EEG Sequence Imaging: A Markov Prior for the Variational Garrote

Sofie Therese Hansen, Lars Kai Hansen

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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 languageEnglish
Title of host publicationProceedings of the 3rd NIPS Workshop on Machine Learning and Interpretation in Neuroimaging 2013
Number of pages6
Publication date2013
Publication statusPublished - 2013
Event27th Annual Conference on Neural Information Processing Systems (NIPS 2013) - Lake Tahoe, Nevada, United States
Duration: 5 Dec 201310 Dec 2013
http://nips.cc/Conferences/2013/

Conference

Conference27th Annual Conference on Neural Information Processing Systems (NIPS 2013)
CountryUnited States
CityLake Tahoe, Nevada
Period05/12/201310/12/2013
Internet address

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