Efficent numerical integration and nonlinear filtering of a stochastic Jansen and Rit model
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
International Conference on Mathematical Neuroscience
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Neural mass models provide a useful framework for modelling mesoscopic neural dynamics and in this poster we consider the Jansen and Rit Neural Mass Model (JR-NMM). This system of ODEs has been introduced as a
model in the context of electroencephalography (EEG) rhythms and evoked
potentials and has been proposed as an underlying model in various application
settings. We use a stochastic version of the JR-NMM which has the
structure of a stochastic Hamiltonian with a nonlinear displacement and
has been shown to have a number of structural properties, such as moment
bounds and ergodicity. We discuss the quality of simulations based on an
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