Adaptive nodes enrich nonlinear cooperative learning beyond traditional adaptation by links.

ABSTRACT: Physical models typically assume time-independent interactions, whereas neural networks and machine learning incorporate interactions that function as adjustable parameters. Here we demonstrate a new type of abundant cooperative nonlinear dynamics where learning is attributed solely to the nodes, instead of the network links which their number is significantly larger. The nodal, neuronal, fast adaptation follows its relative anisotropic (dendritic) input timings, as indicated experimentally, similarly to the slow learning mechanism currently attributed to the links, synapses. It represents a non-local learning rule, where effectively many incoming links to a node concurrently undergo the same adaptation. The network dynamics is now counterintuitively governed by the weak links, which previ

SUBMITTER: Sardi S 

PROVIDER: S-EPMC5865176 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature