MIN1PIPE: A Miniscope 1-Photon-Based Calcium Imaging Signal Extraction Pipeline
| Autor: | Fan Wang, Flavio Fröhlich, Jinghao Lu, Zhe Charles Zhou, Chunyuan Li, Jonnathan Singh-Alvarado, Richard Mooney |
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| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Photon Computer science Pipeline (computing) Imaging data General Biochemistry Genetics and Molecular Biology Field (computer science) Article law.invention 03 medical and health sciences Mice 0302 clinical medicine Calcium imaging Imaging Three-Dimensional In vivo law Animals 030304 developmental biology 0303 health sciences Photons business.industry Reproducibility of Results Pattern recognition Signal Processing Computer-Assisted Fluorescence Lens (optics) 030104 developmental biology Databases as Topic Signal extraction Calcium Artificial intelligence Finches Vocalization Animal business 030217 neurology & neurosurgery Software |
| Zdroj: | Cell reports. 23(12) |
| ISSN: | 2211-1247 |
| Popis: | SUMMARYIn vivo calcium imaging using 1-photon based miniscope and microendoscopic lens enables studies of neural activities in freely behaving animals. However, the high and fluctuating background, the inevitable movements and distortions of imaging field, and the extensive spatial overlaps of fluorescent signals emitted from imaged neurons inherent in this 1-photon imaging method present major challenges for extracting neuronal signals reliably and automatically from the raw imaging data. Here we develop a unifying algorithm called MINiscope 1-photon imaging PIPEline (MIN1PIPE) that contains several standalone modules and can handle a wide range of imaging conditions and qualities with minimal parameter tuning, and automatically and accurately isolate spatially localized neural signals. We quantitatively compare MIN1PIPE with other existing partial methods using both synthetic and real datasets obtained from different animal models, and show that MIN1PIPE has a superior performance both in terms of efficiency and precision in analyzing noisy miniscope calcium imaging data. |
| Databáze: | OpenAIRE |
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