Neural Networks - Algorithms, Applications,and ... - Csbdu.in

16 Introduction to ANS TechnologySalivationsignalSight inputFigure 1.10Two neurons, A and C, are stimulated by the sensory inputsof sound and sight, respectively. The third neuron, B,causes salivation. The two synaptic junctions are labeledSB A anc 'If the experiment is repeated often enough, A will eventually be able to causeB to fire even in the absence of the visual stimulation from C. Then, if the bellis rung, but no food is shown, salivation will still occur, because the excitationdue to A alone is now sufficient to cause B to fire.Because the connection between neurons is through the synapse, it is reasonableto guess that whatever changes occur during learning take place there.Hebb theorized that the area of the synaptic junction increased. More recenttheories assert that an increase in the rate of neurotransmitter release by thepresynaptic cell is responsible. In any event, changes certainly occur at thesynapse. If either the pre- or postsynaptic cell were altered as a whole, otherresponses could be reinforced that are unrelated to the conditioning experiment.Thus we conclude our brief look at neurophysiology. Before moving on,however, we reiterate a caution and issue a challenge to you. On the one hand,although there are many analogies between the basic concepts of neurophysiologyand the neural-network models described in this book, we caution you not toportray these systems as actually modeling the brain. We prefer to say that thesenetworks have been inspired by our current understanding of neurophysiology.On the other hand, it is often too easy for engineers, in their pursuit of solutionsto specific problems, to ignore completely the neurophysiological foundationsof the technology. We believe that this tendency is unfortunate. Therefore, wechallenge ANS practitioners to keep abreast of the developments in neurobiologyso as to be able to incorporate significant results into their systems. Afterall, what better model is there than the one example of a neural network withexisting capabilities that far surpass any of our artificial systems?