ArticleJournal of neuroscience methods2019
Estimating amperometric spike parameters resulting from quantal exocytosis using curve fitting seeded by a matched-filter algorithm.
Article in Journal of neuroscience methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
backgroundQuantal exocytosis of oxidizable neurotransmitters can be detected as spikes of amperometric current using electrochemical microelectrodes. Measurements of spike parameters indicate the maximal transmitter flux, flux duration, and amount of transmitter released from individual vesicles. Automated analysis algorithms need to reject spikes that overlap in time. In addition, many spikes are preceded by small amplitude "foot" signals, attributed to slow release of transmitter through a fusion pore. Accurate pre-spike baseline determination is essential for estimating fusion-pore duration and the amount of transmitter released through the fusion pore. NEW
methodWe developed an estimation approach that is based on fitting a multi-exponential function to the data. Our previously described matched-filter algorithm is used to identify the sections of data to fit and provides seed values to facilitate convergence of the iterative fit. The new estimation algorithm includes overlap rejection, a two-step fitting procedure and a novel baseline estimation procedure.
resultsHistograms of spike parameters demonstrate excellent agreement of the new approach with manually computed parameters. COMPARISON WITH EXISTING
methodsParameter estimates generated using the new approach are closer to blind manual estimates than commonly used existing methods. The improved performance is due to better detection of valid spikes and rejection of overlapping spikes. Moreover, since the complete time course of the spike is fit to a function, more complete information about the spike time course is captured.
conclusionsThe matched-filter seeded algorithm reliably rejects overlaps and estimates spike and foot signal parameters in a fully automated manner.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.