Automated algorithm for measurement of spontaneous adenosine transients in large electrochemical data sets

Ryan Borman
Spontaneous adenosine release events have been discovered in the brain that last only a few seconds. The identification of these adenosine events from fast-scan cyclic voltammetry data has been performed manually and is difficult due to the random nature of adenosine release. In this study, we develop an algorithm that automatically identifies and characterizes adenosine transient features, including event time, concentration, and duration. Automating the data analysis reduces analysis time from 10-18 hours to about...
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