scholarly journals Velocity Dependence of the Interocular Transfer of Dynamic Motion Aftereffects

Perception ◽  
10.1068/p3442 ◽  
2003 ◽  
Vol 32 (7) ◽  
pp. 855-866 ◽  
Author(s):  
Ran Tao ◽  
Martin J M Lankheet ◽  
Wim A van de Grind ◽  
Richard J A van Wezel
Keyword(s):  
Signal To Noise Ratio ◽  
Dominant Role ◽  
Dynamic Test ◽  
Interocular Transfer ◽  
Adaptation Stimulus ◽  
Motion Adaptation ◽  
Pixel Array ◽  
Noise Test ◽  
Motion Aftereffects ◽  
Measured Strength

It is well established that motion aftereffects (MAEs) can show interocular transfer (IOT); that is, motion adaptation in one eye can give a MAE in the other eye. Different quantification methods and different test stimuli have been shown to give different IOT magnitudes, varying from no to almost full IOT. In this study, we examine to what extent IOT of the dynamic MAE (dMAE), that is the MAE seen with a dynamic noise test pattern, varies with velocity of the adaptation stimulus. We measured strength of dMAE by a nulling method. The aftereffect induced by adaptation to a moving random-pixel array was compensated (nulled), during a brief dynamic test period, by the same kind of motion stimulus of variable luminance signal-to-noise ratio (LSNR). The LSNR nulling value was determined in a Quest-staircase procedure. We found that velocity has a strong effect on the magnitude of IOT for the dMAE. For increasing speeds from 1.5 deg s−1 to 24 deg s−1 average IOT values increased about linearly from 18% to 63% or from 32% to 83%, depending on IOT definition. The finding that dMAEs transfer to an increasing extent as speed increases, suggests that binocular cells play a more dominant role at higher speeds.

What is the Transition Point between Static and Dynamic Motion Aftereffects?

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 75-75
Author(s):  
H Ashida ◽  
F A J Verstraten ◽  
S Nishida
Keyword(s):  
Transition Point ◽  
Test Pattern ◽  
Dynamic Properties ◽  
Temporal Frequency ◽  
Dynamic Test ◽  
Interocular Transfer ◽  
Second Order ◽  
Adaptation Stimulus ◽  
Static Test ◽  
First Order

The motion aftereffect (MAE) measured with a dynamic test pattern (eg a counterphase-flickering grating) is distinguishable by a number of properties from the classical MAE obtained with a static test pattern. For a dynamic MAE, however, it is not sufficient simply to introduce dynamic properties into the test pattern. In two experiments we attempted to determine the transition point in the temporal-frequency domain at which a dynamic MAE becomes distinguishable from the static MAE. First, we examined the interocular transfer (IOT) of the MAE with conventional first-order (luminance) gratings. The amount of IOT increased with temporal frequency, and was almost complete at 1 Hz and above. In addition, the IOT of a dynamic MAE shows a drastic reduction in the peripheral visual field, possibly reflecting difficulties in feature tracking or the loss of involuntary attention. Second, we examined the MAE with second-order motion as the adaptation stimulus (contrast modulation of two-dimensional static noise). Under these conditions, similar results were obtained for first-order and second-order test gratings: MAE was not observed at low temporal frequencies and a substantial MAE was observed only at 1 Hz and above. The results agree with recent findings which showed a gradual loss of spatial-frequency selectivity with increasing temporal frequency of the test pattern (Mareschal et al, 1997 Vision Research37 1755 – 1759). The present results support the idea that two mechanisms underlie the different kinds of MAE: a low-level mechanism responsible for the MAE observed at low temporal frequencies, and a high-level mechanism operating predominantly at high temporal frequencies with a transition point at about 1 Hz.

scholarly journals Comparing the quick speech-in-noise test results in migraineurs without aura and normal subjects

2018 ◽  
Author(s):  
Sabihe Amini ◽  
Fahimeh Hajiabolhassan ◽  
Jamileh Fatahi ◽  
Shohreh Jalaie ◽  
Mohammad Hosein Nilforoush
Keyword(s):  
Speech Perception ◽  
Signal To Noise Ratio ◽  
Normal Subjects ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Speech In Noise ◽  
Headache Severity ◽  
Normal Individuals ◽  
Duration Of Disease ◽  
Noise Test

