Evaluating the Modulation Transfer Function of Auditory Steady State Responses in the 65 Hz to 120 Hz Range
Bibliographic record
Abstract
In Brief Objective: Auditory steady state response (ASSR) tests allow frequency-specific assessment of the auditory system. The responses can be elicited with long-duration tones that are modulated at particular rates. The literature has reported that some rates may evoke larger responses than others. Modulation transfer functions (MTFs), which show ASSR response as a function of modulation rate, can be created by presenting a fixed carrier with a modulation rate that is swept over time. Here, we explore the profiles of MTFs with particular effort made toward examining (1) the rates in the MTF that provided the maximum and minimum values, (2) the means and ranges of ASSRs within each MTF, and (3) MTF test-retest repeatability. Because recording ASSRs to a 500-Hz carrier frequency is often difficult at 60 dB SPL or less, we focused our efforts on this frequency. The main objective of this study was to evaluate the possibility of using MTFs for the purpose of identifying both optimal and unfavorable modulation rates. Design: Fifty-four normal hearing adult subjects were allocated to one of four experimental conditions. The first two conditions used a 500-Hz carrier and generated MTFs where modulation rate was varied continuously across a low (66 to 102 Hz) or high (86 to 121 Hz) range. In two additional conditions, a 500-Hz carrier having a modulation rate fixed at 82 Hz and a 2000-Hz carrier having a swept modulation rate (66- to 102-Hz range) were also obtained for comparison. Stimuli were presented at 60 dB SPL. The two ranges of modulation were used because these have implications for the generators and characteristics of the evoked responses. Responses were analyzed for each condition using a Fourier analyzer. To assess the stability of the MTF, two recordings, of 25 mins each, were obtained for each subject. Results: MTF profiles and modulation rates associated with maximum and minimum amplitudes clearly demonstrated repeatability between the two recordings. More specifically, modulation rates for the maximum and minimum amplitudes showed correlations above 0.92 between the two recordings. Using combined data from the two replications, we found that differences between maximum and minimum amplitudes were between 34 and 51 nV when modulation rate was varied. For the fixed modulation rate condition, the difference was only 22 nV, which was due to fluctuations in noise. Response amplitude and noise estimates obtained in this study suggest that ∼30% of individuals would require at least 10 mins more recording time if an actual hearing test was performed using the modulation rate associated with the ASSR amplitude minimum rather than the maximum. For some individuals, the ASSR would not be detected in a practical amount of time if the wrong modulation rate were relied upon during a clinical test. Conclusions: In research applications requiring repeated measurements, or clinical contexts such as intraoperative monitoring or assessment of aided hearing, setting stimulus modulation rate parameters based on a previous analysis of an individual's MTF could be extremely beneficial. Sufficient time must be spent in recording the MTF to adequately attenuate the contribution of noise to the ASSR amplitude estimates. Modulation transfer functions for the auditory steady state response were obtained for a 500 Hz carrier with modulation rates between 66 and 121 Hz. A modulation range between 66 and 102 Hz was also examined using a 2-kHz carrier for comparison. Two 25-minute recordings were made with each subject and repeatability was demonstrated. While some subjects have relative flat modulation transfer functions, about 30% of individuals show enough variation that recording time could be extended by 10 minutes or more were an inappropriate modulation rate selected. For some subjects, their worst modulation rate would fail to elicit a detectable response in a practical amount of time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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) | 0.000 | 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".