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Electrode design characterization for electrophysiology from swine peripheral nervous system

Kip A Ludwig, Ph.D.
,
Nishant Verma

Comparison of cuff, microelectrode, and intrafascicular electrode to make evoked compound action potential (ECAP) and naturally occurring activity recordings from the peripheral nervous system. Dataset from pigs (n=3) - a human-scale large animal model.

Updated on July 14, 2022 (Version 1)

Corresponding Contributor:

Kip Ludwig
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722 Files
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Dataset Overview

Study Purpose: Compare recording electrode type in measuring neural signals in the periphery.

Data Collection: Electrophysiology data of concurrent recordings on cuff, microneurography electrode, and intrafascicular electrode during vagus ECAP and greater auricular sensory stroking.

Primary Conclusion: Cuff recordings have the largest ECAP and has the highest SNR, but microelectrode is the most sensitive and records the most robust naturally occurring activity.


Curator's Notes

Experimental Design: The great auricular nerve, innervating the auricle, and cervical vagus nerve of domestic pigs were instrumented with the three recording electrodes. Naturally occurring neural activity, sensory-evoked neural activity induced by gentle brushing of the auricle, and electrically ECAPs initiated by non-invasive and invasive stimulation electrodes were recorded.

Completeness: This dataset is complete.

Subjects & Samples: Male (n=3) and female (n=3) domestic pigs between 3-4 months of age were used in this study.

Primary vs derivative data: Each specific nested data folder nested under primary data (sub-) includes raw electrophysiology recordings organized by individual session subfolders. Parameters of the individual sessions can be found in the performances.xlsx file. There is no derivative data folder.

Code Availability: The "code" folder contains the Python Jupyter notebooks used to read in the electrophysiology data with the pyeCAP python package. The Jupyter notebooks require installation of the pyeCAP package in python. The pyeCAP package is a python library created by our lab to read in and work with electrophysiology datasets, especially evoked compound action potential (ECAP) datasets.

Important Notes: This dataset is in support of a forthcoming manuscript "Microneurography as a Minimally Invasive Method to Assess Target Engagement During Neuromodulation" (title subject to change)

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About this dataset

Publishing history

July 14, 2022
Originally Published
July 14, 2022 (Version 1)
Last Updated

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