Information Technology Reference
In-Depth Information
on the coupling strength and directionality of mutual information and nonlinear in-
terdependences between different brain cortical regions. Two 1-h EEG recordings
were acquired from four ULD subjects; one prior and one after a minimum of 2
months treatment with an add-on AED. Subjects in this study were siblings of same
parents and suffered from ULD for approximately 37 years. Our results indicated
that the coupling strength was low between different brain cortical regions in the pa-
tients with disease of less severity. Adjunctive AED treatment was associated with
significant decrease of the coupling strength in all subjects. The mutual informa-
tion between different brain cortical regions was also reduced after treatment. These
findings could provide a new insight for developing a novel surrogate outcome mea-
sure for patients with epilepsy when clinical tools or observations could potentially
fail to detect a significant difference.
keywords
Nonlinear interdependence, Mutual information, Electroencephalogram,
epilepsy, Unverricht-Lundborg disease, Progressive myoclonic epilepsy
19.1 Introduction
The EEG is an essential tool used to corroborate the diagnosis of epilepsy and other
neurological disorders. Changes in the frequency and amplitude of EEG activity
arise from spontaneous interactions between excitatory and inhibitory neurons in
the brain. The underlying mechanism of brain function, studied by researchers, sug-
gested the importance of the EEG coupling strength between different brain cortical
regions. For example, it has been shown that the synchronization of EEG activ-
ity is important for the memory [12, 13] and the learning processes [30] of brain.
In one study, different brain synchronization/desynchronization of EEG patterns
were reportedly induced by hippocampal atrophy in subjects with mild cognitive
impairment [18].
Several authors have suggested a direct relationship between changes in synchro-
nization of EEG and the onset of epileptic seizures. Using intracranial EEG record-
ings, Iasemidis et al. reported that the nonlinear dynamical entrainment of cortical
regions is a necessary condition for onset of seizures in patients with temporal lobe
epilepsy [10, 11, 22]. Le Van Quyen et al. showed that epileptic seizures might be
predicted by nonlinear analysis of dynamical similarity between EEG channels [28].
Mormann et al. claimed that a preictal (before a seizure) state could be character-
ized by a decrease in synchronization between some EEG channels [20, 19]. A nor-
mal brain state is associated with a higher degree of complexity in EEG; transition
into a lower degree of complexity may suggest pathology in the brain. In a recent
study, using linear and nonlinear synchronization measures, Aarabi et al. indicated
that during the interictal state, the degree of interdependence between EEG chan-
nels was significantly less than that observed in the ictal state in typical absence
seizure EEG recordings. In some cases, the authors reported that they could identify
preictal states by a significant decrease in the synchronization level with respect to
