Functional Brain Regions Linked to Tinnitus Pathology and Compensation During Task Performance: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To systematically search the literature and organize relevant advancements in the connection between tinnitus and the activity of different functional brain regions using functional magnetic resonance imaging (fMRI). DATA SOURCES: MEDLINE (OVID), EMBASE (OVID), CINAHL (EBSCO), Web of Science, ProQuest Dissertations & Theses Global, Cochrane Database of Systematic Reviews, and PROSPERO from inception to April 2022. REVIEW METHODS: Studies with adult human subjects who suffer from tinnitus and underwent fMRI to relate specific regions of interest to tinnitus pathology or compensation were included. In addition, fMRI had to be performed with a paradigm of stimuli that would stimulate auditory brain activity. Exclusion criteria included non-English studies, animal studies, and studies that utilized a resting state magnetic resonance imaging or other imaging modalities. RESULTS: The auditory cortex may work to dampen the effects of central gain. Results from different studies show variable changes in the Heschl's gyrus (HG), with some showing increased activity and others showing inhibition and volume loss. After controlling for hyperacusis and other confounders, tinnitus does not seem to influence the inferior colliculus (IC) activation. However, there is decreased connectivity between the auditory cortex and IC. The cochlear nucleus (CN) generally shows increased activation in tinnitus patients. fMRI evidence indicates significant inhibition of thalamic gating. Activating the thalamus may be of important therapeutic potential. CONCLUSION: Patients with tinnitus have significantly altered neuronal firing patterns, especially within the auditory network, when compared to individuals without tinnitus. Tinnitus and hyperacusis commonly coexist, making differentiation of the effects of these 2 phenomena frequently difficult.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".