Artificial Consciousness/Neural Correlates/Neural Network Models/Input Layer

Input Layer
In Neural Networks the Input Layer is largely an abstraction of the Output Layer of the previous neurons, used to allow separate modeling of each network snippet. By factoring out the inputs of the network, it is possible to put values into the inputs as if they were part of a larger network, thus allowing the study of the layer as if it were separate, or as if it were linked to the rest of the network simply by how you supply the input values.