The frequency-following response to assess the neural representation of spectral speech cues in older adults
Bibliographic record
Abstract
Older adults often present difficulties understanding speech that cannot be explained by age-related changes in sound audibility. Psychoacoustic and electrophysiologic studies have linked these suprathreshold difficulties to age-related deficits in the auditory processing of temporal and spectral sound information. These studies suggest the existence of an age-related temporal processing deficit in the central auditory system, but the existence of such deficit in the spectral domain remains understudied. The FFR is an electrophysiological evoked response that assesses the ability of the neural auditory system to reproduce the spectral and temporal patterns of a sound. The main goal of this short review is to investigate if the FFR can identify and measure spectral processing deficits in the elderly compared to younger adults (for both, without hearing loss or competing noise). Furthermore, we want to determine what stimuli and analyses have been used in the literature to assess the neural encoding of spectral cues in older adults. Almost all reviewed articles showed an age-related decline in the auditory processing of spectral acoustic information. Even when using different speech and non-speech stimuli, studies reported an age-related decline at the fundamental frequency, at the first formant, and at other harmonic components using different metrics, such as the response's amplitude, inter-trial phase coherence, signal-to-response correlation, and signal-to-noise ratio. These results suggest that older adults may present age-related spectral processing difficulties, but further FFR studies are needed to clarify the effect of advancing age on the neural encoding of spectral speech cues. Spectral processing research on aging would benefit from using a broader variety of stimuli and from rigorously controlling for hearing thresholds even in the absence of disabling hearing loss. Advances in the understanding of the effect of age on FFR measures of spectral encoding could lead to the development of new clinical tools, with possible applications in the field of hearing aid fitting.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".