Aberrant spontaneous brain activity in chronic tinnitus patients revealed by resting-state functional MRI
Bibliographic record
Abstract
OBJECTIVE: The neural mechanisms that give rise to the phantom sound of tinnitus are poorly understood. This study aims to investigate whether aberrant spontaneous brain activity exists in chronic tinnitus patients using resting-state functional magnetic resonance imaging (fMRI) technique. MATERIALS AND METHODS: A total of 31 patients with chronic tinnitus patients and 32 healthy age-, sex-, and education-matched healthy controls were prospectively examined. Both groups had normal hearing thresholds. We calculated the amplitude of low-frequency fluctuations (ALFFs) of fMRI signals to measure spontaneous neuronal activity and detect the relationship between fMRI information and clinical data of tinnitus. RESULTS: Compared with healthy controls, we observed significant increased ALFF within several selected regions including the right middle temporal gyrus (MTG), right superior frontal gyrus (SFG), and right angular gyrus; decreased ALFF was detected in the left cuneus, right middle occipital gyrus and bilateral thalamus. Moreover, tinnitus distress correlated positively with increased ALFF in right MTG and right SFG; tinnitus duration correlated positively with higher ALFF values in right SFG. CONCLUSIONS: The present study confirms that chronic tinnitus patients have aberrant ALFF in many brain regions, which is associated with specific clinical tinnitus characteristics. ALFF disturbance in specific brain regions might be used to identify the neuro-pathophysiological mechanisms in chronic tinnitus patients.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".