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Modeling Müller-Lyer Illusion Using Information Geometry

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Data Intelligence and Cognitive Informatics

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

The present paper investigates the variation of the strength of illusion as a function of different geometrical parameters of the Müller-Lyer stimulus. The illusory effects are quantified through psychometric experiments. Experimental data are fitted with model constructed on neurophysiological evidence and information geometry. The goodness of fit between the experimental and simulated data are computed using the p value of \(\chi^{2}\) measure and found > 99% on an average. The foundation of the model is the population coding of Müller-Lyer stimulus through filtering by difference of Gaussian filter representing the center surround receptive field with adaptive scale factors. It is further hypothesized that in the visual cortex (V1) the population code of the neurons images the stimulus on a visual space which is essentially a statistical parametric space with constant negative curvature (hyperbolic space). Fisher-Rao information distance function appears to be the natural measure of proper distance in this space. Application of information geometric model in real-life problem is also discussed.

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Author information

Authors and Affiliations

  1. CDAC, Plot-E2/1, Block-GP, Sector-V, Salt Lake City, Kolkata, 700091, India

    Debasis Mazumdar, Soma Mitra & Kamales Bhaumik

  2. DISIM, L’aquila, Italy

    Mainak Mandal

  3. Center for Soft Computing Research and Machine Intelligence Unit, Indian Statistical Institute, 203 B T Road, Kolkata, 108, India

    Kuntal Ghosh

Authors
  1. Debasis Mazumdar
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  2. Soma Mitra
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  3. Mainak Mandal
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  4. Kuntal Ghosh
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  5. Kamales Bhaumik
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Corresponding author

Correspondence to Debasis Mazumdar .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, GITAM University, Bangalore, Karnataka, India

    I. Jeena Jacob

  2. Department of Mathematics and Computer Science, Ashland University, River Forest, IL, USA

    Selvanayaki Kolandapalayam Shanmugam

  3. Department of Artificial Intelligence, Lviv Polytechnic National University, Lviv, Ukraine

    Ivan Izonin

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Mazumdar, D., Mitra, S., Mandal, M., Ghosh, K., Bhaumik, K. (2023). Modeling Müller-Lyer Illusion Using Information Geometry. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Izonin, I. (eds) Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-6004-8_1

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