A two-stage model of orientation integration for Battenberg-modulated micropatterns

Alex S. Baldwin*, Jesse S. Husk, Tim S. Meese, Robert F. Hess

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The visual system pools information from local samples to calculate textural properties. We used a novel stimulus to investigate how signals are combined to improve estimates of global orientation. Stimuli were 29 × 29 element arrays of 4 c/deg log Gabors, spaced 1° apart. A proportion of these elements had a coherent orientation (horizontal/vertical) with the remainder assigned random orientations. The observer's task was to identify the global orientation. The spatial configuration of the signal was modulated by a checkerboard pattern of square checks containing potential signal elements. The other locations contained either randomly oriented elements (''noise check'') or were blank (''blank check''). The distribution of signal elements was manipulated by varying the size and location of the checks within a fixed-diameter stimulus. An ideal detector would only pool responses from potential signal elements. Humans did this for medium check sizes and for large check sizes when a signal was presented in the fovea. For small check sizes, however, the pooling occurred indiscriminately over relevant and irrelevant locations. For these check sizes, thresholds for the noise check and blank check conditions were similar, suggesting that the limiting noise is not induced by the response to the noise elements. The results are described by a model that filters the stimulus at the potential target orientations and then combines the signals over space in two stages. The first is a mandatory integration of local signals over a fixed area, limited by internal noise at each location. The second is a taskdependent combination of the outputs from the first stage.

Original languageEnglish
Article number30
Number of pages21
JournalJournal of Vision
Issue number1
Publication statusPublished - 30 Jan 2014

Bibliographical note

© 2014 ARVO

Funding: NSERCouncil (Canada) (#46528-11); EPSRC (UK) (#EP/H000038/1).


  • computational modeling
  • integration
  • orientation
  • summation
  • texture perception


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