Abstract and Keywords
Evoked potentials are those components of the EEG that arise in response to a stimulus (which may be electric, auditory, visual, etc.). Such signals are usually below the noise level and thus not readily distinguished, and one must use a train of stimuli and signal averaging to improve the signal-to-noise ratio. Single-neuron behavior can be examined through the use of microelectrodes which impale the cells of interest. Through studies of the single cell, one hopes to build models of cell networks that will reflect actual tissue properties.
The first recording of the electric field of the human brain was made by the German psychiatrist Hans Berger in 1924 in Jena. He gave this recording the name electroencephalogram (EEG) (Berger, 1929). (From 1929 to 1938 he published 20 scientific papers on the EEG under the same title “Über das Elektroenkephalogram des Menschen.”)
The electric activity of the brain is usually divided into three categories:
1. spontaneous activity,
2. evoked potentials, and
3. bioelectric events produced by single neurons.
Spontaneous activity is measured on the scalp or on the brain and is called the electroencephalogram. The amplitude of the EEG is about 100 μV when measured on the scalp, and about 1–2 mV when measured on the surface of the brain. The bandwidth of this signal is from under 1 Hz to about 50 Hz, as demonstrated in Figure 13.1. As the phrase “spontaneous activity” implies, this activity goes on continuously in the living individual.
Evoked potentials are those components of the EEG that arise in response to a stimulus (which may be electric, auditory, visual, etc.). Such signals are usually below the noise level and thus not readily distinguished, and one must use a train of stimuli and signal averaging to improve the signal-to-noise ratio.
Single-neuron behavior can be examined through the use of microelectrodes which impale the cells of interest. Through studies of the single cell, one hopes to build models of cell networks that will reflect actual tissue properties.
13.2 The Brain as a Bioelectric Generator
Source: Distribution of impressed current source elements J i (volume source)
Conductor: Finite, inhomogeneous
The number of nerve cells in the brain has been estimated to be on the order of 1011. Cortical neurons are strongly interconnected. Here the surface of a single neuron may be covered with 1,000–100,000 synapses (Nunez, 1981). The electric behavior of the neuron corresponds to the description of excitable cells introduced in the earlier chapters. The resting voltage is around −70 mV, and the peak of the action (p.258)
The bioelectric impressed current density J i associated with neuronal activation produces an electric field, which can be measured on the surface of the head or directly on the brain tissue. The electric field was described by Equation 7.10 for a finite inhomogeneous model. This equation is repeated here:
While for most excitable tissue the basis for the impressed current density J i is the propagating action potential, for the EEG it appears to arise from the action of a chemical transmitter on postsynaptic cortical neurons. The action causes localized depolarization—that is, an excitatory postsynaptic potential (EPSP)—or hyperpolarization—that is, an inhibitory postsynaptic potential (IPSP). The result in either case is a spatially distributed discontinuity in the function σΦ (i.e., σoΦo – σiΦi) which, as pointed out in Equation 8.28, evaluates a double-layer source in the membranes of all cells. This will be zero for resting cells; however, when a cell is active by any of the aforementioned processes (in which case Φo – Φi = V m varies over a cell surface), a nonzero primary source will result.
For distant field points the double layer can be summed up vectorially, yielding a net dipole for each active cell. Since neural tissue is generally composed of a very large number of small, densely packed cells, the discussion in Section 8.5 applies, leading to the identification of a continuous volume source distribution J i which appears in Equations 7.6 and 7.10.
Although in principle the EEG can be found from the evaluation of Equation 7.10, the complexity of brain structure and its electrophysiological behavior have thus far precluded the evaluation of the source function J i. Consequently, the quantitative study of the EEG differs from that of the ECG or EMG, in which it is possible to evaluate the source function. Under these conditions the quantitative EEG is based on a statistical treatment, whereas the clinical EEG is largely empirical.
