Latent Causal Modelling of Neuroimaging Data |
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| Abstract | We establish a close connection between Granger causality and convolutive bilinear models. Contrary to Granger causality that considers causal relations between the measurement variables the convolutive model operate with causal relations to underlying latent sources. We derive a Bayesian approach to estimate the model parameters and demonstrate its success on real and
artificial EEG data. |
| Type | Conference paper [With referee] |
| Conference | NIPS Workshop on Connectivity Inference in Neuroimaing |
| Year | 2009 |
| Electronic version(s) | [pdf] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Intelligent Signal Processing |