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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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| Publicado no: | Neuroimage |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Academic Press
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4692455/ https://ncbi.nlm.nih.gov/pubmed/26220742 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2015.07.063 |
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