Mean field/mass action modelling of EEG/MEG at rest, during anaesthesia and in disease. (EEG, MEG, mean field modelling, mass action, anaesthesia, epilepsy)
Principle interest is in elucidating the genesis of rhythmic brain electromagnetic activity and exploring its diagnostic significance. Has developed a well regarded mean-field/mass-action model of electrocortical activity that has been applied successfully to characterising resting EEG activity as well as EEG activity perturbed under the influence of anaesthesia. Mathematically the resulting theory is phenomenologically rich exhibiting a range of unusual dynamical scenarios that include, heretofore unobserved in a real world theory, a dynamically interesting route to chaos (Shil'nikov saddle node bifurcation). Current research is concentrated on fitting model equations of electrocortical activity EEG and MEG data in an effort to estimate model parameters and to compare with independent physiological measurements.