Frequency of Seeing Functions for Intensity Discrimination at Various Levels of Adapting Intensity

Mueller, Conrad G.

doi:10.1085/jgp.34.4.463

Cited by 52 publications

(34 citation statements)

References 7 publications

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“…Each plot shows the threshold (solid symbols) as a function of the value along a background dimension. For both targets, the threshold amplitude increased approximately linearly with local mean luminance in natural backgrounds (solid lines), in agreement with the classic finding of Weber's law reported for detection in uniform backgrounds (3,4). Similarly, the threshold amplitude increased linearly with background RMS contrast (at contrasts above a few percent), in agreement with the classic finding for detection in white noise (7) and more recent findings for targets in 1/f noise (22,24) and in Gaussianized natural backgrounds (22).…”

Section: Resultssupporting

confidence: 89%

“…The classic effects of masking-increases in threshold with background luminance, contrast, and similarity to the target-were primarily discovered and then explored using simple backgrounds that did not randomly vary from trial to trial (4,5,8). Furthermore, the effects observed with these nonrandom backgrounds are similar to those we report here.…”

Section: Discussionsupporting

confidence: 62%

“…1). For example, the detectability of a target pattern with given amplitude decreases with increases in background luminance (3,4), background contrast (5-7), and the similarity of the spatial properties of the background to those of the target (8)(9)(10)(11)(12). In addition to the direct effects of such background properties, there are other factors that affect detection performance.…”

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confidence: 99%

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Constrained sampling experiments reveal principles of detection in natural scenes

Sebastian

Abrams

Geisler

2017

Proc. Natl. Acad. Sci. U.S.A.

124

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A fundamental everyday visual task is to detect target objects within a background scene. Using relatively simple stimuli, vision science has identified several major factors that affect detection thresholds, including the luminance of the background, the contrast of the background, the spatial similarity of the background to the target, and uncertainty due to random variations in the properties of the background and in the amplitude of the target. Here we use an experimental approach based on constrained sampling from multidimensional histograms of natural stimuli, together with a theoretical analysis based on signal detection theory, to discover how these factors affect detection in natural scenes. We sorted a large collection of natural image backgrounds into multidimensional histograms, where each bin corresponds to a particular luminance, contrast, and similarity. Detection thresholds were measured for a subset of bins spanning the space, where a natural background was randomly sampled from a bin on each trial. In low-uncertainty conditions, both the background bin and the amplitude of the target were fixed, and, in high-uncertainty conditions, they varied randomly on each trial. We found that thresholds increase approximately linearly along all three dimensions and that detection accuracy is unaffected by background bin and target amplitude uncertainty. The results are predicted from first principles by a normalized matched-template detector, where the dynamic normalizing gain factor follows directly from the statistical properties of the natural backgrounds. The results provide an explanation for classic laws of psychophysics and their underlying neural mechanisms.natural scene statistics | detection | masking | normalization | Weber's law V isual systems are the result of evolution by natural selection, and, as a consequence, their design is strongly constrained by the properties of natural visual stimuli and by the specific visual tasks performed to survive and reproduce. Thus, to understand the human visual system, it is critical to characterize natural visual stimuli and performance in natural visual tasks (1, 2).Perhaps the most fundamental visual task is to identify target objects in the natural backgrounds that surround us. It is known that the specific properties of a background can have a strong influence on detectability (Fig. 1). For example, the detectability of a target pattern with given amplitude decreases with increases in background luminance (3, 4), background contrast (5-7), and the similarity of the spatial properties of the background to those of the target (8-12). In addition to the direct effects of such background properties, there are other factors that affect detection performance. Specifically, under natural conditions, the strength (amplitude) and location of the target often randomly vary on every occasion, and the target typically appears against a different background scene on every occasion. The uncertainty created by the random amplitude and location of the target ("target...

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Section: Resultssupporting

confidence: 89%

Section: Discussionsupporting

confidence: 62%

mentioning

confidence: 99%

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Constrained sampling experiments reveal principles of detection in natural scenes

Sebastian

Abrams

Geisler

2017

Proc. Natl. Acad. Sci. U.S.A.

