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Record W4407934805 · doi:10.1016/j.brs.2024.12.147

Revealing spatiotemporal dynamics of speech production with chronometric interleaved TMS-fMRI

2025· article· en· W4407934805 on OpenAlexaff
Maria Vasileiadi, Anna‐Lisa Schuler, Michael Woletz, Verena Witz, Sarah Grosshagauer, David Linhardt, Martin Tik

Bibliographic record

VenueBrain stimulation · 2025
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsSpeech productionDynamics (music)Production (economics)PsychologyComputer scienceSpeech recognition

Abstract

fetched live from OpenAlex

restoration of function through remyelination.Vagus nerve stimulation (VNS) drives neuronal activity and plasticity, leading to functional recovery from neuronal injury in stroke, tinnitus and traumatic brain injury.However, whether VNS can be utilized to drive myelin repair and plasticity remains unexplored.We applied non-invasive transcutaneous auricular VNS (taVNS) to mice following cuprizone-mediated demyelination and used longitudinal two-photon in vivo imaging to examine the loss and regeneration of oligodendrocytes and myelin in primary forelimb motor cortex over time.We found that VNS enhances the generation of new oligodendrocytes.These findings highlight the beneficial impact of VNS on myelin repair and motor function recovery following demyelination, supporting its potential as a therapeutic approach for demyelinating diseases Research Category and Technology and Methods Translational Research: 12.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.282
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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