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Non-negative matrix factorization (NMF) has become a widely used blind source separation technique due to its part based representation and ease of interpretability. We currently extend the NMF model to allow for delays between sources and sensors. This is a natural extension for spectrometry data where a shift in onset of frequency profile can be induced(More)
The aim of this study was to investigate, in healthy subjects, the modulation of amplitude and phase precision of the auditory steady-state response (ASSR) to 40 Hz stimulation in two resting conditions varying in the level of arousal. Previously, ASSR measures have shown to be affected by the level of arousal, but the findings are somewhat controversial.(More)
OBJECTIVE To investigate the modulation of amplitude and phase precision of the auditory steady-state response (SSR) to 20 Hz stimulation in two conditions varying in the level of activation. METHODS Click stimuli (20 Hz) were applied while subjects were sitting upright silently reading a book of interest (high activation level) and while subjects were(More)
Multiplicative updates have proven useful for non-negativity constrained optimization. Presently, we demonstrate how multiplicative updates also can be used for unconstrained optimization. This is for instance useful when estimating the least absolute shrinkage and selection operator (LASSO) i.e. least squares minimization with L<sub>1</sub>-norm(More)
BACKGROUND Anomalies of self-awareness (self-disorders, SDs) are theorized to be basic to schizophrenia psychopathology. We have previously observed dysfunction of brain processing of proprioception in schizophrenia spectrum disorders (SZS). We hypothesized that SDs could be associated with abnormalities of early contralateral proprioceptive evoked(More)
Archetypal analysis (AA) proposed by Cutler and Breiman in [1] estimates the principal convex hull of a data set. As such AA favors features that constitute representative 'corners' of the data, i.e. distinct aspects or archetypes. We will show that AA enjoys the interpretability of clustering - without being limited to hard assignment and the uniqueness of(More)
Dynamic functional connectivity (FC) has in recent years become a topic of interest in the neuroimaging community. Several models and methods exist for both functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), and the results point towards the conclusion that FC exhibits dynamic changes. The existing approaches modeling dynamic(More)
In this paper we propose an approach to handle forward model uncertainty for EEG source reconstruction. A stochastic forward model is motivated by the many uncertain contributions that form the forward propagation model including the tissue conductivity distribution, the cortical surface, and electrode positions. We first present a hierarchical Bayesian(More)
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