"Biological learning does not appear to implement the exact global layer-by-layer error-backpropagation mechanism used to train conventional artificial neural networks."
Lillicrap and colleagues examine the relationship between artificial backpropagation and biological learning. They explain why conventional error backpropagation presents biological implementation problems while exploring mechanisms that could approximate its learning properties, supporting the distinction between ANN training algorithms and known neural learning mechanisms.
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