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Extreme reaction times determine fluctuation scaling in human color vision

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  • Medina, José M.
  • Díaz, José A.

Abstract

In modern mental chronometry, human reaction time defines the time elapsed from stimulus presentation until a response occurs and represents a reference paradigm for investigating stochastic latency mechanisms in color vision. Here we examine the statistical properties of extreme reaction times and whether they support fluctuation scaling in the skewness–kurtosis plane. Reaction times were measured for visual stimuli across the cardinal directions of the color space. For all subjects, the results show that very large reaction times deviate from the right tail of reaction time distributions suggesting the existence of dragon-kings events. The results also indicate that extreme reaction times are correlated and shape fluctuation scaling over a wide range of stimulus conditions. The scaling exponent was higher for achromatic than isoluminant stimuli, suggesting distinct generative mechanisms. Our findings open a new perspective for studying failure modes in sensory–motor communications and in complex networks.

Suggested Citation

  • Medina, José M. & Díaz, José A., 2016. "Extreme reaction times determine fluctuation scaling in human color vision," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 125-132.
  • Handle: RePEc:eee:phsmap:v:461:y:2016:i:c:p:125-132
    DOI: 10.1016/j.physa.2016.05.030
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    References listed on IDEAS

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    1. Nicolas P. Cottaris & Russell L. De Valois, 1998. "Temporal dynamics of chromatic tuning in macaque primary visual cortex," Nature, Nature, vol. 395(6705), pages 896-900, October.
    2. Matteo Carandini, 2004. "Amplification of Trial-to-Trial Response Variability by Neurons in Visual Cortex," PLOS Biology, Public Library of Science, vol. 2(9), pages 1-1, August.
    3. Wang, Yanjun & Zhang, Qiqian & Zhu, Chenping & Hu, Minghua & Duong, Vu, 2016. "Human activity under high pressure: A case study on fluctuation scaling of air traffic controller’s communication behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 151-157.
    4. Didier Sornette & Guy Ouillon, "undated". "Dragon-kings: Mechanisms, statistical methods and empirical evidence," Working Papers ETH-RC-12-004, ETH Zurich, Chair of Systems Design.
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    Cited by:

    1. Medina, José M. & Díaz, José A., 2021. "A random multiplicative model of Piéron’s law and choice reaction times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).

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