The Müller-lyer illusion in a computational model of biological object recognition

Astrid Zeman*, Oliver Obst, Kevin R. Brooks, Anina N. Rich

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    6 Citations (Scopus)
    255 Downloads (Pure)

    Abstract

    Studying illusions provides insight into the way the brain processes information. The Müller-Lyer Illusion (MLI) is a classical geometrical illusion of size, in which perceived line length is decreased by arrowheads and increased by arrowtails. Many theories have been put forward to explain the MLI, such as misapplied size constancy scaling, the statistics of image-source relationships and the filtering properties of signal processing in primary visual areas. Artificial models of the ventral visual processing stream allow us to isolate factors hypothesised to cause the illusion and test how these affect classification performance. We trained a feed-forward feature hierarchical model, HMAX, to perform a dual category line length judgment task (short versus long) with over 90% accuracy. We then tested the system in its ability to judge relative line lengths for images in a control set versus images that induce the MLI in humans. Results from the computational model show an overall illusory effect similar to that experienced by human subjects. No natural images were used for training, implying that misapplied size constancy and image-source statistics are not necessary factors for generating the illusion. A post-hoc analysis of response weights within a representative trained network ruled out the possibility that the illusion is caused by a reliance on information at low spatial frequencies. Our results suggest that the MLI can be produced using only feed-forward, neurophysiological connections.

    Original languageEnglish
    Article numbere56126
    Pages (from-to)1-9
    Number of pages9
    JournalPLoS ONE
    Volume8
    Issue number2
    DOIs
    Publication statusPublished - 15 Feb 2013

    Bibliographical note

    Copyright the Author(s) 2013. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

    Fingerprint

    Dive into the research topics of 'The Müller-lyer illusion in a computational model of biological object recognition'. Together they form a unique fingerprint.

    Cite this