with on-board amplification, digitization, and multiplexing. They deliver low-noise recordings from hundreds of neurons, providing a step change in the type of data available to neuroscientists. Here we discuss the opportunities afforded by these probes for large-scale electrophysiology, the challenges associated with data processing and anatomical localization, and avenues for further improvements of the technology.

摘要

电生理学方法是神经科学的金标准,因为它们可以以高时间分辨率和任意脑区揭示单个神经元的活动。基于互补金属氧化物半导体 (CMOS) 技术的微电极阵列,如 Neuropixels 探针,有望改变这些方法。Neuropixels 探针在极细的探臂上提供了约 1000 个记录位点,具有板载放大、数字化和多路复用功能。它们可以从数百个神经元中获取低噪声记录,为神经科学家提供了可用数据类型的重大改变。在这里,我们讨论了这些探针在大规模电生理学方面带来的机遇,以及与数据处理和解剖定位相关的挑战,以及进一步改进该技术的途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3290/5999351/e76681bc0c2c/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3290/5999351/d314ccd0c154/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3290/5999351/e76681bc0c2c/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3290/5999351/d314ccd0c154/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3290/5999351/e76681bc0c2c/gr2.jpg

相似文献

1
Challenges and opportunities for large-scale electrophysiology with Neuropixels probes.神经像素探针进行大规模电生理学研究的挑战与机遇。
Curr Opin Neurobiol. 2018 Jun;50:92-100. doi: 10.1016/j.conb.2018.01.009. Epub 2018 Feb 13.
2
Active pixel sensor array for high spatio-temporal resolution electrophysiological recordings from single cell to large scale neuronal networks.用于从单细胞到大规模神经元网络进行高时空分辨率电生理记录的有源像素传感器阵列。
Lab Chip. 2009 Sep 21;9(18):2644-51. doi: 10.1039/b907394a. Epub 2009 Jul 15.
3
Large-Scale, High-Resolution Microelectrode Arrays for Interrogation of Neurons and Networks.用于神经元和神经网络检测的大规模、高分辨率微电极阵列
Adv Neurobiol. 2019;22:83-123. doi: 10.1007/978-3-030-11135-9_4.
4
An adaptable, reusable, and light implant for chronic Neuropixels probes.一种适用于慢性神经像素探针的可适配、可重复使用且轻便的植入物。
Elife. 2025 Feb 18;13:RP98522. doi: 10.7554/eLife.98522.
5
Active High-Density Electrode Arrays: Technology and Applications in Neuronal Cell Cultures.有源高密度电极阵列:神经元细胞培养中的技术与应用
Adv Neurobiol. 2019;22:253-273. doi: 10.1007/978-3-030-11135-9_11.
6
A CMOS-based microelectrode array for interaction with neuronal cultures.一种用于与神经元培养物相互作用的基于CMOS的微电极阵列。
J Neurosci Methods. 2007 Aug 15;164(1):93-106. doi: 10.1016/j.jneumeth.2007.04.006. Epub 2007 Apr 19.
7
Fully integrated silicon probes for high-density recording of neural activity.用于神经活动高密度记录的全集成硅探针。
Nature. 2017 Nov 8;551(7679):232-236. doi: 10.1038/nature24636.
8
Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings.Neuropixels 2.0:一种小型化高密度探头,用于稳定、长期的大脑记录。
Science. 2021 Apr 16;372(6539). doi: 10.1126/science.abf4588.
9
A very large-scale microelectrode array for cellular-resolution electrophysiology.用于细胞分辨率电生理学的超大规模微电极阵列。
Nat Commun. 2017 Nov 27;8(1):1802. doi: 10.1038/s41467-017-02009-x.
10
Extracellular recordings from patterned neuronal networks using planar microelectrode arrays.使用平面微电极阵列对模式化神经元网络进行细胞外记录。
IEEE Trans Biomed Eng. 2004 Sep;51(9):1640-8. doi: 10.1109/TBME.2004.827252.

引用本文的文献

1
Time-adaptive modulation of evidence evaluation in rat posterior parietal cortex.大鼠顶叶后皮质中证据评估的时间自适应调制。
bioRxiv. 2025 Sep 4:2025.09.04.674303. doi: 10.1101/2025.09.04.674303.
2
Mapping the computational similarity of individual neurons within large-scale ensemble recordings using the SIMNETS analysis framework.使用SIMNETS分析框架绘制大规模整体记录中单个神经元的计算相似性。
Front Neurosci. 2025 Aug 14;19:1634652. doi: 10.3389/fnins.2025.1634652. eCollection 2025.
3
Advances in large-scale electrophysiology with high-density microelectrode arrays.

