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1

Gilchrist, James M., David Jerwood, and H. Sam Ismaiel. "Comparing and unifying slope estimates across psychometric function models." Perception & Psychophysics 67, no. 7 (October 2005): 1289–303. http://dx.doi.org/10.3758/bf03193560.

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2

Strasburger, Hans. "Converting between measures of slope of the psychometric function." Perception & Psychophysics 63, no. 8 (November 2001): 1348–55. http://dx.doi.org/10.3758/bf03194547.

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3

Turpin, Andrew, Darko Jankovic, and Allison McKendrick. "Identifying steep psychometric function slope quickly in clinical applications." Vision Research 50, no. 23 (November 2010): 2476–85. http://dx.doi.org/10.1016/j.visres.2010.08.032.

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4

Maloney, Laurence T. "The slope of the psychometric function at different wavelengths." Vision Research 30, no. 1 (January 1990): 129–36. http://dx.doi.org/10.1016/0042-6989(90)90132-5.

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5

Allen, Prudence, and Frederic Wightman. "Psychometric Functions for Children’s Detection of Tones in Noise." Journal of Speech, Language, and Hearing Research 37, no. 1 (February 1994): 205–15. http://dx.doi.org/10.1044/jshr.3701.205.

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This article reports the results of an experiment that used a two-alternative forced-choice task to measure the ability of 3- to 5-year-old children to detect 501 Hz, 1000 Hz, and 2818 Hz sinusoids in noise. Psychometric functions were fit to each individual’s data, and thresholds (signal level required for 75% correct) were interpolated from the fitted functions. Results showed that, on average, the children’s thresholds were higher and the slopes of their psychometric functions were shallower than those of the adults. However, the between-subjects variability in the children’s data was large, and the performance of many individual children was not well described by group mean performance. One-third of the children produced thresholds that were elevated by an average of 10 dB but psychometric function slopes that were adult-like. Another one-third of the children produced thresholds that were elevated relative to those of the adults by an average of 20 dB and psychometric function slopes that were very shallow. The data from a smaller group of children showed large variability in psychometric function slope and threshold, and for a very few children performance was at chance regardless of the signal level. A replication of the study several months later showed that for most listeners the individual patterns of performance persisted over time.
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6

Gold, Joshua I., Chi-Tat Law, Patrick Connolly, and Sharath Bennur. "Relationships Between the Threshold and Slope of Psychometric and Neurometric Functions During Perceptual Learning: Implications for Neuronal Pooling." Journal of Neurophysiology 103, no. 1 (January 2010): 140–54. http://dx.doi.org/10.1152/jn.00744.2009.

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Perceptual learning involves long-lasting improvements in the ability to perceive simple sensory stimuli. Some forms of perceptual learning are thought to involve an increasingly selective readout of sensory neurons that are most sensitive to the trained stimulus. Here we report novel changes in the relationship between the threshold and slope of the psychometric function during learning that are consistent with such changes in readout and can provide insights into the underlying neural mechanisms. In monkeys trained on a direction-discrimination task, perceptual improvements corresponded to lower psychometric thresholds and slightly shallower slopes. However, this relationship between threshold and slope was much weaker in comparable, ideal-observer “neurometric” functions of neurons in the middle temporal (MT) area, which represent sensory information used to perform the task and whose response properties did not change with training. We propose a linear/nonlinear pooling scheme to account for these results. According to this scheme, MT responses are pooled via linear weights that change with training to more selectively read out responses from the most sensitive neurons, thereby reducing predicted thresholds. An additional nonlinear (power-law) transformation does not change with training and causes the predicted psychometric function to become shallower as uninformative neurons are eliminated from the pooled signal. We show that this scheme is consistent with the measured changes in psychometric threshold and slope throughout training. The results suggest that some forms of perceptual learning involve improvements in a process akin to selective attention that pools the most informative neural signals to guide behavior.
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Kontsevich, Leonid L., and Christopher W. Tyler. "Distraction of attention and the slope of the psychometric function." Journal of the Optical Society of America A 16, no. 2 (February 1, 1999): 217. http://dx.doi.org/10.1364/josaa.16.000217.

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8

Mayer, Melanie J., and Christopher W. Tyler. "Invariance of the slope of the psychometric function with spatial summation." Journal of the Optical Society of America A 3, no. 8 (August 1, 1986): 1166. http://dx.doi.org/10.1364/josaa.3.001166.

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9

Wilson, Richard H., Carol A. Zizz, Janet E. Shanks, and G. Donald Causey. "Normative Data in Quiet, Broadband Noise, and Competing Message for Northwestern University Auditory Test No. 6 by a Female Speaker." Journal of Speech and Hearing Disorders 55, no. 4 (November 1990): 771–78. http://dx.doi.org/10.1044/jshd.5504.771.

