Evidence of peripheral nonlinearity in psychometric function slopes of forward‐masked tones at 250 and 4000 Hz

2003 ◽  
Vol 113 (4) ◽  
pp. 2226-2226 ◽  
Author(s):  
Kim S. Schairer ◽  
Walt Jesteadt
Keyword(s):  
Psychometric Function ◽  
Peripheral Nonlinearity

The psychometric function of infants detecting broadband noise

1998 ◽  
Vol 21 ◽  
pp. 755
Author(s):  
Lynne A. Werner ◽  
Julianne M. Siebens
Keyword(s):  
Psychometric Function ◽  
Broadband Noise

scholarly journals Comparison of Behavioral and Physiological Measures of the Status of the Cochlear Nonlinearity

2021 ◽  
Vol 25 ◽  
pp. 233121652110161
Author(s):  
Michal Fereczkowski ◽  
Torsten Dau ◽  
Ewen N. MacDonald
Keyword(s):  
Otoacoustic Emissions ◽  
Hearing Impaired ◽  
Good Correspondence ◽  
Cochlear Nonlinearity ◽  
Temporal Masking ◽  
The Status ◽  
Peripheral Compression ◽  
Two Measures ◽  
Peripheral Nonlinearity ◽  
Fitting In

While an audiogram is a useful method of characterizing hearing loss, it has been suggested that including a complementary, suprathreshold measure, for example, a measure of the status of the cochlear active mechanism, could lead to improved diagnostics and improved hearing-aid fitting in individual listeners. While several behavioral and physiological methods have been proposed to measure the cochlear-nonlinearity characteristics, evidence of a good correspondence between them is lacking, at least in the case of hearing-impaired listeners. If this lack of correspondence is due to, for example, limited reliability of one of such measures, it might be a reason for limited evidence of the benefit of measuring peripheral compression. The aim of this study was to investigate the relation between measures of the peripheral-nonlinearity status estimated using two psychoacoustical methods (based on the notched-noise and temporal-masking curve methods) and otoacoustic emissions, on a large sample of hearing-impaired listeners. While the relation between the estimates from the notched-noise and the otoacoustic emissions experiments was found to be stronger than predicted by the audiogram alone, the relations between the two measures and the temporal-masking based measure did not show the same pattern, that is, the variance shared by any of the two measures with the temporal-masking curve-based measure was also shared with the audiogram.

Effects of peripheral nonlinearity on psychometric functions for forward-masked tones

2003 ◽  
Vol 113 (3) ◽  
pp. 1560-1573 ◽  
Author(s):  
Kim S. Schairer ◽  
Lance Nizami ◽  
Jason F. Reimer ◽  
Walt Jesteadt
Keyword(s):  
Peripheral Nonlinearity

The Psychometric Function: Continuation

2012 ◽  
pp. 141-166
Author(s):  
Kenneth Knoblauch ◽  
Laurence T. Maloney
Keyword(s):  
Psychometric Function

The Psychometric Function: Introduction

2012 ◽  
pp. 107-139
Author(s):  
Kenneth Knoblauch ◽  
Laurence T. Maloney
Keyword(s):  
Psychometric Function

scholarly journals Model-free estimation of the psychometric function

2010 ◽  
Vol 9 (8) ◽  
pp. 30-30 ◽  
Author(s):  
D. H. Foster ◽  
K. Zychaluk
Keyword(s):  
Psychometric Function ◽  
Model Free

scholarly journals Efficient estimation of stereo thresholds: what slope should be assumed for the psychometric function?

2019 ◽  
Author(s):  
Ignacio Serrano-Pedraza ◽  
Kathleen Vancleef ◽  
William Herbert ◽  
Nicola Goodship ◽  
Maeve Woodhouse ◽  
...  
Keyword(s):  
Psychometric Function ◽  
Population Distribution ◽  
Real Data ◽  
Logistic Function ◽  
Efficient Estimation ◽  
Threshold Estimate ◽  
Bayesian Procedure ◽  
Detection Thresholds ◽  
Bayesian Procedures ◽  
Wide Range

Bayesian staircases are widely used in psychophysics to estimate detection thresholds. Simulations have revealed the importance of the parameters selected for the assumed subject’s psychometric function in enabling thresholds to be estimated with small bias and high precision. One important parameter is the slope of the psychometric function, or equivalently its spread. This is often held fixed, rather than estimated for individual subjects, because much larger numbers of trials are required to estimate the spread as well as the threshold. However, if this fixed value is wrong, the threshold estimate can be biased. Here we determine the optimal slope to minimize bias and maximize precision when measuring stereoacuity with Bayesian staircases. We performed 2- and 4AFC disparity detection stereo experiments in order to measure the spread of the disparity psychometric function in human observers assuming a Logistic function. We found a wide range, between 0.03 and 3.5 log10 arcsec, with little change with age. We then ran simulations to examine the optimal spread using the real data. From our simulations and for three different experiments, we recommend selecting assumed spread values between the percentiles 60-80% of the population distribution of spreads (these percentiles can be extended to other type of thresholds). For stereo thresholds, we recommend a spread σ=1.7 log10 arcsec for 2AFC (slope 𝛽 = 4.3/log10 arcsec), and σ=1.5 log10 arcsec for 4AFC (𝛽 = 4.9/log10 arcsec). Finally, we compared a Bayesian procedure (ZEST using the optimal σ) with five Bayesian procedures that are versions of ZEST-2D, Psi, and Psi-marginal. In general, our recommended procedure showed the lowest threshold bias and highest precision.

Tinnitus as a Source of Internal Noise

1986 ◽  
Vol 29 (3) ◽  
pp. 400-406 ◽  
Author(s):  
M. J. Penner
Keyword(s):  
Hearing Loss ◽  
Sensorineural Hearing Loss ◽  
Psychometric Function ◽  
Correct Response ◽  
Internal Noise ◽  
Average Frequency ◽  
Maximum Frequency ◽  
Minimum Frequency ◽  
Frequency Matching ◽  
Pure Tones

For 7 patients with sensorineural hearing loss and tinnitus, pitch and loudness matches were made to the tinnitus. These matches were followed by measurement of three psychometric functions (probability of a correct response as a function of signal level) for pure tones, one in the presumed tinnitus region (i.e., at the average frequency matching the pitch of the tinnitus), one below the minimum frequency of the matches, and one above the maximum frequency of the matches. The data reveal (a) that pitch-loudness matches are usually quite variable and (b) that the slope of the psychometric function is flattest in the presumed tinnitus region. The first result is consistent with the idea that tinnitus is an unstable signal. The second result is consistent with the notion that the unstable tinnitus acts as a source of "internal" noise.

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