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Modeling the Weber Fraction of Vibrotactile Amplitudes Using Gain Control Through Global Feedforward Inhibition

  • Ken E. FriedlEmail author
  • Yao Qin
  • Daniel Ostler
  • Angelika Peer
Conference paper
  • 1.8k Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8619)

Abstract

Weber’s law describes the linear drop of discriminative performance with increased base intensity of a stimulus. So far, this phenomenon has been modeled using multistable attractor decision networks based on the principle of biased competition between two mutually inhibiting recurrent neural populations. Due to the sensitive balance in a multistable fluctuation-driven regime, these decision models can only account for Weber’s law in a narrow stimulus range. Psychophysical data shows though that the human exhibits this characteristic for a broad stimulus range. Recent neurophysiological evidence suggests that global feedforward inhibition expands the dynamic range of cortical neuron populations and acts as a gain control. In this paper, we introduce a computational model that exploits this type of inhibition and shows through a fit between simulation results and psychophysical data that it is a potential explanation for the principle mechanism behind Weber’s law.

Keywords

Weber’s law Decision making Attractor dynamics  Global inhibition 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Ken E. Friedl
    • 1
    Email author
  • Yao Qin
    • 1
  • Daniel Ostler
    • 1
  • Angelika Peer
    • 1
  1. 1.Institute of Automatic Control Engineering, Technische Universität MünchenMunichGermany

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