Are psychophysical scales of intensities the same or different when stimuli vary on other dimensions? Theory with experiments varying loudness and pitch.

Luce, R. Duncan; Steingrimsson, Ragnar; Narens, Louis

doi:10.1037/a0020174

Cited by 27 publications

(94 citation statements)

References 28 publications

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“…Sensory organs and early sensory processing can expand or compress the signals from the world, and these signals are often subjected to some corruption-typically described as Gaussian internal noise. Though this classic model is by no means complete (e.g., Luce, Steingrimsson, & Narens, 2010;Steingrimsson & Luce, 2012), it remains highly influential and is widely used in cognitive, comparative, and developmental psychology, as well as neuroscience and computational modeling. This classic psychophysical model traditionally has two parameters: (1) the degree of psychophysical scaling (e.g., the power law exponent β, variously named in the literature as β, a, n, r, and slope; Laming, 1997;Stevens, 1964), which is thought to reflect the underlying compression or expansion of the external signal onto the internal scale (e.g., how the means of the Gaussian activations change with increasing stimulus intensity), and (2) the inherent variability, or noise, in the Gaussian activations along the scale, which linearly scales with the mean (σ, also discussed in the literature as CV, the Weber fraction, JND, or k; Laming, 1997).…”

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confidence: 99%

PsiMLE: A maximum-likelihood estimation approach to estimating psychophysical scaling and variability more reliably, efficiently, and flexibly

Odic

Eisinger

et al. 2015

Behav Res

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A simple and popular psychophysical model-usually described as overlapping Gaussian tuning curves arranged along an ordered internal scale-is capable of accurately describing both human and nonhuman behavioral performance and neural coding in magnitude estimation, production, and reproduction tasks for most psychological dimensions (e.g., time, space, number, or brightness). This model traditionally includes two parameters that determine how a physical stimulus is transformed into a psychological magnitude: (1) an exponent that describes the compression or expansion of the physical signal into the relevant psychological scale (β), and (2) an estimate of the amount of inherent variability (often called internal noise) in the Gaussian activations along the psychological scale (σ). To date, linear slopes on log-log plots have traditionally been used to estimate β, and a completely separate method of averaging coefficients of variance has been used to estimate σ. We provide a respectful, yet critical, review of these traditional methods, and offer a tutorial on a maximum-likelihood estimation (MLE) and a Bayesian estimation method for estimating both β and σ [PsiMLE(β,σ)], coupled with free software that researchers can use to implement it without a background in MLE or Bayesian statistics (R-PsiMLE). We demonstrate the validity, reliability, efficiency, and flexibility of this method through a series of simulations and behavioral experiments, and find the new method to be superior to the traditional methods in all respects.

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confidence: 99%

PsiMLE: A maximum-likelihood estimation approach to estimating psychophysical scaling and variability more reliably, efficiently, and flexibly

Odic

Eisinger

et al. 2015

Behav Res

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“…We contend that the ratio scale is more fit for defining outcome satisfaction, than the difference scale. First, the ratio scale is dimensionless and does not depend on the measurement units of the divided goods; second, it is the standard scale in psychophysics, starting with Fechner's law [33] and Steven's power law [34,35] to more recent theories of audio and visual perception [36] and signal detection [37]; third, the ratio scale is very common in physics, biology, evolution, and other exact sciences; fourth, all types of statistical measures are applicable to ratio scales, and only with these scales may we properly indulge in logarithmic transformations [34].…”

Section: Introductionmentioning

confidence: 99%

Economic Harmony: An Epistemic Theory of Economic Interactions

Suleiman

2017

Games

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Abstract:We propose an epistemic theory of micro-economic interactions, termed Economic Harmony. In the theory, we modify the standard utility, by changing its argument from the player's actual payoff, to the ratio between the player's actual payoff and his or her aspired payoff. We show that the aforementioned minor epistemic modification of the concept of utility is quite powerful in generating plausible and successful predictions of experimental results, obtained in the standard ultimatum game, and the sequential common pool resource dilemma (CPR) game. Notably, the cooperation and fairness observed in the studied games are accounted for without adding an other-regarding component in the players' utility functions. For the standard ultimatum game, the theory predicts a division of φ and 1 − φ, for the proposer and responder, respectively, where φ is the famous Golden Ratio (≈0.618), most known for its aesthetically pleasing properties. We discuss possible extensions of the proposed theory to repeated and evolutionary ultimatum games.

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“…The current evidence is that p only changes with the sign of p -1 (Luce, Steingrimsson, & Narens, 2010;Steingrimsson & Luce, 2007;Steingrimsson, Luce, & Narens, in press). …”

Section: The Production Equationmentioning

confidence: 76%

Predictions about bisymmetry and cross-modal matches from global theories of subjective intensities.

Luce¹

2012

Psychological Review

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The article first summarizes the assumptions of Luce (2004, 2008) for inherently binary (2-D) stimuli (e.g., the ears and eyes) that lead to a "p-additive," order-preserving psychophysical representation. Next, a somewhat parallel theory for unary (1-D) signals is developed for intensity attributes such as linear extent, vibration to finger, and money. The 3rd section studies the property of bisymmetry in these 2 cases. For the 2-D case and the nontrivial p-additive forms, Proposition 3 shows that bisymmetry implies commutativity of the presentations. Bisymmetry has been empirically well sustained, whereas commutativity has been rejected for loudness, brightness, and perceived contrast, thus implying that pure additivity must obtain in the 2-D context. By contrast, bisymmetry and commutativity are automatically satisfied by the p-additive 1-D theory. The 4th section explores the resulting complex of cross-modal predictions. For the additive 1-D case and the 2-D case, the predictions are power functions. For the nonadditive 1-D cases, other relations are predicted (see Table 2). Some parameter estimation issues are taken up in Appendices B and C.

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Are psychophysical scales of intensities the same or different when stimuli vary on other dimensions? Theory with experiments varying loudness and pitch.

Abstract: Does the theory extend to other intensive continua (prothetic attributes)? If so, which ones? And does it extend to cross-modal matching?

Cited by 27 publications

References 28 publications

PsiMLE: A maximum-likelihood estimation approach to estimating psychophysical scaling and variability more reliably, efficiently, and flexibly

PsiMLE: A maximum-likelihood estimation approach to estimating psychophysical scaling and variability more reliably, efficiently, and flexibly

Economic Harmony: An Epistemic Theory of Economic Interactions

Predictions about bisymmetry and cross-modal matches from global theories of subjective intensities.

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