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Two descriptive experiments were performed on a version of the Northwestern University Auditory Test No. 6 (NU No. 6) recorded by a female speaker that is included on an audio compact disc recently produced by the Department of Veterans Affairs. In Experiment 1, normative psychometric functions for the female speaker version of the NU No. 6 materials were established on 24 young adults for three monaural listening conditions (in quiet, in 60-dB SPL broadband noise, and in 60-dB SPL competing message). The 60-dB SPL broadband noise shifted the psychometric function for the NU No. 6 words 33 dB, whereas the 60-dB SPL competing message shifted the function only 18–22 dB. In contrast to the slopes of the quiet and noise conditions (4.5%/dB), the slope of the competing message function was more gradual (3.5%/dB). In Experiment 2, comparisons between the psychometric functions for the female and the original male speaker versions of NU No. 6 in quiet and in broadband noise were made on 8 young adults. In comparison to the psychometric functions for the male speaker version of NU No. 6, the functions for the female speaker version of NU No. 6 were displaced between the 10–90% correct points to higher sound-pressure levels by 10–13 dB in quiet and by 12–16 dB in noise. The difference in performance on the two versions of NU No. 6 is attributed to spectral differences between the two sets of materials that produced a calibration anomaly.
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10

Serrano-Pedraza, Ignacio, Kathleen Vancleef, Will Herbert, Maeve Woodhouse, and Jenny Read. "Determination of the slope of the psychometric function for different stereoacuity tasks." Journal of Vision 16, no. 12 (September 1, 2016): 838. http://dx.doi.org/10.1167/16.12.838.

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11

Tokutake, Tomoki, Norihiro Mita, Ken-Ichiro Kawamoto, Kazutaka Kani, and Akio Tabuchi. "Relation between Visual Acuity and Slope of Psychometric Function in Young Adults." i-Perception 2, no. 4 (May 2011): 308. http://dx.doi.org/10.1068/ic308.

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12

KING-SMITH, P. EWEN, and DAVID ROSE. "Principles of an Adaptive Method for Measuring the Slope of the Psychometric Function." Vision Research 37, no. 12 (June 1997): 1595–604. http://dx.doi.org/10.1016/s0042-6989(96)00310-0.

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13

Gros, Bryan L., David R. Pope, and Theodore E. Cohn. "Noise location and the slope of the psychometric function for simple motion stimuli." Journal of the Optical Society of America A 16, no. 3 (March 1, 1999): 718. http://dx.doi.org/10.1364/josaa.16.000718.

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14

HORNER, DOUGLAS G., ADELE D. PAUL, BEVERLEY KATZ, and HAROLD E. BEDELL. "Variations in the Slope of the Psychometric Acuity Function with Acuity Threshold and Scale." Optometry and Vision Science 62, no. 12 (December 1985): 895–900. http://dx.doi.org/10.1097/00006324-198512000-00011.

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15

Serrano-Pedraza, Ignacio, Kathleen Vancleef, William Herbert, Nicola Goodship, Maeve Woodhouse, and Jenny C. A. Read. "Efficient estimation of stereo thresholds: What slope should be assumed for the psychometric function?" PLOS ONE 15, no. 1 (January 2, 2020): e0226822. http://dx.doi.org/10.1371/journal.pone.0226822.

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16

Penner, M. J. "Tinnitus as a Source of Internal Noise." Journal of Speech, Language, and Hearing Research 29, no. 3 (September 1986): 400–406. http://dx.doi.org/10.1044/jshr.2903.400.

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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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17

Wallis, Stuart A., Daniel H. Baker, Tim S. Meese, and Mark A. Georgeson. "The slope of the psychometric function and non-stationarity of thresholds in spatiotemporal contrast vision." Vision Research 76 (January 2013): 1–10. http://dx.doi.org/10.1016/j.visres.2012.09.019.

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18

Sobon, Kathryn A., Nardine M. Taleb, Emily Buss, John H. Grose, and Lauren Calandruccio. "Psychometric function slope for speech-in-noise and speech-in-speech: Effects of development and aging." Journal of the Acoustical Society of America 145, no. 4 (April 2019): EL284—EL290. http://dx.doi.org/10.1121/1.5097377.

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19

Beattie, Randall C., and Michael J. M. Raffin. "Reliability of Threshold, Slope, and PB Max for Monosyllabic Words." Journal of Speech and Hearing Disorders 50, no. 2 (May 1985): 166–78. http://dx.doi.org/10.1044/jshd.5002.166.

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The Auditec recordings of the CID W-22 monosyllables were used to generate test and retest intelligibility functions on normally hearing listeners and subjects with mild-to-moderate sensorineural hearing loss. The normally hearing subjects were tested with 50-word lists at SPLs ranging from 15 to 50 dB. Lists of 25 words were used with the hearing-impaired group. The functions were analyzed to assess the reliability of threshold (50% point), slope (20%–80% points), and maximum intelligibility (PB max). The 50% point was obtained at 28 dB SPL for the normally hearing listeners and at a sensation level (SL) of 12 dB re spondaic thresholds for the hearing-impaired group. Very stable monosyllabic thresholds were found because 95% of the test-retest values were within 6 dB for both subject groups. Slopes of 4.9% per dB and 2.7% per dB were obtained for the normally hearing and hearing-impaired groups, respectively. Fair reliability was observed; 95% of the test-retest values encompassed a range of ± 1.9% per dB for the normally hearing subjects and ± 1.1% per dB for the hearing-impaired group. Although group slopes provide useful information for selecting the range and step size for generating psychometric functions, the value of routinely obtaining slope on an individual basis has not been demonstrated. Even though the same word lists were used for both test and retest measurements, reliability closely agreed with predicted results based on the binomial theorem. In contrast to the large variability for a single list of 25 words, very stable PB max scores were found when two or three scores were averaged on the plateau of the function.
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20

Mertes, Ian B., Erin C. Wilbanks, and Marjorie R. Leek. "Olivocochlear Efferent Activity Is Associated With the Slope of the Psychometric Function of Speech Recognition in Noise." Ear and Hearing 39, no. 3 (2018): 583–93. http://dx.doi.org/10.1097/aud.0000000000000514.

