Open access peer-reviewed chapter

Event-Related Potentials for the Study of Cognition

Written By

Manuel Vazquez-Marrufo

Submitted: September 29th, 2016 Reviewed: April 19th, 2017 Published: November 29th, 2017

DOI: 10.5772/intechopen.69308

Chapter metrics overview

1,532 Chapter Downloads

View Full Metrics

Abstract

Despite the vast literature on event-related potentials (ERPs), many clinical professionals are still unaware of the huge variety of possible applications they offer. The aim of this chapter is not to show the classical use of ERPs, focused on analyzing the first steps of information processing (sensory pathways). On the contrary, this chapter will be focused on the use of these ERPs in the assessment of cognitive function. In particular, this chapter is mainly focused on the use of ERPs to better understand the neural bases of cognitive impairment from the electrical activity of the brain. Describing all the possible ERP components and their cognitive meaning is a huge endeavor, and this chapter will only be focused on three of them: contingent negative variation (CNV), mismatch negativity (MMN), and P300. To improve the reader’s knowledge about these ERPs in cognition, a specific description will be given about the stimulation required to obtain the specific component, the topography, and latency shown. Moreover, a description of the neurophysiological bases of the component, its relationship with psychological processes and neural sources will be also included. Pathological alterations suffered by the component will also be briefly described.

Keywords

  • cognition
  • ERPs
  • latency
  • neural sources
  • pathology
  • topography

1. Introduction

Since the 1960s, a prolific literature has been produced on the field of event-related potentials (ERPs), related to the study of cognitive activity in the brain. In the beginning, these studies were more directed to the study of sensory and motor pathways. However, from studies such as in Refs. [13], ERPs were related to cognitive processes such as relevance of the stimulus, uncertainty, or mismatch with a previous stimulus.

Up to the present day, many studies have been published by numerous groups worldwide using this technology. In spite of the crisis that the ERP technique suffered due to the arrival of neuroimaging, ERPs have survived, and nowadays, still offer an interesting way to explore the cognitive activity with a direct measure of the electrical activity of neurons.

One of the main challenges that ERPs have to overcome is their application in the clinical field through studies that verify the reliability of the technique. Nevertheless, it is necessary to define the possible applications of these potentials to better understand the etiology of cognitive pathology and develop possible therapeutic targeting in this field.

In this chapter, three important ERPs will be detailed: contingent negative variation (CNV), mismatch negativity (MMN), and P300. For each one, several topics will be tackled: (1) a generic description of the component; (2) a brief definition of a procedure that allows evoking the component; (3) evidence of psychological variables that can modulate the component; (4) neurophysiological basis, typical topography, and latency of the component; (5) neural sources identified; (6) alterations that the component suffers in some diseases and its probable meaning.

These three components have been selected because of the order in which they appear in information processing. The first one, CNV, is related to the instants prior to the onset of a stimulus that is expected by the subject. MMN is related to the early phases of the cognitive processing for the stimulus that is evaluated. And finally, P300 represents late phases of the perceptual process and includes many psychological processes of high order.

Advertisement

2. Contingent negative variation (CNV)

2.1. Generic description

In 1964, Walter et al. [2] published a study in which an event-related potential was present prior to the appearance of the stimuli. The psychological meaning of this component was defined as the expectancy caused by a warning stimulus (also called sometimes “cue”) that allows the subject to prepare a response in order to react faster and more accurately to the incoming stimuli (known as “imperative stimuli”).

2.2. Procedure and characteristics of the component

Diverse paradigms have been used to elicit CNV in diverse sensory modalities: visual [4]; auditory [5]; or the interaction between visual and auditory stimulation [6], and even with proprioceptive information [7]. In the last few years, one of these paradigms has been called “Attentional Network Test (ANT),” which has been highly popular in the study of attentional mechanisms such as expectancy or orienting [810]. Depending on the stimulus onset asynchrony (SOAs) used, CNV is present between warning and imperative stimuli in this task [4, 11]. In a basic conception of the ANT paradigm, cues are shown for 150 ms, and then a variable SOA can be defined in a range between 1000 and 2000 ms when the CNV is present. Finally, an imperative stimulus is displayed, and the subject has to respond according to the instructions of the task (see Ref. [4] for a complete description of the parameters of the task; see also Figure 1 for a schematic of this procedure).

