Evidence map›Paper›PMID 33459925›Full record

ArticleBrain topography2021

Observation of Nociceptive Processing: Effect of Intra-Epidermal Electric Stimulus Properties on Detection Probability and Evoked Potentials.

Boudewijn van den Berg, Jan R Buitenweg

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In one paragraph

Article in Brain topography, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Boudewijn van den BergBiomedical Signals and Systems, Technical Medical Centre, University of Twente, PO Box 217, 7500 AE, Enschede, The Netherlands. b.van.den.berg@utwente.nl.ORCID 0000-0002-3901-2645
Jan R BuitenwegBiomedical Signals and Systems, Technical Medical Centre, University of Twente, PO Box 217, 7500 AE, Enschede, The Netherlands.ORCID 0000-0002-2531-3981

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monitoring nociceptive processing is a current challenge due to a lack of objective measures. Recently, we developed a method for simultaneous tracking of psychophysical detection probability and brain evoked potentials in response to intra-epidermal stimulation. An exploratory investigation showed that we could quantify nociceptive system behavior by estimating the effect of stimulus properties on the evoked potential (EP). The goal in this work was to accurately measure nociceptive system behavior using this method in a large group of healthy subjects to identify the locations and latencies of EP components and the effect of single- and double-pulse stimuli with an inter-pulse interval of 10 or 40 ms on these EP components and detection probability. First, we observed the effect of filter settings and channel selection on the EP. Subsequently, we compared statistical models to assess correlation of EP and detection probability with stimulus properties, and quantified the effect of stimulus properties on both outcome measures through linear mixed regression. We observed lateral and central EP components in response to intra-epidermal stimulation. Detection probability and central EP components were positively correlated to the amplitude of each pulse, regardless of the inter-pulse interval, and negatively correlated to the trial number. Both central and lateral EP components also showed strong correlation with detection. These results show that both the observed EP and the detection probability reflect the various steps of processing of a nociceptive stimulus, including peripheral nerve fiber recruitment, central synaptic summation, and habituation to a repeated stimulus.

Indexed as

Evoked PotentialsNociceptionBrainCognitionElectric StimulationHumansProbabilityCentral synaptic summationDetection probabilityDetection thresholdElectroencephalographyEvoked potentialHabituationIntra-epidermal electric stimulationNociceptionNociceptive ProcessingPeripheral nerve fiber recruitmentPsychophysics

Identifiers

PMID33459925
PMCPMC7892744

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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.