ERP evidence that auditory–visual speech facilitates working memory in younger and older adults.
Bibliographic record
Abstract
Auditory-visual (AV) speech enhances speech perception and facilitates auditory processing, as measured by event-related brain potentials (ERPs). Considering a perspective of shared resources between perceptual and cognitive processes, facilitated speech perception may render more resources available for higher-order functions. This study examined whether AV speech facilitation leads to better working memory (WM) performance in 23 younger and 20 older adults. Participants completed an n-back task (0- to 3-back) under visual-only (V-only), auditory-only (A-only), and AV conditions. The results showed faster responses across all memory loads and improved accuracy in the most demanding conditions (2- and 3-back) during AV compared with unisensory conditions. Older adults benefited from the AV presentation to the same extent as younger adults. WM performance of older adults during the AV presentation did not differ from that of younger adults in the A-only condition, suggesting that an AV presentation can help to counteract some of the age-related WM decline. The ERPs showed a decrease in the auditory N1 amplitude during the AV compared with A-only presentation in older adults, suggesting that the facilitation of perceptual processing becomes especially beneficial with aging. Additionally, the N1 occurred earlier in the AV than in the A-only condition for both age groups. These AV-induced modulations of auditory processing correlated with improvement in certain behavioral and ERP measures of WM. These results support an integrated model between perception and cognition, and suggest that processing speech under AV conditions enhances WM performance of both younger and older adults.
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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 | 0.002 |
| 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) | 0.002 | 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".