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• Psychology

With electroencephalography, the electrical potentials on the surface of the scalp can be measured. The electrical potential changes are related to the electrical activity of the brain, although it is difficult to determine the exact location of the activity giving rise to the measured surface potential. In our laboratory, we have two BrainAmp EEG-amplifiers (Brain Products GmbH) with 64 channels. With an extension box (BrainAmp ExG) up to 16 additional channels can be recorded.

There are different aspects of electrical activity in the EEG data that can be analyzed. The most often used type of analysis is the so-called event-related potential or ERP. These potentials are made visible after averaging the electrical signal produced by the brain after stimulus presentation or the execution of a response. ERPs are aggregates of the electrical activity of the brain, assumed to reflect the net electrical activity of locally aligned neurons that are activated in synchrony and that are also in phase.

Another aspect of the EEG data is the analysis of the spontaneous rhythmic electrical activity occurring in multiple frequency bands, which are assumed to reflect different states of arousal or processing stages. Event-related time frequency analyses of EEG data differentiate between evoked and induced electrical activity. When an event-related time frequency analyses of EEG data is performed, activity in a certain frequency band will also reflect electrical activity that is captured in an ERP analysis (evoked activity). To discriminate this from the rhythmic background activity (induced activity), the ERP components are removed before time frequency analysis. A power increase in a certain frequency band is also often referred to as event-related synchronisation (ERS), while a power decrease is referred to as event-related desynchronisation (ERD). Frequency bands that have frequently been associated with specific aspects of cognitive tasks, such as memory encoding and semantic processing are within the theta (4-7Hz) and the gamma frequency (ca. 40 Hz) bands.

The great strength of EEG is its high temporal resolution, which is in the order of tens of milliseconds. This temporal resolution allows to teasing apart the temporal order of processing steps in cognitive tasks. This is a great advantage compared to the very limited temporal resolution that can be achieved with fMRI or NIRS. The spatial resolution of EEG, however, is limited. New mathematical tools attempt to determine the location of the neural sources that generate the surface potentials using inverse modeling, such as, for example, LORETA. A combination of fMRI and EEG data, which has been realized in some labs recently, can greatly contribute to the solution of the inverse problem by constraining the solution space.