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Nat Commun. 2016 Jul 19;7:12190. doi: 10.1038/ncomms12190.

Accurate spike estimation from noisy calcium signals for ultrafast three-dimensional imaging of large neuronal populations in vivo.

Author information

1
Institut de Neurosciences de la Timone (INT), CNRS and Aix-Marseille Université, UMR 7289, 27 boulevard Jean Moulin, Marseille 13005, France.
2
CNRS FRE-3693, Unité de Neurosciences Information et Complexité, 1 Avenue de la Terrasse, Gif-sur-Yvette 91198, France.
3
Aix Marseille Université, Institut de Neuroscience des Systèmes, Marseille 13005, France.
4
Inserm, UMR_S 1106, 27 Bd Jean Moulin, Marseille Cedex 5 13385, France.
5
Two-Photon Imaging Center, Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest 1083, Hungary.
6
Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest 1083, Hungary.
7
Neurobiology Department, Weizmann Institute of Science, Rehovot 76100, Israel.

Abstract

Extracting neuronal spiking activity from large-scale two-photon recordings remains challenging, especially in mammals in vivo, where large noises often contaminate the signals. We propose a method, MLspike, which returns the most likely spike train underlying the measured calcium fluorescence. It relies on a physiological model including baseline fluctuations and distinct nonlinearities for synthetic and genetically encoded indicators. Model parameters can be either provided by the user or estimated from the data themselves. MLspike is computationally efficient thanks to its original discretization of probability representations; moreover, it can also return spike probabilities or samples. Benchmarked on extensive simulations and real data from seven different preparations, it outperformed state-of-the-art algorithms. Combined with the finding obtained from systematic data investigation (noise level, spiking rate and so on) that photonic noise is not necessarily the main limiting factor, our method allows spike extraction from large-scale recordings, as demonstrated on acousto-optical three-dimensional recordings of over 1,000 neurons in vivo.

PMID:
27432255
PMCID:
PMC4960309
DOI:
10.1038/ncomms12190
[Indexed for MEDLINE]
Free PMC Article

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