Dynamic Causal Modeling (DCM) takes a probabilistic Bayesian framework to infer effective or causal connectivity, essentially to model how a stimulus would influence the connectivity…
Dynamic Causal Modeling and the Application of Bayes Theorem
Lab Talk
Solving the EEG/MEG Inverse Problem with Beamformers
Beamformers, a technique adapted from radar applications, are a type of spatial filtering approach to solving the inverse problem in EEG and MEG. Here are…
Source Localization in the EEG
Identifying the source within the brain from which an EEG signal element originates is a complex problem that requires a model of the head and…
The Inverse Problem in EEG – Assumptions and Pitfalls
Solving the inverse problem in EEG to identify the source of a signal requires a number of assumptions to constrain the solution space. These assumptions…