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the mechanisms underlying the spontaneous initiation and termination of epileptic
seizures. The central concept is that seizures represent transitions of the epileptic
brain from its “normal” (less ordered/chaotic) state to an abnormal (more ordered)
state and back to a “normal” state, along the lines of spatiotemporal chaos-to-order-
to-chaos transitions. The hallmark of this research is the ability to predict epileptic
seizures, in the order of tens of minutes prior to their clinical or electrographic on-
set. This research has provided useful insights into the progressive preictal (before
a seizure) entrainment, and the subsequent post-ictal (after a seizure) disentrain-
ment of the epileptic brain's spatiotemporal EEG activity, under the hypothesis of
“dynamical resetting of the epileptic brain” [12, 16]. According to this hypothesis,
seizures do not occur as long as there is no need for the brain to reset. In status
epilepticus though, seizures may continue to occur as the entrainment of normal
brain sites with the focus persists and the internal seizure resetting mechanism is
not effective enough to disrupt it. Thus, the brain typically resets its dynamics after
the occurrence of a seizure except when it is confined in status epilepticus.
In this study, we further validate that SE is due to the non-resetting of the pathol-
ogy of the dynamics of epileptic brain's electrical activity. This pathology of dy-
namics is characterized by an intense and long-term entrainment (the term synchro-
nization may be used selectively herein instead of entrainment) of the dynamics of
normal brain sites with the ones of the epileptogenic focus (foci) and could be re-
set by successful external intervention. Our preliminary results from mathematical
analysis of the available “almost continuous” and “relatively short” scalp EEG, in
two patients with SE, one from each of two participating medical centers, show that
the above described pathology of epileptic brain dynamics can be reset by external
successful intervention, such as administration of antiepileptic drugs (AEDs).
The organization of the rest of this chapter is as follows. The EEG data and
the measures of brain dynamics utilized for the analysis of EEG are described in
Section 17.2. In Section 17.3, results from the application of this analysis to scalp
EEG data from two patients with SE are presented. Discussion of these results and
conclusions are given in Section 17.4.
17.2 Materials and Methods
17.2.1 Recording Procedure and EEG Data
We test our dynamical resetting hypothesis on EEG data from two epilepsy centers,
namely the Barrow Neurological Institute in Phoenix Arizona, and the Mayo Clinic
Hospital in Scottsdale, Arizona. Two patients (one from each center), who had an
episode of SE and were subsequently treated successfully via AEDs, were chosen
for dynamical analysis of their stored, “almost continuous,” scalp EEG recordings.
The available recordings were of duration of about 2 h in one patient and 14 h in the
other. The EEGs were analyzed with the methodology described in the next section.
We have shown in the past [9, 8, 7], that EEG segments of 10.24 s in duration would
be sufficient for the estimation of measures of dynamics from the nonstationary
