  The repertoire of neural activity patterns that a cortical network can
produce constrains the network's ability to transfer and process information.
Here, we measured activity patterns obtained from multi-site local field
potential (LFP) recordings in cortex cultures, urethane anesthetized rats, and
awake macaque monkeys. First, we quantified the information capacity of the
pattern repertoire of ongoing and stimulus-evoked activity using Shannon
entropy. Next, we quantified the efficacy of information transmission between
stimulus and response using mutual information. By systematically changing the
ratio of excitation/inhibition (E/I) in vitro and in a network model, we
discovered that both information capacity and information transmission are
maximized at a particular intermediate E/I, at which ongoing activity emerges
as neuronal avalanches. Next, we used our in vitro and model results to
correctly predict in vivo information capacity and interactions between
neuronal groups during ongoing activity. Close agreement between our
experiments and model suggest that neuronal avalanches and peak information
capacity arise due to criticality and are general properties of cortical
networks with balanced E/I.
