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

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...

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Bibliographic Details
Published in:	Nature communications Vol. 7; no. 1; p. 12190
Main Authors:	Deneux, Thomas, Kaszas, Attila, Szalay, Gergely, Katona, Gergely, Lakner, Tamás, Grinvald, Amiram, Rózsa, Balázs, Vanzetta, Ivo
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 19-07-2016 Nature Publishing Group Nature Portfolio
Subjects:	14/69 631/1647/48 631/378/2571/1696 631/80/86/1999 692/700/1421/2025 Algorithms Cognitive science Humanities and Social Sciences Life Sciences multidisciplinary Neurons and Cognition Neuroscience Neurosciences Noise Physiology Science Science (multidisciplinary) Simulation Three dimensional imaging Hungary France
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Summary:	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 . Two-photon laser scanning microscopy allows functional calcium imaging of large neuronal populations in vivo , but the recorded signals typically suffer from low signal to noise. Here the authors develop an algorithm, MLspike, which estimates action potentials from noisy calcium signals, and benchmark it against existing methods.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	2041-1723 2041-1723
DOI:	10.1038/ncomms12190