  Recent experimental results on spike avalanches measured in the
urethane-anesthetized rat cortex have revealed scaling relations that indicate
a phase transition at a specific level of cortical firing rate variability. The
scaling relations point to critical exponents whose values differ from those of
a branching process, which has been the canonical model employed to understand
brain criticality. This suggested that a different model, with a different
phase transition, might be required to explain the data. Here we show that this
is not necessarily the case. By employing two different models belonging to the
same universality class as the branching process (mean-field directed
percolation) and treating the simulation data exactly like experimental data,
we reproduce most of the experimental results. We find that subsampling the
model and adjusting the time bin used to define avalanches (as done with
experimental data) are sufficient ingredients to change the apparent exponents
of the critical point. Moreover, experimental data is only reproduced within a
very narrow range in parameter space around the phase transition.
