A New Approach to a Classic Surgical Target: Noninvasive Modulation of Deep Brain Circuits for Depression Using Low-Intensity Focused Ultrasound
Bibliographic record
Abstract
Background: Non-invasive brain stimulation (NIBS) techniques have predominantly been used to suppress the contralesional primary motor cortex (cM1) in stroke patients to improve their paretic upper limb performance.However, recent studies have shown that suppressing the cM1 may be detrimental in stroke patients with severe upper limb impairment with absent motor evoked potentials (MEPs).Objective: To identify the effects of cM1 facilitation using NIBS on paretic hand performance in chronic stroke patients stratified according to presence (MEP+) and absence (MEP-) of upper limb MEPs.Methods: In this double-blinded study, facilitatory intermittent theta burst stimulation (iTBS) and sham iTBS were applied to cM1 of 19 chronic stroke participants in two separate sessions in randomised order.Repeated squeeze and release (RSR) of a handgrip dynamometer was used to assess total force squeezed, rate of force production and rate of force release of the paretic hand before and after the application of real and sham iTBS.Results: Single-pulse TMS and MEPs recorded from non-paretic first dorsal interosseous confirmed that real iTBS facilitated cM1 excitability (p ¼ 0.019).After the application of real iTBS, the total force squeezed and rate of force production of the paretic hand was significantly higher compared to baseline in 9 MEP-participants (p ¼ 0.048 and p ¼ 0.012, respectively).There were no effects of real or sham iTBS on rate of force release in MEPparticipants (p > 0.12) and no effects of either stimulation type on any handgrip measure in 10 MEP+ participants (all p > 0.87).Discussion: The facilitation of cM1 is beneficial for paretic hand grip performance in MEP-but not MEP+ chronic stroke patients.The consideration of the MEP status of chronic stroke patients might enable the targeted application of NIBS techniques.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".