Some networks need a neuron to inhibit the other neurons in the same layer. This is called lateral
inhibition. The most common use of this is in the output layer. For example in text recognition if the probability
of a character being a “P” is 0.85 and the probability of the character being an “F ” is 0.65, the network needs
to choose the highest probability and inhibit all the others. It can do that with lateral inhibition. This concept
is also called competition.
Another type of connection is feedback. This is where the output of one layer routes back to a previous
layer. An example of this is shown in ...
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