Publications by authors named "M Haardt"

Magnetoencephalography (MEG) and electroencephalography (EEG) are contemporary methods to investigate the function and organization of the brain. Simultaneously acquired MEG-EEG data are inherently multi-dimensional and exhibit coupling. This study uses a coupled tensor decomposition to extract the signal sources from MEG-EEG during intermittent photic stimulation (IPS).

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The localization of brain sources based on EEG measurements is a topic that has attracted a lot of attention in the last decades and many different source localization algorithms have been proposed. However, their performance is limited in the case of several simultaneously active brain regions and low signal-to-noise ratios. To overcome these problems, tensor-based preprocessing can be applied, which consists in constructing a space-time-frequency (STF) or space-time-wave-vector (STWV) tensor and decomposing it using the Canonical Polyadic (CP) decomposition.

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The identification of signal components in electroencephalographic (EEG) data originating from neural activities is a long standing problem in neuroscience. This area has regained new attention due to the possibilities of multi-dimensional signal processing. In this work we analyze measured visual-evoked potentials on the basis of the time-varying spectrum for each channel.

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The conserved C-terminal peptide motif (1476DTRL) of the cystic fibrosis transmembrane conductance regulator (CFTR) ensures high affinity binding to different PSD-95/Disc-large/zonula occludens-1 (PDZ) domain-containing molecules, including the Na+/H+ exchanger regulatory factor (NHERF)/ezrin-radixin-moesin-binding phosphoprotein of 50 kDa. The physiological relevance of NHERF binding to CFTR is not fully understood. Individuals with mutations resulting in premature termination of CFTR (S1455X or Delta26 CFTR) have moderately elevated sweat Cl- concentration, without an obvious lung and pancreatic phenotype, implying that the CFTR function is largely preserved.

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