We propose the following generalization of the Variational Garrote for sequential EEG imaging: A Markov prior to promote sparse, but temporally smooth source dynamics. We derive a set of modied Variational Garrote updates and analyze the role of the prior's hyperparameters. An experimental evaluation is given in simulated data and in a benchmark EEG data set.
Proceedings of the 3rd Nips Workshop on Machine Learning and Interpretation in Neuroimaging 2013, 2013
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27th Annual Conference on Neural Information Processing Systems (NIPS 2013)Neural Information Processing Systems