Fig. 5.

Encoding efficiency decreases as the correlations’ slope increases. We developed a method to study encoding efficiency as a function of the signal and noise covariance matrices in populations of correlated Poisson neurons. The figure shows the average equivocation, measured in bits, of an ideal estimator; a larger equivocation can be associated with a smaller encoding efficiency. Each color corresponds to a choice of simulation parameters; lines represent linear regressions. Across all sets of parameters studied, we observe that, as the correlations’ slope increases, the encoding efficiency decreases (P < 0.01 for each set of parameters).