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 during (inpatient) epilepsy monitoring, a patient's typical seizure medications may be withdrawn.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). the eeg signals can be captured with opensource hardware such as openbci and the signal can be processed by freely available eeg software such as eeglab or the neurophysiological biomarker toolbox. 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 that affect scalp eeg do not impact ecog, and therefore display filtering is often not needed. a typical adult human eeg signal is about 10 µv to 100 µv in amplitude when measured from the scalp. 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. sequential montageeach 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 montageeach 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 montagethe outputs of all of the amplifiers are summed and averaged, and this averaged signal is used as the common reference for each channel. laplacian montageeach 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. therefore, research has been directed to developing dry and semi-dry eeg bioelectronic interfaces. 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. some eeg systems attempt to circumvent this issue by applying a saline solution. others have a semi dry nature and release small amounts of the gel upon contact with the scalp. another solution uses spring loaded pin setups. these may be uncomfortable. they may also be dangerous if they were used in a situation where a patient could bump their head since they could become lodged after an impact trauma incident. arl also developed a visualization tool, customizable lighting interface for the visualization of eegs or clive, which showed how well two brains are synchronized. currently, headsets are available incorporating dry electrodes with up to 30 channels. 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, have 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. in addition, since eegs represent averages of thousands of neurons, a large population of cells in synchronous activity is necessary to cause a significant deflection on the recordings. action potentials are very fast and, as a consequence, the chances of field summation are slim. however, neural backpropagation, as a typically longer dendritic current dipole, can be picked up by eeg electrodes and is a reliable indication of the occurrence of neural output. not only do eegs capture dendritic currents almost exclusively as opposed to axonal currents, they also show a preference for activity on populations of parallel dendrites and transmitting current in the same direction at the same time. pyramidal neurons of cortical layers ii/iii and v extend apical dendrites to layer i. currents moving up or down these processes underlie most of the signals produced by electroencephalography. therefore, eeg provides information with a large bias to select neuron types, and 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, 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 vs fmri, fnirs, fus and pet eeg has several strong points as a tool for exploring brain activity. eegs can detect changes over milliseconds, which is excellent 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 vs 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 are associated with intracellular ionic currents. normal activity one second of eeg signal