Evidence map›Paper›PMID 39929926›Full record

ArticleNPJ digital medicine2025

Digital twin brain simulator for real-time consciousness monitoring and virtual intervention using primate electrocorticogram data.

Yuta Takahashi, Hayato Idei, Misako Komatsu, Jun Tani, Hiroaki Tomita, Yuichi Yamashita

Abstract read
In one paragraph

Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

6 authors.

Yuta TakahashiDepartment of Information Medicine, National Center of Neurology and Psychiatry, Tokyo, Japan. ytakaha@ncnp.go.jp.ORCID http://orcid.org/0000-0002-6996-3505
Hayato IdeiDepartment of Information Medicine, National Center of Neurology and Psychiatry, Tokyo, Japan.
Misako KomatsuInstitution of Innovative Research, Tokyo Institute of Technology, Tokyo, Japan.ORCID http://orcid.org/0000-0003-4464-4484
Jun TaniCognitive Neurorobotics Research Unit, Okinawa Institute of Science and Technology, Okinawa, Japan.
Hiroaki TomitaDepartment of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan.
Yuichi YamashitaDepartment of Information Medicine, National Center of Neurology and Psychiatry, Tokyo, Japan. yamay@ncnp.go.jp.ORCID http://orcid.org/0000-0002-2779-8222

Funding

Japan Agency for Medical Research and Development (AMED) JP21tm0424601MEXT | Japan Society for the Promotion of Science (JSPS) JP20H00625, JP24H00076, JP24K00499MEXT | Japan Society for the Promotion of Science (JSPS) JP21K15723, JP24K20897MEXT | Japan Society for the Promotion of Science (JSPS) JP22KJ3167MEXT | Japan Society for the Promotion of Science (JSPS) JP23H04978MEXT | Japan Society for the Promotion of Science (JSPS) JP24H02175MEXT | JST | Core Research for Evolutional Science and Technology (CREST) CYC-MS2023002MEXT | JST | Core Research for Evolutional Science and Technology (CREST) JPMJCR21P4
6 · The paper itself

Abstract

At the forefront of bridging computational brain modeling with personalized medicine, this study introduces a novel, real-time, electrocorticogram (ECoG) simulator, based on the digital twin brain concept. Utilizing advanced data assimilation techniques, specifically a Variational Bayesian Recurrent Neural Network model with hierarchical latent units, the simulator dynamically predicts ECoG signals reflecting real-time brain latent states. By assimilating broad ECoG signals from macaque monkeys across awake and anesthetized conditions, the model successfully updated its latent states in real-time, enhancing precision of ECoG signal simulations. Behind successful data assimilation, self-organization of latent states in the model was observed, reflecting brain states and individuality. This self-organization facilitated simulation of virtual drug administration and uncovered functional networks underlying changes in brain function during anesthesia. These results show that the proposed model can simulate brain signals in real-time with high accuracy and is also useful for revealing underlying information processing dynamics.

Identifiers

PMID39929926
PMCPMC11811282

What Socratic holds

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LicenceCC BY
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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 Socratic graph.