TY  - JOUR
A1  - Harter, Patrick Nikolaus
A1  - Bernatz, Simon
A1  - Scholz, Alexander
A1  - Zeiner, Pia Susan
A1  - Zinke, Jenny
A1  - Kiyose, Makoto
A1  - Blasel, Stella
A1  - Beschorner, Rudi
A1  - Senft, Christian
A1  - Bender, Benjamin
A1  - Ronellenfitsch, Michael Wilfried
A1  - Wikman, Harriet
A1  - Glatzel, Markus
A1  - Meinhardt, Matthias
A1  - Juratli, Tareq A.
A1  - Steinbach, Joachim Peter
A1  - Plate, Karl
A1  - Wischhusen, Jörg
A1  - Weide, Benjamin
A1  - Mittelbronn, Michel Guy André
T1  - Distribution and prognostic relevance of tumor-infiltrating lymphocytes (TILs) and PD-1/PD-L1 immune checkpoints in human brain metastases
T2  - Oncotarget
N2  - 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.
KW  - tumor-infiltrating lymphocytes
KW  - brain metastases
KW  - PD-1
KW  - PD-L1
Y1  - 2015
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/41511
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-415115
SN  - 1949-2553
N1  - Licensed under a Creative Commons Attribution 3.0 License.
VL  - 6
IS  - 38
SP  - 40836
EP  - 40849
ER  -