14+Evoked+Potentials

=[|ERP NEXUS 32]=
 * ERP:** The BioTrace+ software for NeXus-32 supports basic event related potential functions (such as for the P300) with programmable audio and visual events in single stimulus or oddball paradigms. Dual screen mode on a single computer is included. Internal software and external hardware stimulus events are supported. (trigger input)

[|Wikipedia]





= [|Wikipedia]  Evoked Potentials   = An evoked potential (or "evoked response") is an [|electrical potential] recorded from the [|nervous system] of a [|human] or other [|animal] following presentation of a [|stimulus], as distinct from spontaneous potentials as detected by [|electroencephalography] (EEG) or [|electromyography] (EMG). Evoked potential [|amplitudes] tend to be low, ranging from less than a [|microvolt] to several microvolts, compared to tens of microvolts for EEG, millivolts for EMG, and often close to a volt for [|ECG]. To resolve these low-amplitude potentials against the background of ongoing EEG, ECG, EMG and other biological signals and ambient noise, signal [|averaging] is usually required. The signal is time-locked to the stimulus and most of the [|noise] occurs randomly, allowing the noise to be averaged out with averaging of repeated responses. [|[1] ] Signals can be recorded from [|cerebral cortex], [|brain stem] , [|spinal cord] and [|peripheral nerves]. Usually the term "evoked potential" is reserved for responses involving either recording from, or stimulation of, central nervous system structures. Thus evoked compound motor action potentials (CMAP) or sensory nerve action potentials (SNAP) as used in [|nerve conduction studies] (NCS) are generally not thought of as evoked potentials, though they do meet the above definition.

Sensory evoked potentials
Sensory evoked potentials (SEP) are recorded from the following stimulation of  (for example,  evoked potentials elicited by a flashing light or changing pattern on a monitor; [|[2] ]  evoked potentials by a click or tone stimulus presented through earphones) or by tactile or  evoked potential (SSEP) elicited by tactile or electrical stimulation of a sensory or mixed nerve in the. They have been widely used in medicine since the 1970s, and also in intraoperative neurophysiology monitoring (IONM), also known as surgical neurophysiology. There are three kinds of evoked potentials in widespread clinical use: auditory evoked potentials, usually recorded from the scalp but originating at level; visual evoked potentials, and , which are elicited by electrical stimulation of peripheral nerve. See below. Long and Allen [|[3] ] reported the abnormal BAEPs in an alcoholic woman who recovered from. These investigators hypothesized that their patient's was poisoned, but not destroyed, by her chronic alcoholism.

Steady-state evoked potential
An evoked potential is the electrical response of the brain to a sensory stimulus. Regan constructed an analogue Fourier series analyzer to record harmonics of the evoked potential to flickering (sinusoidally modulated) light but, rather than integrating the sine and cosine products, fed them to a two-pen recorder via lowpass filters. [|[4] ] This allowed him to demonstrate that the brain attained a steady-state regime in which the amplitude and phase of the harmonics (frequency components) of the response were approximately constant over time. By analogy with the steady-state response of a resonant circuit that follows the initial transient response he defined an idealized steady-state evoked potential (SSEP) as a form of response to repetitive sensory stimulation in which the constituent frequency components of the response remain constant with time in both amplitude and phase. [|[4] ] [|[5] ] Although this definition implies a series of identical temporal waveforms, it is more helpful to define the SSEP in terms of the frequency components that are an alternative description of the time-domain waveform, because different frequency components can have quite different properties [|[5] ] [|[6] ] For example, the properties of the high-frequency flicker SSEP (whose peak amplitude is near 40–50 Hz) correspond to the properties of the subsequently discovered magnocellular neurons the retina of the macaque monkey, while the properties of the medium-frequency flicker SSEP ( whose amplitude peak is near 15–20 Hz) correspond to the properties of parvocellular neurons. [|[7] ] Since a SSEP can be completely described in terms of the amplitude and phase of each frequency component it can be quantified more unequivocally than an averaged transient evoked potential. It is sometimes said that SSEPs are elicited only by stimuli of high repetition frequency, but this is not generally correct. In principle, a sinusoidally modulated stimulus can elicit a SSEP even when its. Because of the high-frequency of the SSEP, high frequency stimulation can produce a near-sinusoidal SSEP waveform, but this is not germane to the definition of a SSEP. By using zoom-FFT to record SSEPs at the theoretical limit of spectral resolution ΔF (where ΔF in Hz is the reciprocal of the recording duration in seconds) Regan and Regan discovered that the amplitude and phase variability of the SSEP can be sufficiently small that the bandwidth of the SSEP’s constituent frequency components can be at the theoretical limit of spectral resolution up to at least a 500 second recording duration (0.002 Hz in this case). [|[8] ] Repetitive sensory stimulation elicits a steady-state magnetic brain response that can be analysed in the same way as the SSEP. [|[6] ]

