Neural networks can be very simple containing just two neurons, one afferent con

Question

Neural networks can be very simple containing just two neurons, one afferent connecting directly to an efferent. In this system a stimulus triggers an action potential in the pre-synaptic neuron (afferent) which then stimulates the post- synaptic neuron (efferent) which sends a message to the effetor organ and causes a response to the original stimulus. Of course there are also more complex systems where multiple neurons are involved. Please describe a simple convergent neural network and a simple divergent neural network. Include one advantage for each. (A description does not have to be of an actual system, you can simply describe what types of neurons are involved and how many. Remember this answer can be completed in roughly 4 lines.)

Explanation / Answer

Simple Convergent Neural Network: One postsynaptic cell receives convergent input from a number of different presynaptic cells.

Advantage: Convergence allows a neuron to receive input from many neurons in a network.

Simple Divergent Neural Network: Any individual neuron can make divergent connections to many different postsynaptic cells.

Advantage: Divergence allows one neuron to communicate with many other neurons in a network.

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