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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.
Glioblastoma multiforme (GBM) is treated by surgical resection followed by radiochemotherapy. Bevacizumab is commonly deployed for anti‐angiogenic therapy of recurrent GBM; however, innate immune cells have been identified as instigators of resistance to bevacizumab treatment. We identified angiopoietin‐2 (Ang‐2) as a potential target in both naive and bevacizumab‐treated glioblastoma. Ang‐2 expression was absent in normal human brain endothelium, while the highest Ang‐2 levels were observed in bevacizumab‐treated GBM. In a murine GBM model, VEGF blockade resulted in endothelial upregulation of Ang‐2, whereas the combined inhibition of VEGF and Ang‐2 leads to extended survival, decreased vascular permeability, depletion of tumor‐associated macrophages, improved pericyte coverage, and increased numbers of intratumoral T lymphocytes. CD206+ (M2‐like) macrophages were identified as potential novel targets following anti‐angiogenic therapy. Our findings imply a novel role for endothelial cells in therapy resistance and identify endothelial cell/myeloid cell crosstalk mediated by Ang‐2 as a potential resistance mechanism. Therefore, combining VEGF blockade with inhibition of Ang‐2 may potentially overcome resistance to bevacizumab therapy.