The “simultaneous stimulation” technique
This technique allows several (e.g. four) SSEPs to be recorded simultaneously from any given location on the scalp. [|[9] ] Different sites of stimulation or different stimuli can be tagged with slightly different frequencies that are virtually identical to the brain, but easily separated by Fourier series analyzers. [|[9] ] For example, when two unpatterned lights are modulated at slightly different frequencies (F1 and F2) and superimposed, multiple nonlinear cross-modulation components of frequency (mF1 ± nF2) are created in the SSEP, where m and n are integers. [|[6] ] These components allow nonlinear processing in the brain to be investigated. By frequency-tagging two superimposed gratings, spatial frequency and orientation tuning properties of the brain mechanisms that process spatial form can be isolated and studied. [|[10] ] [|[11] ] Stimuli of different sensory modalities can also be tagged. For example, a visual stimulus was flickered at Fv Hz and a simultaneously-presented auditory tone was amplitude modulated at Fa Hz. The existence of a (2Fv + 2Fa) component in the evoked magnetic brain response demonstrated an audio-visual convergence area in the human brain, and the distribution of this response over the head allowed this brain area to be localized. [|[12] ] More recently, frequency tagging has been extended from studies of sensory processing to studies of selective attention [|[13] ] and of consciousness. [|[14]

The “sweep” technique
The sweep technique is a hybrid frequency domain/time domain technique. [|[15] ] A plot of, for example, response amplitude versus the check size of a stimulus checkerboard pattern plot can be obtained in 10 seconds, far faster than when time-domain averaging is used to record an evoked potential for each of several check sizes. [|[15] ] In the original demonstration of the technique the sine and cosine products were fed through lowpass filters (as when recording a SSEP ) while viewing a pattern of fine checks whose black and white squares exchanged place six times per second. Then the size of the squares was progressively increased so as to give a plot of evoked potential amplitude versus check size (hence “sweep”). Subsequent authors have implemented the sweep technique by using computer software to increment the spatial frequency of a grating in a series of small steps and to compute a time-domain average for each discrete spatial frequency. [|[16] ] A single sweep may be adequate or it may be necessary to average the graphs obtained in several sweeps with the averager triggered by the sweep cycle. [|[17] ] Averaging 16 sweeps can improve the signal-to-noise ratio of the graph by a factor of four. [|[17] ] The sweep technique has proved useful in measuring rapidly-adapting visual processes [|[18] ] and also for recording from babies, where recording duration is necessarily short. Norcia and Tyler have used the technique to document the development of visual acuity [|[16] ] [|[19] ] and contrast sensitivity [|[20] ] through the first years of life. They have emphasized that, in diagnosing abnormal visual development, the more precise the developmental norms, the more sharply can the abnormal be distinguished from the normal, and to that end have documented normal visual development in a large group of infants. [|[16] ] [|[19] ] [|[20] ] For many years the sweep technique has been used in paediatric ophthalmology clinics Worldwide.

Evoked potential feedback
This technique allows the SSEP to directly control the stimulus that elicits the SSEP without the conscious intervention of the experimental subject. [|[4] ] [|[17] ] For example, the running average of the SSEP can be arranged to increase the luminance of a checkerboard stimulus if the amplitude of the SSEP falls below some predetermined value, and to decrease luminance if it rises above this value. The amplitude of the SSEP then hovers about this predetermined value. Now the wavelength (colour) of the stimulus is progressively changed. The resulting plot of stimulus luminance versus wavelength is a plot of the spectral sensitivity of the visual system. [|[5] ] [|[17] ]

