A Modular Implementation to Handle and Benchmark Drift Correction for High-Density Extracellular Recordings.
| Autor: | Garcia S; Centre de Recherche en Neuroscience de Lyon, CNRS, Lyon 69675, France., Windolf C; Columbia University, New York, New York 10027., Boussard J; Columbia University, New York, New York 10027., Dichter B; CatalystNeuro, Benicia, California 94510., Buccino AP; CatalystNeuro, Benicia, California 94510.; Allen Institute for Neural Dynamics, Seattle, Washington 98109., Yger P; Institut de la Vision, Sorbonne Université, INSERM, Paris 75012, France.; Lille Neurosciences & Cognition (lilNCog)-U1172 (INSERM, Lille), Univ Lille, Centre Hospitalier Universitaire de Lille, Lille 59800, France. |
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| Jazyk: | angličtina |
| Zdroj: | ENeuro [eNeuro] 2024 Feb 26; Vol. 11 (2). Date of Electronic Publication: 2024 Feb 26 (Print Publication: 2024). |
| DOI: | 10.1523/ENEURO.0229-23.2023 |
| Abstrakt: | High-density neural devices are now offering the possibility to record from neuronal populations in vivo at unprecedented scale. However, the mechanical drifts often observed in these recordings are currently a major issue for "spike sorting," an essential analysis step to identify the activity of single neurons from extracellular signals. Although several strategies have been proposed to compensate for such drifts, the lack of proper benchmarks makes it hard to assess the quality and effectiveness of motion correction. In this paper, we present a benchmark study to precisely and quantitatively evaluate the performance of several state-of-the-art motion correction algorithms introduced in the literature. Using simulated recordings with induced drifts, we dissect the origins of the errors performed while applying a motion correction algorithm as a preprocessing step in the spike sorting pipeline. We show how important it is to properly estimate the positions of the neurons from extracellular traces in order to correctly estimate the probe motion, compare several interpolation procedures, and highlight what are the current limits for motion correction approaches. (Copyright © 2024 Garcia et al.) |
| Databáze: | MEDLINE |
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