Cortical Responses to the Amplitude Envelopes of Sounds Change with Age
Bibliographic record
Abstract
Many older listeners have difficulty understanding speech in noise, when cues to speech-sound identity are less redundant. The amplitude envelope of speech fluctuates dramatically over time, and features such as the rate of amplitude change at onsets (attack) and offsets (decay), signal critical information about the identity of speech sounds. Aging is also thought to be accompanied by increases in cortical excitability, which may differentially alter sensitivity to envelope dynamics. Here, we recorded electroencephalography in younger and older human adults (of both sexes) to investigate how aging affects neural synchronization to 4 Hz amplitude-modulated noises with different envelope shapes (ramped: slow attack and sharp decay; damped: sharp attack and slow decay). We observed that subcortical responses did not differ between age groups, whereas older compared with younger adults exhibited larger cortical responses to sound onsets, consistent with an increase in auditory cortical excitability. Neural activity in older adults synchronized more strongly to rapid-onset, slow-offset (damped) envelopes, was less sinusoidal, and was more peaked. Younger adults demonstrated the opposite pattern, showing stronger synchronization to slow-onset, rapid-offset (ramped) envelopes, as well as a more sinusoidal neural response shape. The current results suggest that age-related changes in the excitability of auditory cortex alter responses to envelope dynamics. This may be part of the reason why older adults experience difficulty understanding speech in noise. SIGNIFICANCE STATEMENT Many middle-aged and older adults report difficulty understanding speech when there is background noise, which can trigger social withdrawal and negative psychosocial health outcomes. The difficulty may be related to age-related changes in how the brain processes temporal sound features. We tested younger and older people on their sensitivity to different envelope shapes, using EEG. Our results demonstrate that aging is associated with heightened sensitivity to sounds with a sharp attack and gradual decay, and sharper neural responses that deviate from the sinusoidal features of the stimulus, perhaps reflecting increased excitability in the aged auditory cortex. Altered responses to temporal sound features may be part of the reason why older adults often experience difficulty understanding speech in social situations.
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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".