Test-Retest Variability in the Characteristics of Envelope Following Responses Evoked by Speech Stimuli
Bibliographic record
Abstract
OBJECTIVES: The objective of the present study was to evaluate the between-session test-retest variability in the characteristics of envelope following responses (EFRs) evoked by modified natural speech stimuli in young normal hearing adults. DESIGN: EFRs from 22 adults were recorded in two sessions, 1 to 12 days apart. EFRs were evoked by the token /susa∫ i/ (2.05 sec) presented at 65 dB SPL and recorded from the vertex referenced to the neck. The token /susa∫ i/, spoken by a male with an average fundamental frequency [f0] of 98.53 Hz, was of interest because of its potential utility as an objective hearing aid outcome measure. Each vowel was modified to elicit two EFRs simultaneously by lowering the f0 in the first formant while maintaining the original f0 in the higher formants. Fricatives were amplitude-modulated at 93.02 Hz and elicited one EFR each. EFRs evoked by vowels and fricatives were estimated using Fourier analyzer and discrete Fourier transform, respectively. Detection of EFRs was determined by an F-test. Test-retest variability in EFR amplitude and phase coherence were quantified using correlation, repeated-measures analysis of variance, and the repeatability coefficient. The repeatability coefficient, computed as twice the standard deviation (SD) of test-retest differences, represents the ±95% limits of test-retest variation around the mean difference. Test-retest variability of EFR amplitude and phase coherence were compared using the coefficient of variation, a normalized metric, which represents the ratio of the SD of repeat measurements to its mean. Consistency in EFR detection outcomes was assessed using the test of proportions. RESULTS: EFR amplitude and phase coherence did not vary significantly between sessions, and were significantly correlated across repeat measurements. The repeatability coefficient for EFR amplitude ranged from 38.5 nV to 45.6 nV for all stimuli, except for /∫/ (71.6 nV). For any given stimulus, the test-retest differences in EFR amplitude of individual participants were not correlated with their test-retest differences in noise amplitude. However, across stimuli, higher repeatability coefficients of EFR amplitude tended to occur when the group mean noise amplitude and the repeatability coefficient of noise amplitude were higher. The test-retest variability of phase coherence was comparable to that of EFR amplitude in terms of the coefficient of variation, and the repeatability coefficient varied from 0.1 to 0.2, with the highest value of 0.2 for /∫/. Mismatches in EFR detection outcomes occurred in 11 of 176 measurements. For each stimulus, the tests of proportions revealed a significantly higher proportion of matched detection outcomes compared to mismatches. CONCLUSIONS: Speech-evoked EFRs demonstrated reasonable repeatability across sessions. Of the eight stimuli, the shortest stimulus /∫/ demonstrated the largest variability in EFR amplitude and phase coherence. The test-retest variability in EFR amplitude could not be explained by test-retest differences in noise amplitude for any of the stimuli. This lack of explanation argues for other sources of variability, one possibility being the modulation of cortical contributions imposed on brainstem-generated EFRs.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".