Measuring the spatial extent of texture pooling using reverse correlation

Daniel H. Baker*, Tim Meese

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The local image representation produced by early stages of visual analysis is uninformative regarding spatially extensive textures and surfaces. We know little about the cortical algorithm used to combine local information over space, and still less about the area over which it can operate. But such operations are vital to support perception of real-world objects and scenes. Here, we deploy a novel reverse-correlation technique to measure the extent of spatial pooling for target regions of different areas placed either in the central visual field, or more peripherally. Stimuli were large arrays of micropatterns, with their contrasts perturbed individually on an interval-by-interval basis. By comparing trial-by-trial observer responses with the predictions of computational models, we show that substantial regions (up to 13 carrier cycles) of a stimulus can be monitored in parallel by summing contrast over area. This summing strategy is very different from the more widely assumed signal selection strategy (a MAX operation), and suggests that neural mechanisms representing extensive visual textures can be recruited by attention. We also demonstrate that template resolution is much less precise in the parafovea than in the fovea, consistent with recent accounts of crowding.

Original languageEnglish
Pages (from-to)52-58
Number of pages7
JournalVision Research
Early online date24 Feb 2014
Publication statusPublished - Apr 2014

Bibliographical note

© Copyright 2014 The Authors. Published by Elsevier Ltd. This is an Open Access article under the CC BY license (

Funding: EPSRC Grant EP/H000038/1.


  • Area summation
  • Max operator
  • Reverse correlation


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