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Electroencephalography is the neurophysiologic measurement of the electrical activity of the brain by recording from electrodes placed on the scalp or, in special cases, subdurally or in the cerebral cortex. The resulting traces are known as an electroencephalogram (EEG) and represent an electrical signal (postsynaptic potentials) from a large number of neurons. These are sometimes called brainwaves, though this use is discouraged <ref name="recom_clin_neurophys_1983>Cobb, WA (1983). Recommendations for the practice of clinical neurophysiology. Amsterdam: Elsevier.</ref>. The EEG is a brain function test, but in clinical use it is a "gross correlate of brain activity" <ref name="eeg_daley_2002> (2002) John S. Ebersole: Current Practice of Clinical Electroencephalography. Lippincott Williams & Wilkins.</ref>. Electrical currents are not measured, but rather voltage differences between different parts of the brain.

EEGs are frequently used in experimentation because the process is non-invasive to the research subject. The subject does not need to make a decision or behavioral action in order to log data, and it can detect covert responses to stimuli, such as reading. The EEG is capable of detecting changes in electrical activity in the brain on a millisecond-level. It is one of the few techniques available that has such high temporal resolution. The other common technique is MEG.


[edit] Clinical use

EEG in various forms is most useful as a tool for monitoring and diagnosis in certain clinical situations:

It is sometimes useful in assessing dementia, when other examinations are equivocal. In some jurisdictions it has a legal significance and formal criteria are used to assess brain death. Current research is being done to determine if EEG may also be used to help monitor clinical depression treatment, but such studies are still in the clinical stages.

[edit] Research use

Neuroscientists and biological psychiatrists use EEGs to study the function of the brain by recording cerebral activity during controlled behavior of human volunteers and animals in lab experiments. Theories to explain sleep often rely on EEG patterns recorded during sleep sessions.

The first EEG recording, obtained by Hans Berger in 1924.

[edit] Methods

In conventional scalp EEG, the recording is obtained by placing electrodes on the scalp, usually after preparing the scalp area by light abrasion and application of a conductive gel to reduce impedance. Each electrode is connected to an input of a differential amplifier (one amplifier per pair of electrodes), which amplifies the voltage between them (typically 1,000–100,000 times, or 60–100 dB of voltage gain). The resulting voltage signal is filtered by a high-pass filter and a low-pass filter, typically set at 0.5 hertz and 35-70 Hz, respectively. The high-pass filter typically filters out slow electrogalvanic signals, whereas the low-pass filter filters out electromyographic signals.

The filtered signal is then output on paper (in older systems), or displayed on a computer screen. 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 electrode-amplifier relationships are typically arranged in one of three ways:

Common reference derivation 
One terminal of each amplifier is connected to the same electrode, and all other electrodes are measured relative to this single point. It is typical to use a reference electrode placed somewhere along the scalp midline, or a reference that links both earlobe electrodes.
Average reference derivation 
The outputs of all of the amplifiers are summed and averaged, and this averaged signal is used as the common reference for each amplifier.
Bipolar derivation 
The electrodes are connected in series to an equal number of amplifiers. For example, amplifier 1 measures the difference between electrodes A and B, amplifier 2 measures the difference between B and C, and so on.

This distinction has become void with the advent of digital or paperless EEGs, which record all electrodes against an arbitrary reference and will calculate the above relationships (called montages) post hoc.

[edit] Limitations

EEG has several limitations. Scalp electrodes are not sensitive enough to pick out individual action potentials, the electric unit of signaling in the brain, or whether the resulting electrical activity is releasing inhibitory, excitatory or modulatory neurotransmitters. Instead, the EEG picks up the activity of large groups of neurons, which produces a greater voltage than the firing of an individual neuron. Secondly, EEG has limited anatomical specificity when compared with other functional brain imaging techniques such as functional magnetic resonance imaging (fMRI). Some anatomical specificity can be gained with the use of EEG topography, which uses a large number of electrodes to triangulate the source of the electrical activity.

[edit] Advantages

EEG has several strong sides as a tool of exploring the brain activity. The time resolution is very high. As other methods for researching brain activity have time resolution between seconds and minutes, the EEG has a resolution down to sub-millisecond. As the brain is thought to work through its electric activity, EEG is the only method to measure it directly. Other methods for exploring functions in the brain rely on blood flow or metabolism which may be decoupled from the brain electric activity. Newer research typically combines EEG or MEG with MRI or PET to get high temporal and spatial resolution.

[edit] Activity types

Image:Eeg raw.svg
One second of EEG signal

Historically four major types of continuous rhythmic sinusoidal EEG activity are recognized (alpha, beta, delta and theta). There is no precise agreement on the frequency ranges for each type.

