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Integral methods for automatic quantification of fast-scan-cyclic-voltammetry detected neurotransmitters.

Leonardo X EspínAnders J AspJames K TrevathanKip A LudwigJ Luis Lujan
Published in: PloS one (2021)
Modern techniques for estimating basal levels of electroactive neurotransmitters rely on the measurement of oxidative charges. This requires time integration of oxidation currents at certain intervals. Unfortunately, the selection of integration intervals relies on ad-hoc visual identification of peaks on the oxidation currents, which introduces sources of error and precludes the development of automated procedures necessary for analysis and quantification of neurotransmitter levels in large data sets. In an effort to improve charge quantification techniques, here we present novel methods for automatic selection of integration boundaries. Our results show that these methods allow quantification of oxidation reactions both in vitro and in vivo and of multiple analytes in vitro.
Keyphrases
  • deep learning
  • machine learning
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  • big data
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  • data analysis