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Accuracy and run-time play an important role in medical diagnostics and research as well as in the field of neuroscience. In Electroencephalography (EEG) source reconstruction, a current distribution in the human brain is reconstructed noninvasively from measured potentials at the head surface (the EEG inverse problem). Numerical modeling techniques are(More)
Bioelectric source analysis in the human brain from scalp electroencephalography (EEG) signals is sensitive to geometry and conductivity properties of the different head tissues. We propose a low-resolution conductivity estimation (LRCE) method using simulated annealing optimization on high-resolution finite element models that individually optimizes a(More)
Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique able to induce long-lasting changes in cortical excitability that can benefit cognitive functioning and clinical treatment. In order to both better understand the mechanisms behind tDCS and possibly improve the technique, finite element models are used to simulate(More)
Bioelectric source localization in the brain is sensitive to geometry and conductivity properties of the different head tissues. We propose a method that individually optimizes a realistically-shaped volume conductor with regard to the conductivities using a simulated annealing optimizer in discrete parameter space. We show that the method is able to(More)
Volume conduction models can help in acquiring knowledge about the distribution of the electric field induced by transcranial magnetic stimulation. One aspect of a detailed model is an accurate description of the cortical surface geometry. Since its estimation is difficult, it is important to know how accurate the geometry has to be represented. Previous(More)
In infants, the fontanels and sutures as well as conductivity of the skull influence the volume currents accompanying primary currents generated by active neurons and thus the associated electroencephalography (EEG) and magnetoencephalography (MEG) signals. We used a finite element method (FEM) to construct a realistic model of the head of an infant based(More)
A new type of biosensor is proposed that combines the recognition properties of "intelligent" hydrogels with the sensitivity and reliability of microfabricated pressure transducers. In the proposed device, analyte-induced changes in the osmotic swelling pressure of an environmentally responsive hydrogel are measured by confining it within a small(More)
(*) The first two authors contributed equally to this work. Abstract We propose a new method for a combined MEG/EEG source analysis. We optimize the tissue conductivities of a realistically shaped four-compartment finite-element head volume conductor based on measured somatosensory evoked potentials (SEP) and fields (SEF). Our proposed method uses the(More)
We developed a 375-channel, whole-head magnetoencephalography (MEG) system ("BabyMEG") for studying the electrophysiological development of human brain during the first years of life. The helmet accommodates heads up to 95% of 36-month old boys in the USA. The unique two-layer sensor array consists of: (1) 270 magnetometers (10 mm diameter, ∼15 mm(More)