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21

Schilling, Tim, Alexander Leube, Arne Ohlendorf, and Siegfried Wahl. "Variable slope of the psychometric function for different spatial frequencies measured by the Tuebingen Contrast Sensitivity Test." Journal of Vision 18, no. 10 (September 1, 2018): 208. http://dx.doi.org/10.1167/18.10.208.

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22

Yoshor, Daniel, William H. Bosking, Bradley C. Lega, Ping Sun, and John H. R. Maunsell. "Local cortical function after uncomplicated subdural electrode implantation." Journal of Neurosurgery 108, no. 1 (January 2008): 139–44. http://dx.doi.org/10.3171/jns/2008/108/01/0139.

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Object Although subdural electrodes are routinely used to map regional brain function, it is unknown if the presence of these implants hinders local cortical function. The authors used psychophysical methods to measure the effect of uncomplicated electrode implantation on local cortical function. Methods Local field potentials were used to map receptive fields (RFs) for subdural electrodes that were unilaterally implanted on early visual cortex in 4 patients. After electrode implantation, patients did a task that required them to detect an orientation change in a flashing visual stimulus that was presented either inside the mapped RF or outside the RF in the diametrically opposite portion of the other hemifield. The size of the orientation change was varied to span a wide range of behavioral performance. Psychometric curves were generated by fitting behavioral responses to a logistic function. The threshold was defined as the point at which the fitted function crossed 50% detection. Results Data were well fit by the logistic function in all 4 patients for both RF and non-RF conditions. None of the volunteers tested showed a statistically significant difference in detection threshold, reaction time, or in the slope of the psychometric function for stimuli presented inside or outside the RF. Conclusions Subdural electrodes implanted for extraoperative monitoring do not impair psychophysical performance for a task based on stimuli lying within the RF for recording electrodes. This finding suggests that these electrodes can be used reliably for accurate assessment of regional neurological function.
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23

Harianawala, Jumana, Jason Galster, and Benjamin Hornsby. "Psychometric Comparison of the Hearing in Noise Test and the American English Matrix Test." Journal of the American Academy of Audiology 30, no. 04 (April 2019): 315–26. http://dx.doi.org/10.3766/jaaa.17112.

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AbstractThe hearing in noise test (HINT) is the most popular adaptive test used to evaluate speech in noise performance, especially in context of hearing aid features. However, the number of conditions that can be tested on the HINT is limited by a small speech corpus. The American English Matrix test (AEMT) is a new alternative adaptive speech in noise test with a larger speech corpus. The study examined the relationships between the performance of hearing aid wearers on the HINT and the AEMT.To examine whether there was a difference in performance of hearing aid wearers on the HINT and the AEMT. A secondary purpose, given the AEMT’s steep performance-intensity function, was to determine whether the AEMT is more sensitive to changes in speech recognition resulting from directional (DIR) microphone processing in hearing aids.A repeated measures design was used in this study. Multiple measurements were made on each subject. Each measurement involved a different experimental condition.Ten adults with hearing loss participated in this study.All participants completed the AEMT and HINT, using adaptive and fixed test formats while wearing hearing aids. Speech recognition was assessed in two hearing aid microphone settings—omnidirectional and fixed DIR. All testing was conducted via sound field presentation. Performance on HINT and AEMT were systematically compared across all test conditions using a linear model with repeated measures.The results of this study revealed that adult hearing aid users perform differently on the HINT and AEMT, with adaptive AEMT testing yielding significantly better (more negative) thresholds than the HINT. Slopes of performance intensity functions obtained by testing at multiple fixed signal-to-noise ratios, revealed a somewhat steeper slope for the HINT compared with the AEMT. Despite this steeper slope, the benefit provided by DIR microphones was not significantly different between the two speech tests.The observation of similar DIR benefits of the HINT and AEMT suggests that the HINT and AEMT are equally sensitive to changes in speech recognition thresholds following intervention. Therefore, the decision to use the AEMT or the HINT will depend on the purpose of the study and/or the technology being investigated. Other test related factors such as available sentence corpus, learning effects and test time will also influence test selection.
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Hoover, Eric, Anna Diedesch, Frederick J. Gallun, and David A. Eddins. "Comparison of scoring methods for spatial release from masking for speech based on analysis of psychometric function slope." Journal of the Acoustical Society of America 142, no. 4 (October 2017): 2676–77. http://dx.doi.org/10.1121/1.5014758.

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25

Olsson, Peter, Robin D. Johnsson, James J. Foster, John D. Kirwan, Olle Lind, and Almut Kelber. "Chicken colour discrimination depends on background colour." Journal of Experimental Biology 223, no. 24 (October 23, 2020): jeb209429. http://dx.doi.org/10.1242/jeb.209429.

