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A matched-filter algorithm to detect amperometric spikes resulting from quantal secretion.

Supriya Balaji Ramachandran1, Kevin D Gillis2

  • 1Department of Bioengineering, 254 Agricultural Engineering, Columbia, MO, USA; Dalton Cardiovascular Research Center, University of Missouri, Columbia, MO, USA.

Journal of Neuroscience Methods
|October 25, 2017
PubMed
Summary
This summary is machine-generated.

A new Matched Filter (MF) algorithm accurately detects over 95% of exocytosis spikes from electrochemical microelectrode data with a low false-positive rate. This automated method improves the quantification of exocytosis events.

Keywords:
Carbon-fiber amperometryQuantal exocytosisSignal processingSpike detection

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Area of Science:

  • Electrochemistry
  • Cell Biology
  • Data Analysis

Background:

  • Electrochemical microelectrodes detect exocytosis by sensing oxidized neurotransmitters released from single vesicles.
  • Automated spike detection is crucial for quantifying exocytosis rates.

Purpose of the Study:

  • To develop and validate an automated algorithm for detecting and quantifying exocytosis spikes.
  • To improve the accuracy and efficiency of analyzing electrochemical data from single-cell exocytosis.

Main Methods:

  • Developed a Matched Filter (MF) detection algorithm using prototype spike templates and least-squares fitting.
  • Implemented a criterion score based on amplitude-to-standard error ratio to identify spikes.
  • Used a dual-threshold approach to reduce false positives and extended the method for double-exponential decay spikes.

Main Results:

  • Receiver Operating Characteristic (ROC) plots show the MF algorithm detects over 95% of manually identified spikes.
  • The algorithm achieves a false-positive rate of approximately 2%.

Conclusions:

  • The Matched Filter (MF) approach provides a robust and accurate method for detecting exocytosis spikes.
  • This algorithm facilitates reliable parameter identification for individual spikes.