  A computational model incorporating insights from quantum theory is proposed
to describe and explain synaptic message transmission. We propose that
together, neurotransmitters and their corresponding receptors, function as a
physical "quantum decision tree" to "decide" whether to excite or inhibit the
synapse. When a neurotransmitter binds to its corresponding receptor, it is the
equivalent of randomly choosing different "strategies"; a "strategy" has two
actions to take: excite or inhibit the synapse with a certain probability. The
genetic programming can be applied for learning the observed data sequence to
simulate the synaptic message transmission.