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ABSTRACTHow well can a bird discriminate between two red berries on a green background? The absolute threshold of colour discrimination is set by photoreceptor noise, but animals do not perform at this threshold; their performance can depend on additional factors. In humans and zebra finches, discrimination thresholds for colour stimuli depend on background colour, and thus the adaptive state of the visual system. We have tested how well chickens can discriminate shades of orange or green presented on orange or green backgrounds. Chickens discriminated slightly smaller colour differences between two stimuli presented on a similarly coloured background, compared with a background of very different colour. The slope of the psychometric function was steeper when stimulus and background colours were similar but shallower when they differed markedly, indicating that background colour affects the certainty with which the animals discriminate the colours. The effect we find for chickens is smaller than that shown for zebra finches. We modelled the response to stimuli using Bayesian and maximum likelihood estimation and implemented the psychometric function to estimate the effect size. We found that the result is independent of the psychophysical method used to evaluate the effect of experimental conditions on choice performance.
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Liu, Danzheng, and Lu-Feng Shi. "Performance-Intensity Functions of Mandarin Word Recognition Tests in Noise: Test Dialect and Listener Language Effects." American Journal of Audiology 22, no. 1 (June 2013): 147–56. http://dx.doi.org/10.1044/1059-0889(2013/12-0047).

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Purpose This study established the performance-intensity function for Beijing and Taiwan Mandarin bisyllabic word recognition tests in noise in native speakers of Wu Chinese. Effects of the test dialect and listeners' first language on psychometric variables (i.e., slope and 50%-correct threshold) were analyzed. Method Thirty-two normal-hearing Wu-speaking adults who used Mandarin since early childhood were compared to 16 native Mandarin-speaking adults. Both Beijing and Taiwan bisyllabic word recognition tests were presented at 8 signal-to-noise ratios (SNRs) in 4-dB steps (−12 dB to +16 dB). At each SNR, a half list (25 words) was presented in speech-spectrum noise to listeners' right ear. The order of the test, SNR, and half list was randomized across listeners. Listeners responded orally and in writing. Results Overall, the Wu-speaking listeners performed comparably to the Mandarin-speaking listeners on both tests. Compared to the Taiwan test, the Beijing test yielded a significantly lower threshold for both the Mandarin- and Wu-speaking listeners, as well as a significantly steeper slope for the Wu-speaking listeners. Conclusion Both Mandarin tests can be used to evaluate Wu-speaking listeners. Of the 2, the Taiwan Mandarin test results in more comparable functions across listener groups. Differences in the performance-intensity function between listener groups and between tests indicate a first language and dialectal effect, respectively.
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Höchenberger, Richard, and Kathrin Ohla. "Repeatability of Taste Recognition Threshold Measurements with QUEST and Quick Yes–No." Nutrients 12, no. 1 (December 20, 2019): 24. http://dx.doi.org/10.3390/nu12010024.

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Taste perception, although vital for nutrient sensing, has long been overlooked in sensory assessments. This can, at least in part, be attributed to challenges associated with the handling of liquid, perishable stimuli, but also with scarce efforts to optimize testing procedures to be more time-efficient. We have previously introduced an adaptive, QUEST-based procedure to measure taste sensitivity thresholds that was quicker than other existing approaches, yet similarly reliable. Despite its advantages, the QUEST procedure lacks experimental control of false alarms (i.e., response bias) and psychometric function slope. Variations of these parameters, however, may also influence the threshold estimate. This raises the question as to whether a procedure that simultaneously assesses threshold, false-alarm rate, and slope might be able to produce threshold estimates with higher repeatability, i.e., smaller variation between repeated measurements. Here, we compared the performance of QUEST with a method that allows measurement of false-alarm rates and slopes, quick Yes–No (qYN), in a test–retest design for citric acid, sodium chloride, quinine hydrochloride, and sucrose recognition thresholds. We used complementary measures of repeatability, namely test–retest correlations and coefficients of repeatability. Both threshold procedures yielded largely overlapping thresholds with good repeatability between measurements. Together the data suggest that participants used a conservative response criterion. Furthermore, we explored the link between taste sensitivity and taste liking or which we found, however, no clear association.
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Jaschinski, W. "Fixation Disparity as a Function of Viewing Distance and Prism Load." Perception 25, no. 1_suppl (August 1996): 76. http://dx.doi.org/10.1068/v96p0211.

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In binocular vision, fixation disparity is present when a fixation point falls within Panum's area, but not on corresponding retinal points. To investigate the effect of vergence load, fixation disparity was measured at viewing distances of 20, 30, 40, 60, and 100 cm (while the test subtended a constant angular size) by the psychophysical method of dichoptically presented nonius lines with a central fusion stimulus. As the viewing distance was shortened from 100 to 20 cm, mean fixation disparity changed monotonically from 1 min arc esophoria (ie the eyes converged in front of the target) to 3 min arc exophoria. The average standard deviation of the psychometric function, which is a measure of the temporal variability of vergence, was smallest at 100 cm (when fixation disparity was esophoric) and increased at shorter distances. Fixation disparity was also measured at a constant distance of 40 cm, but with prisms in front of the eyes that induced the same vergence angles as would be induced by viewing distances between 20 and 100 cm. The slope of these conventional ‘fixation disparity curves’ as a function of prism load correlated with the slope of fixation disparity as a function of viewing distance ( r=0.39, p=0.02, n=25). However, testing at different distances, as introduced here, has the advantage of preserving the natural interaction between vergence and accommodation. Since the change of fixation disparity with distance differed reliably among subjects (with a test — retest correlation of 0.65 in 34 subjects with good binocular vision) this measure may be useful for identifying subjects who are prone to near-vision complaints.
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Carkeet, Andrew, Linda Lee, Jennifer R. Kerr, and Maile M. Keung. "The Slope of the Psychometric Function for Bailey-Lovie Letter Charts: Defocus Effects and Implications for Modeling Letter-By-Letter Scores." Optometry and Vision Science 78, no. 2 (February 2001): 113–21. http://dx.doi.org/10.1097/00006324-200102000-00012.

