  Recently, it has been shown that the communities in neuronal networks of the
integrate-and-fire type can be identified by considering patterns containing
the beginning times for each cell to receive the first non-zero activation. The
received activity was integrated in order to facilitate the spiking of each
neuron and to constrain the activation inside the communities, but no time
decay of such activation was considered. The present article shows that, by
taking into account exponential decays of the stored activation, it is possible
to identify the communities also in terms of the patterns of activation along
the initial steps of the transient dynamics. The potential of this method is
illustrated with respect to complex neuronal networks involving four
communities, each of a different type (Erd\H{o}s-R\'eny, Barab\'asi-Albert,
Watts-Strogatz as well as a simple geographical model). Though the
consideration of activation decay has been found to enhance the communities
separation, too intense decays tend to yield less discrimination.
