  Balance of excitation and inhibition is a fundamental feature of in vivo
network activity and is important for its computations. However, its presence
in the neocortex of higher mammals is not well established. We investigated the
dynamics of excitation and inhibition using dense multielectrode recordings in
humans and monkeys. We found that in all states of the wake-sleep cycle,
excitatory and inhibitory ensembles are well balanced, and co-fluctuate with
slight instantaneous deviations from perfect balance, mostly in slow-wave
sleep. Remarkably, these correlated fluctuations are seen for many different
temporal scales. The similarity of these computational features with a network
model of self-generated balanced states suggests that such balanced activity is
essentially generated by recurrent activity in the local network and is not due
to external inputs. Finally, we find that this balance breaks down during
seizures, where the temporal correlation of excitatory and inhibitory
populations is disrupted. These results show that balanced activity is a
feature of normal brain activity, and break down of the balance could be an
important factor to define pathological states.
