SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters
Spike sorting is a crucial step in electrophysiological studies of neuronal activity. While many spike sorting packages are available, there is little consensus about which are most accurate under different experimental conditions. SpikeForest is an open-source and reproducible software suite that b...
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doaj-8745ab8e7d884d6788f1a9ee4cea37232021-05-05T21:07:19ZengeLife Sciences Publications LtdeLife2050-084X2020-05-01910.7554/eLife.55167SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sortersJeremy Magland0https://orcid.org/0000-0002-5286-4375James J Jun1Elizabeth Lovero2https://orcid.org/0000-0002-2642-603XAlexander J Morley3https://orcid.org/0000-0002-4997-4063Cole Lincoln Hurwitz4https://orcid.org/0000-0002-2023-1653Alessio Paolo Buccino5Samuel Garcia6Alex H Barnett7Center for Computational Mathematics, Flatiron Institute, New York, United StatesCenter for Computational Mathematics, Flatiron Institute, New York, United StatesScientific Computing Core, Flatiron Institute, New York, United StatesMedical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, United KingdomInstitute for Adaptive and Neural Computation Informatics, University of Edinburgh, Edinburgh, United KingdomCentre for IntegrativeNeuroplasticity (CINPLA), University of Oslo, Oslo, NorwayCentre de Recherche en Neuroscience de Lyon, Université de Lyon, Lyon, FranceCenter for Computational Mathematics, Flatiron Institute, New York, United StatesSpike sorting is a crucial step in electrophysiological studies of neuronal activity. While many spike sorting packages are available, there is little consensus about which are most accurate under different experimental conditions. SpikeForest is an open-source and reproducible software suite that benchmarks the performance of automated spike sorting algorithms across an extensive, curated database of ground-truth electrophysiological recordings, displaying results interactively on a continuously-updating website. With contributions from eleven laboratories, our database currently comprises 650 recordings (1.3 TB total size) with around 35,000 ground-truth units. These data include paired intracellular/extracellular recordings and state-of-the-art simulated recordings. Ten of the most popular spike sorting codes are wrapped in a Python package and evaluated on a compute cluster using an automated pipeline. SpikeForest documents community progress in automated spike sorting, and guides neuroscientists to an optimal choice of sorter and parameters for a wide range of probes and brain regions.https://elifesciences.org/articles/55167spike sortingelectrophysiologyreproducibilityvalidationground truth |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jeremy Magland James J Jun Elizabeth Lovero Alexander J Morley Cole Lincoln Hurwitz Alessio Paolo Buccino Samuel Garcia Alex H Barnett |
spellingShingle |
Jeremy Magland James J Jun Elizabeth Lovero Alexander J Morley Cole Lincoln Hurwitz Alessio Paolo Buccino Samuel Garcia Alex H Barnett SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters eLife spike sorting electrophysiology reproducibility validation ground truth |
author_facet |
Jeremy Magland James J Jun Elizabeth Lovero Alexander J Morley Cole Lincoln Hurwitz Alessio Paolo Buccino Samuel Garcia Alex H Barnett |
author_sort |
Jeremy Magland |
title |
SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters |
title_short |
SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters |
title_full |
SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters |
title_fullStr |
SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters |
title_full_unstemmed |
SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters |
title_sort |
spikeforest, reproducible web-facing ground-truth validation of automated neural spike sorters |
publisher |
eLife Sciences Publications Ltd |
series |
eLife |
issn |
2050-084X |
publishDate |
2020-05-01 |
description |
Spike sorting is a crucial step in electrophysiological studies of neuronal activity. While many spike sorting packages are available, there is little consensus about which are most accurate under different experimental conditions. SpikeForest is an open-source and reproducible software suite that benchmarks the performance of automated spike sorting algorithms across an extensive, curated database of ground-truth electrophysiological recordings, displaying results interactively on a continuously-updating website. With contributions from eleven laboratories, our database currently comprises 650 recordings (1.3 TB total size) with around 35,000 ground-truth units. These data include paired intracellular/extracellular recordings and state-of-the-art simulated recordings. Ten of the most popular spike sorting codes are wrapped in a Python package and evaluated on a compute cluster using an automated pipeline. SpikeForest documents community progress in automated spike sorting, and guides neuroscientists to an optimal choice of sorter and parameters for a wide range of probes and brain regions. |
topic |
spike sorting electrophysiology reproducibility validation ground truth |
url |
https://elifesciences.org/articles/55167 |
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