General differential Hebbian learning: Capturing temporal relations between events in neural networks and the brain
Table 1
Summary of the regressions of the nine STDP data sets regressed with the G-DHL rule.
The table indicates: the species and brain area from which the neurons have been taken (Hip: hippocampus; VisCtx: visual cortex; EntCtx: enthorinal cortex; Tec: Tectum); the reference where the data were published (Ref.); the parameters of the G-DHL selected model (i.e., the 2 or 3 parameters of the components of the model chosen by the model comparison technique); the type of pre- and post-synaptic neuron (Exc: excitatory; Inh: inhibitory); the taxonomy with which the STDP data set has been classified in Caporale and Dan [18] (C.&D. classes); our taxonomy proposed on the basis of the components found by the G-DHL regression. Our classes: ‘E’ and ‘I’ refer to the excitatory/inhibitory neurons involved, specifying the class, and the numbers refer to the subtypes within the class.