Auditory Steady-State Responses to Exponential Modulation Envelopes
Bibliographic record
Abstract
OBJECTIVE: This study examined the steady-state responses evoked by tones modulated with exponential envelopes. The hypothesis was that stimuli with envelopes containing more rapid changes would evoke larger responses. DESIGN: Multiple auditory steady-state responses were recorded simultaneously to eight tonal stimuli, four in each ear. The carrier frequencies of the stimuli ranged from 500 to 6000 Hz and the modulation rates were between 75 and 95 Hz. The modulation envelopes were based on functions using sin' where N was 1, 2, 3, or 4. Setting N to 1 produced the traditional sinusoidal modulation. RESULTS: Exponential envelopes with N greater than 1 produced larger steady-state responses than a sinusoidal envelope. For amplitude-modulation (AM), exponential envelopes increased response amplitudes by 21% at 55 dB pSPL, and by 29% at 35 dB pSPL. The increases were smaller for carrier frequencies of 1500 to 2000 Hz than for lower and higher carrier frequencies. Latencies calculated from phase data increased significantly with increasing N. This was likely caused by the point of maximal envelope-slope shifting later in time as N increased. For frequency modulation (FM), the steady-state responses did not significantly change with changes in the power of the exponential envelopes. CONCLUSIONS: When tones are amplitude-modulated with exponential envelopes based on sin(N), the amplitude and latency of the steady-state response increased significantly with increasing N. Using exponential envelopes with N greater than 1 should considerably shorten the time needed for responses to become significant when using steady-state responses in objective audiometry.
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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".