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1 results

  • 9 - Electroencephalography (EEG)

  • Geir Halnes, Norwegian University of Life Sciences, Torbjørn V. Ness, Norwegian University of Life Sciences, Solveig Næss, Universitetet i Oslo, Espen Hagen, Universitetet i Oslo, Klas H. Pettersen, The Norwegian Artificial Intelligence Research Consortium, Gaute T. Einevoll, Norwegian University of Life Sciences
  • Book:
    Electric Brain Signals
    Published online:
    30 May 2024
    Print publication:
    06 June 2024, pp 241-269

  • Summary

    The electroencephalographic (EEG) signal is the electric potential recorded on the scalp, and it is believed to originate from the combined activity of large populations of neurons. In forward models of EEG signals, one typically (i) represents neuronal sources in terms of effective current dipoles, (ii) defines a head model, which is a specification of the conductivity profile for the medium between the sources and the recording position (brain tissue, cerebrospinal fluid, skull, scalp), and (iii) uses volume-conductor theory to compute the resulting electric potential at the scalp. In this chapter, we introduce the key theory and computational frameworks for modeling EEG signals. We illustrate how biophysically detailed models of neurons can be reduced to approximate equivalent dipoles, and we discuss further ways to simplify neural simulations in order to reduce the computational cost. Using a combination of computational modeling and analytical approximations, we analyze how various factors are involved in shaping the EEG signal.