Tremor reduction using a multi-focus transcranial ultrasound stimulation system targeting thalamus: Preliminary results
Bibliographic record
Abstract
Background: Transcranial ultrasound stimulation (TUS) is a non-invasive technique that focuses mechanical energy deep in the brain to modulate neural activity.However, targeting errors due to neuronavigation tracking imperfections can hinder TUS effectiveness, especially with deep brain targets.We report our multi-focus TUS strategy to target thalamus for tremor reduction in patients with essential (ET) and Parkinson tremor (PD).Methods: Three patients (2 ET, 1 PD) underwent TUS, targeting the thalamic ventrointermedius nucleus (Vim), using a 128-element phased array operating at 250 kHz.TUS was first delivered at 7 locations arranged in a circular disc pattern with inhibitory parameters (100 Hz pulse repetition frequency, 10% duty cycle, intensity at situ of 5 W/cm 2 , 30 s sonication durations).BabelBrain software (10.1109/TUFFC.2023.3274046)was used for planning the TUS delivery using subject MR tractography and CT imaging.Tremor was measured using accelerometry at baseline, immediately (0 min) and 5 min post-sonications.The 7 locations were split into two groups (G1 and G2, Fig 1-A), and the group showing the most tremor reduction was further explored with individual location targeting using 2 min sonication durations (e.g.G1-S1 is group 1, sonication 1).Results: All subjects showed significant tremor reduction.Fig 1-B shows the overlay of the normalized predicted acoustic field and Fig 1-C shows a rendering of the transducer relative to one subject.Examples of baseline acceleration compared to the lowest amplitude tremor achieved during testing is shown in Fig 1-D.Area under the curve (AUC) of the power spectral density (PSD) from 4 to 7 Hz of the tremor amplitude for all time points drops over multiple sonications (Fig 1-E).Conclusions: Multi-focus TUS improved targeting by identifying optimal stimulation locations, enhancing tremor reduction compared to baseline and over time.Because tremor seemed to remain suppressed after initial sonications, TUS may have cumulative effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".