Topic: cortical multi-layer networks

Learning in cortical multi-layer networks is thought to occur through spatially and temporally local synaptic plasticity aided by ubiquitous feedback connections from upper layers. However, the known biologically plausible learning rules for such networks are yet to reach the high performance of the machine learning algorithms, such as backpropagation [1], on difficult tasks that the brain is capable of solving. It has been shown that one of the obstacles to backpropagation-like algorithm implementation in the brain, the ’weight transport’ problem, can be overcome with initially random feedbac