"... We propose a computational model that uses as afferent inputs the responses of model LGN cells with center-surround receptive fields (RFs) and we refer to it as a Combination of Receptive Fields (CORF) model. We use shifted gratings as test stimuli and simulated reverse correlation to explore the nature of the proposed model. We study its behavior regarding the effect of contrast on its response and orientation bandwidth as well as the effect of an orthogonal mask on the response to an optimally oriented stimulus. We also evaluate and compare the performances of the CORF and GF (Gabor Filter) models regarding contour detection, using two public data sets of images of natural scenes with associated contour ground truths. ... The proposed CORF model is more realistic than the GF model and is more effective in contour detection, which is assumed to be the primary biological role of simple cells."
Model Type: Neuron or other electrically excitable cell
Model Concept(s): Simplified Models; Methods
Simulation Environment: MATLAB (web link to model)
References:
Azzopardi G, Petkov N. (2012). A CORF computational model of a simple cell that relies on LGN input outperforms the Gabor function model. Biological cybernetics. 106 [PubMed]