Complications of Neuron model
Every complication listed below introduces a new dimension of complexity in building of the neuron model that reflects its functionality fully as it is real.
Dynamic morphology.
Neuron is a cell that constantly changes its form. Though it is a partial change only. Imagine a tree that drops off some old branches and grows new ones of different shape, direction and place of growth instead. Neuron behaves similarly to that tree. For this purpose neuron has a skeleton made of actin. It is called an actin cytoskeleton. More info at Wiki and in this article.
Different types of receptors.
Neuron contains receptors that allow him to receive signals from other neurons. Different neighbours send different signals. This forces the target neuron to have different types of receptors for all types of signals it receives. If continue with our tree abstraction, it would be as the tree had leaves of different colours. More info at Wiki.
Different density and conductivity of receptors of the same type
Receptors do not compose a layer of the same density and thickness. Receptors are scattered all over the neuron with different density. The overwhelming majority of them are located in synapses. The stronger the synapse the highest the density of receptors there. Also the stronger the conductivity of receptors. The tree analogy would give us that on some branches there are many leaves and all of them are of very bright colour. The colour here denotes conductivity. Those rich branches are strong synapses. As opposed to rich branches there are poor branches with not many leaves which are pale. An article about conductivity. An article about receptor density.
Perineuronal nets.
There is an external cage around the neuron that blocks its extensive outgrowth in case its synapses become stronger and larger. This cage is called a perineuronal net. Imagine that one part of the tree starts to grow more and more branches with very dense leaves on them. Such part would misbalance the tree itself so it can fall. Also it can block and damage the neighbour trees. Remember that neurons are very close to each other. So the perineuronal net is kind of a safe mechanism. One article about it. Another article