  This work concerns the long-term dynamics of a spatiotemporal many-body
deterministic model that exhibits emergence and self-organization, and which
has been recently proposed as a new paradigm for Artificial Life. Collective
structures emerge in the form of dynamic networks, created by bursts of
spatiotemporal activity (avalanches) at the edge of a synchronization phase
transition. The spatiotemporal dynamics is portraited by a motion picture and
quantified by time varying collective parameters, which revealed that the
dynamic networks undergo a "life cycle", made of self-creation,
self-regulation, and self-destruction. The power spectra of the collective
parameters show 1/f power-law tails, and the statistical properties of the
avalanches, evaluated in terms of their size and durations, show power laws
with characteristic exponents in agreement with those values found in the
literature concerning neural networks. The mechanism underlying avalanches is
discussed in terms of local-to-collective excitability. Finally, the
connections that link the present work to self-organized criticality, neural
networks and artificial life are discussed.