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30

Sutu, Adrian, El-Mehdi Meftah, and C. Elaine Chapman. "Physical determinants of the shape of the psychophysical curve relating tactile roughness to raised-dot spacing: implications for neuronal coding of roughness." Journal of Neurophysiology 109, no. 5 (March 1, 2013): 1403–15. http://dx.doi.org/10.1152/jn.00717.2012.

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There are conflicting reports as to whether the shape of the psychometric relation between perceived roughness and tactile element spacing [spatial period (SP)] follows an inverted U-shape or a monotonic linear increase. This is a critical issue because the former result has been used to assess neuronal codes for roughness. We tested the hypothesis that the relation's shape is critically dependent on tactile element height (raised dots). Subjects rated the roughness of low (0.36 mm)- and high (1.8 mm)-raised-dot surfaces displaced under their fingertip. Inverted U-shaped curves were obtained as the SP of low-dot surfaces was increased (1.3–6.2 mm, tetragonal arrays); a monotonic increase was observed for high-dot surfaces. We hypothesized that roughness is not a single sensory continuum across the tested SPs of low-dot surfaces, predicting that roughness discrimination would show deviations from the invariant relation between threshold (ΔS) and the value of the standard (S) surface (Weber fraction, ΔS/S) expected for a single continuum. The results showed that Weber fractions were increased for SPs on the descending limb of the inverted U-shaped curve. There was also an increase in the Weber fraction for high-dot surfaces but only at the peak (3 mm), corresponding to the SP at which the slope of the psychometric function showed a modest decline. Together the results indicate that tactile roughness is not a continuum across low-dot SPs of 1.3–6.2 mm. These findings suggest that correlating the inverted U-shaped function with neuronal codes is of questionable validity. A simple intensive code may well contribute to tactile roughness.
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Elmer, Stefan, Carina Klein, Jürg Kühnis, Franziskus Liem, Martin Meyer, and Lutz Jäncke. "Music and Language Expertise Influence the Categorization of Speech and Musical Sounds: Behavioral and Electrophysiological Measurements." Journal of Cognitive Neuroscience 26, no. 10 (October 2014): 2356–69. http://dx.doi.org/10.1162/jocn_a_00632.

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In this study, we used high-density EEG to evaluate whether speech and music expertise has an influence on the categorization of expertise-related and unrelated sounds. With this purpose in mind, we compared the categorization of speech, music, and neutral sounds between professional musicians, simultaneous interpreters (SIs), and controls in response to morphed speech–noise, music–noise, and speech–music continua. Our hypothesis was that music and language expertise will strengthen the memory representations of prototypical sounds, which act as a perceptual magnet for morphed variants. This means that the prototype would “attract” variants. This so-called magnet effect should be manifested by an increased assignment of morphed items to the trained category, by a reduced maximal slope of the psychometric function, as well as by differential event-related brain responses reflecting memory comparison processes (i.e., N400 and P600 responses). As a main result, we provide first evidence for a domain-specific behavioral bias of musicians and SIs toward the trained categories, namely music and speech. In addition, SIs showed a bias toward musical items, indicating that interpreting training has a generic influence on the cognitive representation of spectrotemporal signals with similar acoustic properties to speech sounds. Notably, EEG measurements revealed clear distinct N400 and P600 responses to both prototypical and ambiguous items between the three groups at anterior, central, and posterior scalp sites. These differential N400 and P600 responses represent synchronous activity occurring across widely distributed brain networks, and indicate a dynamical recruitment of memory processes that vary as a function of training and expertise.
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32

Kaernbach, Christian. "Slope bias of psychometric functions derived from adaptive data." Perception & Psychophysics 63, no. 8 (November 2001): 1389–98. http://dx.doi.org/10.3758/bf03194550.

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33

Cameron, Sharon, Nicky Chong-White, Kiri Mealings, Tim Beechey, Harvey Dillon, and Taegan Young. "The Phoneme Identification Test for Assessment of Spectral and Temporal Discrimination Skills in Children: Development, Normative Data, and Test–Retest Reliability Studies." Journal of the American Academy of Audiology 29, no. 02 (February 2018): 135–50. http://dx.doi.org/10.3766/jaaa.16145.