Background and Aim: Migraine is a relatively common neurovascular disease. Audiology studies have shown some ways of influencing migraine by the auditory pathways from cochlea to the auditory cortex. Considering that one of the most important functions of the central auditory system is speech perception in challenging conditions, the purpose of this study was to evaluate the ability to understand speech in noise in migraineurs without aura, and compare it with normal subjects.Methods: In this cross-sectional study, 30 migraineurs without aura aged 17 to 41 years (mean=31.9, SD=6.89) and 30 normal individuals who were matched for age and sex with the migraine group were evaluated by quick speech-in-noise test (Q-SIN). The correlation between duration of the disease and the frequency of attacks per month and signal-to-noise ratio (SNR) loss, as well as the role of headache severity on the scores were assessed.Results: In Q-SIN test, the mean SNR loss in migraineurs without aura was greater than that in controls (p<0.05). But this ability did not differ between males and females (p>0.05). There was no correlation between the duration of migraine, frequency of attacks per month and the severity of headache with SNR loss (p>0.05).Conclusion: Migraineurs without aura sometimes have difficulties in speech perception in noise which is not affected by duration of disease, its frequency and the severity of the attacks.

Local and Global Properties of Motion Aftereffects

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 170-170
Author(s):  
N J Wade ◽  
V Pardieu ◽  
M T Swanston
Keyword(s):  
Vision Research ◽  
Motion Aftereffect ◽  
Test Display ◽  
Adaptation Process ◽  
Local Motion ◽  
Motion Adaptation ◽  
Global Properties ◽  
Differential Adaptation ◽  
Induced Motion ◽  
Motion Aftereffects

The local motion adaptation at the basis of the motion aftereffect (MAE) can be expressed in a variety of ways, depending upon the structure of the test display (N J Wade, L Spillmann, M T Swanston Vision Research in press). This has been demonstrated with MAEs from induced motion: if adaptation is to two moving (Surround) gratings, an MAE is seen in the central grating if two gratings surround it, but in the flanking gratings when they are themselves surrounded in the test stimulus. We report two experiments in which the characteristics of the test display and of the local adaptation process have been examined. In experiment 1, five vertical gratings were presented during adaptation; the outermost and central gratings remained stationary and those flanking the centre moved laterally. The test display always consisted of three stationary gratings: either the central three or the lower three equivalent to the locations of the adaptation display. MAEs were only recorded in the Centre and not in the Surround, irrespective of whether the Centre or Surround had been exposed to motion during adaptation. MAEs in the Centre were in opposite directions, reflecting the influence of Surround adaptation. The influence of adapting motion in different directions was examined in experiment 2. The upper grating always received the same direction of motion during adaptation, and the lower grating was absent, stationary, or moving in the same or in the opposite direction. The results indicate that an MAE is visible in the upper grating only after differential adaptation between the upper and lower gratings.

Development of a quick speech-in-noise test for measuring signal-to-noise ratio loss in normal-hearing and hearing-impaired listeners

2004 ◽  
Vol 116 (4) ◽  
pp. 2395-2405 ◽  
Author(s):  
Mead C. Killion ◽  
Patricia A. Niquette ◽  
Gail I. Gudmundsen ◽  
Lawrence J. Revit ◽  
Shilpi Banerjee
Keyword(s):  
Signal To Noise Ratio ◽  
Normal Hearing ◽  
Hearing Impaired ◽  
Signal To Noise ◽  
Speech In Noise ◽  
Noise Test ◽  
Noise Ratio ◽  
Measuring Signal

Speech in noise testing before and after grommet insertion

2012 ◽  
Vol 126 (10) ◽  
pp. 1010-1015 ◽  
Author(s):  
V Possamai ◽  
G Kirk ◽  
A Scott ◽  
D Skinner
Keyword(s):  
Small Group ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Sound Field ◽  
Noise Signal ◽  
Signal To Noise ◽  
Speech In Noise ◽  
Before And After ◽  
Noise Test ◽  
Noise Ratio

