Dynamic causal modelling of electrographic seizure activity using Bayesian belief updating

Seizure activity in EEG recordings can persist for hours with seizure dynamics changing rapidly over time and space. To characterise the spatiotemporal evolution of seizure activity, large data sets often need to be analysed. Dynamic causal modelling (DCM) can be used to estimate the synaptic driver...

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Detalles Bibliográficos
Autores principales: Cooray, Gerald K., Sengupta, Biswa, Douglas, Pamela K., Friston, Karl
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2016
Materias:
Technical Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4692455/
https://www.ncbi.nlm.nih.gov/pubmed/26220742
http://dx.doi.org/10.1016/j.neuroimage.2015.07.063

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4692455/
https://www.ncbi.nlm.nih.gov/pubmed/26220742
http://dx.doi.org/10.1016/j.neuroimage.2015.07.063

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