Evidence map›Paper›PMID 35410871›Full record

ArticleeNeuro

The Listening Zone of Human Electrocorticographic Field Potential Recordings.

Meredith J McCarty, Oscar Woolnough, John C Mosher, John Seymour, Nitin Tandon

Open access · goldAbstract read
In one paragraph

Article in eNeuro. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.6field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
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  7. Predictive encoding of auditory sequences in the human prefrontal cortex.bioRxiv : the preprint server for biology · 2025
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  12. Review
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  18. Spatiotemporally distributed frontotemporal networks for sentence reading.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  19. Article
  20. 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

5 authors at 3 institutions in 1 country.

Meredith J McCartyVivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Houston, Houston, TX 77030.ORCID 0000-0002-4632-1403
Oscar WoolnoughVivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Houston, Houston, TX 77030.ORCID 0000-0002-5878-6865
John C MosherTexas Institute for Restorative Neurotechnologies, University of Texas Health Science Center at Houston, Houston, TX 77030.
John SeymourVivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Houston, Houston, TX 77030.
Nitin TandonVivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Houston, Houston, TX 77030 nitin.tandon@uth.tmc.edu.ORCID 0000-0002-2752-2365
The University of Texas Health Science Center · USMemorial Hermann · USThe University of Texas Health Science Center at Houston · US

Funding

A unified cognitive network model of languageU01NS098981 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI CRONE, NATHAN E, TANDON, NITIN · 2016 to 2018
$3.0M
Brain Networks of Noun GenerationR01DC014589 · NIDCD · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI TANDON, NITIN · 2015 to 2019
$2.0M
NIDCD NIH HHS R01 DC014589NINDS NIH HHS U01 NS098981
6 · The paper itself

Abstract

Intracranial electroencephalographic (icEEG) recordings provide invaluable insights into neural dynamics in humans because of their unmatched spatiotemporal resolution. Yet, such recordings reflect the combined activity of multiple underlying generators, confounding the ability to resolve spatially distinct neural sources. To empirically quantify the listening zone of icEEG recordings, we computed correlations between signals as a function of distance (full width at half maximum; FWHM) between 8752 recording sites in 71 patients (33 female) implanted with either subdural electrodes (SDEs), stereo-encephalography electrodes (sEEG), or high-density sEEG electrodes. As expected, for both SDEs and sEEGs, higher frequency signals exhibited a sharper fall off relative to lower frequency signals. For broadband high γ (BHG) activity, the mean FWHM of SDEs (6.6 ± 2.5 mm) and sEEGs in gray matter (7.14 ± 1.7 mm) was not significantly different; however, FWHM for low frequencies recorded by sEEGs was 2.45 mm smaller than SDEs. White matter sEEGs showed much lower power for frequencies 17-200 Hz (q < 0.01) and a much broader decay (11.3 ± 3.2 mm) than gray matter electrodes (7.14 ± 1.7 mm). The use of a bipolar referencing scheme significantly lowered FWHM for sEEGs, relative to a white matter reference or a common average reference (CAR). These results outline the influence of array design, spectral bands, and referencing schema on local field potential recordings and source localization in icEEG recordings in humans. The metrics we derive have immediate relevance to the analysis and interpretation of both cognitive and epileptic data.

Indexed as

EpilepsyWhite MatterBrain MappingElectrocorticographyElectrodes, ImplantedElectroencephalographyFemaleGray MatterHumansMaleelectrocorticographyhumanintracranial recordinginverse modelingreferencing

Identifiers

PMID35410871
PMCPMC9034754
OpenAlexW4226203857

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.