Probability Summation in the Detection of Multiple Bar Patterns

1975 ◽  
Author(s):  
Stanley Klein
Keyword(s):  
Probability Summation

scholarly journals Combining Visual Contrast Information with Sound Can Produce Faster Decisions

2019 ◽  
Author(s):  
Birgitta Dresp-Langley ◽  
Marie Monfouga
Keyword(s):  
Response Times ◽  
Luminance Contrast ◽  
Forced Choice ◽  
Sound Frequency ◽  
Choice Response ◽  
Relative Depth ◽  
Probability Summation ◽  
Visual Contrast ◽  
Contrast Information ◽  
The Right

Pieron's and Chocholle’s seminal psychophysical work predicts that human response time to information relative to visual contrast and/or sound frequency decreases when contrast intensity or sound frequency increases. The goal of this study is to bring to the fore the ability of individuals to use visual contrast intensity and sound frequency in combination for faster perceptual decisions of relative depth (“nearer”) in planar (2D) object configurations on the basis of physical variations in luminance contrast. Computer controlled images with two abstract patterns of varying contrast intensity, one on the left and one on the right, preceded or not by a pure tone of varying frequency, were shown to healthy young humans in controlled experimental sequences. Their task (two-alternative forced-choice) was to decide as quickly as possible which of two patterns, the left or the right one, in a given image appeared to “stand out as if it were nearer” in terms of apparent (subjective) visual depth. The results show that the combinations of varying relative visual contrast with sounds of varying frequency exploited here produced an additive effect on choice response times in terms of facilitation, where a stronger visual contrast combined with a higher sound frequency produced shorter forced-choice response times. This new effect is predicted by cross-modal audio-visual probability summation.

Vibrotactile temporal summation: probability summation or neural integration?

1999 ◽  
Vol 16 (3) ◽  
pp. 229-242 ◽  
Author(s):  
George A. Gescheider ◽  
Marian E. Berryhill ◽  
Ronald T. Verrillo ◽  
Stanley J. Bolanowski
Keyword(s):  
Temporal Summation ◽  
Probability Summation ◽  
Neural Integration

The Binocular Summation of Chromatic Contrast

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 145-145 ◽  
Author(s):  
D R Simmons ◽  
F A A Kingdom
Keyword(s):  
Contrast Sensitivity ◽  
Detection Threshold ◽  
Luminance Contrast ◽  
Binocular Summation ◽  
Chromatic Contrast ◽  
Probability Summation ◽  
Investigative Ophthalmology ◽  
Contrast Thresholds ◽  
Detection Mechanisms ◽  
Neural Summation

The level of binocularity possessed by mechanisms sensitive to chromatic contrast is still unclear. Recent studies of stereopsis and chromatic contrast have suggested that stereopsis is maintained at isoluminance, although the contrast sensitivity and disparity ranges of chromatic stereopsis mechanisms are reduced compared to luminance stereopsis mechanisms. Rose, Blake, and Halpern (1988 Investigative Ophthalmology and Visual Science29 283 – 290) hypothesised a link between binocular summation (ie the superiority of binocular detection over monocular detection) and stereopsis. Is this link maintained with heterochromatic isoluminant stimuli? To address this question, the binocular and monocular contrast thresholds for the detection of 0.5 cycle deg−1 Gabor patches were measured. The stimuli possessed different relative amounts of colour and luminance contrast ranging from isoluminance (red/green) to isochrominance (yellow/black) through intermediate values. It was found that, with these stimuli, binocular detection was well modelled by assuming independent mechanisms sensitive to chromatic contrast and luminance contrast. Furthermore, with isoluminant stimuli, levels of binocular summation were above those expected from probability summation between the eyes, thus providing evidence for binocular neural summation within chromatic detection mechanisms. Given that stereoscopic depth identification is impossible at contrast detection threshold with isoluminant heterochromatic stimuli, these results suggest that the link between stereopsis and levels of binocular neural summation may not be a particularly strong one. These results also provide clear evidence for the binocularity of chromatic detection mechanisms.

A Method of Identification of Analyser Characteristics That is Free of Probability Summation Effect

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 245-245
Author(s):  
A D Logvinenko
Keyword(s):  
Decision Rule ◽  
Quadratic Forms ◽  
Diagonal Matrix ◽  
Weighted Sum ◽  
General Belief ◽  
Probability Summation ◽  
Detection Model ◽  
Similarity Transform ◽  
Summation Effect ◽  
The Matrix

A detection model (originally proposed by Quick) comprising, in a sequence of linear analysers, varphi1, …, varphi n, nonlinear transducer functions, and the Minkowski decision rule, is widely used, especially when it is necessary to take into account the effect of probability summation. However, there is a general belief that the analyser characteristics cannot be determined in detection experiments since there is a trade-off between these characteristics and the decision rule. Here we show how to overcome this problem, ie how to identify the analysers varphi1, …, varphi n despite the probability summation between them. The observer's performance is assumed to be quantitatively defined in terms of an equidetection surface (EDS). Each analyser varphi i is expressed as a weighted sum of linear (coordinate) analysers {phi j}: varphi i=sum j=1 n a ijphi j, so that an identification of the analysers {phi i} is then reduced to evaluating the weight matrix A={ a ij}. It has been proven that A can be uniquely recovered from an ellipsoidal approximation of EDS in the neighbourhood of at least two points. More specifically, the following equation holds true: A−1 DA= H1−1 H2, where D is a diagonal matrix, H1 and H2 are the matrices of the quadratic forms determining the n-dimensional ellipsoids approximating EDS. Thus, the matrix H1−1 H2 known from experiment is a similarity transform of the diagonal matrix, the columns of A being the eigenvectors of H1−1 H2. Hence, any eigensystem routine can be used to derive A from H1−1 H2.

scholarly journals Combining Visual Contrast Information with Sound Can Produce Faster Decisions

Information ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 346 ◽  
Author(s):  
Birgitta Dresp-Langley ◽  
Marie Monfouga
Keyword(s):  
Response Times ◽  
Luminance Contrast ◽  
Forced Choice ◽  
Sound Frequency ◽  
Choice Response ◽  
Relative Depth ◽  
Probability Summation ◽  
Visual Contrast ◽  
Contrast Information ◽  
The Right

Pieron’s and Chocholle’s seminal psychophysical work predicts that human response time to information relative to visual contrast and/or sound frequency decreases when contrast intensity or sound frequency increases. The goal of this study is to bring to the forefront the ability of individuals to use visual contrast intensity and sound frequency in combination for faster perceptual decisions of relative depth (“nearer”) in planar (2D) object configurations based on physical variations in luminance contrast. Computer controlled images with two abstract patterns of varying contrast intensity, one on the left and one on the right, preceded or not by a pure tone of varying frequency, were shown to healthy young humans in controlled experimental sequences. Their task (two-alternative, forced-choice) was to decide as quickly as possible which of two patterns, the left or the right one, in a given image appeared to “stand out as if it were nearer” in terms of apparent (subjective) visual depth. The results showed that the combinations of varying relative visual contrast with sounds of varying frequency exploited here produced an additive effect on choice response times in terms of facilitation, where a stronger visual contrast combined with a higher sound frequency produced shorter forced-choice response times. This new effect is predicted by audio-visual probability summation.

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