A deep learning framework for synaptic event detection
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Updated
Jul 24, 2024 - Jupyter Notebook
A deep learning framework for synaptic event detection
calculates synaptic parameters by fitting synaptic currents from train stimulation to NpRf model. Estimates N (RRP size), p (initial release probability), R (replenishment), and f (synaptic facilitation).
This project explores the effect of insulin on neuronal communication and excitability in the rat dorsomedial hypothalamus.
Performs offline series resistance correction/compensation of recorded currents based on "Traynelis SF (1998) Software-based correction of single compartment series resistance errors. J Neurosci Methods 86:25–34."
Python2 code accompanying the paper https://doi.org/10.1101/748400
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