AbstractObjectives:To assess the feasibility of designing and implementing a speech in noise test in children before and after grommet insertion, and to analyse the results of such a test in a small group of children.Methods:Twelve children aged six to nine years who were scheduled to undergo grommet insertion were identified. They underwent speech in noise testing before and after grommet insertion. This testing used Arthur Boothroyd word lists read at 60 dB in four listening conditions presented in a sound field: firstly in quiet conditions, then in signal to noise ratios of +10 (50 dB background noise), 0 (60 dB) and −10 (70 dB).Results:Mean phoneme scores were: in quiet conditions, 28.1 pre- and 30 post-operatively (p = 0.04); in 50 dB background noise (signal to noise ratio +10), 24.2 pre- and 29 post-operatively (p < 0.01); in 60 dB background noise (signal to noise ratio 0), 22.6 pre- and 27.5 post-operatively (p = 0.06); and in 70 dB background noise (signal to noise ratio −10), 13.9 pre- and 21 post-operatively (p = 0.05).Conclusion:This small study suggests that speech in noise testing is feasible in this scenario. Our small group of children demonstrated a significant improvement in speech in noise scores following grommet insertion. This is likely to translate into a significant advantage in the educational environment.

Diagnostic Accuracy of the AzBio Speech Recognition in Noise Test

2021 ◽  
pp. 1-14
Author(s):  
Andrew J. Vermiglio ◽  
Lauren Leclerc ◽  
Meagan Thornton ◽  
Hannah Osborne ◽  
Elizabeth Bonilla ◽  
...  
Keyword(s):  
Steady State ◽  
Speech Recognition ◽  
Diagnostic Accuracy ◽  
Signal To Noise Ratio ◽  
Area Under The Curve ◽  
Self Report ◽  
Reference Standard ◽  
Operating Characteristics ◽  
Noise Test ◽  
Speech Recognition In Noise

Purpose The goal of this study was to determine the ability of the AzBio speech recognition in noise (SRN) test to distinguish between groups of participants with and without a self-reported SRN disorder and a self-reported signal-to-noise ratio (SNR) loss. Method Fifty-four native English-speaking young adults with normal pure-tone thresholds (≤ 25 dB HL, 0.25–6.0 kHz) participated. Individuals who reported hearing difficulty in a noisy restaurant (Reference Standard 1) were placed in the SRN disorder group. SNR loss groups were created based on the self-report of the ability to hear Hearing in Noise Test (HINT) sentences in steady-state speech-shaped noise, four-talker babble, and 20-talker babble in a controlled listening environment (Reference Standard 2). Participants with HINT thresholds poorer than or equal to the median were assigned to the SNR loss group. Results The area under the curve from the receiver operating characteristics curves revealed that the AzBio test was not a significant predictor of an SRN disorder, or an SNR loss using the steady-state noise Reference Standard 2 condition. However, the AzBio was a significant predictor of an SNR loss using the four-talker babble and 20-talker babble Reference Standard 2 conditions ( p < .05). The AzBio was a significant predictor of an SNR loss when using the average HINT thresholds across the three Reference Standard 2 masker conditions (area under the curve = .79, p = .001). Conclusions The AzBio test was not a significant predictor of a self-reported SRN disorder or a self-reported SNR loss in steady-state noise. However, it was a significant predictor of a self-reported SNR loss in babble noise and the average across all noise conditions. A battery of reference standard tests with a range of maskers in a controlled listening environment is recommended for diagnostic accuracy evaluations of SRN tests.

Homogeneity of the 18 QuickSIN™ Lists

2006 ◽  
Vol 17 (03) ◽  
pp. 157-167 ◽  
Author(s):  
Rachel A. McArdle ◽  
Richard H. Wilson
Keyword(s):  
Hearing Loss ◽  
High Performance ◽  
Signal To Noise Ratio ◽  
Normal Hearing ◽  
Signal To Noise ◽  
Speech In Noise ◽  
Performance Variability ◽  
Noise Test ◽  
Noise Ratio ◽  
Db Difference

The purpose of this study was to determine the list equivalency of the 18 QuickSIN™ (Quick Speech in Noise test) lists. Individuals with normal hearing (n = 24) and with sensorineural hearing loss (n = 72) were studied. Mean recognition performances on the 18 lists by the listeners with normal hearing were 2.8 to 4.3 dB SNR (signal-to-noise ratio), whereas the range was 10.0 to 14.3 dB SNR for the listeners with hearing loss. The psychometric functions for each list showed high performance variability across lists for listeners with hearing loss but not for listeners with normal hearing. For listeners with hearing loss, Lists 4, 5, 13, and 16 fell outside of the critical difference. The data from this study suggest nine lists that provide homogenous results for listeners with and without hearing loss. Finally, there was an 8.7 dB difference in performances between the two groups indicating a more favorable signal-to-noise ratio required by the listeners with hearing loss to obtain equal performance.

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