Visual evoked potential
Visual evoked potentials (VEPs) are described by O'Shea et al. (2009). [|[2] ] They are caused by sensory stimulation of a subject's and are observed using. Commonly used visual stimuli are flashing lights, or checkerboards on a video screen that flicker between to white on black (invert contrast). The resulting waveform includes the followed by the. Visual evoked potentials are very useful in detecting in patients that cannot communicate, such as babies or animals. If repeated stimulation of the visual field causes no changes in potentials, then the subject's brain is probably not receiving any signals from his/her eyes. Other applications include the diagnosis of, which causes the signal to be delayed. Such a delay is also a classic finding in. Visual evoked potentials are furthermore used in the investigation of basic functions of. VEPs are also sometimes used to determine if someone is alleging blindness. The term "visual evoked potential" is used interchangeably with "visually evoked potential". It usually refers to responses recorded from the. Sometimes, the term "visual evoked cortical potential" (VECP) is used to distinguish the VEP from or subcortical potentials. The VEP is used to record separate responses for visual field locations. Some specific VEPs are:
 * Sweep visual evoked potential
 * Binocular visual evoked potential
 * Chromatic visual evoked potential
 * Hemi-field visual evoked potential
 * Flash visual evoked potential
 * LED Goggle visual evoked potential
 * Motion visual evoked potential
 * [[file://wiki/Multifocal_visual_evoked_potential|Multifocal visual evoked potential]]
 * Multi-channel visual evoked potential
 * Multi-frequency visual evoked potential
 * Stereo-elicited visual evoked potential

Auditory evoked potential
Auditory evoked potential can be used to trace the signal generated by a sound through the ascending auditory pathway. The evoked potential is generated in the cochlea, goes through the, through the  ,  ,  , to the  in the midbrain, on to the  , and finally to the. [|[21] ] Auditory evoked potentials (AEPs) are a subclass of event-related potentials (ERP)s. ERPs are brain responses that are time-locked to some “event”, such as a sensory stimulus, a mental event (such as recognition of a target stimulus), or the omission of a stimulus. For AEPs, the “event” is a sound. AEPs (and ERPs) are very small electrical voltage potentials originating from the brain recorded from the scalp in response to an auditory stimulus, such as different tones, speech sounds, etc. [|[22] ]

Somatosensory evoked potential
(SSEPs) are used in to assess the function of a patient's  during. They are recorded by stimulating peripheral nerves, most commonly the,  or  , typically with an  stimulus. The response is then recorded from the patient's. Because of the low of the signal once it reaches the patient's scalp and the relatively high amount of electrical noise caused by background , scalp muscle  or electrical devices in the room, the signal must be averaged. The use of averaging improves the. Typically, in the operating room, over 100 and up to 1,000 averages must be used to adequately resolve the evoked potential. The two most looked at aspects of an SSEP are the amplitude and latency of the peaks. The most predominant peaks have been studied and named in labs. Each peak is given a letter and a number in its name. For example, N20 refers to a negative peak (N) at 20ms. This peak is recorded from the cortex when the median nerve is stimulated. It most likely corresponds to the signal reaching the. When used in intraoperative monitoring, the latency and amplitude of the peak relative to the patient's post-intubation baseline is a crucial piece of information. Dramatic increases in latency or decreases in amplitude are indicators of neurological. During surgery, the large amounts of gases used can affect the amplitude and latencies of SSEPs. Any of the agents or  will increase latencies and decrease amplitudes of responses, sometimes to the point where a response can no longer be detected. For this reason, an anesthetic utilizing less halogenated agent and more intravenous hypnotic and narcotic is typically used.

Intraoperative monitoring
Somatosensory evoked potentials provide monitoring for the dorsal columns of the spinal cord. Sensory evoked potentials may also be used during surgeries which place brain structures at risk. They are effectively used to determine cortical ischemia during carotid endarterectomy surgeries and for mapping the sensory areas of the brain during brain surgery. Electrical stimulation of the scalp can produce an electrical current within the brain that activates the motor pathways of the pyramidal tracts. This technique is known as transcranial electrical motor potential (TcMEP) monitoring. This technique effectively evaluates the motor pathways in the central nervous system during surgeries which place these structures at risk. These motor pathways, including the lateral corticospinal tract, are located in the lateral and ventral funiculi of the spinal cord. Since the ventral and dorsal spinal cord have separate blood supply with very limited collateral flow, an anterior cord syndrome (paralysis or paresis with some preserved sensory function) is a possible surgical sequela, so it is important to have monitoring specific to the motor tracts as well as dorsal column monitoring. Transcranial magnetic stimulation versus electrical stimulation is generally regarded as unsuitable for intraoperative monitoring because it is more sensitive to anesthesia. Electrical stimulation is too painful for clinical use in awake patients. The two modalities are thus complementary, electrical stimulation being the choice for intraoperative monitoring, and magnetic for clinical applications.