124

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“…Olfaction's differential sensitivity no longer seems inferior to that of other modalities, including vision and hearing, where k is approximately 10070 (i.e., 0.10) for successively presented stimuli (Mueller, 1951;Schacknow & Raab, 1973). Unacknowledged fluctuations in the stimulus are apparently responsible for olfaction's previous reputation.…”

Section: Resultsmentioning

confidence: 94%

Odor magnitude: Coarse vs. fine grain

Cain

1977

Perception & Psychophysics

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Despite a dismal reputation, olfaction's resolving power actually appears to be keen, especially when the contaminating influence of noise in the stimulus is discounted from psychophysical performance. In a previous investigation, subjects were able to resolve a change of 4% in the concentration of butyl alcohol. In the present experiment, these same subjects resolved a change of 9% in the concentration of amyl butyrate. The data imply that resolving power varies among odorants. The growth of odor intensity assessed by magnitude estimations of easily discriminable (i.e., grossly different) concentrations also varies among odorants. These observations prompt the question: Does an odorant for which resolution is relatively difficult lead to slower growth of perceived intensity with concentration than an odorant for which resolution is easy? In a scaling experiment, amyl butyrate indeed led to slower growth of intensity than butyl alcohol. Nevertheless, amyl alcohol, which permitted poorer resolution than butyl alcohol, led to approximately the same rate of growth as butyl alcohol. Accordingly, growth of odor intensity with concentration may correlate only weakly with resolving power.

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“…L'i I' wnere e 6 I is the standard deviation of the threshold) andtheWeberfraction depends on the form of the transducer function, and so can be used to determine the latter. Applying this procedure to Mueller's (1951) data for two subjects gave exponents of 0.5 and 0.6, and data obtained by Blackwell and Law (1958) from four SUbjects gave a mean of 1.1.…”

Section: ) What Is the Form Of The Transducer Function?mentioning

confidence: 87%

A statistical decision model for sensory discrimination which predicts Weber’s law and other sensory laws: Some results of a computer simulation

Treisman

1966

Perception & Psychophysics

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I. The Model"Weber's law stands as a milestone in psychological research. It is one of the first psychological laws worthy of the name, and it may prove to be of far greater and more general significance than the differential threshold problems that provided its initial formulation. In effect, it establishes a lawofpsychological relativity: subjective discriminations are not bound to absolute characteristics of stimuli but to relations between them." (Berelson & Steiner, 1964). This claim illustrates a conunon error among psychologists: the over-evaluation of "laws," whose discovery is taken as an end in itself for psychology. We need to substitute for this nineteenth century fallacy the appreciation that the observation of a behavioral regularity is not the conclusion to a psychological investigation, but a question inviting one; a "law" can only be said to be satisfactorily understood when we have a model of how the subject functions from which the observed behavior follows as a logical consequence. No grandiloquent generalization can substitute for this. The present paper arises from an attempt to examine whether we are yet in a position to devise such a model to account for Weber's law and some related findings (Treisman, 1964a); to examine the implications of the model devised it was simulated on a digital computer.The model as presented is intended to apply only to the simplest detection situation: determination of the increment or absolute threshold for a flash superimposed on a background of the same area or larger. Extra assumptions will be needed to extend it to more complex situations, such as determination of the CFF, Perception & Psychophysics, 1966, Vol. 1 but it will be better to add these assumptions when the basic model has been evaluated. It has been applied to visual thresholds since we know more about the absorption of energy by the receptors for vision than for other senses, but in principle it is capable of being adapted to any sense.The main assumptions on which the model rests are: (i) There is a statistical relation between the nominal intensity of a stimulus and its effect on the retinal receptors. The variation from trial to trial in the number of quanta absorbed from a light-flash of constant nominal intensity is described by a Poisson distribution. (ii) There is a statistical relation between the effect on the sense organ and the nervous message received centrally. Thus if the same number of quanta were absorbed by the receptors on more than one trial, sensory noise would nevertheless cause the number of nerve impulses arriving at the point where the threshold is determined to vary. (iii) The variation due to this sensory noise is, to somedegree,positivelycorrelated. (iv) A statistical decision procedure determines the response made.For the most part, these assumptions are not new. The last three could be adapted to apply to any sensory system, and would then account for the occurrence of Weber's law (Treisman, 1964a). A number of lesser assumptions are included in the model to give ...

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Frequency of Seeing Functions for Intensity Discrimination at Various Levels of Adapting Intensity

Cited by 52 publications

References 7 publications

Constrained sampling experiments reveal principles of detection in natural scenes

Constrained sampling experiments reveal principles of detection in natural scenes

Odor magnitude: Coarse vs. fine grain

A statistical decision model for sensory discrimination which predicts Weber’s law and other sensory laws: Some results of a computer simulation

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