Several studies have also established statistical evidence of dependence between the occurrences of the spikes of several neurons (see [5, 6, 13 15]) or even within a given neuron.
Consecutive stimulus volleys recruited a given neuron after a variable number of synaptic translations.
The U-matrix value associated with a given neuron, U height (v ), is defined as the average Euclidean distance between that neuron and its eight closest neighbours: U height (v ) = 1 8 ∑ μ ∈ N (v ) E d (v, μ ), where N (v ) is the set of neighbours and E d is the Euclidean distance between neurons.
The number of neurons that receive synaptic input from a given neuron x is called out-degree of x.
The multiplicity of synapses between two given neurons is mapped to a binary value by applying a threshold to the data.
Between these two points, the synaptic strength received by neuron A, given by g B ( Q ∗ ), is larger than g ¯ A → B. Since the cells are identical, the neurons must give equal amount of response (so that their steady-state firing periods will be equal) for a steady-state solution to occur.
This characteristic is apparent on multiple scales: in the cerebral cortex of the macaque monkey, both the number of connections between neurons in a given area and those between neurons across different brain areas decay rapidly with distance (Markov et al., 2011, 2014).
Suppose that there exist M homogeneous neuronal subpopulations labeled i = 1, …, M, each consisting of N neurons.1 Assume that all neurons of a given subpopulation are equivalent in the sense that the pairwise synaptic interaction between a neuron of subpopulation i and a neuron of subpopulation j only depends on i and j.
All the standard deviations appearing in the equations are adimensional quantities as they represent measures of distance between the indices of the neurons within a given layer.