Motor evoked potentials
Motor evoked potentials (MEP) are recorded from muscles following direct stimulation of exposed motor cortex, or transcranial stimulation of motor cortex, either or electrical. Transcranial magnetic MEP (TCmMEP) potentially offer clinical diagnostic applications. Transcranial electrical MEP (TCeMEP) has been in widespread use for several years for intraoperative monitoring of pyramidal tract functional integrity. During the 1990s there were attempts to monitor "motor evoked potentials", including "neurogenic motor evoked potentials" recorded from peripheral nerves, following direct electrical stimulation of the spinal cord. It has become clear that these "motor" potentials were almost entirely elicited by antidromic stimulation of sensory tracts—even when the recording was from muscles (antidromic sensory tract stimulation triggers myogenic responses through synapses at the root entry level). TCMEP, whether electrical or magnetic, is the most practical way to ensure pure motor responses, since stimulation of sensory cortex cannot result in descending impulses beyond the first synapse (synapses cannot be backfired). -induced MEPs have been used in experiments regarding. [|[23] ] =  Event-related Potential   = An **event-related potential** (ERP) is any measured [|brain] response that is directly the result of a [|thought] or [|perception]. More formally, it is any stereotyped [|electrophysiological] response to an internal or external stimulus. ERPs are measured with [|electroencephalography] (EEG). The [|magnetoencephalography] (MEG) counterpart of ERP is the ERF, or event-related field.[|[1]]

Measurement
ERPs can be [|reliably] measured using [|electroencephalography] (EEG), a procedure that measures [|electrical] activity of the brain through the [|skull] and [|scalp]. As the EEG reflects thousands of simultaneously [|ongoing brain processes], the brain response to a single stimulus or event of interest is not usually visible in the EEG recording of a single trial; to see the brain response to the stimulus, the experimenter must conduct many trials (100 or more) and average the results together, causing random brain activity to be averaged out and the relevant ERP to remain.[|[2]] While [|evoked potentials] reflect the processing of the physical stimulus, event-related potentials are caused by the "higher" processes, that might involve [|memory], [|expectation], [|attention], or changes in the mental state, among others

Nomenclature
Though some ERP components are referred to with acronyms (e.g., [|early left anterior negativity] - ELAN), most components are referred to by a preceding letter indicating polarity followed by the typical latency in milliseconds. Thus, the [|N400] ERP component is described as a negative voltage deflection occurring approximately 400ms after stimulus onset, whereas the P600 component describes a positive voltage deflection 600ms after stimulus onset. The stated latencies for ERP components are often quite variable; for example, the N400 component may exhibit a latency between 300ms - 500ms.

Clinical ERP
[|Physicians] and [|neurologists] will sometimes use a flashing [|visual] checkerboard stimulus to test for any damage or trauma in the visual system. In a healthy person, this stimulus will elicit a strong response over the primary [|visual cortex] located in the [|occipital lobe] in the back of the brain.

Research ERP
[|Experimental psychologists] and [|neuroscientists] have discovered many different stimuli that elicit reliable ERPs from participants. The timing of these responses is thought to provide a measure of the timing of the brain's communication or time of information processing. For example, in the checkerboard paradigm described above, in healthy participants the first response of the visual cortex is around 50-70 msec. This would seem to indicate that this is the amount of time it takes for the transduced visual stimulus to reach the [|cortex] after [|light] first enters the [|eye]. Alternatively, the [|P300] response occurs at around 300ms in the [|oddball paradigm], for example, regardless of the stimulus presented: visual, [|tactile] , [|auditory] , [|olfactory] , gustatory, etc. Because of this general invariance in regard to stimulus type, this ERP is understood to reflect a higher cognitive response to unexpected and/or cognitively salient stimuli. Due to the consistency of the P300 response to novel stimuli, a [|brain-computer interface] can be constructed which relies on it. By arranging many signals in a grid, randomly flashing the rows of the grid as in the previous paradigm, and observing the P300 responses of a subject staring at the grid, the subject may communicate which stimulus he is looking at, and thus slowly "type" words.[//[|citation needed]//] Other ERPs used frequently in research, especially [|neurolinguistics research], include the [|ELAN] , the [|N400] , and the [|P600/SPS].

