Investigating the impact of skull vibrations on motor responses to focused ultrasound neuromodulation in small rodents and methods to mitigate them
Bibliographic record
Abstract
Abstract Objective . Focused ultrasound (FUS) neuromodulation non-invasively alters brain activity, likely via acoustic radiation force with dynamics of the pulse repetition frequency (PRF). PRF impacts neuromodulation as well as indirect auditory activation, a confound linked to skull vibrations. This study aimed to minimize these vibrations, by adjusting and randomizing PRF, and determine their impact on FUS-induced motor activity. We hypothesized that: the skull would vibrate most at a specific PRF; randomizing PRF would reduce skull vibrations without affecting motor responses; and FUS would yield motor activity while actuator-induced skull vibrations would not. Approach . Three objectives were studied in parallel using C57Bl/6 mice ( n = number of mice used per objective). First, skull vibration amplitude, measured as a percentage of maximum amplitude per treatment, was recorded via contact microphone over a range of PRFs to assess the PRF-dependency of skull vibrations ( n = 19). Vibrations were then compared between random and fixed PRFs ( n = 15). Lastly, motor responses were compared between fixed 1.5 kHz PRF FUS, random PRF FUS, air-puff stimulation, sham stimulation, and vibration induction via piezoelectric actuator ( n = 30). Main Results. The study found amplitude peaked at 1.51 kHz (88.1 ± 11.5%), significantly higher than at 0.54 kHz (75.5 ± 15.1%; p = 0.0149). Random PRF reduced amplitude by 4.2% ( p = 0.0181). Motor response rates to actuator-induced skull vibrations at the PRF (5.73 ± 6.96%) and its third harmonic (22.9 ± 22.7%) were not significantly different than sham (14.1 ± 11.6%), but lower than FUS (70.2 ± 16.3%; p < 0.0001). Significance . Based on these results, PRF near 0.5 kHz may best avoid skull vibrations, while random PRF could be utilized to slightly reduce vibration amplitude. The results also suggested that skull vibrations likely do not significantly impact motor responses to FUS neuromodulation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".