Evidence map›Paper›PMID 35286575›Full record

ArticleNeuroinformatics2022

ERP Analysis Using a Multi-Channel Matching Pursuit Algorithm.

Joanna Duda-Goławska, Kamil K Imbir, Jarosław Żygierewicz

Abstract read
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In one paragraph

Article in Neuroinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Joanna Duda-GoławskaFaculty of Physics, University of Warsaw, L. Pasteura 5 Street, Warsaw, 02-093, Poland. Joanna.Duda@fuw.edu.pl.ORCID 0000-0002-6029-1108
Kamil K ImbirFaculty of Psychology, University of Warsaw, Stawki 5/7 Street, Warsaw, 10-587, Poland.
Jarosław ŻygierewiczFaculty of Physics, University of Warsaw, L. Pasteura 5 Street, Warsaw, 02-093, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we propose a new algorithm for analysing event-related components observed in EEG signals in psychological experiments. We investigate its capabilities and limitations. The algorithm is based on multivariate matching pursuit and clustering. It is aimed to find patterns in EEG signals which are similar across different experimental conditions, but it allows for variations in amplitude and slight variability in topography. The method proved to yield expected results in numerical simulations. For the real data coming from an emotional categorisation task experiment, we obtained two indications. First, the method can be used as a specific filter that reduces the variability of components, as defined classically, within each experimental condition. Second, equivalent dipoles fitted to items of the activity clusters identified by the algorithm localise in compact brain areas related to the task performed by the subjects across experimental conditions. Thus this activity may be studied as candidates for hypothetical latent components. The proposed algorithm is a promising new tool in ERP studies, which deserves further experimental evaluations.

Indexed as

ElectroencephalographyEvoked PotentialsAlgorithmsBrainHumansERPExploratory analysisMMP

Identifiers

What OpenQuestion holds

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Registered trials

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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.