A simple single-interval adaptive procedure for estimating thresholds in normal and impaired listeners

Abstract

This report presents a single-interval adaptive procedure for measuring thresholds in untrained normal and impaired listeners. The accuracy of the procedure is evaluated using Monte Carlo methods and human data allowing a method to be proposed for deciding in advance the number of trials required to achieve a specified level of accuracy. The number of trials depends on the slope of the psychometric function. The slope of the psychometric function is evaluated in normal and impaired listeners, and is found to give a useful guide to the required number of trials. The single-interval up/down procedure is subsequently compared with two other popular traditional methods ͑two-interval forced-choice, two-down/one-up and maximum-likelihood procedures͒ and is shown to yield similar thresholds and be more efficient.

The single interval adjustment matrix (SIAM) yes–no task: an empirical assessment using auditory and gustatory stimuli

“…The MLE YN task mostly assumes an underlying psychometric function based on the logistic function (Green, 1990). This assumption has not been found to be robust (e.g., Lecluyse & Meddis, 2009), though Gu and Green (1994) argued this finding away, claiming that because the threshold estimates produced by the procedure are consistent with others reported in the literature, it is a moot point whether these assumptions are upheld. However, Lecluyse and Meddis reported that psychometric functions do differ across clinical groups, and a universal form should not be assumed; this stance was supported by Leek (2001).…”

“…It soon became apparent after Green's (1990) initial description of the MLE YN task that threshold estimates could be significantly different from those reported in the literature (Green, 1993). Since then, it has been consistently demonstrated (e.g., Baker & Rosen, 2001;Green, 1995;Gu & Green, 1994;Lecluyse & Meddis, 2009;Leek, 2001) that the MLE YN task is extremely unforgiving of errors that occur early in a track, especially in the first five trials (Gu & Green, 1994). Such mistakes are more likely to be made with naive participants than experienced ones, and because of this issue the MLE YN task cannot be relied on to give estimates of true threshold with untrained participants.…”

“…These misleading estimates were modelled by Green (1995) as lapses in attention, and he concluded that the MLE YN task can severely underestimate or overestimate true thresholds, depending on when the attentional lapses occur. However, Lecluyse and Meddis (2009) demonstrated that these erroneous threshold estimates can be explained by processes intrinsic to the MLE YN task itself, rather than by factors associated with the participant. Though Gu and Green offer a correction for unintended errors, the number of trials necessary to use the correction effectively eliminates any efficiency gains and introduces additional complexity into the procedure.…”

The psychophysics of absolute threshold and signal duration: A probabilistic approach

“…A single-interval, adaptive, up-down procedure was used throughout as described and evaluated by Lecluyse and Meddis (2009). Data were collected from eight NH and eight hearing-impaired listeners.…”

Increased intensity discrimination thresholds in tinnitus subjects with a normal audiogram

“…Comparison sounds (pure tones of 250, 500, 1000, 1500, 2000, 3000, 4000, 6000, 8000, 12 000, and 16 000 Hz) were generated using custom-made MATLAB software and were presented via Sennheiser HD600 headphones. The comparison tones were first matched to the loudness of the tinnitus using a singleinterval adaptive procedure (Lecluyse and Meddis, 2009). During loudness matching, sound intensity was limited to levels 100 dB SPL.…”