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How Structure Determines Correlations in Neuronal Networks
Figure 7
Distance dependence of correlations and population fluctuations.
A,B: Evaluation of 
for parameters 
and 
, localised inhibition (A) and 
, localised excitation (B). Other parameters as in Figure 2. Contributions of different paths, numerically (full lines) and analytically (dashed lines). Higher orders add up to extreme values for localised excitation but cancel out for localised inhibition. Correlations of individual neurons with distant neighbours vary considerably (grey, 50 traces shown). C: Variance of population spike counts over population size. Comparison between populations of neighbouring neurons in a ring and in a random network with fixed output. Plotted are results from analytical approximation, numerical calculation using the connectivity matrix and direct simulation, averaged over 5 populations in each case. Network Parameters: random network as in Figure 2, ring: 
. Simulation parameters: total simulation time: 
, bin size for spike counts: 
, others as in Figure 2.
doi: https://doi.org/10.1371/journal.pcbi.1002059.g007