Effects of age on the neural correlates of auditory working memory in cochlear implant users
Bibliographic record
Abstract
Following a conversation in a noisy environment is challenging, especially for individuals who received cochlear implants (CIs) to remediate severe-to-profound hearing loss. CI users likely work harder than their normal-hearing counterparts to understand speech in adverse listening conditions. Recruiting cognitive resources can be taxing and may interfere with attentional regulation and working memory processes. Few studies have, however, examined the impact of CIs on the neural correlates of attention and working memory. We used a high-density electroencephalogram to investigate behavioural and neural correlates of auditory attention and working memory in 14 CI users and age-matched normal hearing (NH) controls (age ranges: 21-75). All participants completed an auditory n-back task with zero- and two-back memory load conditions. Behaviourally, CI users were slower in identifying targets during the two-back condition, especially older adults. The sensory-evoked responses were reduced in CI users compared to NH. With increasing memory load, younger CI users and NH controls displayed decreased amplitudes, while older CI users showed no change in amplitude. We also observed reduced frontal theta synchrony and greater alpha/beta desynchrony in CI users where alpha/beta in the left inferior frontal gyrus was related to slower response times in CI users. Attenuated frontotemporal connectivity was also evident compared to NH. These findings suggest that CI users adapt to higher task demands by allocating more attentional resources while encoding and maintaining stimuli in working memory. This pattern of activity potentially indexes a delay in identification and possible neural correlates of cognitive deficits while aging with a CI.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".