Non-invasive neuromodulation for tinnitus: A meta-analysis and modeling studies
Bibliographic record
Abstract
BACKGROUND: Patients with tinnitus often have poor quality of life, as well as severe anxiety and depression. New approaches to treat tinnitus are needed. OBJECTIVE: Evaluate the effects of non-invasive neuromodulation on tinnitus through a metaanalysis and modeling study. The main hypothesis was that real as compared to sham neuromodulation that decreases tinnitus will modulate regions in line with the neurobiological models of tinnitus. METHODS AND RESULTS: The systematic review, conducted from Pubmed, Cochrane and PsycINFO databases, showed that active as compared to sham repetitive transcranial magnetic stimulation (rTMS) reduced tinnitus, but active and sham transcranial direct current stimulation did not significantly differ. Further, rTMS over the auditory cortex was the most effective protocol. The modeling results indicate that this rTMS protocol elicited the strongest electric fields in the insula. Also, rTMS was particularly beneficial in women. Finally, the placebo effects were highly variable, highlighting the importance of conducting sham-controlled trials. CONCLUSION: In sum, neuromodulation protocols that target the auditory cortex and the insula may hold clinical potential to treat tinnitus.
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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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.045 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".