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Effects of Spatial Frequency Similarity and Dissimilarity on Contour Integration

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  • Malte Persike
  • Günter Meinhardt

Abstract

We examined the effects of spatial frequency similarity and dissimilarity on human contour integration under various conditions of uncertainty. Participants performed a temporal 2AFC contour detection task. Spatial frequency jitter up to 3.0 octaves was applied either to background elements, or to contour and background elements, or to none of both. Results converge on four major findings. (1) Contours defined by spatial frequency similarity alone are only scarcely visible, suggesting the absence of specialized cortical routines for shape detection based on spatial frequency similarity. (2) When orientation collinearity and spatial frequency similarity are combined along a contour, performance amplifies far beyond probability summation when compared to the fully heterogenous condition but only to a margin compatible with probability summation when compared to the fully homogenous case. (3) Psychometric functions are steeper but not shifted for homogenous contours in heterogenous backgrounds indicating an advantageous signal-to-noise ratio. The additional similarity cue therefore not so much improves contour detection performance but primarily reduces observer uncertainty about whether a potential candidate is a contour or just a false positive. (4) Contour integration is a broadband mechanism which is only moderately impaired by spatial frequency dissimilarity.

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  • Malte Persike & Günter Meinhardt, 2015. "Effects of Spatial Frequency Similarity and Dissimilarity on Contour Integration," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-19, June.
    • Handle: RePEc:plo:pone00:0126449
    DOI: 10.1371/journal.pone.0126449
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    References listed on IDEAS

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    1. Li Zhaoping & Li Zhe, 2012. "Properties of V1 Neurons Tuned to Conjunctions of Visual Features: Application of the V1 Saliency Hypothesis to Visual Search behavior," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-15, June.
    2. Robert F. Hess & Steven C. Dakin, 1997. "Absence of contour linking in peripheral vision," Nature, Nature, vol. 390(6660), pages 602-604, December.
    3. Uri Polat & Keiko Mizobe & Mark W. Pettet & Takuji Kasamatsu & Anthony M. Norcia, 1998. "Collinear stimuli regulate visual responses depending on cell's contrast threshold," Nature, Nature, vol. 391(6667), pages 580-584, February.
    4. Aniruddha Das & Charles D. Gilbert, 1999. "Topography of contextual modulations mediated by short-range interactions in primary visual cortex," Nature, Nature, vol. 399(6737), pages 655-661, June.
    5. Udo A Ernst & Sunita Mandon & Nadja Schinkel–Bielefeld & Simon D Neitzel & Andreas K Kreiter & Klaus R Pawelzik, 2012. "Optimality of Human Contour Integration," PLOS Computational Biology, Public Library of Science, vol. 8(5), pages 1-17, May.
    6. Sophie Hall & Patrick Bourke & Kun Guo, 2014. "Low Level Constraints on Dynamic Contour Path Integration," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-9, June.
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