human eeg with prominent resting state activity – alpha-rhythm. left: eeg traces (horizontal – time in seconds; vertical – amplitudes, scale 100 μv). right: power spectra of shown signals (vertical lines – 10 and 20 hz, scale is linear). alpha-rhythm consists of sinusoidal-like waves with frequencies in 8–12 hz range (11 hz in this case) more prominent in posterior sites. alpha range is red at power spectrum graph. human eeg with in resting state. left: eeg traces (horizontal – time in seconds; vertical – amplitudes, scale 100 μv). right: power spectra of shown signals (vertical lines – 10 and 20 hz, scale is linear). 80–90% of people have prominent sinusoidal-like waves with frequencies in 8–12 hz range – alpha rhythm. others (like this) lack this type of activity. common artifacts in human eeg. 1: electrooculographic artifact caused by the excitation of eyeball's muscles (related to blinking, for example). big-amplitude, slow, positive wave prominent in frontal electrodes. 2: electrode's artifact caused by bad contact (and thus bigger impedance) between p3 electrode and skin. 3: swallowing artifact. 4: common reference electrode's artifact caused by bad contact between reference electrode and skin. huge wave similar in all channels. 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. frequency bands are usually extracted using spectral methods (for instance welch) as implemented for instance in freely available eeg software such as eeglab or the neurophysiological biomarker toolbox. computational processing of the eeg is often named quantitative electroencephalography (qeeg). 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). waveforms are subdivided into bandwidths known as alpha, beta, theta, and delta to signify the majority of the eeg used in clinical practice. comparison of eeg bands comparison of eeg bands bandfrequency (hz)locationnormallypathologically delta < 4frontally in adults, posteriorly in children; high-amplitude waves adult slow-wave sleep in babies has been found during some continuous-attention tasks subcortical lesions diffuse lesions metabolic encephalopathy hydrocephalus deep midline lesions theta 4–7found in locations not related to task at hand higher in young children drowsiness in adults and teens idling associated with inhibition of elicited responses (has been found to spike in situations where a person is actively trying to repress a response or action). focal subcortical lesions metabolic encephalopathy deep midline disorders some instances of hydrocephalus alpha 8–12posterior regions of head, both sides, higher in amplitude on dominant side. central sites (c3-c4) at rest relaxed/reflecting closing the eyes also associated with inhibition control, seemingly with the purpose of timing inhibitory activity in different locations across the brain. coma beta 13–30both sides, symmetrical distribution, most evident frontally; low-amplitude waves range span: active calm → intense → stressed → mild obsessive active thinking, focus, high alert, anxious benzodiazepines dup15q syndrome gamma > 32somatosensory cortex displays during cross-modal sensory processing (perception that combines two different senses, such as sound and sight) also is shown during short-term memory matching of recognized objects, sounds, or tactile sensations a decrease in gamma-band activity may be associated with cognitive decline, especially when related to the theta band; however, this has not been proven for use as a clinical diagnostic measurement mu 8–12sensorimotor cortex shows rest-state motor neurons. mu suppression could indicate that motor mirror neurons are working. deficits in mu suppression, and thus in mirror neurons, might play a role in autism. the practice of using only whole numbers in the definitions comes from practical considerations in the days when only whole cycles could be counted on paper records. this leads to gaps in the definitions, as seen elsewhere on this page. the theoretical definitions have always been more carefully defined to include all frequencies. unfortunately there is no agreement in standard reference works on what these ranges should be – values for the upper end of alpha and lower end of beta include 12, 13, 14 and 15. if the threshold is taken as 14 hz, then the slowest beta wave has about the same duration as the longest spike (70 ms), which makes this the most useful value. human eeg with prominent alpha-rhythm wave patterns delta waves delta waves is the frequency range up to 4 hz. it tends to be the highest in amplitude and the slowest waves. it is seen normally in adults in slow-wave sleep. it is also seen normally in babies. it may occur focally with subcortical lesions and in general distribution with diffuse lesions, metabolic encephalopathy hydrocephalus or deep midline lesions. it is usually most prominent frontally in adults (e.g. firda – frontal intermittent rhythmic delta) and posteriorly in children (e.g. oirda – occipital intermittent rhythmic delta). theta waves theta is the frequency range from 4 hz to 7 hz. theta is seen normally in young children. it may be seen in drowsiness or arousal in older children