Biophysical vision model and learning paradigms about vision: review

A learning paradigm of a new biophysical vision model (BVM) is presented. I t incorporates anatomical and physiological evidence from micro- and macros copic research on vision as reported in the literature during the past five years. Anatomical and physiological vision research tends to drift away fr om the technological foundations of encoding and reproducing size-defined i mages of real ongoing life scenarios. White and color light waves reflectin g life scenarios are converted by the retina to encoded electrical train pu lses with attached real information to be decoded by cortical vision neuron s. The BVM paradigm is based on the ideas that: (1) cinema technology repro duces real-life scenes just as the human eye sees them; (2) virtual reality and robotics are computerized replications of categorized human vision fac ulties in operation. We believe that vision-related technology may extend o ur knowledge about vision and direct vision research into new horizons. The biophysical vision-model has three prerequisites: (1) The faculties of hum an vision must be categorized. (2) Logic circuits of the 'hardware' of neur onal vision must be present. (3) Vision faculties are operated by self-indu ced 'software'. Vision research may be enhanced with devices constructed ac cording to BVM that would enable biophysical vision experiments in both hum ans and animals. (C) 2001 Harcourt Publishers Ltd.