A Computer Simulation Model of Backwards Feedback Across Synapse Via Arachidonic Acid
Algorithms for artificial neural networks are usually developed assuming in the most of the models that information propagates fordward and backward across the neural network. Fordwards propagation is modeled easily in ANN and biologically plausible in biological neurons, however for backwards propagation the plausibility of the algorithms developed for ANN seems remote in biological neurons. Based on the presynaptic changes induced by the arachidonic acid released by postsynaptic neurons during long-term potentiation (LTP) in the dentate gyrus, we show a computer simulation model where a backward feedback is performed across local synapses by arachidonic acid. Our simulation model shows how arachidonic acid could be playing the role of retrograde messenger during LTP.
KeywordsArachidonic Acid Artificial Neural Network Synaptic Cleft Postsynaptic Neuron Phospholipase Activity
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