Sense Element Engagement Theory Explains How Neural Networks Produce
Cortical Prosthetic Vision
Abstract
Demonstrating that an understanding of how neural networks produce a
specific quality of experience has been achieved would provide a
foundation for new research programs and neurotechnologies. The
phenomena that comprise cortical prosthetic vision have two desirable
properties for the pursuit of this goal: 1) Models of the subjective
qualities of cortical prosthetic vision can be constructed; and 2) These
models can be related in a natural way to models of the objective
aspects of cortical prosthetic vision. Sense element engagement theory
portrays the qualities of cortical prosthetic vision together with
coordinated objective neural phenomena as constituting sensible
spatiotemporal patterns that are produced by neural interactions.
Small-scale neural network simulations are used to illustrate how these
patterns are thought to arise. It is proposed that simulations and an
electronic neural network (ENN) should be employed in devising tests of
the theory. Large-scale simulations can provide estimates of parameter
values that are required to construct an ENN. The ENN will be used to
develop a prosthetic device that is predicted by the theory to produce
visual forms in a novel fashion. According to the theory, confirmation
of this prediction would also provide evidence that this ENN is a
sentient device.