| Summary: | The brain is a complex dynamic and self-organizing system. Normal brain function emerges from synchronized neuronal firing between local neurons which are integrated into large scale networks via white matter tracts. Normal brain function and consciousness arise from the continual integration and dissolution of neuronal networks, and this fluctuation in synchronization is termed variability. Brain electrical activity is recorded as local field potentials using electroencephalography (EEG). The phase synchrony and variability of EEG waveforms can be quantified. The healthy brain exhibits a relatively low degree of phase synchrony and a high degree of variability.
Clinicians are interested in using a complex system approach to brain function to provide dynamic information on neuronal physiology and pathology not available by other evaluation methods. A common challenge in paediatric critical care is evaluation of the comatose child post brain injury. Coma and medical interventions confound the clinical examination making monitoring and prognostication of outcome difficult. Brain cells and white matter tracts are disrupted post injury altering the phase synchrony between neuronal networks. It is proposed in this thesis that the estimation of the variability in EEG phase synchrony can evaluate paediatric brain function.
The EEG recordings of normal children and patients in coma post brain injury are used, in a series of studies, to test the main hypothesis that slow EEG wave brain states associated with brain injury have higher magnitudes of EEG phase synchrony and lower variability values than those of EEG waves associated with consciousness. Further, the effects of age, brain development brain and the effect of a conscious slow wave EEG state (hyperventilation) on phase synchrony and variability are evaluated.
Results of the studies showed that EEG phase synchrony is increased in all slow wave states and is highest in comatose children with poor neurological outcome. Younger children’s brains have higher phase synchrony than older children. The variability of the EEG phase synchrony differentiates between the awake (higher values) and unconscious states (lower values). Physiologic models underlying EEG phase synchrony are discussed. The EEG phase synchrony and variability measures provide new insight into paediatric brain function.
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