Accurate Silent Synapse Estimation from Simulator-Corrected Electrophysiological Data Using the SilentMLE Python Package

Michael Lynn; Richard Naud; Jean-Claude Béïque

STAR Protocols (Dec 2020)

Accurate Silent Synapse Estimation from Simulator-Corrected Electrophysiological Data Using the SilentMLE Python Package

Michael Lynn,
Richard Naud,
Jean-Claude Béïque

Affiliations

Michael Lynn: Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Corresponding author
Richard Naud: Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Centre for Neural Dynamics, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Department of Physics, University of Ottawa, STEM Complex, Room 336, 150 Louis Pasteur Pvt., Ottawa, ON K1N 6N5, Canada
Jean-Claude Béïque: Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Canadian Partnership for Stroke Recovery, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Centre for Neural Dynamics, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada

Journal volume & issue: Vol. 1, no. 3
p. 100176

Abstract

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Summary: The proportion of silent (AMPAR-lacking) synapses is thought to be related to the plasticity potential of neural networks. We created a maximum-likelihood estimator of silent synapse fraction based on simulations of the underlying experimental methodology. Here, we provide a set of guidelines for running a Python package on compatible experimental synaptic data. Compared with traditional failure-rate approaches, this synthetic likelihood estimator improves the validity and accuracy of the estimates of the silent synapse fraction.For complete details on the use and execution of this protocol, please refer to Lynn et al. (2020).

Published in STAR Protocols

ISSN: 2666-1667 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Science: Science (General)
Website: https://star-protocols.cell.com/

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