Figure 2. The six layers of the human cortex (adapted from http://www.maxicours.com/se/fiche/0/2/142702.html).

The electrical potentials generated by neurons are captured by small sensors, called electrodes, which are usually silver chloride electrodes (AgCl). The electrodes can be attached to the scalp by means of paste or with a conductive gel and a cap. EEG helmets often have 32 or 64 electrodes, but some can have up to 256!  EEG systems thus allow a continuous recording of a huge number of signals. Since the EEG signals are of low amplitude (i.e. at the microvolt-range [μV]; typically between 0.5 and 100 μV), they must be amplified thousands of times (10,000 to 50,000) using an amplification device (Teplan, 2002). Paste or gel reduces impedance (i.e. resistance to current passage), measured in ohms, which facilitates recordings.

In addition to measuring the electrical activity of neurons, EEG also captures the electrical activity generated by body movements, eye blinks, and surrounding devices such as computers and cellphones! Therefore, people undertaking an EEG exam are usually asked to keep their face as relaxed as possible, and to minimize eye blinks and body movements. Furthermore, laboratory experiments often take place inside a Faraday cage, a special room which blocks of electromagnetic noise generated by electronic devices located outside of the room. Minimizing movements and using faraday cages limit the amount noise in the EEG signal and facilitate its analysis.

Types of EEG signals

EEG can be used to measure the spontaneous electrical activity of the resting brain, for example when an awake person does not do a specific activity, which makes it possible to quantify different brain rhythms. It is also possible to use EEG to measure electrical activity associated with speech and language processes (e.g., Tremblay et al., 2021; Pinto et al., 2019; Tremblay et al., 2008) or cognitive processes such as memory, for example, which allows measuring evoked potentials. Brain rhythms and evoked potentials are defined in the following sections.

Brain rythms

Brain rhythms are spontaneous signals that can be measured even in the absence of external stimulation. These rhythms are often used in cognitive neuroscience to classify sleep patterns and to identify patterns of atypical neuronal activity associated with pathologies (e.g., epilepsy, cervical tumours), states of consciousness and alertness. The frequency of the brain oscillations (i.e. the number of cycles per second) is measured in Hertz (Hz) (see Figure 3). Here are the main brain rhythms:

Delta rhythms: These are slow waves. They are present during a state of deep meditation or during sleep without dreams.

Theta rhythms: These are waves present during a deep sleep. These waves play a role in learning and consolidation in long-term memory.

Alpha rhythms: These waves are present during a state of alertness or light meditation. They are associated with the coordination of mental activities and learning. They are also associated with semantic processing, which allows us to access knowledge about the meaning of words (Klimesch, 1997;2012).

Beta rhythms: These waves are present during an awakening state when our attention is engaged by cognitive activities (e.g., making a decision, solve a problem) or by the environment. They would play an important role for the integration of audiovisual signals during speech perception (Romero et al., 2015).

Gamma rhythms: These are the fastest waves. They are associated with the processing of information by different regions of the brain (i.e., the synchronization of several regions of the brain). They are also present in states requiring a high level of attention or concentration. Research works also suggest that these oscillations may be associated with the acoustic treatment of speech sounds (Ou & Law, 2018).