Demonstration of two distributions of vesicle radius in the dopamine neuron of Planorbis corneus from electrochemical data

Brian B. Anderson, Guangyao Chen, David A. Gutman, Andrew G. Ewing

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


An electrochemical model to calculate the relative size and neurotransmitter concentration of individual nerve cell vesicles is presented to examine potentially different types of vesicles in Planorbis corneus. Amperometric current transients resulting from individual exocytosis events detected from single cells contain the information necessary to quantify vesicular neurotransmitter amount and to estimate other important cellular properties such as vesicular neurotransmitter concentration and vesicle radius. Use of a simplifying assumption that the cross-sectional area of the contents of each release event is the apparent electroactive area of the electrode and that the shape of the decreasing phase of each current transient follows Cottrell-like behavior, the Cottrell equation and Faraday's law can be combined to yield expressions for relative vesicle radius and neurotransmitter concentration. This analysis has been applied to data obtained from the cell body of the giant dopamine neuron of the pond snail P. corneus. The histogram of vesicular dopamine concentration reveals a single wide distribution and the histogram of vesicle radius reveals a bimodal radius distribution. These data strongly suggest two distinct classes of vesicle radius in the P. corneus neuron lead to the bimodal distribution of amount released reported earlier. Copyright (C) 1999 Elsevier Science B.V.

Original languageEnglish (US)
Pages (from-to)153-161
Number of pages9
JournalJournal of Neuroscience Methods
Issue number2
StatePublished - May 1 1999

All Science Journal Classification (ASJC) codes

  • General Neuroscience


Dive into the research topics of 'Demonstration of two distributions of vesicle radius in the dopamine neuron of Planorbis corneus from electrochemical data'. Together they form a unique fingerprint.

Cite this