… Abstract In neuronal networks, the changes of synaptic strength (or … network structure. This
article investigates how this phenomenon occurs for the excitatory recurrent connections of a …

… A network with local recurrent connections only results in a band-diagonal recurrent weight
matrix … The recurrent weight matrix structure is shown in Figure 2c. This allows for complex …

… In this extension we take the structural component, M, to be a low-rank matrix … in recurrent
neural networks. Our model consists of rate-based neurons whose recurrent connections …

… corresponding to learned connections linking together active … network made of the largest
synaptic connections only. Hence, … in neural networks could shape the network structure to …

… we will analyze emerging network structures and their functional implications. … connection
from an external input to a given network neuron on the one hand, and a recurrent connection …

… connect with the previous literature and introduce the methods that underlie our results, we
start by describing the spontaneous dynamics ( I i = 0 ) in a network with a unit-rank structure …

… -style recurrent networks can simulate any FRA, while neither cascade-correlation networks
nor … Moreover, n t j i , will receive connections from every unit in the label field, where the rth …

… partiallyconnected networks, where nK denotes the number of input connections and nJ the
number of recurrent connections. Partially-connected networks are generated by randomly …

… the same network structure … connections from population to , and their average synaptic
amplitude. Once the mean activity in the network has been found, we can determine the structure …

… It follows from this analysis that the stronger the recurrent connections are in a neuron
group, the more its weights tend to evolve together. Weakly connected sets of weights are more …