Abstract: Patch-clamp is used to study all sorts of ionic channels and their regulations through measuring pA current of cell ionic channel, but the C-Fast transient currents caused by measuring objects and measuring instruments themselves will change the properties of action potentials. Aiming at the shortage of traditional C-Fast compensation method, a compensation algorithm for the C-Fast based on BP neural networks is proposed. Establish circuit model of patch-clamp through MATLAB SIMULINK, and the circuit is simulated in accordance with compensation parameters from the traditional compensation algorithm and the compensation algorithm based on BP neural networks. The experiment result shows that transient currents decreases from 10nA to 2.4pA based on the BP neural networks compensation algorithm, and the BP neural networks compensation algorithm can improve the C-Fast compensation precision.
Keywords: Patch-clamp, C-Fast，action potential，BP neural networks algorithm, capacitance compensation.
Title: BP Neural Network in Patch-Clamp Amplifier C-Fast Compensation
Author: ZHENG Yu, HONG Hui, LI Jing, QIU Qian, CHEN Zhitang, TIAN Lei, WANG Jin-Hai
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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