Literature DB >> 8550938

On measuring psychometric functions: a comparison of the constant-stimulus and adaptive up-down methods.

H Dai1.   

Abstract

Psychometric functions were obtained using the conventional constant-stimulus method and an adaptive up-down method, for both computer-simulated and human observers. Except when the stimuli are closely placed, psychometric functions obtained with the adaptive method are as accurate as those obtained with the constant-stimulus method. Empirically, the adaptive method has some potential advantages owing to its ability to automatically concentrate the trials within the dynamic range of the psychometric function. It needs no pilot measurements for setting the signals as required by the constant-stimulus method. Furthermore, following a marked change in the underlying psychometric function, the distribution of the trials is automatically readjusted. Thus, on the basis of empirical considerations, the adaptive method is a better choice than the constant-stimulus method for measuring psychometric functions.

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Year:  1995        PMID: 8550938     DOI: 10.1121/1.413802

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  23 in total

1.  Cues for masked amplitude-modulation detection.

Authors:  Paul C Nelson; Laurel H Carney
Journal:  J Acoust Soc Am       Date:  2006-08       Impact factor: 1.840

2.  Neural correlates of tactile detection: a combined magnetoencephalography and biophysically based computational modeling study.

Authors:  Stephanie R Jones; Dominique L Pritchett; Steven M Stufflebeam; Matti Hämäläinen; Christopher I Moore
Journal:  J Neurosci       Date:  2007-10-03       Impact factor: 6.167

3.  The effect of signal-temporal uncertainty on detection in bursts of noise or a random-frequency complex.

Authors:  Angela Yarnell Bonino; Lori J Leibold
Journal:  J Acoust Soc Am       Date:  2008-11       Impact factor: 1.840

4.  Sensory constraints on auditory identification of the material and geometric properties of struck bars.

Authors:  Robert A Lutfi; Christophe N J Stoelinga
Journal:  J Acoust Soc Am       Date:  2010-01       Impact factor: 1.840

5.  Quantitative analysis and biophysically realistic neural modeling of the MEG mu rhythm: rhythmogenesis and modulation of sensory-evoked responses.

Authors:  Stephanie R Jones; Dominique L Pritchett; Michael A Sikora; Steven M Stufflebeam; Matti Hämäläinen; Christopher I Moore
Journal:  J Neurophysiol       Date:  2009-10-07       Impact factor: 2.714

6.  Relative effects of increment and pedestal duration on the detection of intensity increments.

Authors:  Daniel L Valente; Harisadhan Patra; Walt Jesteadt
Journal:  J Acoust Soc Am       Date:  2011-04       Impact factor: 1.840

7.  Comparison of distortion-product otoacoustic emission growth rates and slopes of forward-masked psychometric functions.

Authors:  Joyce Rodríguez; Stephen T Neely; Walt Jesteadt; Hongyang Tan; Michael P Gorga
Journal:  J Acoust Soc Am       Date:  2011-02       Impact factor: 1.840

8.  Psychometric functions for pure-tone frequency discrimination.

Authors:  Huanping Dai; Christophe Micheyl
Journal:  J Acoust Soc Am       Date:  2011-07       Impact factor: 1.840

9.  Amplitude modulation depth discrimination of a sinusoidal carrier: effect of stimulus duration.

Authors:  J Lee; S P Bacon
Journal:  J Acoust Soc Am       Date:  1997-06       Impact factor: 1.840

10.  Effect of signal-temporal uncertainty in children and adults: tone detection in noise or a random-frequency masker.

Authors:  Angela Yarnell Bonino; Lori J Leibold; Emily Buss
Journal:  J Acoust Soc Am       Date:  2013-12       Impact factor: 1.840

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