The electrical activity of the brain was first demonstrated in 1929 by the German psychiatrist Hans Berger. The scientific professions were slow in giving proper attention to Berger's discovery of the brain rhythms he named alpha waves, but since then at least three other standard brainwave patterns have been isolated and identified. Alpha waves are fast, medium-amplitude oscillations, now known to represent the background activity of the brain in the physically and psychologically healthy adult. They are most characteristically visible during dream-sleep or when a subject is relaxing with eyes closed. Delta waves are large, slow-moving, regular waves, typically associated with the deepest levels of sleep. In children up to the age of puberty the appearance of high-amplitude theta waves, having a velocity between those of alpha and delta rhythms, usually signals the onset of emotional stimulation. The presence of theta waves in adults may be a sign of brain damage or of an immature personality. Beta rhythms are small, very fast wave patterns that indicate intense physiological stress, such as that resulting from barbiturate intoxification.
By observing abnormalities in recordings and determining the area of the brain from which they originate, the physician's ability to diagnose and treat such conditions as epilepsy, cerebral tumor, encephalitis, and stroke, is greatly enhanced. Electroencephalograms have also proven valuable in the general study of brain physiology and in the particular study of sleep. Various types of Eastern meditation, e.g., yoga, use techniques that increase alpha and theta wave activity. Because of concomitant physiological changes during meditation, e.g., lessened anxiety, the techniques have recently become popular in the West. Using EEGs to enhance biofeedback, a subject can be taught to monitor and regulate his or her own brain waves; the technique has been used experimentally in control of epilepsy. EEGs are also used to determine brain death (see death).
Technique for recording electrical activity in the brain, whose cells emit distinct patterns of rhythmic electrical impulses. Pairs of electrodes on the scalp transmit signals to an electroencephalograph, which records them as peaks and troughs on a tracing called an electroencephalogram (EEG). Different wave patterns on the EEG are associated with normal and abnormal waking and sleeping states. They help diagnose conditions such as tumours, infections, and epilepsy. The electroencephalograph was invented in the 1920s by Hans Berger (1873–1941).
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Just as the activity in a computer can be understood on multiple levels, from the activity of individual transistors to the function of applications, so can the electrical activity of the brain be described on relatively small to relatively large scales. At one end are action potentials in a single axon or currents within a single dendrite of a single neuron, and at the other end is the activity measured by the EEG which aggregates the electric voltage fields from millions of neurons. So-called scalp EEG is collected from tens to hundreds of electrodes positioned on different locations at the surface of the head. EEG signals (in the range of milli-volts) are amplified and digitalized for later processing. The data measured by the scalp EEG are used for clinical and research purposes. In neurology, the main diagnostic application of EEG is for epilepsy but this technique is also used to investigate many other pathologies such as sleep-related disorders, sensory deficits, brain tumors, etc. In cognitive neuroscience, EEG is used to investigate the neural correlates of mental activity from low-level perceptual and motor processes to higher-order cognition (attention, memory, reading, etc).
In some cases, such as epileptic studies, when deeper brain activity needs to be recorded with more accuracy than provided by scalp EEG, clinicians use an invasive form of EEG known as intracranial EEG (icEEG) where electrodes are placed directly inside the skull. In some cases, a grid of electrodes is laid on the external surface of the brain, on dura mater yielding epidural EEG but in other cases, brain activity is recorded using deeper electrodes known as subdural EEG (sdEEG) and electrocorticography (ECoG). Because of the filtering characteristics of the skull and scalp, icEEG activity has a much higher spatial resolution than surface EEG. The technique is sometimes also referred to as stereotactic EEG (stereo-EEG or sEEG) to emphasize that it records from precise 3D locations defined by stereotaxy. However, since icEEG uses macro-electrodes for recording it can not detect single-neuron activity as it is feasible with neural implants based on micro-electrodes.
Although post-synaptic potentials generate the EEG signal, it is not possible for a scalp EEG to determine the activity within a single dendrite or neuron. Rather, a surface EEG reading is the summation of the synchronous activity of thousands of neurons that have similar spatial orientation, radial to the scalp. Currents that are tangential to the scalp are not picked up by the EEG. The EEG therefore benefits from the parallel, radial arrangement of apical dendrites in the cortex. Because voltage fields fall off with the fourth power of the radius, activity from deep sources is more difficult to detect than currents near the skull.
Scalp EEG activity oscillates at multiple frequencies having different characteristic spatial distributions associated with different states of brain functioning such as waking and sleeping. These oscillations represent synchronized activity over a network of neurons. The neuronal networks underlying some of these oscillations are understood (such as the thalamocortical resonance underlying sleep spindles) while many others are not (e.g. the system that generates the posterior basic rhythm).
