Evidence map›Paper›PMID 40060477›Full record

ArticlebioRxiv : the preprint server for biology2025

Assessing the impact of artifact correction and artifact rejection on the performance of SVM-based decoding of EEG signals.

Guanghui Zhang, Steven J Luck

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

5 · Who and what money

Authors and funding

2 authors.

Guanghui ZhangResearch Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, Liaoning, China.ORCID 0000-0003-0134-3614
Steven J LuckCenter for Mind & Brain, University of California-Davis, Davis, CA, USA.

Funding

ERPLAB: Extensible, open source software for analysis of event-related potentialsR01MH087450 · NIMH · UNIVERSITY OF CALIFORNIA AT DAVIS · PI LUCK, STEVEN J · 2010 to 2025
$2.7M
Using Population Vectors to Understand Visual Working Memory for Natural StimuliR01EY033329 · NEI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI LUCK, STEVEN J · 2022 to 2025
$1.8M
NEI NIH HHS R01 EY033329NIMH NIH HHS R01 MH087450
6 · The paper itself

Abstract

Numerous studies have demonstrated that eyeblinks and other large artifacts can decrease the signal-to-noise ratio of EEG data, resulting in decreased statistical power for conventional univariate analyses. However, it is not clear whether eliminating these artifacts during preprocessing enhances the performance of multivariate pattern analysis (MVPA;

Indexed as

artifact rejectionEEGERPICAMVPA

Identifiers

PMID40060477
PMCPMC11888300

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.