Evaluating the Modulation Transfer Function of Auditory Steady State Responses in the 65 Hz to 120 Hz Range
Notice bibliographique
Résumé
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.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».