Solveig Næss

• Næss, Solveig; Chintaluri, Chaitanya; Ness, Torbjørn Vefferstad; Dale, Anders; Einevoll, Gaute & Wójcik, Daniel K. (2017). Corrected four-sphere head model for EEG signals. Frontiers in Human Neuroscience.  ISSN 1662-5161.  11, s 1- 7 . doi: 10.3389/fnhum.2017.00490 Full text in Research Archive. Show summary

  The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying EEG forward models we can compute the contribution from such dipoles to the electrical potential recorded by EEG electrodes. Forward models are key both for generating understanding and intuition about the neural origin of EEG signals as well as inverse modeling, i.e., the estimation of the underlying dipole sources from recorded EEG signals. Different models of varying complexity and biological detail are used in the field. One such analytical model is the four-sphere model which assumes a four-layered spherical head where the layers represent brain tissue, cerebrospinal fluid (CSF), skull, and scalp, respectively. While conceptually clear, the mathematical expression for the electric potentials in the four-sphere model is cumbersome, and we observed that the formulas presented in the literature contain errors. Here, we derive and present the correct analytical formulas with a detailed derivation. A useful application of the analytical four-sphere model is that it can serve as ground truth to test the accuracy of numerical schemes such as the Finite Element Method (FEM). We performed FEM simulations of the four-sphere head model and showed that they were consistent with the corrected analytical formulas. For future reference we provide scripts for computing EEG potentials with the four-sphere model, both by means of the correct analytical formulas and numerical FEM simulations.

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• Hagen, Espen; Næss, Solveig; Ness, Torbjørn V & Einevoll, Gaute (2017). Computing Brain Signals (CBra): Concurrent simulation of network activity, extracellular electric potentials and magnetic fields.
• Hagen, Espen; Næss, Solveig; Ness, Torbjørn V & Einevoll, Gaute (2017). Computing Brain Signals: concurrent simulation of network activity, extracellular electric potentials and magnetic fields.
• Hagen, Espen; Næss, Solveig; Ness, Torbjørn V & Einevoll, Gaute (2017). Computing brain signals (CBra): Concurrent simulation of network activity, extracellular electric potentials and magnetic fields.
• Hagen, Espen; Næss, Solveig; Ness, Torbjørn Vefferstad & Einevoll, Gaute (2017). Computing Brain Signals: Concurrent simulation of network activity, extracellular electric poten- tials and magnetic fields..
• Næss, Solveig (2017). Biophysical Modeling of Single Neuron Contributions to ECoG and EEG signals.
• Næss, Solveig; Ness, Torbjørn V; Halnes, Geir; Halgren, Eric; Dale, Anders M. & Einevoll, Gaute (2017). Biophysical modeling of single neuron contributions to ECoG and EEG signals.
• Næss, Solveig; Ness, Torbjørn V; Halnes, Geir; Halgren, Eric; Dale, Anders M. & Einevoll, Gaute (2017). Biophysical modeling of single-neuron contributions to ECoG and EEG signals.
• Næss, Solveig; Ness, Torbjørn V; Halnes, Geir; Halgren, Eric; Dale, Anders & Einevoll, Gaute (2017). Biophysical modeling of single-neuron contributions toECoG, EEG and MEG signals.
• Buccino, Alessio Paolo; Stöber, Tristan Manfred; Næss, Solveig; Cauwenberghs, Gert & Häfliger, Philipp (2016). Extracellular single neuron stimulation with high-density multi-electrode array.
• Næss, Solveig & Einevoll, Gaute (2016). Modeling Extracellular Potentials from Neurons in the Brain.
• Næss, Solveig; Ness, Torbjørn Vefferstad; Dale, Anders M. & Einevoll, Gaute (2016). Understanding EEG with Biophysical Modeling.
• Næss, Solveig; Ness, Torbjørn Vefferstad; Halnes, Geir; Halgren, Eric; Dale, Anders M. & Einevoll, Gaute (2016). Biophysical modeling of single-neuron contributions to EEG and ECoG signals.

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