In certain cases, video-EEG monitoring may be required. This is simultaneous recording of EEG and time-locked video/audio. Video-EEG monitoring may involve inpatient admissions for days to weeks. During these admissions, a patient's anti-epileptic medications are often titrated off so that seizures can be recorded. The EEG appearance of the onset of the seizure can provide significantly more definitive information about the patient's epilepsy than interictal recordings can in many cases.
Continuous EEG monitoring typically involves the use of a portable EEG machine connected to an ICU patient to look for seizure activity that is not apparent clinically (i.e., in the patient's mental status or by observing his/her movements). When patients are put into medically-induced comas, the EEG pattern may be used as measure of depth of coma, and the medication may be titrated to an EEG end-point. "Amplitude-integrated EEG" refers to a specific representation of the EEG signal that is used with continuous monitoring of cerebral function in some neonatal ICUs.
These various forms of EEG recording can be used in the following clinical situations:
Use of the quantitative EEG (mathematical measurement of aspects of the EEG signal) in primary psychiatric, behavioral and learning disorders is somewhat controversial.
There are a number of benefits to using EEG in neuroscience research. One is that EEG is non-invasive to the research subject. Furthermore, the need for the subject to hold still is perhaps less stringent than in functional magnetic resonance imaging (fMRI). Another benefit is that many applications of EEG record spontaneous brain activity, and the subject does not need to be able to cooperate with the research (e.g., as is necessary in the behavioral testing of neuropsychology). Also, EEG has a high temporal resolution compared to techniques such as fMRI and is capable of detecting changes in electrical activity in the brain on a millisecond time scale.
Much of the cognitive research conducted with EEG uses the event-related potential (ERP) technique. Most ERP paradigms involve a subject being provided a stimulus to react to either overtly or covertly. There are often at least two conditions that vary in some manner of interest to the researcher. As this stimulus-response is going on, an EEG is being recorded from the subject. The ERP is obtained by averaging the EEG signal from each of the trials within a certain condition; averages from one stimulus-response condition can then be compared with averages from the other stimulus-response condition(s).
In conventional scalp EEG, the recording is obtained by placing electrodes on the scalp with a conductive gel or paste, usually after preparing the scalp area by light abrasion to reduce impedance due to dead skin cells. The technique has been advanced by the use of carbon nanotubes to penetrate the outer layers of the skin for improved electrical contact. The sensor is known as ENOBIO ; however, this technique is not in common research or clinical use. Many systems typically use electrodes, each of which is attached to an individual wire. Some systems use caps or nets into which electrodes are embedded; this is particularly common when high-density arrays of electrodes are needed.
Electrode locations and names are specified by the International 10–20 system for most clinical and research applications (except when high-density arrays are used). This system ensures that the naming of electrodes is consistent across laboratories. In most clinical applications, 19 recording electrodes (plus ground and system reference) are used. A smaller number of electrodes are typically used when recording EEG from neonates. Additional electrodes can be added to the standard set-up when a clinical or research application demands increased spatial resolution for a particular area of the brain. High-density arrays (typically via cap or net) can contain up to 256 electrodes more-or-less evenly spaced around the scalp.
Each electrode is connected to one input of a differential amplifier (one amplifier per pair of electrodes); a common system reference electrode is connected to the other input of each differential amplifier. These amplifiers amplify the voltage between the active electrode and the reference (typically 1,000–100,000 times, or 60–100 dB of voltage gain). In analog EEG, the signal is then filtered (next paragraph), and the EEG signal is output as the deflection of pens as paper passes underneath. Most EEG systems these days, however, are digital, and the amplified signal is digitized via an analog-to-digital converter, after being passed through an anti-aliasing filter. Analog-to-digital sampling typically occurs at 256-512 Hz in clinical scalp EEG; sampling rates of up to 10 kHz are used in some research applications.
The digital EEG signal is stored electronically and can be filtered for display. Typical settings for the high-pass filter and a low-pass filter are 0.5-1 Hz and 35–70 Hz, respectively. The high-pass filter typically filters out slow artifact, such as electrogalvanic signals and movement artifact, whereas the low-pass filter filters out high-frequency artifacts, such as electromyographic signals. An additional notch filter is typically used to remove artifact caused by electrical power lines (60 Hz in the United States and 50 Hz in many other countries).
As part of an evaluation for epilepsy surgery, it may be necessary to insert electrodes near the surface of the brain, under the surface of the dura mater. This is accomplished via burr hole or craniotomy. This is referred to variously as "electrocorticography (ECoG)", "intracranial EEG (I-EEG)" or "subdural EEG (SD-EEG)". Depth electrodes may also be placed into brain structures, such as the amygdala or hippocampus, structures which are common epileptic foci and may not be "seen" clearly by scalp EEG. The electrocorticographic signal is processed in the same manner as digital scalp EEG (above), with a couple of caveats. ECoG is typically recorded at higher sampling rates than scalp EEG because of the requirements of Nyquist theorem—the subdural signal is composed of a higher predominance of higher frequency components. Also, many of the artifacts which affect scalp EEG do not impact ECoG, and therefore display filtering is often not needed.
