Audiovisual Deficits in Older Adults with Hearing Loss: Biological Evidence
Bibliographic record
Abstract
In Brief Objective: To examine the impact of hearing loss (HL) on audiovisual (AV) processing in the aging population. We hypothesized that age-related HL would have a pervasive effect on sensory processing, extending beyond the auditory domain. Specifically, we predicted that decreased auditory input to the neural system, in the form of HL over time, would have deleterious effects on multisensory mechanisms. Design: This study compared AV processing between older adults with normal hearing (N = 12) and older adults with mild to moderate sensorineural HL (N = 12). To do this, we recorded cortical evoked potentials that were elicited by watching and listening to recordings of a speaker saying the syllable “bi.” Stimuli were presented in three conditions: when hearing the syllable “bi” (auditory), when viewing a person say “bi” (visual), and when seeing and hearing the syllables simultaneously (AV). Presentation level of the auditory stimulus was set to +30 dB SL for each listener to equalize auditory input across groups. Results: In the AV condition, the normal-hearing group showed a clear and consistent decrease in P1 and N1 latencies as well as a reduction in P1 amplitude compared with the sum of the unimodal components (auditory + visual). These integration effects were absent or less consistent in HL participants. Conclusions: Despite controlling for auditory sensation level, visual influence on auditory processing was significantly less pronounced in HL individuals compared with controls, indicating diminished AV integration in this population. These results demonstrate that HL has a deleterious effect on how older adults combine what they see and hear. Although auditory amplification vastly improves the communication abilities in most hearing impaired individuals, the associated atrophy of multisensory mechanisms may contribute to a patient’s difficulty in everyday settings. Our findings and related studies emphasize the potential value of multimodal tasks and stimuli in the assessment and rehabilitation of hearing impairments. Hearing loss in older adults impacts communication skills. We hypothesized that these difficulties extend to biological correlates of multisensory speech processing. Here, we show that although normal-hearing participants show robust differences between seeing and hearing speech, their hearing-impaired counterparts do not. The clinical implication of these findings is that the effects of hearing loss extend to multisensory domains.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".