Retinal Prosthesis Dissertation - Student Home Pages

Red
(660nm)
R / G Red
( 620750nm )
Green
(520nm)
Blue
(470nm)
Yellow
(575nm)
photodiodes
Artificial
Neural
Network
(ANN)
G/
R Green
( 495570nm)
B/
Y Blue
( 450475nm )
Output
signals
(5 – 50)
impulses/s
Figure 8 pixel by pixel mapping
Using Artificial Neural Network Theory (ANN) to mimic the processing of the
neural network of the retina has the advantage that given the correct inputs to the
network and the expected output the designed network is self-training in the sense
that once trained with a set of quality test inputs; of a predetermined quantity, it will
always produce the required results even with differing inputs applied. The following
subsections give a primer for the theory which needs to be understood for an ANN to
be designed as an approach to replace the retina using a photodiode approach as
opposed to bypassing it with a camera.
2.2.1 The first artificial neuron
Warren McCulloch and Walter Pitts in their 1943 paper, “A logical calculus of Ideas
Immanent in Nervous Activity” postulated that neurons with a binary threshold
function were analogous to first order logic sentences. This first neuron model is
shown here.
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