本文引用的文献

1
Neural Recording and Modulation Technologies.神经记录与调制技术
Nat Rev Mater. 2017 Feb;2(2). doi: 10.1038/natrevmats.2016.93. Epub 2017 Jan 4.
2
State-of-the-art MEMS and microsystem tools for brain research.用于脑研究的先进微机电系统和微系统工具。
Microsyst Nanoeng. 2017 Jan 2;3:16066. doi: 10.1038/micronano.2016.66. eCollection 2017.
3
A spike sorting toolbox for up to thousands of electrodes validated with ground truth recordings in vitro and in vivo.一个用于多达数千个电极的尖峰分选工具箱,已通过体外和体内的真实记录进行验证。
高密度微电极阵列在大规模电生理学方面的进展。
Lab Chip. 2025 Aug 28. doi: 10.1039/d5lc00058k.
4
Model-based inference of synaptic plasticity rules.基于模型的突触可塑性规则推理。
Adv Neural Inf Process Syst. 2024;37:48519-48540.
5
Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes.绕过尖峰分类:基于密度的解码,利用来自密集多电极探针的尖峰定位
Adv Neural Inf Process Syst. 2023;36:77604-77631.
6
Electrophysiology in neuropathic pain: a bibliometric analysis and literature review.神经病理性疼痛中的电生理学:文献计量分析与文献综述
Front Neurosci. 2025 Jun 3;19:1616973. doi: 10.3389/fnins.2025.1616973. eCollection 2025.
7
Signal acquisition of brain-computer interfaces: A medical-engineering crossover perspective review.脑机接口的信号采集:医学与工程交叉视角综述
Fundam Res. 2024 Apr 16;5(1):3-16. doi: 10.1016/j.fmre.2024.04.011. eCollection 2025 Jan.
8
HIPPIE: A Multimodal Deep Learning Model for Electrophysiological Classification of Neurons.HIPPIE:一种用于神经元电生理分类的多模态深度学习模型。
bioRxiv. 2025 Mar 15:2025.03.14.642461. doi: 10.1101/2025.03.14.642461.
9
Integrating multimodal data to understand cortical circuit architecture and function.整合多模态数据以理解皮层回路结构与功能。
Nat Neurosci. 2025 Apr;28(4):717-730. doi: 10.1038/s41593-025-01904-7. Epub 2025 Mar 24.
10
Interpretable deep learning for deconvolutional analysis of neural signals.用于神经信号反卷积分析的可解释深度学习
Neuron. 2025 Apr 16;113(8):1151-1168.e13. doi: 10.1016/j.neuron.2025.02.006. Epub 2025 Mar 12.
Elife. 2018 Mar 20;7:e34518. doi: 10.7554/eLife.34518.
4
Fully integrated silicon probes for high-density recording of neural activity.用于神经活动高密度记录的全集成硅探针。
Nature. 2017 Nov 8;551(7679):232-236. doi: 10.1038/nature24636.
5
Brain technology: Neurons recorded en masse.脑技术:大规模记录神经元。
Nature. 2017 Nov 8;551(7679):172-173. doi: 10.1038/551172a.
6
Time Multiplexed Active Neural Probe with 1356 Parallel Recording Sites.具有1356个并行记录位点的时分复用有源神经探针
Sensors (Basel). 2017 Oct 19;17(10):2388. doi: 10.3390/s17102388.
7
A Fully Automated Approach to Spike Sorting.一种用于尖峰排序的全自动方法。
Neuron. 2017 Sep 13;95(6):1381-1394.e6. doi: 10.1016/j.neuron.2017.08.030.
8
Automated long-term recording and analysis of neural activity in behaving animals.在活动动物中自动进行长期的神经活动记录和分析。
Elife. 2017 Sep 8;6:e27702. doi: 10.7554/eLife.27702.
9
TaiNi: Maximizing research output whilst improving animals' welfare in neurophysiology experiments.台尼:在神经生理学实验中提高动物福利的同时最大限度地提高研究成果。
Sci Rep. 2017 Aug 14;7(1):8086. doi: 10.1038/s41598-017-08078-8.
10
Next-generation probes, particles, and proteins for neural interfacing.用于神经接口的下一代探针、颗粒和蛋白质。
Sci Adv. 2017 Jun 9;3(6):e1601649. doi: 10.1126/sciadv.1601649. eCollection 2017 Jun.