Figure 1.

Schematic representation of attention network test. Adapted from Galvao-Carmona [4].

During its history, CNV has been studied extensively in terms of psychological variables that can modulate it. One of the earliest studies was about how uncertainty affects CNV [12]. In the case that the subject is not certainly sure when the imperative stimuli will be displayed, the amplitude grows fast; however, in the case that the subject knows approximately when the imperative stimuli will be presented, the amplitude grows gradually. In the case that there is no need to respond to the stimuli following the warning cue, CNV is not usually elicited [12]. However, some studies have shown that a nonmotoric activity is evoked in the absence of direct overt motor activity [13].

Another interesting fact is that even when the subject is not warned by a cue, there is a slow negative trend in the human brain that represents our general expectancy during an experimental session [4] (see Figure 2).

Figure 2.

CNV component modulation in the no-cue condition showing a general expectancy during the execution of a warning-target paradigm. Zero value inx-axis represents the onset of the imperative stimuli. Adapted from Galvao-Carmona [4].

In regard to its relationship with development, Segalowitz and Davies [14] published a study in which it is possible to see the evolution of this component along infancy and adolescence. An increase in the amplitude is correlated with age and represents the maturation of the frontal lobe and, consequently, better behavioral capacities. In the elderly population, CNV has been used to detect different psychological processing of cue-relevant information between this population and younger subjects [15].

The latency of this component depends on the task employed. Sometimes, CNV reaches a peak (or valley) around 400 ms after the onset of the warning stimuli [12]. In other occasions, the component does not reach this maximum negative point and displays a continuous trend to negative values until the imperative stimuli show up [4]. Indeed, one of the critical variables for CNV is the SOA between warning and imperative stimuli [16]. In the case that a SOA of 3 or more seconds is used, two subcomponents can be observed. First, an O-wave, where O represents “Orienting” [17], is present at the beginning of the CNV trace, and then, an E-wave (expectancy and response preparation) [18] appears prior to the onset of the imperative stimulus. If the SOA is reduced, both subcomponents are confounded [19].

With respect to topography, CNV usually shows a maximum value in the vertex, which is symmetrically distributed over the scalp [4]. However, if the subcomponents are clearly distinguished, the O-wave is mainly frontal, and the E-wave is more postcentrally located [19].

The identification of the neural sources for this component remains under debate, perhaps due to the complete set of different processes present in the CNV latencies. Using magnetoencephalography, some authors [20] determined that the neural source for the magnetic counterpart of the CNV was located in the premotor cortex (Brodmann Area 6). In another study, Zappoli described that patients with lobotomy of frontal lobes exhibited decreased amplitude of the CNV [21]. In a study performed in our lab, in which different time intervals of the CNV trace were analyzed, numerous cortical areas were active, and a complex dynamic was present during the process [4]. These cortical areas belong to different lobes, including the frontal, parietal, occipital, and other regions, such as the cingulated lobe and insula, among others (see Figure 3).

Figure 3.

Cortical activation maps presented inZ-scores according to the baseline and showing significant activity (FDR-adjustedp< 0.01). Sources of the CNV effect were estimated in 2 CNV intervals of interest, −500 to −400 and −100 to 0 ms before the target stimulus. Adapted from Galvao-Carmona [4].

2.3. Psychological meaning and pathology

Once the component was described, many studies have been performed to find alterations in the component and the possible meaning in diverse pathologies. In Huntington disease (HD), de Tommaso et al. [22] examined a sample of mild, demented, and nonmedicated HD patients. The main result was that CNV amplitude was reduced in these patients compared to healthy control subjects, and this reduction was significantly correlated to the bradykinesia score. A strong activation in the posterior part of the cingulated cortex in HD is likely responsible for the amplitude reduction, and some authors suggested that it is probably caused by a basal ganglia dysfunction.

With regard to Alzheimer's disease, Zappoli et al. [23] found no significant CNV activity in these patients, who also showed slower reaction times and other EEG alterations. However, another group [24] observed that the CNV amplitude was not different between groups, also showing low test-retest reliability, which makes it difficult to be applied in the clinical field.