and adults; it can also be seen in meditation. excess theta for age represents abnormal activity. it can be seen as a focal disturbance in focal subcortical lesions; it can be seen in generalized distribution in diffuse disorder or metabolic encephalopathy or deep midline disorders or some instances of hydrocephalus. on the contrary this range has been associated with reports of relaxed, meditative, and creative states. alpha waves alpha is the frequency range from 8 hz to 12 hz. hans berger named the first rhythmic eeg activity he observed the "alpha wave". this was the "posterior basic rhythm" (also called the "posterior dominant rhythm" or the "posterior alpha rhythm"), seen in the posterior regions of the head on both sides, higher in amplitude on the dominant side. it emerges with closing of the eyes and with relaxation, and attenuates with eye opening or mental exertion. the posterior basic rhythm is actually slower than 8 hz in young children (therefore technically in the theta range). sensorimotor rhythm aka mu rhythm in addition to the posterior basic rhythm, there are other normal alpha rhythms such as the mu rhythm (alpha activity in the contralateral sensory and motor cortical areas) that emerges when the hands and arms are idle; and the "third rhythm" (alpha activity in the temporal or frontal lobes). alpha can be abnormal; for example, an eeg that has diffuse alpha occurring in coma and is not responsive to external stimuli is referred to as "alpha coma". beta waves beta is the frequency range from 13 hz to about 30 hz. it is seen usually on both sides in symmetrical distribution and is most evident frontally. beta activity is closely linked to motor behavior and is generally attenuated during active movements. 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, such as dup15q syndrome, and drug effects, especially benzodiazepines. it may be absent or reduced in areas of cortical damage. it is the dominant rhythm in patients who are alert or anxious or who have their eyes open. gamma waves gamma is the frequency range approximately 30–100 hz. gamma rhythms are thought to represent binding of different populations of neurons together into a network for the purpose of carrying out a certain cognitive or motor function. mu range is 8–13 hz and partly overlaps with other frequencies. it reflects the synchronous firing of motor neurons in rest state. mu suppression is thought to reflect motor mirror neuron systems, because when an action is observed, the pattern extinguishes, possibly because the normal and mirror neuronal systems "go out of sync" and interfere with one other. "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 seen in normal sleep. there are types of activity that are statistically uncommon, but 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 electroencephalogram (eeg) varies by age. the prenatal eeg and neonatal eeg is quite different from the adult eeg. fetuses in the third trimester and newborns display two common brain activity patterns: "discontinuous" and "trace alternant." "discontinuous" electrical activity refers to sharp bursts of electrical activity followed by low frequency waves. "trace alternant" electrical activity describes sharp bursts followed by short high amplitude intervals and usually indicates quiet sleep in newborns. the eeg in childhood generally has 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 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. artifacts "breach effect" redirects here. for the birth position, see breech birth. main types of artifacts in human eeg eeg is an extremely useful technique for studying brain activity, but the signal measured is always contaminated by artifacts which can impact the analysis of the data. an artifact is any measured signal that does not originate within the brain. although multiple algorithms exist for the removal of artifacts, the problem of how to deal with them remains an open question. the source of artifacts can be from issues relating to the instrument, such as faulty electrodes, line noise or high electrode impedance, or they may be from the physiology of the subject being recorded. this can include, eye blinks and movement, cardiac activity and muscle activity and these types of artifacts are more complicated to remove. artifacts may bias the visual interpretation of eeg data as some may mimic cognitive activity that could affect diagnoses of problems such as alzheimer's disease or sleep disorders. as such the removal of such artifacts in eeg data used for practical applications is of the upmost importance. artifact removal it is important to be able to distinguish artifacts from genuine brain activity in order to prevent incorrect interpretations of eeg data. general approaches for the removal of artifacts from the data are, prevention, rejection and cancellation. the goal of any approach is to develop methodology capable of identifying and removing artifacts without affecting the quality of the eeg signal. as artifact sources are quite different the majority of researchers focus on developing algorithms that will identify and remove a single type of