FISSA: A neuropil decontamination toolbox for calcium imaging signals

Abstract In vivo calcium imaging has become a method of choice to image neuronal population activity throughout the nervous system. These experiments generate large sequences of images. Their analysis is computationally intensive and typically involves motion correction, image segmentation into regi...

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Autores principales:	Sander W. Keemink, Scott C. Lowe, Janelle M. P. Pakan, Evelyn Dylda, Mark C. W. van Rossum, Nathalie L. Rochefort
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d00c1fe9dd304ffba9288039c690613b
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spelling	oai:doaj.org-article:d00c1fe9dd304ffba9288039c690613b2021-12-02T15:08:57ZFISSA: A neuropil decontamination toolbox for calcium imaging signals10.1038/s41598-018-21640-22045-2322https://doaj.org/article/d00c1fe9dd304ffba9288039c690613b2018-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-21640-2https://doaj.org/toc/2045-2322Abstract In vivo calcium imaging has become a method of choice to image neuronal population activity throughout the nervous system. These experiments generate large sequences of images. Their analysis is computationally intensive and typically involves motion correction, image segmentation into regions of interest (ROIs), and extraction of fluorescence traces from each ROI. Out of focus fluorescence from surrounding neuropil and other cells can strongly contaminate the signal assigned to a given ROI. In this study, we introduce the FISSA toolbox (Fast Image Signal Separation Analysis) for neuropil decontamination. Given pre-defined ROIs, the FISSA toolbox automatically extracts the surrounding local neuropil and performs blind-source separation with non-negative matrix factorization. Using both simulated and in vivo data, we show that this toolbox performs similarly or better than existing published methods. FISSA requires only little RAM, and allows for fast processing of large datasets even on a standard laptop. The FISSA toolbox is available in Python, with an option for MATLAB format outputs, and can easily be integrated into existing workflows. It is available from Github and the standard Python repositories.Sander W. KeeminkScott C. LoweJanelle M. P. PakanEvelyn DyldaMark C. W. van RossumNathalie L. RochefortNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-12 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Sander W. Keemink Scott C. Lowe Janelle M. P. Pakan Evelyn Dylda Mark C. W. van Rossum Nathalie L. Rochefort FISSA: A neuropil decontamination toolbox for calcium imaging signals
description	Abstract In vivo calcium imaging has become a method of choice to image neuronal population activity throughout the nervous system. These experiments generate large sequences of images. Their analysis is computationally intensive and typically involves motion correction, image segmentation into regions of interest (ROIs), and extraction of fluorescence traces from each ROI. Out of focus fluorescence from surrounding neuropil and other cells can strongly contaminate the signal assigned to a given ROI. In this study, we introduce the FISSA toolbox (Fast Image Signal Separation Analysis) for neuropil decontamination. Given pre-defined ROIs, the FISSA toolbox automatically extracts the surrounding local neuropil and performs blind-source separation with non-negative matrix factorization. Using both simulated and in vivo data, we show that this toolbox performs similarly or better than existing published methods. FISSA requires only little RAM, and allows for fast processing of large datasets even on a standard laptop. The FISSA toolbox is available in Python, with an option for MATLAB format outputs, and can easily be integrated into existing workflows. It is available from Github and the standard Python repositories.
format	article
author	Sander W. Keemink Scott C. Lowe Janelle M. P. Pakan Evelyn Dylda Mark C. W. van Rossum Nathalie L. Rochefort
author_facet	Sander W. Keemink Scott C. Lowe Janelle M. P. Pakan Evelyn Dylda Mark C. W. van Rossum Nathalie L. Rochefort
author_sort	Sander W. Keemink
title	FISSA: A neuropil decontamination toolbox for calcium imaging signals
title_short	FISSA: A neuropil decontamination toolbox for calcium imaging signals
title_full	FISSA: A neuropil decontamination toolbox for calcium imaging signals
title_fullStr	FISSA: A neuropil decontamination toolbox for calcium imaging signals
title_full_unstemmed	FISSA: A neuropil decontamination toolbox for calcium imaging signals
title_sort	fissa: a neuropil decontamination toolbox for calcium imaging signals
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/d00c1fe9dd304ffba9288039c690613b
work_keys_str_mv	AT sanderwkeemink fissaaneuropildecontaminationtoolboxforcalciumimagingsignals AT scottclowe fissaaneuropildecontaminationtoolboxforcalciumimagingsignals AT janellemppakan fissaaneuropildecontaminationtoolboxforcalciumimagingsignals AT evelyndylda fissaaneuropildecontaminationtoolboxforcalciumimagingsignals AT markcwvanrossum fissaaneuropildecontaminationtoolboxforcalciumimagingsignals AT nathalielrochefort fissaaneuropildecontaminationtoolboxforcalciumimagingsignals
_version_	1718387967444123648

FISSA: A neuropil decontamination toolbox for calcium imaging signals

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