Evidence map›Paper›PMID 32565881›Full record

ArticleComputational and mathematical methods in medicine2020

A Lead Field Two-Domain Model for Longitudinal Neural Tracts-Analytical Framework and Implications for Signal Bandwidth.

G Fischer, M Kofler, M Handler, D Baumgarten

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Implementation ofMethodsX · 2023
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

G FischerInstitute of Electrical and Biomedical Engineering, UMIT-Private University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, 6060 Hall in Tirol, Austria.ORCID https://orcid.org/0000-0002-7292-2333
M KoflerDepartment of Neurology, Hochzirl Hospital, Zirl, Austria.ORCID https://orcid.org/0000-0002-2962-0903
M HandlerInstitute of Electrical and Biomedical Engineering, UMIT-Private University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, 6060 Hall in Tirol, Austria.ORCID https://orcid.org/0000-0001-7958-3162
D BaumgartenInstitute of Electrical and Biomedical Engineering, UMIT-Private University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, 6060 Hall in Tirol, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Somatosensory evoked potentials are a well-established tool for assessing volley conduction in afferent neural pathways. However, from a clinical perspective, recording of spinal signals is still a demanding task due to the low amplitudes compared to relevant noise sources. Computer modeling is a powerful tool for gaining insight into signal genesis and, thus, for promoting future innovations in signal extraction. However, due to the complex structure of neural pathways, modeling is computationally demanding. We present a theoretical framework which allows computing the electric potential generated by a single axon in a body surface lead by the convolution of the neural lead field function with a propagating action potential term. The signal generated by a large cohort of axons was obtained by convoluting a single axonal signal with the statistical distribution of temporal dispersion of individual axonal signals. For establishing the framework, analysis was based on an analytical model. Our approach was further adopted for a numerical computation of body surface neuropotentials employing the lead field theory. Double convolution allowed straightforward analysis in the frequency domain. The highest frequency components occurred at the cellular membrane. A bandpass type spectral shape and a peak frequency of 1800 Hz was observed. The volume conductor transmitting the signal to the recording lead acted as an additional bandpass reducing the axonal peak frequency from 200 Hz to 500 Hz. The superposition of temporally dispersed axonal signals acted as an additional low-pass filter further reducing the compound action potential peak frequency from 90 Hz to 170 Hz. Our results suggest that the bandwidth of spinal evoked potentials might be narrower than the bandwidth requested by current clinical guidelines. The present findings will allow the optimization of noise suppression. Furthermore, our theoretical framework allows the adaptation in numerical methods and application in anatomically realistic geometries in future studies.

Indexed as

Models, NeurologicalAction PotentialsAfferent PathwaysAnimalsAxonsComputational BiologyComputer SimulationElectric StimulationElectrophysiological PhenomenaEvoked Potentials, SomatosensoryHumansMathematical ConceptsNeural Conduction

Identifiers

PMID32565881
PMCPMC7275970

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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 OpenQuestion graph.