DREDge: robust motion correction for high-density extracellular recordings across species

IF 32.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Nature Methods Pub Date : 2025-03-06 DOI:10.1038/s41592-025-02614-5
Charlie Windolf, Han Yu, Angelique C. Paulk, Domokos Meszéna, William Muñoz, Julien Boussard, Richard Hardstone, Irene Caprara, Mohsen Jamali, Yoav Kfir, Duo Xu, Jason E. Chung, Kristin K. Sellers, Zhiwen Ye, Jordan Shaker, Anna Lebedeva, RT Raghavan, Eric Trautmann, Max Melin, João Couto, Samuel Garcia, Brian Coughlin, Margot Elmaleh, David Christianson, Jeremy D. W. Greenlee, Csaba Horváth, Richárd Fiáth, István Ulbert, Michael A. Long, J. Anthony Movshon, Michael N. Shadlen, Mark M. Churchland, Anne K. Churchland, Nicholas A. Steinmetz, Edward F. Chang, Jeffrey S. Schweitzer, Ziv M. Williams, Sydney S. Cash, Liam Paninski, Erdem Varol
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Abstract

High-density microelectrode arrays have opened new possibilities for systems neuroscience, but brain motion relative to the array poses challenges for downstream analyses. We introduce DREDge (Decentralized Registration of Electrophysiology Data), a robust algorithm for the registration of noisy, nonstationary extracellular electrophysiology recordings. In addition to estimating motion from action potential data, DREDge enables automated, high-temporal-resolution motion tracking in local field potential data. In human intraoperative recordings, DREDge’s local field potential-based tracking reliably recovered evoked potentials and single-unit spike sorting. In recordings of deep probe insertions in nonhuman primates, DREDge tracked motion across centimeters of tissue and several brain regions while mapping single-unit electrophysiological features. DREDge reliably improved motion correction in acute mouse recordings, especially in those made with a recent ultrahigh-density probe. Applying DREDge to recordings from chronic implantations in mice yielded stable motion tracking despite changes in neural activity between experimental sessions. These advances enable automated, scalable registration of electrophysiological data across species, probes and drift types, providing a foundation for downstream analyses of these rich datasets. DREDge is a software tool for motion correction of high-density electrophysiology recordings. It can handle action potential or local field potential data and is demonstrated on a variety of acute or chronic recordings from humans, nonhuman primates and mice.

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DREDge:跨物种高密度细胞外记录的鲁棒运动校正。
高密度微电极阵列为系统神经科学开辟了新的可能性,但相对于阵列的大脑运动为下游分析带来了挑战。我们介绍了DREDge(去中心化电生理数据注册),这是一种用于注册嘈杂、非平稳细胞外电生理记录的鲁棒算法。除了从动作电位数据中估计运动之外,DREDge还可以在局部场电位数据中实现自动化、高时间分辨率的运动跟踪。在人类术中记录中,DREDge基于局部场电位的跟踪可靠地恢复了诱发电位和单单位尖峰分类。在非人类灵长类动物的深度探针插入记录中,DREDge在绘制单个电生理特征的同时,跟踪了跨厘米组织和几个大脑区域的运动。DREDge可靠地改善了急性小鼠记录的运动矫正,特别是在最近使用超高密度探针的小鼠记录中。尽管在实验期间神经活动发生了变化,但DREDge对小鼠慢性植入的记录进行了稳定的运动跟踪。这些进步使得跨物种、探针和漂移类型的电生理数据的自动、可扩展注册成为可能,为这些丰富数据集的下游分析提供了基础。
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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.
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