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Sense Element Engagement Theory Explains How Neural Networks Produce Cortical Prosthetic Vision
  • Raymond Pavloski
Raymond Pavloski
Independent Researcher

Corresponding Author:[email protected]

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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.