Biophysical vision model and learning paradigms about vision: review

A learning paradigm of a new biophysical vision model (BVM) is presented. It incorporates anatomical and physiological evidence from micro- and macroscopic research on vision as reported in the literature during the past five years. Anatomical and physiological vision research tends to drift away from the technological foundations of encoding and reproducing size-defined images of real ongoing life scenarios. White and color light waves reflecting life scenarios are converted by the retina to encoded electrical train pulses with attached real information to be decoded by cortical vision neurons. The BVM paradigm is based on the ideas that: (1) cinema technology reproduces real-life scenes just as the human eye sees them; (2) virtual reality and robotics are computerized replications of categorized human vision faculties in operation. We believe that vision-related technology may extend our knowledge about vision and direct vision research into new horizons. The biophysical vision model has three prerequisites: (1) The faculties of human vision must be categorized. (2) Logic circuits of the 'hardware' of neuronal vision must be present. (3) Vision faculties are operated by self-induced 'software'. Vision research may be enhanced with devices constructed according to BVM that would enable biophysical vision experiments in both humans and animals.