The principal importance of a neural network is not only the way a neuron is implemented but also how their interconnections (more commonly called topology) are made.
The topology of a human brain is too complicated to be used as a model because a brain is made of hundreds of billions of connections which can't be effectively described using such a low-level (and highly simplified) model.
The topology we will study is therefore not the topology of a human (or even fruitfly!) brain but actually a simple topology designed for easy implementation on a digital computer. One of the easiest forms of this topology at the moment is made of three layers :
all neurons from one layer are connected to all neurons in the next layer.
This forms a whole nn with full interconnection, please note also that the weight (and therefore the importance) of each connection is not represented (for practical reason) here but must exist in the reality.
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