  While criticality is widely observed in neural networks, its underlying
neural mechanism is not known well. We consider a network of $N$ excitatory
leaky integrated and fire (LIF) neurons that reside on a regular lattice with
periodic boundary conditions. The cooperation between neurons, $K$, plays the
role of the control parameter that is expected to generate criticality when the
critical cooperation strength, $K_c$, is adopted. We show that the coupling
between spike timing and the phase of temporal fluctuations of a cooperative
activity of the network, i.e. population-averaged voltage (PAV), resorts to
identifying an order parameter. By increasing $K$, we find a continuous
transition from irregular spiking to a phase-locked state at the critical
point, $K_c$. Moreover, we deploy the finite-size scaling analysis to obtain
the critical exponents of this transition. We also show that the neuronal
avalanches created at this critical point, display a remarkable scaling
behavior with the exponents in a fair agreement with the experimental values.