13.3 EEG Lead Systems
The internationally standardized 10–20 system is usually employed to record the spontaneous EEG. In this system 21 electrodes are located on the surface of the scalp, as shown in Figure 13.2A and B. The positions are determined as follows: Reference points are nasion, which is the delve at the top of the nose, level with the eyes; and inion, which is the bony lump at the base of the skull on the midline at the back of the head. From these points, the skull perimeters are measured in the transverse and median planes. Electrode locations are determined by dividing these perimeters into 10% and 20% intervals. Three other electrodes are placed on each side equidistant from the neighboring points, as shown in Figure 13.2B (Jasper, 1958; Cooper, Osselton, and Shaw, 1969).
In addition to the 21 electrodes of the international 10–20 system, intermediate 10% electrode positions are also used. The locations and nomenclature of these electrodes are standardized by the American Electroencephalographic Society (Sharbrough et al., 1991; see Fig. 13.2C). In this recommendation, four electrodes have different names compared to the 10–20 system; these are T7, T8, P7, and P8. These electrodes are drawn black with white text in the figure. (p.259)
Besides the international 10–20 system, many other electrode systems exist for recording electric potentials on the scalp. The Queen Square system of electrode placement has been proposed as a standard in recording the pattern of evoked potentials in clinical testings (Blumhardt et al., 1977).
13.4 Sensitivity Distribution of EEG Electrodes
Rush and Driscoll (1969) calculated the sensitivity distribution of bipolar surface electrodes on the scalp based on a concentric spherical head model. They published the results in the form of lead field isopotential lines. The direction of the lead field current density—that is, the direction of the sensitivity—is a negative gradient of the potential field. This is not immediately evident from such a display.
Puikkonen and Malmivuo (1987) recalculated the sensitivity distribution of EEG electrodes with the same model as Rush and Driscoll, but they presented the results with the lead field current flow lines instead of the isopotential lines of the lead field. This display is illustrative since it is easy to find the direction of the sensitivity from the lead field current flow lines. Also the magnitude of the sensitivity can be seen from the density of the flow lines. A minor problem in this display is that because the lead field current distributes both in the plane of the illustration as well as in the plane normal to it, part of the flow lines must break in order to illustrate correctly the current density with the flow line density in a three-dimensional problem. Suihko, Malmivuo, and Eskola (1993) calculated further the isosensitivity lines and the half-sensitivity volume for the electric leads. As discussed in Section 11.6.1, the concept of half-sensitivity volume denotes the region where the lead field current density is at least one half of its maximum value. Thus this concept is a figure of merit to describe how concentrated the sensitivity distribution of the lead is. As discussed in Section 11.6.6, when the conductivity is isotropic, as it is in this head model, the isosensitivity lines follow the isofield lines of the (reciprocal) electric field. If the lead would exhibit such a symmetry that adjacent isopotential surfaces would be a constant distance apart, the isosensitivity lines would coincide with the isopotential lines. That is not the case in the leads of Figure 13.4.
Figure 13.4 displays the lead field current flow lines, isosensitivity lines and half-sensitivity volumes for the spherical head model with
13.5 The Behavior of the EEG Signal
From the EEG signal it is possible to differentiate alpha (α), beta (β), delta (δ), and theta (Θ) waves as well as spikes associated with epilepsy. An example of each waveform is given in Figure 13.5.
13.6 The Basic Principles of EEG Diagnosis
The EEG signal is closely related to the level of consciousness of the person. As the activity increases, the EEG shifts to higher dominating frequency and lower amplitude. When the eyes are closed, the alpha waves begin to dominate the EEG. When the person falls asleep, the dominant EEG frequency decreases. In a certain phase of sleep, rapid eye movement called (REM) sleep, the person dreams and has active movements of the eyes, which can be seen as a characteristic EEG signal. In deep sleep, the EEG has large and slow deflections called delta waves. No cerebral activity can be detected from a patient with complete cerebral death. Examples of the above-mentioned waveforms are given in Figure 13.6.
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