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

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, R. T. Raghavan, Eric Trautmann, Max Melin, João CoutoSamuel 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

Résultat de rechercheexamen par les pairs

Résumé

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.

Langue d'origineEnglish
Numéro d'article2344
JournalNature Methods
DOI
Statut de publicationAccepted/In press - 2025

ASJC Scopus Subject Areas

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology

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Windolf, C., Yu, H., Paulk, A. C., Meszéna, D., Muñoz, W., Boussard, J., Hardstone, R., Caprara, I., Jamali, M., Kfir, Y., Xu, D., Chung, J. E., Sellers, K. K., Ye, Z., Shaker, J., Lebedeva, A., Raghavan, R. T., Trautmann, E., Melin, M., ... Varol, E. (Accepter/ En production). DREDge: robust motion correction for high-density extracellular recordings across species. Nature Methods, Article 2344. https://doi.org/10.1038/s41592-025-02614-5