History
[] The different components within the category of VEPs was first described by [|Spehlmann in 1965] who compared human ERPs when viewing patterned and diffuse stimuli that were quickly flashed on the screen while a person was viewing the general area where the flash was to appear. However, it was not until [|Jeffreys and Axford (1972)] that the earliest individual components of those VEPs where delineated, including the C1 component. Jeffreys and Axford had human participants view stimulus patterns of squares for a very short time (25ms), aperiodically, in different parts of the participant’s visual fields while being recorded using electrodes placed towards the back of the head. Specifically, they recorded from three electrode sites placed on the longitudinal midline of the head: one 3 cm anterior to the [|inion] (the bony projection at the posterioinferior part of the skull), and two 3 cm to either side of the midline. After averaging between like trials (trials where the stimuli were presented in the same part of the visual field) and looking at the ERPs, Jeffreys and Axford postulated that there are two distinct components in the first 150msm, the C1 and the C2. But of the two components, the C1 tended to show polarity shifts across the scalp for trials where a stimulus was shown on one side of the visual field was compared to trials where stimuli were shown on the opposite side of the visual field. The C1’s polarity is also inverted whenever trials where the stimuli were presented in the top half of the visual field versus when stimuli were presented in the lower half of the visual field. Based on this evidence, Jeffreys and Axford proposed that the C1 reflected activity in the striate cortex as the activity tends to reflect a [|retinotopic map] very similar to the one in the striate cortex. Since its initial discovery, the common theory about the C1 continues to state that it is an early component when viewing stimuli and that it represents activity in the primary visual cortex. One of the initial descriptions of the P1 can be credited to [|Spehlmann (1965)] with his categorization of components within the VEPs. Whereas previous papers had looked at human ERPs to visual stimuli, and, undoubtedly, recorded P1 components as can be seen by visually inspecting the waveforms in the early articles (e.g. [|Cobb & Dawson, 1960] ), Spehlmann was one of the first to describe a “surface positive component at 80-120ms.” In his experiment, Spehlmann showed participants patterns of black and white squares, arranged in a checkerboard manner. These patterns were flashed to the participant by using a strobe light that had a frequency of 1-2 flashes per second. Averaging across trials, Spehlmann noted two different positivites, the first of which would later go on to be known as the P1. In the last quarter of the 20th century, the P1 started to be studied looking at what is called the P1 “effect” in the selective attention domain. In [|1977 Van Voorhis and Hillyard] found modulations in the P1 due to attention using the famous paradigm used by [|Eason, Harter, and White (1969)]. For their experiment, [|Van Voorhis and Hillyard (1977)] had participants view circular flashes of light to the left and to the right of a central fixation with the right and left flashes occurring independently with each side having flashes 2 to 8 seconds apart (a replication of [|Eason et al., 1969] ), the flashes occurring randomly with 1 to 4 seconds between each flash (left or right), or the flashes occurring randomly with 300 to 600ms between each flash. Participants were instructed to either attend to the left visual field, the right visual hemisphere, or both visual hemispheres for a double flash (two flashes within 70ms of each other). Participants were also instructed to either look for the target passively or press a button whenever the double flash occurs. To record the ERPs, they had two electrodes down the midline (Cz and Oz) all referenced to the right mastoid. Van Voorhis and Hillyard found that the P1 had a greater positive amplitude when the target was presented in the attended field than when it was presented outside the attended field across all conditions. This was one of the first papers to show that attention could modulate a visually evoked potential as early on as the P1. Ever since this experiment, the difference between the P1 amplitude when the participant is attending in the correct and incorrect visual field (or the P1 effect) has been extensively studied as part of selective attention.

