Interpretation of correlated neural variability from models of feed-forward and recurrent circuits
Fig 2
Response-covariance relations depend on the origin of correlations.
A-C: Average population response, 〈r〉, versus average (co-)variances in recurrent network (top), feed-forward network with shared inputs (middle) and feed forward network with common gain fluctuations (bottom). Each dot corresponds to a random stimulus, blue dashed lines represent analytic results, Eqs (24)–(27). Larger ρ indicates larger variability of effective weights in the network models; larger Vext indicates increased variance of gain fluctuations. Inset: Ratio slope/intercept of linear fits to the (co-)variances, for different networks; scatter plots of ratios for covariances vs variances show that they coincide only in the recurrent network model. D-F: Dependence of normalized variability projected on direction of average response for the three network architectures. In D, E, colors indicate results for different network parameters, in F, size of markers indicates strength of gain fluctuations. Square markers on the left indicate numerical value of . G-I: Same for the normalized variability projected on diagonal direction. See S1 Appendix for further details and the numerical parameters.