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AbstractPrevious research suggests that a proportion of children experiencing reading and listening difficulties may have an underlying primary deficit in the way that the central auditory nervous system analyses the perceptually important, rapidly varying, formant frequency components of speech.The Phoneme Identification Test (PIT) was developed to investigate the ability of children to use spectro-temporal cues to perceptually categorize speech sounds based on their rapidly changing formant frequencies. The PIT uses an adaptive two-alternative forced-choice procedure whereby the participant identifies a synthesized consonant-vowel (CV) (/ba/ or /da/) syllable. CV syllables differed only in the second formant (F2) frequency along an 11-step continuum (between 0% and 100%—representing an ideal /ba/ and /da/, respectively). The CV syllables were presented in either quiet (PIT Q) or noise at a 0 dB signal-to-noise ratio (PIT N).Development of the PIT stimuli and test protocols, and collection of normative and test–retest reliability data.Twelve adults (aged 23 yr 10 mo to 50 yr 9 mo, mean 32 yr 5 mo) and 137 typically developing, primary-school children (aged 6 yr 0 mo to 12 yr 4 mo, mean 9 yr 3 mo). There were 73 males and 76 females.Data were collected using a touchscreen computer. Psychometric functions were automatically fit to individual data by the PIT software. Performance was determined by the width of the continuum for which responses were neither clearly /ba/ nor /da/ (referred to as the uncertainty region [UR]). A shallower psychometric function slope reflected greater uncertainty. Age effects were determined based on raw scores. Z scores were calculated to account for the effect of age on performance. Outliers, and individual data for which the confidence interval of the UR exceeded a maximum allowable value, were removed. Nonparametric tests were used as the data were skewed toward negative performance.Across participants, the median value of the F2 range that resulted in uncertain responses was 33% in quiet and 40% in noise. There was a significant effect of age on the width of this UR (p < 0.00001) in both quiet and noise, with performance becoming adult like by age 9 on the PIT Q and age 10 on the PIT N. A skewed distribution toward negative performance occurred in both quiet (p = 0.01) and noise (p = 0.006). Median UR scores were significantly wider in noise than in quiet (T = 2041, p < 0.0000001). Performance (z scores) across the two tests was significantly correlated (r = 0.36, p = 0.000009). Test–retest z scores were significantly correlated in both quiet and noise (r = 0.4 and 0.37, respectively, p < 0.0001).The PIT normative data show that the ability to identify phonemes based on changes in formant transitions improves with age, and that some children in the general population have performance much worse than their age peers. In children, uncertainty increases when the stimuli are presented in noise. The test is suitable for use in planned studies in a clinical population.
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34

Recanzone, G. H., W. M. Jenkins, G. T. Hradek, and M. M. Merzenich. "Progressive improvement in discriminative abilities in adult owl monkeys performing a tactile frequency discrimination task." Journal of Neurophysiology 67, no. 5 (May 1, 1992): 1015–30. http://dx.doi.org/10.1152/jn.1992.67.5.1015.

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1. Adult owl monkeys were trained to detect a difference in the frequency of sequentially applied tactile stimuli presented to a constant, restricted location on the glabrous skin of a single finger. Psychophysical performance functions and thresholds were determined on daily sessions over a 3- to 20-wk-long training period. 2. Thresholds for the trained digit progressively decreased from a 6- to 8-Hz difference to a 2- to 3-Hz difference relative to a 20-Hz standard. These thresholds were similar to those described for macaques and humans determined by the use of a two-alternative forced-choice procedure. 3. Six of the seven studied monkeys showed a continuously progressive improvement in performance with training. Early in the training period, the performance improved at about the same rate for all frequencies. Later in the training period, the performance for frequencies much greater than the comparison frequency improved sooner than did the performances for frequencies more similar to the comparison frequency. This resulted in an increase of the slope of the psychometric function near threshold. In a single monkey, no clear later-component improvements were recorded. 4. Analyses of performances using the theory of signal detection revealed a progressive increase in the measure of d' for all frequencies above threshold. 5. Some improvements in performance were also recorded when stimuli were applied on an adjacent digit, which was trained for 2 or 3 sessions spaced throughout the course of training. However, thresholds on these digits were always greater than those on the trained digit. These findings suggest that there are local changes generated by this training at somatotopically restricted regions of the central somatosensory nervous system. 6. It is concluded that this training resulted in a genuine progressive improvement in temporal acuity specific to the trained skin. The initial rapid improvement was likely due to an improvement in the "strategy" or "cognitive" aspects of the task, whereas more gradual improvements in performance recorded throughout the training period were most probably due to somatotopically localized changes in the neural representations of the behaviorally relevant stimulus.
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35

Tolhurst, David J., and Yoav Tadmor. "Discrimination of Changes in the Slopes of the Amplitude Spectra of Natural Images: Band-Limited Contrast and Psychometric Functions." Perception 26, no. 8 (August 1997): 1011–25. http://dx.doi.org/10.1068/p261011.

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Thresholds were measured for discriminating changes in the slopes of the amplitude spectra of stimuli derived from photographs of natural scenes and from random-luminance patterns. The variety and magnitudes of the thresholds could be explained by a model based on the discrimination of the changes in band-limited local contrast. Different spatial scales of local contrast (or different spatial-frequency bands of about 1 octave) were implicated for different reference spectral slopes; the model implicated a lower frequency-band for stimuli with shallower amplitude spectra. The implications of the model were tested experimentally by using stimuli in which the spectra were changed within restricted spatial-frequency bands. When the amplitude spectra of the test and reference stimuli differed only within the implicated frequency bands, thresholds were affected little. However, when the test and reference spectra differed at all frequencies except those in the implicated bands, the thresholds were elevated markedly. The forms of the psychometric functions for the discrimination task were entirely compatible with the hypothesis that the task relies upon the ability to discriminate changes of contrast. The Weibull functions fitted to the data had slope parameters (β) in the range 1 to 3, compatible with discrimination of low (but suprathreshold) contrasts.
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36

Carkeet, Andrew, and Ian L. Bailey. "Slope of psychometric functions and termination rule analysis for low contrast acuity charts." Ophthalmic and Physiological Optics 37, no. 2 (February 17, 2017): 118–27. http://dx.doi.org/10.1111/opo.12357.