Component Characteristics
The C1 component typically peaks anywhere from 50-100ms and its polarity and scalp distribution are dependent on where the stimulus is presented ( [|Jeffreys & Axford, 1972] ; [|Mangun, Hillyard, & Luck, 1993] ). The C1 has a negative polarity if the stimuli is presented in the upper half of the visual field (when using a mastoid reference) but it has a positive polarity if the stimuli is presented in the lower half of the visual field. The C1 scalp distribution is fairly broad with greatest polarity typically along the occipito-parietal sites ( [|Mangun et al., 1993] ), although the scalp can be lateralized with greater polarity along the occipito-parietal sites contralateral to the stimulus ( [|Jeffreys & Axford, 1972] ). The P1 component is a negative going component (when using a mastoid reference) that typically begins around 70-90ms with a peak around 80-130ms ( [|Mangun, 1995] ). Its amplitude maximum is over the lateral occipital scalp, approximately right over the ventrolateral prestriate cortex, contralateral to the visual field in which the stimuli is presented ( [|Mangun et al., 1993] ). =  P300    = [] The **P300** (P3) wave is an [|event related potential] (ERP) elicited by infrequent, task-relevant stimuli. It is considered to be an endogenous potential as its occurrence links not to the physical attributes of a stimulus but to a person's reaction to the stimulus. More specifically, the P300 is thought to reflect processes involved in stimulus evaluation or categorization. It is usually elicited using the [|oddball paradigm] in which low-probability target items are inter-mixed with high-probability non-target (or "standard") items. When recorded by [|electroencephalography] ( [|EEG] ), it surfaces as a positive deflection in voltage with a latency (delay between stimulus and response) of roughly 300 to 600 ms. The signal is typically measured most strongly by the electrodes covering the [|parietal lobe]. The presence, magnitude, topography and timing of this signal are often used as metrics of [|cognitive function] in decision making processes. While the neural substrates of this ERP still remain hazy, the reproducibility of this signal makes it a common choice for psychological tests in both the clinic and laboratory.

History
Early observations of the P3b were reported in the mid-1960s. In 1964, researchers Chapman and Bragdon [|[1]] found that ERP responses to [|visual] stimuli differed depending on whether the stimuli had meaning or not. They showed subjects two kinds of visual stimuli: numbers and flashes of light. Subjects viewed these stimuli one at a time in a sequence. For every two numbers, the subjects were required to make simple decisions, such as telling which of the two numbers was numerically smaller or larger, which came first or second in the sequence, or whether they were equal. When examining evoked potentials to these stimuli (i.e., ERPs), Chapman and Bragdon found that both the numbers and the flashes elicited the expected sensory responses (e.g., [|visual N1] components), and that the amplitude of these responses varied in an expected fashion with the intensity of the stimuli. They also found that the ERP responses to the numbers, but not to the light flashes, contained a large positivity that peaked around 300ms after the stimulus appeared. Chapman and Bragdon speculated that this differential response to the numbers, which came to be known as the P300 response, resulted from the fact that the numbers were meaningful to the participants, based on the task that they were asked to perform. In 1965, Sutton and colleagues published results from two experiments that further explored this late positivity. They presented subjects with either a cue that indicated whether the following stimulus would be a click or a flash, or a cue which required subjects to guess whether the following stimulus would be a click or a flash. They found that when subjects were required to guess what the following stimulus would be, the amplitude of the “late positive complex”[|[2]] was larger than when they knew what the stimulus would be. In a second experiment, they presented two cue types. For one cue there was a 2 in 3 chance that the following stimulus would be a click and a 1 in 3 chance that the following stimulus would be a flash. The second cue type had probabilities that were the reverse of the first. They found that the amplitude of the positive complex was larger in response to the less probable stimuli, or the one that only had a 1 in 3 chance of appearing. Another important finding from these studies is that this late positive complex was observed for both the clicks and flashes, indicating that the physical type of the stimulus (auditory or visual) did not matter. In later studies published in 1967, Sutton and colleagues had subjects guess whether they would hear one click or two clicks.[|[3]] They observed a positivity around 300ms after the second click occurred or would have occurred in the case of the single click. They also had subjects guess how long the interval between clicks might be, and the late positivity occurred 300ms after the second click. This shows two important findings: first that this late positivity occurred when the uncertainty about the type of click was resolved, and second that even an absence of a stimulus, when it was relevant to the task, would elicit the late positive complex. These early studies encouraged the use of ERP methods to study cognition and provided a foundation for the extensive work on the P3b in the decades that followed. Since the initial discovery of this ERP component, research has shown that the P300 is not a unitary phenomenon. Rather, we can distinguish between two subcomponents of the P300: the novelty P3, or [|P3a], and the classic P3, or [|P3b] .[|[4]

