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Record W4407933512 · doi:10.1016/j.brs.2024.12.684

Enhancing Transcranial Ultrasound Stimulation Planning with MRI-Derived Skull Masks: A Comparative Analysis with CT-Based Processing

2025· article· en· W4407933512 on OpenAlexaff
Ali K. Zadeh, Oula Puonti, Björn Sigurðsson, Axel Thielscher, Oury Monchi, Samuel Pichardo

Bibliographic record

VenueBrain stimulation · 2025
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsComputer Research Institute of MontréalOntario Brain InstituteUniversité de MontréalUniversity of Calgary
Fundersnot available
KeywordsSkullMedicineUltrasoundRadiologyBiomedical engineeringComputer sciencePsychologyAnatomy

Abstract

fetched live from OpenAlex

We assessed the potential of stereotactic radiosurgery (SRS) to modulate neuronal network states without apparent damage of cellular integrity.For that, we irradiated a 1 mm-diameter target in the mouse visual cortex with doses of 5, 20, and 40 Gy using a small animal radiation research platform (SARRP).About six months post-irradiation, we monitored cortical neuronal microcircuit activity by 2-photon calcium imaging in the awake mouse.We found, that already one single dose SRS of 5 Gy led to a significant increase of spontaneous neuronal activity, indicative of a lasting shift in the functional architecture of the local network.A higher dose of 20 Gy further increased network excitability, while 40 Gy SRS did not alter network state.This suggest a neuromodulatory window of SRS with the potential to focally and durably modulate neuronal circuitry.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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 designBench or experimental
Domainnot available
GenreMethods

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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