Are v1 simple cells optimized for visual occlusions? A comparative study

PLoS Comput Biol. 2013;9(6):e1003062. doi: 10.1371/journal.pcbi.1003062. Epub 2013 Jun 6.

Abstract

Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they linked their receptive fields to the statistics of visual stimuli. However, a salient feature of image statistics, occlusions of image components, is not considered by these models. Here we ask if occlusions have an effect on the predicted shapes of simple cell receptive fields. We use a comparative approach to answer this question and investigate two models for simple cells: a standard linear model and an occlusive model. For both models we simultaneously estimate optimal receptive fields, sparsity and stimulus noise. The two models are identical except for their component superposition assumption. We find the image encoding and receptive fields predicted by the models to differ significantly. While both models predict many Gabor-like fields, the occlusive model predicts a much sparser encoding and high percentages of 'globular' receptive fields. This relatively new center-surround type of simple cell response is observed since reverse correlation is used in experimental studies. While high percentages of 'globular' fields can be obtained using specific choices of sparsity and overcompleteness in linear sparse coding, no or only low proportions are reported in the vast majority of studies on linear models (including all ICA models). Likewise, for the here investigated linear model and optimal sparsity, only low proportions of 'globular' fields are observed. In comparison, the occlusive model robustly infers high proportions and can match the experimentally observed high proportions of 'globular' fields well. Our computational study, therefore, suggests that 'globular' fields may be evidence for an optimal encoding of visual occlusions in primary visual cortex.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computational Biology
  • Humans
  • Models, Theoretical
  • Vision, Ocular*
  • Visual Cortex / cytology*

Grants and funding

The work was funded by the German Research Foundation (DFG) grant LU 1196/4-2, by the German Ministry of Research and Education (BMBF) grant 01GQ0840 (BFNT Frankfurt), and by the Honda Research Institute Europe. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.