Evidence map›Paper›PMID 33359339›Full record

ArticleNeuroImage2021

Structural templates for imaging EEG cortical sources in infants.

Christian O'Reilly, Eric Larson, John E Richards, Mayada Elsabbagh

Open access · goldAbstract read
In one paragraph

Article in NeuroImage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

23 citing papers in PubMed, 36 citations in OpenAlex.

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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

4 authors at 3 institutions in 2 countries.

Christian O'ReillyMontreal Neurological Institute, Azrieli Centre for Autism Research, McGill University, 3775 Rue University, Room C18, Duff Medical Building, Montreal, Québec H3A 2B4, Canada. Electronic address: christian.oreilly@mcgill.ca.
Eric LarsonInstitute for Learning and Brain Sciences, University of Washington, Seattle, WA, USA.
John E RichardsDepartment of Psychology, University of South Carolina, USA; Institute for Mind and Brain, University of South Carolina, USA.
Mayada ElsabbaghMontreal Neurological Institute, Azrieli Centre for Autism Research, McGill University, 3775 Rue University, Room C18, Duff Medical Building, Montreal, Québec H3A 2B4, Canada.
Montreal Neurological Institute and Hospital · CAUniversity of South Carolina · USUniversity of Washington · US

Funding

Scalable Software for Distributed Processing and Visualization of Multi-Site MEG/EEG DatasetsR01NS104585 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI MATTI HAMALAINEN · 2018 to 2026
$4.3M
The development of sustained attention in infantsR01HD018942 · NICHD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI RICHARDS, JOHN E · 1988 to 2021
$4.2M
The Neurodevelopmental MRI DatabaseR03HD091464 · NICHD · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI RICHARDS, JOHN E · 2017 to 2018
$128k
NICHD NIH HHS R01 HD018942NICHD NIH HHS R03 HD091464NINDS NIH HHS R01 NS104585
6 · The paper itself

Abstract

Electroencephalographic (EEG) source reconstruction is a powerful approach that allows anatomical localization of electrophysiological brain activity. Algorithms used to estimate cortical sources require an anatomical model of the head and the brain, generally reconstructed using magnetic resonance imaging (MRI). When such scans are unavailable, a population average can be used for adults, but no average surface template is available for cortical source imaging in infants. To address this issue, we introduce a new series of 13 anatomical models for subjects between zero and 24 months of age. These templates are built from MRI averages and boundary element method (BEM) segmentation of head tissues available as part of the Neurodevelopmental MRI Database. Surfaces separating the pia mater, the gray matter, and the white matter were estimated using the Infant FreeSurfer pipeline. The surface of the skin as well as the outer and inner skull surfaces were extracted using a cube marching algorithm followed by Laplacian smoothing and mesh decimation. We post-processed these meshes to correct topological errors and ensure watertight meshes. Source reconstruction with these templates is demonstrated and validated using 100 high-density EEG recordings from 7-month-old infants. Hopefully, these templates will support future studies on EEG-based neuroimaging and functional connectivity in healthy infants as well as in clinical pediatric populations.

Indexed as

BrainElectroencephalographyModels, AnatomicSignal Processing, Computer-AssistedBrain MappingComputer SimulationFemaleHumansInfantInfant, NewbornMaleSoftwareElectroencephalographyForward modelInfantNeurodevelopmentPopulation templateSource reconstruction

Identifiers

PMID33359339
PMCPMC7901726
OpenAlexW3114823596

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.