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

Potas JR, de Castro NG, Maddess T, de Souza MN - PLoS ONE (2015)

Bottom Line: 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.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-to-noise 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Neuroscience, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia; Medical School, Australian National University, Canberra, ACT, Australia; Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil.

ABSTRACT
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, 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-to-noise 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.

No MeSH data available.


Related in: MedlinePlus

Magnitude profiles derived from WSA and TEA.N10avR total magnitudes (TMags) were calculated by quantifying and summing magnitudes of all events for each response of intact (A1) and regenerating (A2) sural nerves using WSA (black) and TEA (grey). TMags derived from WSA were amplitude-corrected (dashed) by multiplying the TMagWSA by a constant (indicated) derived from the ratio of [mean TMagTEA]/[mean TMagWSA] (see Materials and Methods) evoked from the strongest stimulus pulse (1.4 mA). Magnitude profiles were also derived from M5avR TMags for intact (B1) and regenerating (B2) nerves. Similarly, TMagWSA of M5avRs were amplitude-corrected (dashed) by multiplying by a constant (indicated) based on the ratio of mean total magnitudes with the greatest inter-pulse interval (10 ms).
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pone.0136992.g007: Magnitude profiles derived from WSA and TEA.N10avR total magnitudes (TMags) were calculated by quantifying and summing magnitudes of all events for each response of intact (A1) and regenerating (A2) sural nerves using WSA (black) and TEA (grey). TMags derived from WSA were amplitude-corrected (dashed) by multiplying the TMagWSA by a constant (indicated) derived from the ratio of [mean TMagTEA]/[mean TMagWSA] (see Materials and Methods) evoked from the strongest stimulus pulse (1.4 mA). Magnitude profiles were also derived from M5avR TMags for intact (B1) and regenerating (B2) nerves. Similarly, TMagWSA of M5avRs were amplitude-corrected (dashed) by multiplying by a constant (indicated) based on the ratio of mean total magnitudes with the greatest inter-pulse interval (10 ms).

Mentions: Magnitude profiles were generated (as described for response latency quantification above) to enable the comparison of response magnitude quantification by WSA and TEA. TMagWSA demonstrated a consistent and proportional quantification when compared with TMagTEA for both intact (Fig 7A1) and regenerating nerves (Fig 7A2). There was no significant difference between TMagWSA and TMagTEA at any of the stimulus intensities after TMagWSA was amplitude-corrected to TMagTEA, indicating that quantification by the WSA method was in agreement with that derived by TEA for both intact and regenerating nerves (Fig 7A1 and 7A2).


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

Potas JR, de Castro NG, Maddess T, de Souza MN - PLoS ONE (2015)

Magnitude profiles derived from WSA and TEA.N10avR total magnitudes (TMags) were calculated by quantifying and summing magnitudes of all events for each response of intact (A1) and regenerating (A2) sural nerves using WSA (black) and TEA (grey). TMags derived from WSA were amplitude-corrected (dashed) by multiplying the TMagWSA by a constant (indicated) derived from the ratio of [mean TMagTEA]/[mean TMagWSA] (see Materials and Methods) evoked from the strongest stimulus pulse (1.4 mA). Magnitude profiles were also derived from M5avR TMags for intact (B1) and regenerating (B2) nerves. Similarly, TMagWSA of M5avRs were amplitude-corrected (dashed) by multiplying by a constant (indicated) based on the ratio of mean total magnitudes with the greatest inter-pulse interval (10 ms).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4556619&req=5

pone.0136992.g007: Magnitude profiles derived from WSA and TEA.N10avR total magnitudes (TMags) were calculated by quantifying and summing magnitudes of all events for each response of intact (A1) and regenerating (A2) sural nerves using WSA (black) and TEA (grey). TMags derived from WSA were amplitude-corrected (dashed) by multiplying the TMagWSA by a constant (indicated) derived from the ratio of [mean TMagTEA]/[mean TMagWSA] (see Materials and Methods) evoked from the strongest stimulus pulse (1.4 mA). Magnitude profiles were also derived from M5avR TMags for intact (B1) and regenerating (B2) nerves. Similarly, TMagWSA of M5avRs were amplitude-corrected (dashed) by multiplying by a constant (indicated) based on the ratio of mean total magnitudes with the greatest inter-pulse interval (10 ms).
Mentions: Magnitude profiles were generated (as described for response latency quantification above) to enable the comparison of response magnitude quantification by WSA and TEA. TMagWSA demonstrated a consistent and proportional quantification when compared with TMagTEA for both intact (Fig 7A1) and regenerating nerves (Fig 7A2). There was no significant difference between TMagWSA and TMagTEA at any of the stimulus intensities after TMagWSA was amplitude-corrected to TMagTEA, indicating that quantification by the WSA method was in agreement with that derived by TEA for both intact and regenerating nerves (Fig 7A1 and 7A2).

Bottom Line: 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.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-to-noise 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Neuroscience, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia; Medical School, Australian National University, Canberra, ACT, Australia; Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil.

ABSTRACT
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, 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-to-noise 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.

No MeSH data available.


Related in: MedlinePlus