  Realistic modeling of brain involves large number of neurons. The important
question is how this size affects transmission efficiency? Here, these issue is
studied in terms of Shannon's Theory. Mutual Information between input and
output signals for simple class of networks with an increasing number of
neurons is analyzed theoretically and numerically. Levy-Baxter neural model is
applied. It turned out, that for these networks the Mutual Information
converges, with increasing size, asymptotically very slowly to saturation
level. This suggests that from certain level, the increase of neurons number
does not imply significant increase in transmission efficiency, contributes
rather to reliability.
