TY - JOUR
T1 - Automated analyses for single-fiber electrophysiological recordings using a newly developed Microsoft Excel application and graphical user interface
AU - Grayson, Max
AU - Nagle-Pinkham, Daniel
AU - Gokhman, Dmitry
AU - Ruparel, Shivani
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/10
Y1 - 2021/10
N2 - Background: Electrophysiological recordings of isolated sensory afferents are commonly used in the field of pain research to investigate peripheral mechanisms of nociception in various pain models. The method involves skillful and tedious recordings of teased fibers from nerve preparations as well as time-consuming post-recording analyses. To increase efficiency and productivity of data analyses of recorded action potentials, we developed and validated a novel, easy-to-use Microsoft Excel-based application using Visual Basic Programming. New method: A code for the novel program, shigraspike1.0, was written to create a module to include customizable subroutines for analyses for electrical and mechanical responses. Using previously recorded action potentials with tongue-lingual nerve preparations, the program was validated for appropriate execution, ease-of-use, accuracy of the output data and time taken for analyses. Results: We observed appropriate execution of shigraspike1.0 on Windows and iOS desktop platforms that included computation of response latency of the spike of interest using electrical stimulus as well as estimation of the number of impulses at each force with a step-and-hold mechanical ramp of 10–200mN. Output data obtained by shigrapsike1.0 for both stimulus types were accurate and statistically insignificant from manual analyses. Comparison with existing method: The novel application shigraspike1.0, allows for rapid analyses for single-fiber recordings and takes less than half the time to analyze electrical and mechanical responses compared to manual analyses. Conclusions: The newly developed shigraspike1.0 application can be a very productive tool to be routinely used for efficient analyses of single-fiber electrophysiology in pain research.
AB - Background: Electrophysiological recordings of isolated sensory afferents are commonly used in the field of pain research to investigate peripheral mechanisms of nociception in various pain models. The method involves skillful and tedious recordings of teased fibers from nerve preparations as well as time-consuming post-recording analyses. To increase efficiency and productivity of data analyses of recorded action potentials, we developed and validated a novel, easy-to-use Microsoft Excel-based application using Visual Basic Programming. New method: A code for the novel program, shigraspike1.0, was written to create a module to include customizable subroutines for analyses for electrical and mechanical responses. Using previously recorded action potentials with tongue-lingual nerve preparations, the program was validated for appropriate execution, ease-of-use, accuracy of the output data and time taken for analyses. Results: We observed appropriate execution of shigraspike1.0 on Windows and iOS desktop platforms that included computation of response latency of the spike of interest using electrical stimulus as well as estimation of the number of impulses at each force with a step-and-hold mechanical ramp of 10–200mN. Output data obtained by shigrapsike1.0 for both stimulus types were accurate and statistically insignificant from manual analyses. Comparison with existing method: The novel application shigraspike1.0, allows for rapid analyses for single-fiber recordings and takes less than half the time to analyze electrical and mechanical responses compared to manual analyses. Conclusions: The newly developed shigraspike1.0 application can be a very productive tool to be routinely used for efficient analyses of single-fiber electrophysiology in pain research.
KW - Analysis
KW - Automation
KW - ShigraSpike
KW - Single-fiber recordings
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U2 - 10.1016/j.jneumeth.2021.109312
DO - 10.1016/j.jneumeth.2021.109312
M3 - Article
C2 - 34371025
AN - SCOPUS:85112194410
SN - 0165-0270
VL - 362
JO - Journal of Neuroscience Methods
JF - Journal of Neuroscience Methods
M1 - 109312
ER -