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. 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 power 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 20 kHz are used in some research applications. During the recording, a series of activation procedures may be used. These procedures may induce normal or abnormal EEG activity that might not otherwise be seen. These procedures include hyperventilation, photic stimulation (with a strobe light), eye closure, mental activity, sleep and sleep deprivation. During (inpatient) epilepsy monitoring, a patient's typical seizure medications may be withdrawn. 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). Since an EEG voltage signal represents a difference between the voltages at two electrodes, the display of the EEG for the reading electroencephalographer may be set up in one of several ways. The representation of the EEG channels is referred to as a
montage. ; Sequential 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 for this reference; 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, such as Cz, Oz, Pz etc. as online reference. The other popular offline references are: • REST reference: which is an offline computational reference at infinity where the potential is zero. REST (reference electrode standardization technique) takes the equivalent sources inside the brain of any a set of scalp recordings as springboard to link the actual recordings with any an online or offline( average, linked ears etc.) non-zero reference to the new recordings with infinity zero as the standardized reference. • "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. The EEG is read by a
clinical neurophysiologist or
neurologist (depending on local custom and law regarding
medical specialities), optimally one who has specific training in the interpretation of EEGs for clinical purposes. This is done by visual inspection of the waveforms, called graphoelements. The use of computer signal processing of the EEG – so-called
quantitative electroencephalography – is somewhat controversial when used for clinical purposes (although there are many research uses).
Dry EEG electrodes In the early 1990s Babak Taheri, at
University of California, Davis demonstrated the first single and also multichannel dry active electrode arrays using micro-machining. The single channel dry EEG electrode construction and results were published in 1994. The arrayed electrode was also demonstrated to perform well compared to
silver/
silver chloride electrodes. The device consisted of four sites of sensors with integrated electronics to reduce noise by
impedance matching. The advantages of such electrodes are: (1) no electrolyte used, (2) no skin preparation, (3) significantly reduced sensor size, and (4) compatibility with EEG monitoring systems. The active electrode array is an integrated system made of an array of capacitive sensors with local integrated circuitry housed in a package with batteries to power the circuitry. This level of integration was required to achieve the functional performance obtained by the electrode. The electrode was tested on an electrical test bench and on human subjects in four modalities of EEG activity, namely: (1) spontaneous EEG, (2) sensory event-related potentials, (3) brain stem potentials, and (4) cognitive event-related potentials. The performance of the dry electrode compared favorably with that of the standard wet electrodes in terms of skin preparation, no gel requirements (dry), and higher signal-to-noise ratio. In 1999 researchers at
Case Western Reserve University, in
Cleveland,
Ohio, led by Hunter Peckham, used 64-electrode EEG skullcap to return limited hand movements to
quadriplegic Jim Jatich. As Jatich concentrated on simple but opposite concepts like up and down, his beta-rhythm EEG output was analysed using software to identify patterns in the noise. A basic pattern was identified and used to control a switch: Above average activity was set to on, below average off. As well as enabling Jatich to control a computer cursor the signals were also used to drive the nerve controllers embedded in his hands, restoring some movement. In 2018, a functional dry electrode composed of a polydimethylsiloxane
elastomer filled with conductive carbon
nanofibers was reported. This research was conducted at the
U.S. Army Research Laboratory. EEG technology often involves applying a gel to the scalp which facilitates strong signal-to-noise ratio. This results in more reproducible and reliable experimental results. Since patients dislike having their hair filled with gel, and the lengthy setup requires trained staff on hand, utilizing EEG outside the laboratory setting can be difficult. Additionally, it has been observed that wet electrode sensors' performance reduces after a span of hours. Dry electrode signals depend upon mechanical contact. Therefore, it can be difficult getting a usable signal because of impedance between the skin and the electrode. Others have a semi dry nature and release small amounts of the gel upon contact with the scalp. Such designs are able to compensate for some of the signal quality degradation related to high impedances by optimizing pre-amplification, shielding and supporting mechanics.
Limitations EEG has several limitations. Most important is its poor spatial resolution. EEG is most sensitive to a particular set of post-synaptic potentials: those generated in superficial layers of the cortex, on the crests of
gyri directly abutting the skull and radial to the skull. Dendrites which are deeper in the cortex, inside
sulci, in midline or deep structures (such as the
cingulate gyrus or
hippocampus), or producing currents that are tangential to the skull, make far less contribution to the EEG signal. EEG recordings do not directly capture axonal
action potentials. An action potential can be accurately represented as a current
quadrupole, meaning that the resulting field decreases more rapidly than the ones produced by the current dipole of post-synaptic potentials. EEG thus provides information with a large bias in favor of particular neuron types, locations and orientations. So it generally should not be used to make claims about global brain activity. The
meninges,
cerebrospinal fluid and skull "smear" the EEG signal, obscuring its intracranial source. It is mathematically impossible to reconstruct a unique intracranial current source for a given EEG signal,
EEG's benefits over fMRI, fNIRS, fUS and PET EEG has several strong points as a tool for exploring brain activity. EEG have excellent temporal resolution and can detect changes over milliseconds, which is particularly useful to assess a reaction to a stimulus considering an
action potential takes approximately 0.5–130 milliseconds to propagate across a single neuron, depending on the type of neuron. Other methods of looking at brain activity, such as
PET,
fMRI or
fUS have time resolution between seconds and minutes. EEG measures the brain's electrical activity directly, while other methods record changes in blood flow (e.g.,
SPECT, fMRI, fUS) or metabolic activity (e.g., PET,
NIRS), which are indirect markers of brain electrical activity. EEG can be used simultaneously with fMRI or fUS so that high-temporal-resolution data can be recorded at the same time as high-spatial-resolution data, however, since the data derived from each occurs over a different time course, the data sets do not necessarily represent exactly the same brain activity. There are technical difficulties associated with combining EEG and fMRI including the need to remove the
MRI gradient artifact present during MRI acquisition. Furthermore, currents can be induced in moving EEG electrode wires due to the magnetic field of the MRI. EEG can be used simultaneously with
NIRS or fUS without major technical difficulties. There is no influence of these modalities on each other and a combined measurement can give useful information about electrical activity as well as hemodynamics at medium spatial resolution. EEG is also frequently combined with functional near-infrared spectroscopy (fNIRS) to enable simultaneous measurement of fast neuronal electrical activity and slower hemodynamic responses associated with neurovascular coupling. In such multimodal approaches, EEG provides millisecond-level temporal resolution, while fNIRS contributes complementary information on changes in oxygenated and deoxygenated hemoglobin with moderate spatial resolution. Combined EEG–fNIRS measurements can be performed without major technical interference between modalities and are therefore well suited for studies conducted outside highly controlled imaging environments. Integrated wireless EEG–fNIRS research systems have been developed to support synchronized data acquisition in a single wearable setup, including platforms such as the g.Nautilus wireless EEG and fNIRS headset produced by g.tec medical engineering GmbH, which enables concurrent recording of multi-channel EEG and fNIRS signals for applications in cognitive neuroscience, brain–computer interface research, and neurorehabilitation.
EEG vis-à-vis MEG EEG reflects correlated synaptic activity caused by
post-synaptic potentials of cortical
neurons. The ionic currents involved in the generation of fast
action potentials may not contribute greatly to the averaged
field potentials representing the EEG. More specifically, the scalp electrical potentials that produce EEG are generally thought to be caused by the extracellular ionic currents caused by
dendritic electrical activity, whereas the fields producing
magnetoencephalographic signals ==Normal activity==