Applications
Since the mid 1980s, one of the most discussed uses of ERPs such as the P300 is related to [|lie detection]. In a proposed "guilty knowledge test [|[5]]" a subject is interrogated via the oddball paradigm much as they would be in a typical lie-detector situation. This practice has recently enjoyed increased legal permissibility while conventional [|polygraphy] has seen its use diminish, in part owing to the unconscious and uncontrollable aspects of the P300. The technique relies on reproducible elicitation of the P300 wave, central to the idea of a Memory and Encoding Related Multifaceted Electroencephalographic Response (MERMER) developed by Dr. [|Lawrence Farwell]. Applications in [|brain-computer interfacing] have also been proposed [|[6]][|[7]][|[8]]. The P300 has a number of desirable qualities that aid in implementation of such systems. First, the waveform is consistently detectable and is elicited in response to precise stimuli. The P300 waveform can also be evoked in nearly all subjects with little variation in measurement techniques, which may help simplify interface designs and permit greater usability. The speed at which an interface is able to operate depends on how detectable the signal is despite “noise.” One negative characteristic of the P300 is that the amplitude of the waveform requires averaging of multiple recordings to isolate the signal. This and other post-recording processing steps determine the overall speed of an interface [|[7]]. The algorithm proposed by Farwell and Donchin [|[9]] provides an example of a simple BCI that relies on the unconscious decision making processes of the P300 to drive a computer. A 6x6 grid of characters is presented to the subject, and various columns or rows are highlighted. When a column or row contains the character a subject desires to communicate, the P300 response is elicited (since this character is “special” it is the target stimulus described in the typical oddball paradigm). The combination of the row and column which evoked the response locates the desired character. A number of such trials must be averaged to clear noise from the EEG. The speed of the highlighting determines the number of characters processed per minute. Results from studies using this setup show that normal subjects could achieve a 95% success rate at 3.4-4.3 chars/min, and trends suggest that 40 chars/min is the maximum theoretical limit achievable. It remains to be shown whether such systems provide similar results in patients suffering from [|locked-in syndrome], the main target population for such brain driven devices. Scientific research often relies on measurement of the P300 to examine event related potentials, especially with regard to decision making. Because cognitive impairment is often correlated with modifications in the P300, the waveform can be used as a measure for the efficacy of various treatments on cognitive function. Some have suggested its use as a clinical marker for precisely these reasons. There is a broad range of uses for the P300 in clinical research [|[10]]. =  Brain Fingerprinting   = is a controversial [|forensic science] technique that uses [|brain-reading] techniques to determine whether specific information is stored in a subject’s brain. It does this by measuring electrical [|brainwave] responses to words, phrases, or pictures that are presented on a computer screen ( [|Farwell & Smith 2001] ). Brain fingerprinting was invented by [|Lawrence Farwell]. The theory is that the brain processes known, relevant information differently from the way it processes unknown or irrelevant information ( [|Farwell & Donchin 1991] ). The brain’s processing of known information, such as the details of a crime stored in the brain, is revealed by a specific pattern in the EEG ( [|electroencephalograph] ) ( [|Farwell & Smith 2001], [|Farwell 1994] ). Farwell’s brain fingerprinting originally used the well known [|P300] brain response to detect the brain’s recognition of the known information ( [|Farwell & Donchin 1986], [|1991] ; [|Farwell 1995a] ). Later Farwell discovered the MERMER ("Memory and Encoding Related Multifaceted Electroencephalographic Response"), which includes the P300 and additional features and is reported to provide a higher level of accuracy than the P300 alone ( [|Farwell & Smith 2001], [|Farwell 1994] , [|Farwell 1995b] ). In peer-reviewed publications Farwell and colleagues report over 99% accuracy in laboratory research ( [|Farwell & Donchin 1991], [|Farwell & Richardson 2006] ) and real-life field applications ( [|Farwell & Smith 2001] , [|Farwell //et al.// 2006] ). In independent research William Iacono and others who followed identical or similar scientific protocols to Farwell’s have reported a similar high level of accuracy (e.g., [|Allen & Iacono 1997] ). Brain fingerprinting has been applied in a number of high-profile criminal cases, including helping to catch serial killer JB Grinder ( [|Dalbey 1999] ) and to exonerate innocent convict Terry Harrington after he had been falsely convicted of murder ( [|Harrington v. State] ). Brain fingerprinting has been ruled admissible in court ( [|Harrington v. State], [|Farwell & Makeig 2005] ). In the controversial [|Sister Abhaya murder case], the [|Ernakulam] Chief Judicial Magistrate court had asked the [|Central Bureau of Investigation] to make use of all modern investigation techniques, including brain fingerprinting.[|[1]] Brain fingerprinting technique has been criticized on a number of fronts ( [|Fox 2006b], [|Abdollah 2003] ). Although independent scientists who have used the same or similar methods as Farwell’s brain fingerprinting have achieved similar, highly accurate results ( [|Allen & Iacono 1997] ; see also [|Harrington v. State] ), different methods have yielded different results. J. Peter Rosenfeld used P300-based tests incorporating fundamentally different methods, resulting in as low as chance accuracy ( [|Rosenfeld //et al.// 2004] ) as well as susceptibility to countermeasures, and criticized brain fingerprinting based on the premise that the shortcomings of his alternative technique should generalize to all other techniques in which the P300 is among the brain responses measured, including brain fingerprinting. Brain Fingerprinting was an international finalist in the [|Global Security Challenge] 2008 in London.

