Abstract
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.
| Original language | English |
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| Title of host publication | Proceedings of the 3rd NIPS Workshop on Machine Learning and Interpretation in Neuroimaging 2013 |
| Number of pages | 6 |
| Publication date | 2013 |
| Publication status | Published - 2013 |
| Event | 27th Annual Conference on Neural Information Processing Systems (NIPS 2013) - Lake Tahoe, Nevada, United States Duration: 5 Dec 2013 → 10 Dec 2013 http://nips.cc/Conferences/2013/ |
Conference
| Conference | 27th Annual Conference on Neural Information Processing Systems (NIPS 2013) |
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| Country/Territory | United States |
| City | Lake Tahoe, Nevada |
| Period | 05/12/2013 → 10/12/2013 |
| Internet address |