Does audiovisual speech offer a fountain of youth for old ears? An event-related brain potential study of age differences in audiovisual speech perception.
Bibliographic record
Abstract
The current study addressed the question whether audiovisual (AV) speech can improve speech perception in older and younger adults in a noisy environment. Event-related potentials (ERPs) were recorded to investigate age-related differences in the processes underlying AV speech perception. Participants performed an object categorization task in three conditions, namely auditory-only (A), visual-only (V), and AVspeech. Both age groups revealed an equivalent behavioral AVspeech benefit over unisensory trials. ERP analyses revealed an amplitude reduction of the auditory P1 and N1 on AVspeech trials relative to the summed unisensory (A + V) response in both age groups. These amplitude reductions are interpreted as an indication of multisensory efficiency as fewer neural resources were recruited to achieve better performance. Of interest, the observed P1 amplitude reduction was larger in older adults. Younger and older adults also showed an earlier auditory N1 in AVspeech relative to A and A + V trials, an effect that was again greater in the older adults. The degree of multisensory latency shift was predicted by basic auditory functioning (i.e., higher hearing thresholds were associated with larger latency shifts) in both age groups. Together, the results show that AV speech processing is not only intact in older adults, but that the facilitation of neural responses occurs earlier in and to a greater extent than in younger adults. Thus, older adults appear to benefit more from additional visual speech cues than younger adults, possibly to compensate for more impoverished unisensory inputs because of sensory aging.
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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".