A typical adult human EEG signal is about 10µV to 100 µV in amplitude when measured from the scalp and is about 10–20 mV when measured from subdural electrodes.
Since an EEG voltage signal represents a difference between the voltages at two electrodes, the display of the EEG for the reading encephalographer may be set up in one of several ways. The representation of the EEG channels is referred to as a montage. Bipolar montage : Each channel (i.e., waveform) represents the difference between two adjacent electrodes. The entire montage consists of a series of these channels. For example, the channel "Fp1-F3" represents the difference in voltage between the Fp1 electrode and the F3 electrode. The next channel in the montage, "F3-C3," represents the voltage difference between F3 and C3, and so on through the entire array of electrodes. Referential montage: Each channel represents the difference between a certain electrode and a designated reference electrode. There is no standard position at which this reference is always placed; it is, however, at a different position than the "recording" electrodes. Midline positions are often used because they do not amplify the signal in one hemisphere vs. the other. Another popular reference is "linked ears," which is a physical or mathematical average of electrodes attached to both earlobes or mastoids. Average reference montage : The outputs of all of the amplifiers are summed and averaged, and this averaged signal is used as the common reference for each channel. Laplacian montage : Each channel represents the difference between an electrode and a weighted average of the surrounding electrodes.
When analog (paper) EEGs are used, the technologist switches between montages during the recording in order to highlight or better characterize certain features of the EEG. With digital EEG, all signals are typically digitized and stored in a particular (usually referential) montage; since any montage can be constructed mathematically from any other, the EEG can be viewed by the electroencephalographer in any display montage that is desired.
It is mathematically impossible to reconstruct a unique intracranial current source for a given EEG signal, as some currents produce potentials that cancel each other out. This is referred to as the inverse problem. However, much work has been done to produce remarkably good estimates of, at least, a localized electric dipole that represents the recorded currents.
EEG can be recorded at the same time as MEG so that data from these complimentary high-time-resolution techniques can be combined.
The EEG is typically described in terms of (1) rhythmic activity and (2) transients. The rhythmic activity is divided into bands by frequency. To some degree, these frequency bands are a matter of nomenclature (i.e., any rhythmic activity between 8-12 Hz can be described as "alpha"), but these designations arose because rhythmic activity within a certain frequency range was noted to have a certain distribution over the scalp or a certain biological significance.
Most of the cerebral signal observed in the scalp EEG falls in the range of 1-20 Hz (activity below or above this range is likely to be artifactual, under standard clinical recording techniques).
|Delta||up to 3||frontally in adults, posteriorly in children; high amplitude waves|| |
|Theta||4 - 7 Hz|| |
|Alpha||8 - 12 Hz||posterior regions of head, both sides, higher in amplitude on dominant side. Central sites (c3-c4) at rest .|| |
|Beta||12 - 30 Hz||both sides, symmetrical distribution, most evident frontally; low amplitude waves|| |
"Ultra-slow" or "near-DC" activity is recorded using DC amplifiers in some research contexts. It is not typically recorded in a clinical context because the signal at these frequencies is susceptible to a number of artifacts.
Some features of the EEG are transient rather than rhythmic. Spikes and sharp waves may represent seizure activity or interictal activity in individuals with epilepsy or a predisposition toward epilepsy. Other transient features are normal: vertex waves and sleep spindles are transient events which are seen in normal sleep.
It should also be noted that there are types of activity which are statistically uncommon but are not associated with dysfunction or disease. These are often referred to as "normal variants." The mu rhythm is an example of a normal variant.
The normal EEG varies by age. The neonatal EEG is quite different from the adult EEG. The EEG in childhood is generally comprised of slower frequency oscillations than the adult EEG.
The normal EEG also varies depending on state. The EEG is used along with other measurements (EOG, EMG) to define sleep stages in polysomnography. Stage I sleep (equivalent to drowsiness in some systems) appears on the EEG as drop-out of the posterior basic rhythm. There can be an increase in theta frequencies. Santamaria and Chiappa cataloged a number of the variety of patterns associated with drowsiness. Stage II sleep is characterized by sleep spindles--transient runs of rhythmic activity in the 12-14 Hz range (sometimes referred to as the "sigma" band) that have a frontal-central maximum. Most of the activity in Stage II is in the 3-6 Hz range. Stage III and IV sleep are defined by the presence of delta frequencies and are often referred to collectively as "slow-wave sleep." Stages I-IV are comprise non-REM (or "NREM") sleep. The EEG in REM (rapid eye movement) sleep appears somewhat similar to the awake EEG.
