Electroencephalography (EEG): neurophysics, experimental methods, and signal processing


Electroencephalography (EEG) is the measurement of the electric potentials on the scalp surface generated (in part) by neural activity originating from the brain. The sensitivity of EEG to changes in brain activity on such a millisecond time scale is the major advantage of EEG over other brain imaging modalities such as functional magnetic resonance imaging (fMRI) or near-infrared spectroscopy (NIRS) that operate on time scales in the seconds to minutes range. Over the past 100 years, neuroscientists and clinical neurologists have made use of EEG to obtain insight into cognitive or clinical disease state by applying a variety of signal processing and statistical analyses to EEG time series. More recently there has been growing interest in making use of statistical modeling of EEG signals to directly control physical devices in brain-computer interfaces. In this chapter we provide an introduction to EEG generation and measurement as well as the experimental designs that optimize information acquired by EEG.


Nunez, M. D., Nunez, P., & Srinivasan, R. (2016). Electroencephalography (EEG): neurophysics, experimental methods, and signal processing. Handbook of Neuroimaging Data Analysis, 175–197.


    title   = {{E}lectroencephalography ({E}{E}{G}): neurophysics, experimental methods, and signal processing},
    author  = {Nunez, Michael D. and Nunez, Paul and Srinivasan, Ramesh},
    year    = {2016},
    journal = {Handbook of Neuroimaging Data Analysis},
    pages   = {175--197}