In an extensive simulation study , we show that NEMix improves learning of pathway structures over classical NEMs significantly in the presence of hidden pathway stimulation.

Like in the simulation study above, we compared the NEMix model to the NEM and the sc-NEM approach.

Like for the simulation study , we derived the cell population effects for the NEM from Wilcoxon tests, comparing the knockdown experiment to the control.

Like in the simulation study , p0 was initialized by drawing randomly from a uniform distribution.

To test our model, we performed a large simulation study .

To assess the edge recovery performance for larger NEMiX models, we ran a reduced simulation study .

To begin to answer these questions, we conducted analytical and simulation studies examining the propagation of spike correlation in feedback neural circuits.

Several simulation studies further revealed that neurons acquire receptive field [17—19] or spike patterns [20] through STDP by introducing lateral inhibition; yet, those studies were limited to simplified cases for which a large population of independent neurons was suggested to be sufficient [5,21,22].

Previous simulation studies showed lateral inhibition has critical effects on excitatory STDP learning [17—19]; however, it has not yet been well studied how a secondary correlation generated through the lateral circuits influences STDP at feedforward connections, and it is still largely unknown how lateral inhibition functions with various stimuli in different neural circuits.

Therefore, both analytical and simulation studies indicate that lateral inhibition should be strong, fast and sharp to detect higher correlation structure.