Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study

作     者：Bornschein, Joerg Henniges, Marc Luecke, Joerg 

作者机构：Goethe Univ Frankfurt Frankfurt Inst Adv Studies D-60054 Frankfurt Germany Goethe Univ Frankfurt Dept Phys D-60054 Frankfurt Germany 

出 版 物：《PLOS COMPUTATIONAL BIOLOGY》 (PLoS计算生物学)

年 卷 期：2013年第9卷第6期

页      面：e1003062-e1003062页

核心收录：

学科分类：0710[理学-生物学] 08[工学] 09[农学] 0901[农学-作物学] 0836[工学-生物工程] 090102[农学-作物遗传育种] 

基　　金：German Research Foundation (DFG) [LU 1196/4-2] German Ministry of Research and Education (BMBF) [01GQ0840] Honda Research Institute Europe 

主　　题：BiologyCoding mechanismsComputational biologyComputational neuroscienceMathematicsNeuroscienceProbability theoryResearch ArticleSensory systemsStatistical methodsStatisticsVisual system 

摘      要：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.