The impact of noise on auditory processing in children and adults: A time–frequency analysis perspective
Bibliographic record
Abstract
OBJECTIVE: The current study investigated the impact of listening conditions on cortical oscillatory activities in adults and children. EXPERIMENTAL PROCEDURE: Fifteen adults and 15 children participated in this study. Electrophysiological measures were recorded with 64 electrodes. Stimulation was presented binaurally with parameters modulation: stimuli, listening conditions, noise and SNR. Intertrial phase clustering (ITPC) and power values were computed using spatially filtered data and complex Morlet wavelets. Data were statistically analyzed with mixed factorial ANOVAs. RESULTS: In quiet, children exhibited stronger theta-alpha (ta-) ITPC than adults, especially for verbal stimuli, in bilateral temporal regions, while adults showed no regional differences. Beta-gamma (bg-) ITPC responses revealed that tonal stimuli only elicited stronger right temporal responses in children. Theta-alpha power was greater for tonal stimuli in children, while adults showed stronger right temporal responses. In noise, ta-ITPC reductions were more pronounced in children, especially in babble noise. In white noise, unlike babble noise, there was a systematic reduction of the ta-ITPC values as a function of the SNR level. The bg-ITPC responses were also weaker at lower than higher SNRs. Ta-Power was lower for tonal than verbal stimuli at the right electrode, with greater reductions in babble than in white noise. Bg-Power differences were observed only at the central electrode, where adults showed smaller reductions than children. DISCUSSION: Results indicated that phase and power measures are sensitive to parameter modulation and could be used to understand auditory processing in noise, as they revealed increased susceptibility to noise in children compared to 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".