Computer analyses of EEG/sleep states can be used as physiologic biomarkers of developmental neural plasticity. Frequency- and time-dependent signal processing strategies of cerebral and noncerebral measures can help test current theories of neuronal network maturation in terms of segregation and integration of short-distance versus long-distance neuronal connections throughout the neuroaxis. Specific phenotypic expressions of adaptive or maladaptive neuronal connectivity are proposed based on comparisons of whole-brain EEG/sleep resting states between preterm and full-term cohorts when developmental outcome measures are applied. Combined use of neurophysiological datasets with neuroimaging and genetic methodologies define endophenotypes that will more accurately diagnose children at risk for developmental disorders, as well as design appropriate neuroprotective interventions for the individual’s age and disease progress.

Keywords:
EEG sleep, Neonate, Computational phenotypes, Endophenotypes, Developmental neural plasticity, Fetal/neonatal brain disorders, Neuroprotection, Developmental origins theory
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© 2009 S. Karger AG, Basel
2009
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