  We examine bootstrap percolation in d-dimensional, directed metric graphs in
the context of recent measurements of firing dynamics in 2D neuronal cultures.
There are two regimes, depending on the graph size N. Large metric graphs are
ignited by the occurrence of critical nuclei, which initially occupy an
infinitesimal fraction, f_* -> 0, of the graph and then explode throughout a
finite fraction. Smaller metric graphs are effectively random in the sense that
their ignition requires the initial ignition of a finite, unlocalized fraction
of the graph, f_* >0. The crossover between the two regimes is at a size N_*
which scales exponentially with the connectivity range \lambda like_* \sim
\exp\lambda^d. The neuronal cultures are finite metric graphs of size N \simeq
10^5-10^6, which, for the parameters of the experiment, is effectively random
since N<< N_*. This explains the seeming contradiction in the observed finite
f_* in these cultures. Finally, we discuss the dynamics of the firing front.
