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Waveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials

Potas, Jason; Gonvales de Castro, Newton; Maddess, Ted; de Souza, Marcio Nogueira

Description

Experimental electrophysiological assessment of evoked responses from regenerating nerves is challenging due to the typical complex response of events dispersed over various latencies and poor signal-to-noise ratio. Our objective was to automate the detection of compound action potential events and derive their latencies and magnitudes using a simple cross-correlation template comparison approach. For this, we developed an algorithm called Waveform Similarity Analysis. To test the algorithm,...[Show more]

dc.contributor.authorPotas, Jason
dc.contributor.authorGonvales de Castro, Newton
dc.contributor.authorMaddess, Ted
dc.contributor.authorde Souza, Marcio Nogueira
dc.date.accessioned2015-12-10T21:53:25Z
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/1885/38512
dc.description.abstractExperimental electrophysiological assessment of evoked responses from regenerating nerves is challenging due to the typical complex response of events dispersed over various latencies and poor signal-to-noise ratio. Our objective was to automate the detection of compound action potential events and derive their latencies and magnitudes using a simple cross-correlation template comparison approach. For this, we developed an algorithm called Waveform Similarity Analysis. To test the algorithm, challenging signals were generated in vivo by stimulating sural and sciatic nerves, whilst recording evoked potentials at the sciatic nerve and tibialis anterior muscle, respectively, in animals recovering from sciatic nerve transection. Our template for the algorithm was generated based on responses evoked from the intact side. We also simulated noisy signals and examined the output of the Waveform Similarity Analysis algorithm with imperfect templates. Signals were detected and quantified using Waveform Similarity Analysis, which was compared to event detection, latency and magnitude measurements of the same signals performed by a trained observer, a process we called Trained Eye Analysis. The Waveform Similarity Analysis algorithm could successfully detect and quantify simple or complex responses from nerve and muscle compound action potentials of intact or regenerated nerves. Incorrectly specifying the template outperformed Trained Eye Analysis for predicting signal amplitude, but produced consistent latency errors for the simulated signals examined. Compared to the trained eye, Waveform Similarity Analysis is automatic, objective, does not rely on the observer to identify and/or measure peaks, and can detect small clustered events even when signal-tonoise ratio is poor. Waveform Similarity Analysis provides a simple, reliable and convenient approach to quantify latencies and magnitudes of complex waveforms and therefore serves as a useful tool for studying evoked compound action potentials in neural regeneration studies.
dc.publisherPublic Library of Science
dc.rightsAuthor/s retain copyright
dc.sourcePLOS ONE (Public Library of Science)
dc.titleWaveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume10
dc.date.issued2015
local.identifier.absfor111301 - Ophthalmology
local.identifier.absfor110900 - NEUROSCIENCES
local.identifier.ariespublicationu4693331xPUB162
local.type.statusPublished Version
local.contributor.affiliationPotas, Jason, College of Medicine, Biology and Environment, ANU
local.contributor.affiliationGonvales de Castro, Newton, Universidade Federal do Rio de Janeiro
local.contributor.affiliationMaddess, Ted, College of Medicine, Biology and Environment, ANU
local.contributor.affiliationde Souza, Marcio Nogueira, Federal University of Rio de Janeiro
local.bibliographicCitation.issue9
local.bibliographicCitation.startpage1
local.bibliographicCitation.lastpage18
local.identifier.doi10.1371/journal.pone.0136992
dc.date.updated2015-12-09T07:17:56Z
local.identifier.scopusID2-s2.0-84943339570
dcterms.accessRightsOpen Access
CollectionsANU Research Publications

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