  Complex systems are typically characterized as an intermediate situation
between a complete regular structure and a random system. Brain signals can be
studied as a striking example of such systems: cortical states can range from
highly synchronous and ordered neuronal activity (with higher spiking
variability) to desynchronized and disordered regimes (with lower spiking
variability). It has been recently shown, by testing independent signatures of
criticality, that a phase transition occurs in a cortical state of intermediate
spiking variability. Here, we use a symbolic information approach to show that,
despite the monotonical increase of the Shannon entropy between ordered and
disordered regimes, we can determine an intermediate state of maximum
complexity based on the Jensen disequilibrium measure. More specifically, we
show that statistical complexity is maximized close to criticality for cortical
spiking data of urethane-anesthetized rats, as well as for a network model of
excitable elements that presents a critical point of a non-equilibrium phase
transition.

Neurons and Cognition