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Bayesian correlated component analysis for inference of joint EEG activation | IEEE Conference Publication | IEEE Xplore
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Bayesian correlated component analysis for inference of joint EEG activation

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Andreas Trier Poulsen; Simon Kamronn; Lucas C. Parra; Lars Kai Hansen
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Abstract:

We propose a probabilistic generative multi-view model to test the representational universality of human information processing. The model is tested in simulated data an...Show More

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Abstract:

We propose a probabilistic generative multi-view model to test the representational universality of human information processing. The model is tested in simulated data and in a well-established benchmark EEG dataset.
Published in: 2014 International Workshop on Pattern Recognition in Neuroimaging
Date of Conference: 04-06 June 2014
Date Added to IEEE Xplore: 21 July 2014
ISBN Information:
DOI: 10.1109/PRNI.2014.6858539
Conference Location: Tuebingen, Germany
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