Deconvolution Analysis of Neuroendocrine Data: Waveform-Specific and Waveform-Independent Methods and Applications

Johannes D Veldhuis, John Moorman, Michael L. Johnson

Research output: Contribution to journalArticle

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Abstract

We present two of our waveform-specific and waveform-independent deconvolution methodologies and illustrate their application in three domains: (i) validating discrete hormone peak-detection methods, such as Cluster analysis; (ii) estimating the influence of one or more high-affinity plasma-binding proteins on the time course of free, bound, and total hormone, when a neurohormone is secreted into the bloodstream in the form of a nonlinear pulse; and (iii) evaluating the coincident behavior of multiple neuroendocrine pulse trains, given nonuniformity of peak frequency over time, unequal peak amplitudes and durations, and varying baselines of hormone secretion. In short, the development, refinement, and extension of deconvolution technologies in the arena of neuroscience investigation now offer a substantial and informative foundation for reliable statistical quantitation of neuroendocrine data.

Original languageEnglish (US)
Pages (from-to)279-325
Number of pages47
JournalMethods in Neurosciences
Volume20
Issue numberC
DOIs
StatePublished - Jan 1 1994
Externally publishedYes

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ASJC Scopus subject areas

  • Neuroscience(all)

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