Evidence map›Paper›PMID 31168330›Full record

ArticleCognitive neurodynamics2019

A cognitive brain-computer interface monitoring sustained attentional variations during a continuous task.

Antoine Gaume, Gérard Dreyfus, François-Benoît Vialatte

Abstract read
In one paragraph

Article in Cognitive neurodynamics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  3. [Prospects and technical challenges of non-invasive brain-computer interfaces in manned space missions].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025
    Article
  4. Article
  5. Article
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  8. Article
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  12. Article
  13. Brain-Computer Interface: Advancement and Challenges.Sensors (Basel, Switzerland) · 2021
    Review
  14. Review
  15. Article
  16. Article
  17. Article
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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

3 authors.

Antoine Gaume1ESPCI Paris, PSL Université Paris, Paris, France.
Gérard Dreyfus1ESPCI Paris, PSL Université Paris, Paris, France.
François-Benoît Vialatte1ESPCI Paris, PSL Université Paris, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We introduce a cognitive brain-computer interface based on a continuous performance task for the monitoring of variations of visual sustained attention, i.e. the self-directed maintenance of cognitive focus in non-arousing conditions while possibly ignoring distractors and avoiding mind wandering. We introduce a visual sustained attention continuous performance task with three levels of task difficulty. Pairwise discrimination of these task difficulties from electroencephalographic features was performed using a leave-one-subject-out cross validation approach. Features were selected using the orthogonal forward regression supervised feature selection method. Cognitive load was best predicted using a combination of prefrontal theta power, broad spatial range gamma power, fronto-central beta power, and fronto-central alpha power. Generalization performance estimates for pairwise classification of task difficulty using these features reached 75% for 5 s epochs, and 85% for 30 s epochs.

Indexed as

AttentionBrain–computer interfaceCognitive BCICPTEEG

Identifiers

PMID31168330
PMCPMC6520431

What OpenQuestion holds

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LicenceCC BY
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.