The electroencephalographic (EEG) signal is a bioelectric potential related to brain activity recorded on the scalp with electrodes and appropriate instrumentation. The system for measuring brain bioelectric potentials has, indeed, the function of taking the weak electrical signal on the scalp, increasing its amplitude, processing it (including digitization), and, finally, registering it. Increasingly complex processing of the raw signal (e.g., processed EEG through Fourier analysis or Joint Time-Frequency Analysis, JTFA, and dedicated algorithms) allows the use of the signal in different fields of application such as general anesthesia and for research purposes (e.g., neuroscience, and cognitive psychology).
Basically, this signal is produced by pyramidal cells that reside in the upper layers of the cerebral cortex. EEG represents the expression of synaptic processes (pre- and postsynaptic electrical potentials), dendritic potentials, and probably also neuroglia potentials. The mathematical law describing the conduction of the electric potential from pyramidal neurons to the detection surface is known as the "Poisson equation." This law relates the surface distribution of potential to the charge underlying and the permittivity of the mass of tissue. Because pyramidal cells behave like dipole sources, they produce the so-called "dipolar fields"; the total field generated results from the linear combination of the potential fields that each source produces individually. The presence of a dipole of this type requires a significant population of depolarized neurons in unison to produce external potential. This phenomenon is defined as local synchrony. The role of local synchrony in EEG rhythm generation is so intense that less than 5 percent of pyramidal cells can be responsible for over 90 percent of the energy of the EEG signal.
Moreover, the vast majority of pyramidal cells operate asynchronously (external potentials cancel each other out); if the pyramidal cells begin to polarize in unison, the effect will be visible and recorded on the EEG. In other words, groups of neurons can produce measurable potentials in the form of EEG signals. These signals are distinct in rhythms (or bands) according to the differences in amplitude (in microVolts) and in frequency (in cycles per second or hertz, Hz).
As electrodes are not in direct contact with the signal generator (conduction volume phenomenon), brain activity, even localized, can appear widely dispersed on the scalp, and any brain event can be reflected in more than one site on the scalp. As a general rule, 50 percent of the signal recorded by a sensor positioned on the leather arises from the brain tissue immediately below that sensor as the remaining signal comes received from other locations, primarily from adjacent sites. Consequently, the EEG represents an exam that has poor localization ability. However, technological advances such as the high-density EEG have allowed more localization information to be obtainable from the EEG.
The cerebral cortex contains tens of billions of neurons organized into functional groups; these groups are interconnected through a complex series of connections between cortical regions and subcortical brain structures. During the normal brain function, these networks are subjected to rhythmic activity at frequencies ranging from 1 to 100 Hz and more. Although the underlying neuronal activity proceeds at a frequency of thousands of Hz, the measurable external potentials are all in the EEG range. These groups of cortical neurons undergo cycles of activity in which they get sequentially recruited. These potential fluctuations are characterizable in terms of spectral content or characteristics in the time domain. Indeed, this coordinated activity is highlighted by rhythmic waves that are distinguished in particular positions and are evident in particular conditions (for example, during sleep) or after stimulation (hyperventilation, light stimulation, sleep deprivation, evoked potentials). This cyclical pattern of activity produces an identifiable growing and falling in rhythms, which has a temporal trend of the order of seconds and shows great variability.
A neurophysiological process that conditions the recorded electrical activity concerns the activation of repetitive cyclical patterns involving the thalamus and subcortical regions but also different cortical regions. Thalamo-cortical reverberation activities give rise to the alpha rhythm (8 to 12 Hz, 50 microV) and the slow beta rhythm (12 to 15 Hz, 10 to 20 microV, and associated with alertness, concentration, and intentions to remain immobile). In contrast, the low-frequency theta rhythm (4 to 7 Hz, 20 to 100-microV.) is an expression of the reverberation between the cortex and the subthalamic nuclei. Cortico-cortical reverberations are the basis of the genesis of beta waves (15 to 20 Hz) commonly associated with thinking conscious and intentional. Furthermore, high beta waves (typically 20 to 30 Hz) are typical of anxious states and agitation. Gamma waves are fast waves (35 to 45 Hz) not easy to record because of their very small amplitude. They are present in moments of maximum performance (physical and mental) and profound concentration.
All this cyclical-repetitive activity is evident in the EEG, whose characteristic pattern reveals the general state of activation and deactivation of the areas at the origin of the measured surface potentials. A classic example is the alpha rhythm. It is a rhythm of the rest of the visual system (inactivation rhythm), which is maximum posteriorly and increases when the eyes close, and has a typical increasing and decreasing trend. All these characteristics derive from the fact that the thalamocortical reverberation at the base of the alpha rhythm involves the optical pathways and the primary visual cortex (relaxation of the visual system). Therefore, during alpha periods, an individual is typically aware but relaxed. Normal EEG of an awake subject shows an alpha rhythm of 8-12 Hz, which increases and decreases on the occipital and parietal lobes and beta waves at the frontal level, interspersed with theta waves. During sleep, both beta waves and delta and theta waves are present (theta in non-REM sleep).
The length of the cycles also varies according to the bands. Alpha bursts typically last from 100 to 500 milliseconds, while the gamma rhythm usually consists of very short bursts, from 20 to 50 milliseconds. In this context, the digital filtering of the signal is of fundamental importance. In addition to the frequency and amplitude, the characteristics of the waves are their shape and trend. For example, the "mu" rhythm can occupy the alpha rhythm band, although compared to this latter; it does not have a clearly sinusoidal aspect; it is maximum centrally and does not have a characteristic growth and degrowth. Again, another aspect to consider is the different expressions of a specific rhythm between the two hemispheres. For example, in healthy individuals, the left frontal alpha is typically between 10% and 15% lower than the controlateral; this asymmetry seems to be important for normal mood control.