Evidence map›Paper›PMID 42131571›Full record

ArticleFrontiers in human neuroscience2026

Human brain data: a valuable and open-ended resource for artificial intelligence.

Maël Donoso

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2026. 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

1 author.

Maël DonosoOuroboros Neurotechnologies, Lausanne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Experimental evidence increasingly demonstrates that human brain data can be leveraged to train artificial intelligence models. In this context, neuroimaging data is both valuable, since it can improve model performance and could be prioritized for high-value steps in model training, and open-ended, since future neuroscience discoveries could retroactively identify new neural signals of interest in current neuroimaging datasets. The emergence of human brain data as a valuable and open-ended resource for artificial intelligence, including for foundation models, could translate into a new and strategic role for neuroscientists, and open new possibilities for the simulation of human cognition.

Indexed as

AI safetyalignmentbrain foundation modelsbrain-trained AIbrain-trained foundation modelsNeuroAIneuroimagingreasoning

Identifiers

PMID42131571
PMCPMC13161143

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.