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Record W4411192715 · doi:10.1016/j.neurom.2025.05.002

Optimization Simulations of Transcranial Direct Current Stimulation Montages in Children With Perinatal Stroke

2025· article· en· W4411192715 on OpenAlex
Martin Bardhi, Ephrem Zewdie, Adam Kirton, Helen L. Carlson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNeuromodulation Technology at the Neural Interface · 2025
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsAlberta Children's HospitalUniversity of AlbertaUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta InnovatesHeart and Stroke Foundation of Canada
KeywordsTranscranial direct-current stimulationStroke (engine)MedicinePhysical medicine and rehabilitationCurrent (fluid)StimulationNeuroscienceAudiologyPsychologyPhysicsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Perinatal stroke (PS) is a vascular brain injury that causes most hemiparetic cerebral palsy. Transcranial direct current stimulation (tDCS) applies a weak electric field (EF) to the scalp, and targeting motor cortex (M1) paired with therapy may improve motor function. However, owing to developmental differences and idiosyncratic anatomy after early injury, optimal electrode placements are not known. We optimized electrode placements on the basis of individual anatomy and explored the resulting EF propagation patterns. OBJECTIVE/HYPOTHESIS: We hypothesized that children with PS would have greater electrode displacement distances from standard montages and that optimizations could improve the strength and direction of EF at M1 targets. MATERIALS AND METHODS: Magnetic resonance images of participants with PS and of controls were preprocessed, segmented, and converted to three-dimensional meshes. SimNIBS (Thielscher, Copenhagen, Denmark) modeled EF for various tDCS electrode placements. Optimal placements were modeled to maximize EF strength or direction at the targeted M1. Electrode displacement distances and directions in addition to EF metrics were compared in groups and optimization strategies. RESULTS: Optimal electrode displacement distance was greater in the arterial ischemic stroke group when EF strength in the lesioned M1 was optimized (W = 4.31, p < 0.01), located further posterior than controls. The opposite trend was observed when current direction was optimized (W = 3.68, p = 0.025). Displacement direction had higher variability in children with PS across all optimizations. Montage optimization improved EF metrics. Specifically, the anodal nondirectionally optimized protocol caused greater EF strength in simulations of participants with PS. Directionally optimized montages altered average current angle through the target M1, making it closer to perpendicular to the posterior bank of the precentral gyrus in all groups. CONCLUSIONS: Individualized electrode placements may optimize tDCS current propagation in children with PS, with tradeoffs between current direction and EF strength. tDCS current optimization may improve noninvasive neuromodulation therapies in children with disabilities.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.286
Teacher spread0.270 · 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