In other pathologies, CNV has been used to determine if any anatomical structure could be related to a specific cognitive impairment. For instance, Kuoppamäki et al. [25] observed that Parkinson patients with bilateral lesions in the globus pallidus present a deficit in motor tasks and alterations in the early phases of CNV.

From our laboratory, a study in a sample of multiple sclerosis patients, reduced amplitude of CNV was associated with impairment in the alerting and orienting attentional mechanisms. These results were also in accordance with neuropsychological scores from attentional tests [26] (see Figure 4).

Figure 4.

Contingent negative variation modulations at Cz electrode and topographic maps for healthy control subjects and patients in the attention network test. Adapted from Vazquez-Marrufo [26].

In the psychopathological field, one of the main disorders studied with CNV has been schizophrenia. Some authors have described a reduction of the amplitude related to the frontal lobe dysfunction, and it was manifested in the frontal-central derivations and at the early CNV phase [27]. At the same time, some studies have been focused on the relationship between CNV and some items of questionnaires used in the assessment of negative or positive symptoms [28]. Another interesting field is related to the study of the neural mechanisms underlying cephalea and migraine. In their study, Siniatchkin et al. [29] selected three groups: migraine, chronic daily headache, and healthy control subjects. CNV values were lower for the migraine group, especially at the beginning of the CNV. Chronic daily headache patients showed a reduced negativity of the late component of CNV. An interesting result was the absence of habituation to CNV in both types of patients and the potential application of CNV in diagnostic and therapeutic strategies for these pathologies.

Advertisement

3. Mismatch negativity (MMN)

3.1. Generic description

Described for the first time by Näätänen et al. [3], mismatch negativity appears when a change in a stream of stimulation is detected. This generic fact has been employed in different approaches for studying the bases of cognition in healthy and pathological subjects.

3.2. Procedure and characteristics of the component

A typical way to obtain this component consists of using an auditory oddball task, in which two types of stimuli are listened to binaurally through headphones: standard stimuli (1000 Hz tones and a probability of 0.80) and deviant stimuli (2000 Hz tones and a probability of 0.20). The interstimulus interval can be around 1 s, and the intensity of auditory stimuli can be set at 70 dB. The duration of the stimuli is 50-ms plateau and a 10-ms rise-fall time. Two blocks with 200 trials (including 80 deviant stimuli) are enough to obtain the MMN [30]. See Figure 5 for a schematic representation of the experimental procedure.

Figure 5.

Schematic representation of the experimental procedure to evoke a MMN response.

The component can be elicited during active tasks (counting deviant stimuli) [30] or during passive tasks [3]. Indeed, this last option can be extremely useful in some pathological conditions, such as coma [31]. MMN shows up as the result of subtraction between the standard and deviant associated waves. This component is evoked not only by a change in the frequency but also in pitch duration, intensity of stimuli…, and so forth. [32]. Other properties such as short SOAs [33] or the saliency of the deviant stimuli [34] produce greater MMN amplitudes.

Although MMN is usually based on auditory procedures, it can also be obtained with visual stimulation [35, 36] or even other sensory modalities [37]. The component is present even in newborns [38], and, during childhood, MMN presents differences in latency and topography with respect to adults, which suggests a development of the component throughout youth [39]. In healthy aging, elderly subjects showed a reduction in the amplitude [40], as well as a delay in the latency [41].

With regard to the specific parameters of the component, the latency is between 150 and 250 ms after the onset of the stimuli, and its distribution is fronto-central in the scalp (although the topography depends on the location of the reference) [42]. In auditory paradigms, neural generators are located in the primary and nonprimary auditory cortex, although they can also include frontal lobe areas, the thalamus, and the hippocampus, as evidenced by intracranial studies with animals [42].

3.3. Psychological meaning and pathology

The main application of MMN has probably been as an exponent of accuracy in the discrimination of small changes in stimuli in untrained [43] or trained subjects [44]. Since the presence of standard stimuli is necessary for obtaining MMN in deviant stimuli, this component has also been proposed as an index of the violation of the memory trace built during the experiment by the standard stimuli [45].

With regard to its application in several pathologies, attenuated amplitudes in patients with schizophrenia have been reported in Ref. [46]. This reduction has been interpreted as a poor social/occupational and executive functioning in these patients [47].

