A complete self-control mechanism is proposed in the dynamics of neura
l networks through the introduction of a time-dependent threshold, det
ermined in function of both the noise and the pattern activity in the
network. Especially for sparsely coded models this mechanism is shown
to considerably improve the storage capacity, the basins of attraction
, and the mutual information content.