Age‐related hearing loss and cognitive decline: MRI and cellular evidence
Bibliographic record
Abstract
Extensive evidence supports the association between age-related hearing loss (ARHL) and cognitive decline. It is, however, unknown whether a causal relationship exists between these two, or whether they both result from shared mechanisms. This paper intends to study this relationship through a comprehensive review of MRI findings as well as evidence of cellular alterations. Our review of structural MRI studies demonstrates that ARHL is independently linked to accelerated atrophy of total and regional brain volumes and reduced white matter integrity. Resting-state and task-based fMRI studies on ARHL also show changes in spontaneous neural activity and brain functional connectivity; and alterations in brain areas supporting auditory, language, cognitive, and affective processing independent of age, respectively. Although MRI findings support a causal relationship between ARHL and cognitive decline, the contribution of potential shared mechanisms should also be considered. In this regard, the review of cellular evidence indicates their role as possible common mechanisms underlying both age-related changes in hearing and cognition. Considering existing evidence, no single hypothesis can explain the link between ARHL and cognitive decline, and the contribution of both causal (i.e., the sensory hypothesis) and shared (i.e., the common cause hypothesis) mechanisms is expected.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".