Electroencephalography (EEG) is the measurement of the electrical activity of the brain, measured with millisecond precision by electrodes positioned on the surface of the scalp. The high temporal resolution of EEG makes it an ideal tool to study the dynamics of cognitive processes. Typically, EEG signals are analysed in terms of their response to sensory stimulation (e.g. visual, auditory) or motor actions. In the EEG the perturbation of the rhythmical electrical activity in a range of frequency bands is considered, whereas averaging the EEG triggered by a stimulus or action results in the event related potentials (ERPs). Recent advances in signal processing and the development of more sophisticated tools for modelling the inverse problem allow the determination of the neural sources generating the scalp potential.
This Figure depicts the recording of EEG raw data (upper left), showing the EEG signal of a single electrode (upper right). EEG signals are then averaged to reveal the event-related brain potential (ERP) activity time-locked to a stimulus, cognitive, or motor event (middle left). ERP waveforms allow to examine with millisecond precision possible influences of experimental factors on information processing in the brain. Alternatively, EEG may be decomposed in time-frequency components that allow for a representation of the signals frequency spectrum over time (middle right). In a next step the cortical generators (lower left) of specific ERP components or of a specific time-frequency band can be determined. As a kind of spatial filter backprojection of the dipole source solution into the individual EEG data may then allow to derive even single-trial measures in the EEG (bottom right).
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