The effect of Transcranial Ultrasound Pulse Repetition Frequency on Sustained Inhibition in the Human Primary Motor Cortex: A Double-Blind, Sham-Controlled Study
Bibliographic record
Abstract
Background: Non-invasive brain stimulation (NIBS) techniques like transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) have been widely used but are limited in spatial resolution and deep brain targeting.Transcranial ultrasound stimulation (TUS) offers higher precision and access to deep brain regions.TUS has shown potential in treating neurological disorders and inducing long-lasting neural changes.However, the effects of sonication parameters, especially pulse repetition frequency (PRF), on neuromodulation remain unclear, warranting further investigation.Objective: To explore the long-lasting effects of different PRFs of TUS on motor corticospinal excitability and to determine the optimal PRF for modulating cortical excitability effectively.Methods: High-resolution T1-and T2-weighted MRI scans, along with zero echo time (ZTE) images, were collected from 21 neurologically healthy individuals.These scans were used to reconstruct the skull accurately for neuronavigation and model transcranial ultrasound and thermal effects using BabelBrain software.The study investigated the impact of TUS at three pulse repetition frequencies (10, 100, and 1000 Hz) with a 10% duty cycle on motor cortex excitability.Changes in excitability were tracked by recording TMS-induced motor evoked potentials (MEPs) at 5-, 30-, and 60-minute intervals after stimulation.Results: Safety assessments indicated that maximum temperature increases remained within FDA guidelines, with participants reporting mild to moderate symptoms during stimulation; however, no symptoms were rated as definitely related to the ultrasound.A linear mixed-effects model (LMM) analysis revealed significant effects of PRF on MEP amplitudes, with notable reductions at 10 Hz and 100 Hz PRFs, lasting up to 30 and 60 minutes respectively.No significant changes were observed with 1000 Hz PRF or sham conditions.Conclusions: The findings affirm PRF's critical role in TUS's efficacy for reducing corticospinal excitability, suggesting TUS's promising potential as a non-invasive brain stimulation technique for neurological and psychiatric applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".