Fig. 10.

Weak correlation limits the fidelity of a neural code. The plot shows the variability in the number of spikes that arrive in an average ISI from a pool of input neurons modeled as Poisson point processes. Pool size is varied along theabscissa. In one ISI, the expected number of input spikes equals the number of neurons. Uncertainty is the SD of the input spike count divided by the mean. For one input neuron, the uncertainty is 100%. The diagonal gray line shows the expected relationship for independent Poisson inputs; uncertainty is reduced by the square root of the number of neurons. If the input neurons are weakly correlated, then uncertainty approaches an asymptote of $\sqrt{\overline{\text{r}}}$ (see Appendix ). For an average correlation of 0.2, the uncertainty from a pool of 100 neurons (arrow) is approximately the same as for five independent neurons or, equivalently, the count from one neuron in an epoch of five average ISIs.