Abstract: Neuronal excitation and inhibition of the brain is tracked in the hippocampal CA1 network during a latent period, wherein biomarkers are observed which include a sustained increase in the firing rate of the excitatory postsynaptic field activity, paired with a subsequent decrease in the firing rate of the inhibitory postsynaptic field activity; the mean amplitude profiles of both fEPSP and fEPSP field potential activity during the latent period have characteristic shapes; both excitatory and inhibitory CA1 field activity firing rates are observed to follow a circadian rhythm that drifts during epileptogenesis; the circadian rhythms described are in-phase in controls and anti-phase during epileptogenesis; and the fEPSP rate drifts from a circadian rhythm to a greater extent than the fEPSP rate. An additional biomarker is a change in a circadian rhythm of core body temperature. Therapeutic measures can include thermal, chemical, or electrical modulation, in an open or closed loop process.

Abstract: Neuronal excitation and inhibition of the brain is tracked in the hippocampual CA1 network during a latent period, wherein biomarkers are observed which include a sustained increase in the firing rate of the excitatory postsynaptic field activity, paired with a subsequent decrease in the firing rate of the inhibitory postsynaptic field activity within the CA1 region of the hippocampus; the mean amplitude profiles of both fEPSP and fIPSP field potential activity during the latent period have characteristic shapes; both excitatory and inhibitory CA1 field activity firing rates are observed to follow a circadian rhythm that drifts during epileptogenesis; the circadian rhythms described are in-phase in controls and anti-phase during epileptogenesis; and the fEPSP rate drifts from a circadian rhythm to a greater extent than the fIPSP rate. An additional biomarker is a change in a circadian rhythm of core body temperature.

Abstract: An exemplary method for monitoring neonate brain function includes processing electroencephalographic data of the neonate to calculate at least one measure, the at least one measure including a non-linear measure, comparing the calculated at least one measure against at least one baseline threshold, wherein the at least one baseline threshold corresponds to a neonate age range, and outputting a result of the comparison. An exemplary system for monitoring neonate brain function includes a computing device for processing electroencephalographic data of the neonate to calculate at least one measure, the at least one measure including a non-linear measure, and for comparing the calculated at least one measure against at least one baseline threshold, wherein the at least one baseline threshold corresponds to a neonate age range, and a display for displaying a result of the comparison.