Evidence map›Paper›PMID 42516171›Full record

ArticleImaging neuroscience (Cambridge, Mass.)

MEG-GPT: A transformer-based foundation model for magnetoencephalography data.

Rukuang Huang, SungJun Cho, Chetan Gohil, Oiwi Parker Jones, Mark Woolrich

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Rukuang HuangOxford Centre for Integrative Neuroimaging (OxCIN), University of Oxford, Oxford, United Kingdom.
SungJun ChoOxford Centre for Integrative Neuroimaging (OxCIN), University of Oxford, Oxford, United Kingdom.
Chetan GohilOxford Centre for Integrative Neuroimaging (OxCIN), University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0002-0888-1207
Oiwi Parker JonesOxford Centre for Integrative Neuroimaging (OxCIN), University of Oxford, Oxford, United Kingdom.
Mark WoolrichOxford Centre for Integrative Neuroimaging (OxCIN), University of Oxford, Oxford, United Kingdom.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Modelling the complex spatio-temporal patterns of large-scale brain dynamics is crucial for neuroscience, but traditional methods fail to capture the rich structure in modalities such as magnetoencephalography (MEG). Recent advances in deep learning have enabled significant progress in other domains, such as language and vision, by using

Indexed as

electrophysiologyfoundation modelGPTMEGtokenisationtransformer

Identifiers

PMID42516171
PMCPMC13403652

What OpenQuestion holds

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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.