Interpretation of correlated neural variability from models of feed-forward and recurrent circuits
Fig 3
Relation between signal and noise correlations in the recurrent network model.
A: Dependence of average signal correlations, cS (continuous lines), and average noise correlations, cN (dashed lines), on input correlation and network properties, Eqs (28) and (29). Low variability of the transfer matrix elements, ρ, increases cN and cS. Input signal correlations affect only cS. B: Same data, average signal versus noise correlation. C: Scatter plot of all pairwise signal versus pairwise noise correlations (dots), in five network realizations, for cin = 0.05. Circles indicate network average across pairs, orange dotted line corresponds to analytical expressions displayed in B for cN and cS.