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A synthetic likelihood solution to the silent synapse estimation problem

View ORCID ProfileMichael Lynn, Kevin F.H. Lee, Cary Soares, View ORCID ProfileRichard Naud, View ORCID ProfileJean-Claude Béïque
doi: https://doi.org/10.1101/781898
Michael Lynn
aDepartment of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Canada K1H 8M5
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Kevin F.H. Lee
aDepartment of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Canada K1H 8M5
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Cary Soares
aDepartment of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Canada K1H 8M5
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Richard Naud
aDepartment of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Canada K1H 8M5
eDepartment of Physics, STEM Complex, room 336, 150 Louis Pasteur Pvt., University of Ottawa, K1N 6N5, Ottawa, Canada
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Jean-Claude Béïque
aDepartment of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Canada K1H 8M5
bCanadian Partnership for Stroke Recovery, University of Ottawa, Ottawa, Canada K1H 8M5
cCentre for Neural Dynamics, University of Ottawa, Ottawa, Canada K1H 8M5
dBrain and Mind Research Institute, University of Ottawa, Ottawa, Canada K1H 8M5
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  • For correspondence: jbeique@uottawa.ca
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  • https://github.com/micllynn/SilentMLE

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Posted November 20, 2019.
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A synthetic likelihood solution to the silent synapse estimation problem
Michael Lynn, Kevin F.H. Lee, Cary Soares, Richard Naud, Jean-Claude Béïque
bioRxiv 781898; doi: https://doi.org/10.1101/781898
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A synthetic likelihood solution to the silent synapse estimation problem
Michael Lynn, Kevin F.H. Lee, Cary Soares, Richard Naud, Jean-Claude Béïque
bioRxiv 781898; doi: https://doi.org/10.1101/781898

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