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37

MacPherson, Alexandra, and Michael A. Akeroyd. "Variations in the Slope of the Psychometric Functions for Speech Intelligibility: A Systematic Survey." Trends in Hearing 18 (June 6, 2014): 233121651453772. http://dx.doi.org/10.1177/2331216514537722.

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38

Schairer, Kim S., Jessica Messersmith, and Walt Jesteadt. "Psychometric‐function slopes for forward‐masked tones in listeners with cochlear hearing loss." Journal of the Acoustical Society of America 117, no. 4 (April 2005): 2599. http://dx.doi.org/10.1121/1.4809469.

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39

Schairer, Kim S., Jessica Messersmith, and Walt Jesteadt. "Use of psychometric-function slopes for forward-masked tones to investigate cochlear nonlinearity." Journal of the Acoustical Society of America 124, no. 4 (October 2008): 2196–215. http://dx.doi.org/10.1121/1.2968686.

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40

Allen, Prudence, and Frederic Wightman. "Effects of Signal and Masker Uncertainty on Children’s Detection." Journal of Speech, Language, and Hearing Research 38, no. 2 (April 1995): 503–11. http://dx.doi.org/10.1044/jshr.3802.503.

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This paper reports the results of two experiments that examined the effects of signal and masker uncertainty on preschool-age children’s and adults’ detection of tonal signals in noise maskers. In Experiment 1 (signal uncertainty) the signal was randomly at 501 or 2818 Hz. The majority of the adult listeners showed a slight decrement in performance consistent with an ability to monitor both frequencies simultaneously. The majority of the children, however, showed no decrement in performance, suggesting that the children may not have focused attention at the signal frequency even when it was fixed. In Experiment 2 (masker uncertainty), random-frequency, random-level, tonal distracters were added to each interval of the 2 alternative-forced-choice (2afc) procedure. The effect of masker uncertainty was much larger than that of signal uncertainty. For most of the adult listeners and some of the children, the distracters produced higher thresholds (on average by 10 dB) and shallower psychometric function slopes. For most of the children, thresholds increased by 20 dB or more and psychometric functions were often nearly flat. This paper reports the results of two experiments that examined the effects of signal and masker uncertainty on preschool-age children's and adults' detection of tonal signals in noise maskers. In Experiment 1 (signal uncertainty) the signal was randomly at 501 or 2818 Hz. The majority of the adult listeners showed a slight decrement in performance consistent with an ability to monitor both frequencies simultaneously. The majority of the children, however, showed no decrement in performance, suggesting that the children may not have focused attention at the signal frequency even when it was fixed. In Experiment 2 (masker uncertainty), random-frequency, random-level, tonal distracters were added to each interval of the 2 alternative-forced-choice (2afc) procedure. The effect of masker uncertainty was much larger than that of signal uncertainty. For most of the adult listeners and some of the children, the distracters produced higher thresholds (on average by 10 dB) and shallower psychometric function slopes. For most of the children, thresholds increased by 20 dB or more and psychometric functions were often nearly flat.
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41

Marshall, Lynne, and Thomas E. Hanna. "Evaluation of Stopping Rules for Audiological Ascending Test Procedures Using Computer Simulations." Journal of Speech, Language, and Hearing Research 32, no. 2 (June 1989): 265–73. http://dx.doi.org/10.1044/jshr.3202.265.

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Stopping rules for ascending audiological test procedures were evaluated by Monte Carlo simulation. The stopping rules differed in the minimum number of responses required at a level, whether these responses occurred on half or a majority of the ascending series, and whether all or only the most recent ascending series were considered. For all procedures, shallow psychometric function slopes yielded estimated thresholds closer to the level giving 50% detection than did steeper slopes, which yielded estimated thresholds roughly 2.5 dB above the level corresponding to 50% on the psychometric function. Shallow slopes also resulted in decreased reliability across threshold measurements, an increased number of trials required for threshold estimates, and a higher proportion of measurements that had to be repeated. Stopping rules using a two-response criterion were faster than those using a three-response criterion, with only a small decrease in reliability. Among stopping rules using the same number of responses for criterion, differences were seen primarily in efficiency for shallow slopes, particularly for procedures using a three-response rather than a two-response criterion for stopping. Results from these simulations should be useful to standards groups.
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42

Buss, Emily, Joseph W. Hall, and John H. Grose. "Psychometric functions for pure tone intensity discrimination: Slope differences in school-aged children and adults." Journal of the Acoustical Society of America 125, no. 2 (February 2009): 1050–58. http://dx.doi.org/10.1121/1.3050273.

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43

Wilson, Richard H., John P. Preece, and Courtney S. Crowther. "Enhancement of Word-Recognition Performance With a Filtering Technique." Journal of Speech, Language, and Hearing Research 34, no. 6 (December 1991): 1436–38. http://dx.doi.org/10.1044/jshr.3406.1436.

