Abstract. Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented...
Abstract. We propose a two-step approach for the analysis of functional magnetic resonance images, in the context of natural stimuli. In the first step, elements of functional bra...
Jarkko Ylipaavalniemi, Eerika Savia, Ricardo Vig&a...
This paper considers the use of the EM-algorithm, combined with mean field theory, for parameter estimation in Markov random field models from unlabelled data. Special attention ...
Abstract. Functional magnetic resonance (fMRI) data are often corrupted with colored noise. To account for this type of noise, many prewhitening and pre-coloring strategies have be...
We propose inferring functional connectivity between brain regions by examining the spatial modulation of the blood oxygen level dependent (BOLD) signals within brain regions of i...
Event-related functional magnetic resonance imaging (fMRI) is considered as an estimation and reconstruction problem. A linear model of the fMRI system based on the Fourier sampler...
Andre Lehovich, Harrison H. Barrett, Eric Clarkson...
In this paper we derive an independent-component analysis (ICA) method for analyzing two or more data sets simultaneously. Our model permits there to be components individual to t...
Ana S. Lukic, Lars Kai Hansen, Miles N. Wernick, S...