Evidence map›Paper›PMID 37699935›Full record

ArticleScientific data2023

Open access dataset integrating EEG and fNIRS during Stroop tasks.

Zemeng Chen, Chenyang Gao, Ting Li, Xiang Ji, Shuyu Liu, Ming Xiao

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
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  3. Open access individual finger movement dataset with fNIRS.Frontiers in human neuroscience · 2026
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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

6 authors.

Zemeng ChenInstitute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300192, China.
Chenyang GaoInstitute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300192, China.
Ting LiInstitute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300192, China. liting@bme.cams.cn.ORCID http://orcid.org/0000-0001-5145-3024
Xiang JiInstitute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300192, China.
Shuyu LiuApplied Physiology and Kinesiology, College of Health and Human Performance, University of Florida, Gainesville, 32611, USA.
Ming XiaoDivision of Information Science and Engineering, KTH Royal Institute of Technology, MALVINAS VÄG 10, 100 44, Stockholm, Sweden.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 81971660
6 · The paper itself

Abstract

Conflict monitoring and processing are crucial components of the human cognitive system, with significant implications for daily life and the diagnosis of cognitive disorders. The Stroop task, combined with brain function detection technology, has been widely employed as a classical paradigm for investigating conflict processing. However, there remains a lack of public datasets that integrate Electroencephalogram (EEG) and functional Near-infrared Spectroscopy (fNIRS) to simultaneously record brain activity during a Stroop task. We introduce a dual-modality Stroop task dataset incorporating 34-channel EEG (sampling frequency is 1000 Hz) and 20-channel high temporal resolution fNIRS (sampling frequency is 100 Hz) measurements covering the whole frontal cerebral cortex from 21 participants (9 females/12 males, aged 23.0 ± 2.3 years). Event-related potential analysis of EEG recordings and activation analysis of fNIRS recordings were performed to show the significant Stroop effect. We expected that the data provided would be utilized to investigate multimodal data processing algorithms during cognitive processing.

Indexed as

ElectroencephalographySpectroscopy, Near-InfraredStroop TestAlgorithmsCerebral CortexFemaleHumansMale

Identifiers

PMID37699935
PMCPMC10497617

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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.