  • Delta is the frequency range up to 4 Hz and is often associated with the very young and certain encephalopathies and underlying lesions. It is seen in stage 3 and 4 sleep.
Image:Eeg delta.svg
Delta waves.
  • Theta is the frequency range from 4 Hz to 8 Hz and is associated with drowsiness, childhood, adolescence and young adulthood. This EEG frequency can sometimes be produced by hyperventilation. Theta waves can be seen during hypnagogic states such as trances, hypnosis, deep day dreams, lucid dreaming and light sleep and the preconscious state just upon waking, and just before falling asleep.
Image:Eeg theta.svg
Theta waves.
  • Alpha (Berger's wave) is the frequency range from 8 Hz to 12 Hz. It is characteristic of a relaxed, alert state of consciousness. Alpha rhythms are best detected with the eyes closed. Alpha attenuates with drowsiness and open eyes, and is best seen over the occipital (visual) cortex. An alpha-like normal variant called mu is sometimes seen over the motor cortex (central scalp) and attenuates with movement, or rather with the intention to move.
Image:Eeg alpha.svg
Alpha waves.
  • sensorimotor rhythm (SMR) is a middle frequency (about 12–16 Hz) associated with physical stillness and body presence.
  • Beta is the frequency range above 12 Hz. Low amplitude beta with multiple and varying frequencies is often associated with active, busy or anxious thinking and active concentration. Rhythmic beta with a dominant set of frequencies is associated with various pathologies and drug effects, especially benzodiazepines.
Image:Eeg beta.svg
Beta waves.
  • Gamma is the frequency range approximately 26–100 Hz. Gamma rhythms appear to be involved in higher mental activity, including perception, problem solving, fear, and consciousness.
Image:Eeg gamma.svg
Gamma waves.

Rhythmic slow activity in wakefulness is common in young children, but is abnormal in adults. In addition to the above types of rhythmic activity, individual transient waveforms such as sharp waves, spikes, spike-and-wave complexes occur in epilepsy, and other types of transients occur during sleep.

In the transition from wakefulness, through Stage I sleep (drowsiness), Stage II (light) sleep, to Stage III and IV (deep) sleep, first the alpha becomes intermittent and attenuated, then disappears. Stage II sleep is marked by brief bursts of highly rhythmic beta activity (sleep spindles) and K complexes (transient slow waves associated with spindles, often triggered by an auditory stimulus). Stage III and IV are characterized by slow wave activity. After a period of deep sleep, the sleeper cycles back to stage II sleep and/or rapid eye movement (REM) sleep, associated with dreaming. These cycles may occur many times during the night.

EEG under general anesthesia depends on the type of anesthetic employed. With halogenated anesthetics and 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.

[edit] Artifacts

[edit] Biological Artifacts

Signals in the EEG that are of non-cerebral origin are called artifacts. The EEG is nearly always contaminated by such signals. This is one of the reasons why it takes considerable experience to interpret EEGs clinically. The most common types of artifacts are:

  • Eye artifacts (including eyeball, ocular muscles and eyelid)
  • EKG artifacts
  • EMG artifacts
  • Glossokinetic artifacts

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. Eye movements - whether vertical or horizontal [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 artefactual appearance of the EEG (see Bell's phenomenon).

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 extremeties. This also allows the EEG to identify cardiac arrythmias 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.

[edit] External Artifacts

In addition to internal artifacts, there are many artifacts which originate from outside the patient. Movement by the patient, or even just settling of the electrodes, may cause electrode pops, spikes originating from a momentary change in the impedence of a given electrode. From a completely different source, within the United States, poor grounding of the EEG electrodes can cause a significant 60 Hz artifact (50 Hz in many other countries). A third source of possible interference can be the presence of an IV drip; such devices can cause rhythmic, fast, low-voltage bursts, which may be confused for spikes.

[edit] Artifact Correction

Recently, source decomposition techniques have been used to "correct" or "remove" EEG artifacts. These source decomposition models, in one way or another, assume the ability to "unmix" EEG signal into some number of independent sources. If one happens to agree with the principle behind a particular decomposition approach, then there is no argument against "remixing" only those sources that do not resemble artifact. There is no proof yet as to the validity or preciseness of these methods since simulated EEG recordings are the only way to know beforehand, the exact properties of the uncontaminated signal. In reality, EEG is to some extent stochastic.

[edit] History

A brief timeline is given here <ref>Template:Cite journal</ref>. Richard Caton (18421926), a physician practicing in Liverpool, presented his findings about electrical phenomena of the exposed cerebral hemispheres of rabbits and monkeys in the British Medical Journal in 1875. In 1890, Beck publishes an investigation of spontaneous electrical activity of the brain of rabbits and dogs which included rhythmic oscillations altered by light.

In 1912, Russian physiologist, Vladimir Vladimirovich Pravdich-Neminsky published the first EEG and the evoked potential of the mammalian (dog)<ref>Pravdich-Neminsky VV. Ein Versuch der Registrierung der elektrischen Gehirnerscheinungen (In German). Zbl Physiol 27: 951–960, 1913.</ref>. In 1914, Cybulsky and Jelenska-Macieszyna photograph EEG-recordings of experimentally induced seizures.

German physiologist Hans Berger (18731941) 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 demonstrate epileptiform spikes. In 1935 Gibbs, Davis and Lennox describe interictal spike waves and the 3 cycles/s pattern of clinical absence seizures, beginning the field of clinical electroencephalography. In 1936 Gibbs and Jasper report 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 piezoelectronic inkwriter called a Crystograph (the whole device was typically known as the Offner Dynograph).

In 1947, The American EEG Society is founded and the first International EEG congress is 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.

In 2004, Antoine Lutz et al., collaborating with Richard J. Davidson, reported that long-term meditators could "self-induce high-amplitude gamma synchrony during mental practice" in the Proceedings of the National Academy of Sciences<ref>Antoine Lutz et al. "Long-term meditators self-induce high-amplitude gamma synchrony during mental practice". Proceedings of the National Academy of Sciences 101:46, 16369-16373, 2004. (full text)</ref>.

[edit] References

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[edit] See also

[edit] External links

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