Quantifying EEG model parameter changes in the sleep-wake cycle

Proposal details

Title: Quantifying EEG model parameter changes in the sleep-wake cycle
Research Area(s): Brain Modeling
Background: Developing an integrated sleep-wake and EEG model of the brain requires a clear understanding of the changes in model parameters over the sleep-wake cycle. This project will correlate experimental EEGs to spectra in the model, in order to rigorously identify regions of model parameter space that correspond to different brain states. This component of the project will use the BRC data sets to help separate EC and EO in terms of model parameters
Aims: To identify parameter combinations in the Robinson-Rennie corticothalamic model that are associated with EEG spectra corresponding to EC and EO in terms of spectral features that are present in the BRC data. Secondly, to use these parameter combinations to separate the two states in parameter space, and express the transition from EC to EO in terms of model parameter changes.
Method: The EEG data in the BRC database will be processed to generate power spectra using pre-existing algorithms that have already been used to generate spectra for other EEG data. The power spectra will be analysed to determine spectral properties such as relative spectral band power, and peak strength. These properties will be characterised in terms of their distributions, which will inform the generation of EEG criteria that can be used to classify power spectra. Finally, EEG spectra in the model will be compared against the spectral criteria in order to classify regions of the model parameter space.