title: Are sparse-coding simple cell receptive field models physiologically plausible?
abstract: Olshausen and Field (1996) developed a simple cell receptive field model for natural scene processing in V1, based on unsupervised learning and non-orthogonal basis function optimization of an overcomplete representation of visual space. The model was originally tested with an ensemble of whitened natural scenes, simulating pre-cortical filtering in the retinal ganglia and lateral geniculate nucleus, and the basis functions qualitatively resembled the orientation-specific responses of V1 simple cells in the spatial domain. In this study, the quantitative tuning responses of the basis functions in the spectral domain are estimated using a Gaussian model, to determine their goodness-of-fit to the known bandwidths of simple cells in primate V1. Five simulation experiments which examined key features of the model are reported: changing the size of the basis functions; using a complete versus over-complete representation; changing the sparseness factor; using a variable learning rate; and mapping the basis functions with a whitening spatial function. The key finding of this study is that across all image themes, basis function sizes, number of basis functions, sparseness factors and learning rates, the spatial-frequency tuning did not closely resemble that of primate area 17 -- the model results more closely resembled the unclassified cat neurones of area 19 with a single exception, and not area 17 as predicted.
authors.affiliation: Department of Computing, Macquarie University, NSW 2109, Australia. pwatters@ics.mq.edu.au
authors.forename: Paul A
authors.initials: PA
authors.lastname: Watters
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D016571:Neural Networks, Computer; D009434:Neural Pathways / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D016011:Normal Distribution; D010775:Photic Stimulation / Q000379:methods; D011323:Primates; D009435:Synaptic Transmission / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology*; D014794:Visual Fields / Q000502:physiology; D014795:Visual Pathways / Q000502:physiology; D014796:Visual Perception / Q000502:physiology*