Technique
The technique uses the well known fact that an electrical signal known as [|P300] is emitted from an individual's brain beginning approximately 300 milliseconds after it is confronted with a stimulus of special significance, e.g. a rare vs. a common stimulus or a stimulus the subject is asked to count (see [|P300], [|Gaillard and Ritter 1983] , and [|Picton 1988] for a comprehensive discussion of this effect). The application of this in brain fingerprinting is to detect the P300 as a response to stimuli related to the crime or other investigated situation, e.g., a murder weapon, victim's face, or knowledge of the internal workings of a terrorist cell ( [|Farwell 1992a], [|Farwell & Donchin 1991] , [|Harrington v. State] ). Because it is based on EEG signals, the system does not require the subject to issue verbal responses to questions or stimuli. The person to be tested wears a special headband with electronic sensors that measure the [|EEG] from several locations on the scalp. The subject views stimuli consisting of words, phrases, or pictures presented on a computer screen. Stimuli are of three types: 1) “irrelevant” stimuli that are irrelevant to the investigated situation and to the test subject, 2) “target” stimuli that are relevant to the investigated situation and are known to the subject, and 3) “probe” stimuli that are relevant to the investigated situation and that the subject denies knowing. Probes contain information that is known only to the perpetrator and investigators, and not to the general public or to an innocent suspect who was not at the scene of the crime. Before the test, the scientist identifies the targets to the subject, and makes sure that he/she knows these relevant stimuli. The scientist also makes sure that the subject does not know the probes for any reason unrelated to the crime, and that the subject denies knowing the probes. The subject is told why the probes are significant (e.g., “You will see several items, one of which is the murder weapon”), but is not told which items are the probes and which are irrelevant ( [|Farwell 1994], [|Simon 2005] ). Since brain fingerprinting uses cognitive brain responses, brain fingerprinting does not depend on the emotions of the subject, nor is it affected by emotional responses ( [|Farwell & Smith 2001], [|Farwell 1992a] , [|1995a] ). Brain fingerprinting is fundamentally different from the [|polygraph] (lie-detector), which measures emotion-based physiological signals such as heart rate, sweating, and blood pressure ( [|Farwell 1994] ). Also, unlike polygraph testing, it does not attempt to determine whether or not the subject is lying or telling the truth. Rather, it measures the subject’s brain response to relevant words, phrases, or pictures to detect whether or not the relevant information is stored in the subject’s brain ( [|Farwell & Smith 2001], [|Simon 2005] , [|Harrington v. State] ). By comparing the responses to the different types of stimuli, the brain fingerprinting system mathematically computes a determination of “information present” (the subject knows the crime-relevant information contained in the probe stimuli) or “information absent” (the subject does not know the information) and a statistical confidence for the determination. This determination is mathematically computed, and does not involve the subjective judgment of the scientist.