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The NU No. 6 materials spoken by a female speaker were passed through a notch filter centered at 247 Hz with a 34-dB depth The filtering reduced the amplitude range within the spectrum of the materials by 10 dB that was reflected as a 7.5-vu reduction measured on a true vu meter. Thus, the notch filtering in effect changed the level calibration of the materials. Psychometric functions of the NU No. 6 materials filtered and unfiltered in 60-dB SPL broadband noise were obtained from 12 listeners with normal hearing. Although the slopes of the functions for the two conditions were the same, the functions were displaced by an average of 5 8 dB with the function for the filtered materials located at the lower sound-pressure levels.
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44

Yasin, Ifat, and Christopher J. Plack. "Slopes of psychometric functions for forward‐masked tones with and without a suppressor." Journal of the Acoustical Society of America 123, no. 5 (May 2008): 3857. http://dx.doi.org/10.1121/1.2935705.

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45

Rohde, Melanie S., Alexandra L. Georgescu, Kai Vogeley, Rolf Fimmers, and Christine M. Falter-Wagner. "Absence of sex differences in mental rotation performance in autism spectrum disorder." Autism 22, no. 7 (August 4, 2017): 855–65. http://dx.doi.org/10.1177/1362361317714991.

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Mental rotation is one of the most investigated cognitive functions showing consistent sex differences. The ‘Extreme Male Brain’ hypothesis attributes the cognitive profile of individuals with autism spectrum disorder to an extreme version of the male cognitive profile. Previous investigations focused almost exclusively on males with autism spectrum disorder with only limited implications for affected females. This study is the first testing a sample of 12 female adults with high-functioning autism spectrum disorder compared to 14 males with autism spectrum disorder, 12 typically developing females and 14 typically developing males employing a computerised version of the mental rotation test. Reaction time and accuracy served as dependent variables. Their linear relationship with degree of rotation allows separation of rotational aspects of the task, indicated by slopes of the psychometric function, and non-rotational aspects, indicated by intercepts of the psychometric function. While the typical and expected sex difference for rotational task aspects was corroborated in typically developing individuals, no comparable sex difference was found in autism spectrum disorder individuals. Autism spectrum disorder and typically developing individuals did not differ in mental rotation performance. This finding does not support the extreme male brain hypothesis of autism.
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46

Shen, Yi, and Virginia M. Richards. "A maximum-likelihood procedure for estimating psychometric functions: Thresholds, slopes, and lapses of attention." Journal of the Acoustical Society of America 132, no. 2 (August 2012): 957–67. http://dx.doi.org/10.1121/1.4733540.

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47

Gelfand, Stanley A., and Jessica T. Gelfand. "Psychometric Functions for Shortened Administrations of a Speech Recognition Approach Using Tri-Word Presentations and Phonemic Scoring." Journal of Speech, Language, and Hearing Research 55, no. 3 (June 2012): 879–91. http://dx.doi.org/10.1044/1092-4388(2011/11-0123).

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Method Complete psychometric functions for phoneme and word recognition scores at 8 signal-to-noise ratios from −15 dB to 20 dB were generated for the first 10, 20, and 25, as well as all 50, three-word presentations of the Tri-Word or Computer Assisted Speech Recognition Assessment (CASRA) Test (Gelfand, 1998) based on the results of 12 normal-hearing young adult participants from the original study. Results The psychometric functions for both phoneme and word scores were very similar and essentially overlapping for all set sizes. Performance on the shortened tests accounted for 98.8% to 99.5% of the full (50-set) test variance with phoneme scoring, and 95.8% to 99.2% of the full test variance with word scoring. Shortening the tests accounted for little if any of the variance in the slopes of the functions. Conclusions The psychometric functions for abbreviated versions of the Tri-Word speech recognition test using 10, 20, and 25 presentation sets were described and are comparable to those of the original 50-presentation approach for both phoneme and word scoring in healthy, normal-hearing, young adult participants.
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48

Rodríguez, Joyce, Stephen T. Neely, Walt Jesteadt, Hongyang Tan, and Michael P. Gorga. "Comparison of distortion-product otoacoustic emission growth rates and slopes of forward-masked psychometric functions." Journal of the Acoustical Society of America 129, no. 2 (February 2011): 864–75. http://dx.doi.org/10.1121/1.3523340.

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49

Jesteadt, Walt, Stephen T. Neely, and Kim S. Schairer. "Estimating the form of the peripheral nonlinearity from slopes of psychometric functions in forward masking." Journal of the Acoustical Society of America 111, no. 5 (2002): 2358. http://dx.doi.org/10.1121/1.4777930.

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50

Arehart, Kathryn Hoberg, Edward M. Burns, and Robert S. Schlauch. "A Comparison of Psychometric Functions for Detection in Normal-Hearing and Hearing-Impaired Listeners." Journal of Speech, Language, and Hearing Research 33, no. 3 (September 1990): 433–39. http://dx.doi.org/10.1044/jshr.3303.433.

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Psychometric functions (PFD) for the detection of pure tones were obtained with a two-interval forced-choice procedure from a group of listeners with normal hearing and a group of listeners with sensorineural impairments of presumed cochlear origin. Five PFDs were obtained for each group at each of the four test frequencies (500, 2000, 4000, and 8000 Hz). The slopes of PFDs were abnormally steep in some of the hearing-impaired listeners, but were statistically significant only at 2000 Hz.
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