Evidence map›Paper›PMID 38452019›Full record

ArticlePloS one2024

EEG as a potential ground truth for the assessment of cognitive state in software development activities: A multimodal imaging study.

Júlio Medeiros, Marco Simões, João Castelhano, Rodolfo Abreu, Ricardo Couceiro, Jorge Henriques, Miguel Castelo-Branco, Henrique Madeira, César Teixeira, Paulo de Carvalho

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
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

10 authors at 1 institution in 1 country.

Júlio MedeirosDepartment of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal.ORCID 0000-0003-2852-6285
Marco SimõesDepartment of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal.
João CastelhanoICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal.
Rodolfo AbreuICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal.
Ricardo CouceiroDepartment of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal.
Jorge HenriquesDepartment of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal.
Miguel Castelo-BrancoICNAS-Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra, Portugal.
Henrique MadeiraDepartment of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal.ORCID 0000-0001-8146-4664
César TeixeiraDepartment of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal.
Paulo de CarvalhoDepartment of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal.
University of Coimbra · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cognitive human error and recent cognitive taxonomy on human error causes of software defects support the intuitive idea that, for instance, mental overload, attention slips, and working memory overload are important human causes for software bugs. In this paper, we approach the EEG as a reliable surrogate to MRI-based reference of the programmer's cognitive state to be used in situations where heavy imaging techniques are infeasible. The idea is to use EEG biomarkers to validate other less intrusive physiological measures, that can be easily recorded by wearable devices and useful in the assessment of the developer's cognitive state during software development tasks. Herein, our EEG study, with the support of fMRI, presents an extensive and systematic analysis by inspecting metrics and extracting relevant information about the most robust features, best EEG channels and the best hemodynamic time delay in the context of software development tasks. From the EEG-fMRI similarity analysis performed, we found significant correlations between a subset of EEG features and the Insula region of the brain, which has been reported as a region highly related to high cognitive tasks, such as software development tasks. We concluded that despite a clear inter-subject variability of the best EEG features and hemodynamic time delay used, the most robust and predominant EEG features, across all the subjects, are related to the Hjorth parameter Activity and Total Power features, from the EEG channels F4, FC4 and C4, and considering in most of the cases a hemodynamic time delay of 4 seconds used on the hemodynamic response function. These findings should be taken into account in future EEG-fMRI studies in the context of software debugging.

Indexed as

BrainElectroencephalographyCognitionHumansMagnetic Resonance ImagingMultimodal ImagingSoftware

Identifiers

PMID38452019
PMCPMC10919648
OpenAlexW4392545094

What OpenQuestion holds

Textmetadata
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.