Evidence map›Paper›PMID 31624252›Full record

ArticleScientific data2019

High-density EEG mobile brain/body imaging data recorded during a challenging auditory gait pacing task.

Johanna Wagner, Ramon Martinez-Cancino, Arnaud Delorme, Scott Makeig, Teodoro Solis-Escalante, Christa Neuper, Gernot Mueller-Putz

Open access · goldAbstract readDataset
In one paragraph

Article in Scientific data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 21% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Walking Modulates Active Auditory Sensing.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
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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

7 authors at 4 institutions in 3 countries.

Johanna WagnerSwartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA. j9wagner@ucsd.edu.
Ramon Martinez-CancinoSwartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA.
Arnaud DelormeSwartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA.
Scott MakeigSwartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA.
Teodoro Solis-EscalanteLaboratory for Brain Computer Interfaces, Institute of Neural Engineering, Graz University of Technology, Graz, Austria.
Christa NeuperLaboratory for Brain Computer Interfaces, Institute of Neural Engineering, Graz University of Technology, Graz, Austria.
Gernot Mueller-PutzLaboratory for Brain Computer Interfaces, Institute of Neural Engineering, Graz University of Technology, Graz, Austria.ORCID http://orcid.org/0000-0002-0087-3720
University of California San Diego · USGraz University of Technology · ATRadboud University Nijmegen · NLUniversity of Graz · AT

Funding

EEGLAB: Software for Analysis of Human Brain DynamicsR01NS047293 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Arnaud Delorme, Scott Makeig · 2004 to 2026
$10.2M
NINDS NIH HHS R01 NS047293U.S. Department of Health & Human Services | National Institutes of Health (NIH) 5R01-NS047293-13
6 · The paper itself

Abstract

In this report we present a mobile brain/body imaging (MoBI) dataset that allows study of source-resolved cortical dynamics supporting coordinated gait movements in a rhythmic auditory cueing paradigm. Use of an auditory pacing stimulus stream has been recommended to identify deficits and treat gait impairments in neurologic populations. Here, the rhythmic cueing paradigm required healthy young participants to walk on a treadmill (constant speed) while attempting to maintain step synchrony with an auditory pacing stream and to adapt their step length and rate to unanticipated shifts in tempo of the pacing stimuli (e.g., sudden shifts to a faster or slower tempo). High-density electroencephalography (EEG, 108 channels), surface electromyography (EMG, bilateral tibialis anterior), pressure sensors on the heel (to register timing of heel strikes), and goniometers (knee, hip, and ankle joint angles) were concurrently recorded in 20 participants. The data is provided in the Brain Imaging Data Structure (BIDS) format to promote data sharing and reuse, and allow the inclusion of the data into fully automated data analysis workflows.

Indexed as

ElectroencephalographyGait AnalysisAdultAuditory PerceptionBrainCuesElectromyographyFemaleHumansMaleMuscle, SkeletalNeuroimagingWalkingYoung Adult

Identifiers

PMID31624252
PMCPMC6797727
OpenAlexW2980341363

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.