EEG under general anesthesia depends on the type of anesthetic employed. With halogenated anesthetics, such as halothane or intravenous agents, such as propofol, a rapid (alpha or low beta), nonreactive EEG pattern is seen over most of the scalp, especially anteriorly; in some older terminology this was known as a WAR (widespread anterior rapid) pattern, contrasted with a WAIS (widespread slow) pattern associated with high doses of opiates. Anesthetic effects on EEG signals are beginning to be understood at the level of drug actions on different kinds of synapses and the circuits that allow synchronized neuronal activity (see: http://www.stanford.edu/group/maciverlab/).
Eyeball artifacts are caused by the potential difference between the cornea and retina, which is quite large compared to cerebral potentials. When the eye is completely still, this is not a problem. But there are nearly always small or large reflexive eye movements, which generates a potential which is picked up in the frontopolar and frontal leads. Involuntary eye movements, known as saccades, are caused by ocular muscles, which also generate electromyographic potentials. Purposeful or reflexive eye blinking also generates electromyographic potentials, but more importantly there is reflexive movement of the eyeball during blinking which gives a characteristic artifactual appearance of the EEG (see Bell's phenomenon).
Eyelid fluttering artifacts of a characteristic type were previously called Kappa rhythm (or Kappa waves). It is usually seen in the prefrontal leads, that is, just over the eyes. Sometimes they are seen with mental activity. They are usually in the Theta (4–7 Hz) or Alpha (8–13 Hz) range. They were named because they were believed to originate from the brain. Later study revealed they were generated by rapid fluttering of the eyelids, sometimes so minute that it was difficult to see. They are in fact noise in the EEG reading, and should not technically be called a rhythm or wave. Therefore, current usage in electroencephalography refers to the phenomenon as an eyelid fluttering artifact, rather than a Kappa rhythm (or wave).
Some of these artifacts are useful. Eye movements are very important in polysomnography, and is also useful in conventional EEG for assessing possible changes in alertness, drowsiness or sleep.
EKG artifacts are quite common and can be mistaken for spike activity. Because of this, modern EEG acquisition commonly includes a one-channel EKG from the extremities. This also allows the EEG to identify cardiac arrhythmias that are an important differential diagnosis to syncope or other episodic/attack disorders.
Glossokinetic artifacts are caused by the potential difference between the base and the tip of the tongue. Minor tongue movements can contaminate the EEG, especially in parkinsonian and tremor disorders.
Focal epileptiform discharges represent fast, synchronous potentials in a large number of neurons in a somewhat discrete area of the brain. These can occur as interictal activity, between seizures, and represent an area of cortical irritability that may be predisposed to producing epileptic seizures. Interictal discharges are not wholly reliable for determining whether a patient has epilepsy nor where his/her seizure might originate. (See focal epilepsy.)
Generalized epileptiform discharges often have an anterior maximum, but these are seen synchronously throughout the entire brain. They are strongly suggestive of a generalized epilepsy.
Focal non-epileptiform abnormal activity may occur over areas of the brain where there is focal damage of the cortex or white matter. It often consists of an increase in slow frequency rhythms and/or a loss of normal higher frequency rhythms. It may also appear as focal or unilateral decrease in amplitude of the EEG signal.
Diffuse non-epileptiform abnormal activity may manifest as diffuse abnormally slow rhythms or bilateral slowing of normal rhythms, such as the PBR.
In 1912, Russian physiologist, Vladimir Vladimirovich Pravdich-Neminsky published the first EEG and the evoked potential of the mammalian (dog). In 1914, Cybulsky and Jelenska-Macieszyna photographed EEG-recordings of experimentally induced seizures.
German physiologist and psychiatrist Hans Berger (1873–1941) began his studies of the human EEG in 1920. He gave the device its name and is sometimes credited with inventing the EEG, though others had performed similar experiments. His work was later expanded by Edgar Douglas Adrian.
In 1934, Fisher and Lowenback first demonstrated epileptiform spikes. In 1935 Gibbs, Davis and Lennox described interictal spike waves and the 3 cycles/s pattern of clinical absence seizures, which began the field of clinical electroencephalography. Subsequently, in 1936 Gibbs and Jasper reported the interictal spike as the focal signature of epilepsy. The same year, the first EEG laboratory opened at Massachusetts General Hospital.
Franklin Offner (1911–1999), professor of biophysics at Northwestern University developed a prototype of the EEG which incorporated a piezoelectric inkwriter called a Crystograph (the whole device was typically known as the Offner Dynograph).
In 1947, The American EEG Society was founded and the first International EEG congress was held. In 1953 Aserinsky and Kleitmean describe REM sleep.
In the 1950s, English physician William Grey Walter developed an adjunct to EEG called EEG topography which allowed for the mapping of electrical activity across the surface of the brain. This enjoyed a brief period of popularity in the 1980s and seemed especially promising for psychiatry. It was never accepted by neurologists and remains primarily a research tool.