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 techniques such as transcranial magnetic stimulation and transcranial direct current stimulation hold promise for inducing brain plasticity. However, their limited precision may hamper certain applications. In contrast, Transcranial Ultrasound Stimulation (TUS), known for its precision and deep brain targeting capabilities, requires further investigation to establish its efficacy in producing enduring effects for treating neurological and psychiatric disorders. OBJECTIVE: To investigate the enduring effects of different pulse repetition frequencies (PRF) of TUS on motor corticospinal excitability. METHODS: T1-, T2-weighted, and zero echo time magnetic resonance imaging scans were acquired from 21 neurologically healthy participants for neuronavigation, skull reconstruction, and the performance of transcranial ultrasound and thermal modelling. The effects of three different TUS PRFs (10, 100, and 1000 Hz) with a constant duty cycle of 10 % on corticospinal excitability in the primary motor cortex were assessed using TMS-induced motor evoked potentials (MEPs). Each PRF and sham condition was evaluated on separate days, with measurements taken 5-, 30-, and 60-min post-TUS. RESULTS: A significant decrease in MEP amplitude was observed with a PRF of 10 Hz (p = 0.007), which persisted for at least 30 min, and with a PRF of 100 Hz (p = 0.001), lasting over 60 min. However, no significant changes were found for the PRF of 1000 Hz and the sham conditions. CONCLUSION: This study highlights the significance of PRF selection in TUS and underscores its potential as a non-invasive approach to reduce corticospinal excitability, offering valuable insights for future clinical applications.
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 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 | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".