With respect to bipolar disorder, several studies have shown contradictory results for this component (for a review, see Ref. [45]. The main conclusion is that there is no clear evidence of auditory discrimination ability in these patients after all.

In multiple sclerosis, some studies have reported alterations in this component, showing deficits in the auditory discrimination system [48]. Moreover, some authors have shown that the amplitude reduction in MMN could be linked to disorganization of spectral modulations (beta and gamma bands) in patients with low EDSS. These results suggest a complex set of alterations even in the early phases of this disease [30] (see Figure 6).

Figure 6.

(A and B). Event-related brain potentials (ERPs) elicited at Cz in the deviant and standard conditions for MS patients and the control group, respectively. (C). Difference wave (MMN) (deviant—standard) for both groups. In all cases, arrows indicate the incoming of the tone. Adapted from Vazquez-Marrufo [30].

In stroke patients, an amplitude reduction in MMN has been found for changes in tone duration and frequency after a left-hemisphere stroke [49]. Another approach in the stroke field has been the use of this component as an assessment of function recovery in patients [50].

With regard to development, some studies have been focused on the use of MMN to determine deficits in dyslexic children. In particular, a reduction in the amplitude of this component found by Shafer et al. [51] could represent a poor auditory discrimination or language learning disability for phonetic cues in these patients. In autism spectrum disorder, some studies have shown an increase in the amplitude of this component with nonspeech stimuli and the opposite effect with speech stimuli [52, 53].

Advertisement

4. P300

4.1. Generic description

Chapman and Bragdon [1] described a positive wave around 300 ms after the onset of numerical and nonnumerical visual stimuli, and the subject was required to solve a problem with those numbers. These authors suggest that this positive wave was originated because the numbers were relevant to the task. A vast number of studies have found multiple possible meanings for this component, and a general consensus accepts that P3 represents the summation of different areas in the brain with diverse psychological processes intertwined. Indeed, P3 has two clear distinguishable subcomponents with different psychological meanings. In a simplified conception, P3b is evoked by relevant stimuli (target) and not usually evoked by standard stimuli in several paradigms (i.e., oddball task). On the other hand, P3a is evoked by the presence of novel stimuli along a sequence of target and standard stimuli.

4.2. Procedure and characteristics of the component

In this section, a brief description of a visual oddball paradigm is presented in comparison to the auditory type described in the MMN section (see Ref. [54] for complete specifications). In this “visual oddball task,” the subject is asked to discriminate uncommon visual stimuli (target) from a sequence of frequent stimuli (standard). In this study, the target stimulus (probability: 25%) was a rectangle with a checkerboard pattern comprising red and white squares. The standard stimulus (probability: 75%) was equivalent in size and pattern but with black and white squares. Both stimuli were presented in the center of the screen and the size of both stimuli was 7.98 and 9.42 (visual angle) on the xand yaxes, respectively. The duration of the stimuli was 500 ms, and the interstimulus interval was 1 s, which is the time when the subject could respond. The task for the participants was to press a button whenever a target stimulus appeared and ignore the standard stimuli. It is also possible to elicit P3 if the task is not a motor response, e.g., the subject just counts the targets silently [55]. Only one block with 200 trials (50 target stimuli) is enough to evoke the P3 component (see Figure 7).

Figure 7.

Schematic representation of a visual oddball to elicit P3.

Multiple studies have defined variables that can modulate this component. An interesting finding is about P3 being evoked by the absence of a stimulus if it is relevant to the subject [56]. Another important issue about this component is that it has been observed with different sensory modalities (auditory, visual, somatosensory, olfactory, or taste stimulation) [57]. P3 amplitude is mainly independent of sensory modality; however, it is possible to find some differences in shape and latency when auditory and visual stimulation are compared [58]. When using auditory stimulation, different features of the stimulation, such as the tone frequency or the use of a mask of white noise, can affect P3 latency [59].

An important consensus regarding the meaning of P3 is that it reflects the timing of cognitive processes. However, on the other hand, it is not correlated with reaction time [60]. Considering the multiple psychological processes comprised in the component, there does not seem to exist a strong correlation between P3 and behavioral response.

With regard to age, children showed an increase in latency and a decrease in amplitude in the 1st years of life compared to adults (up to 3 years) [61]. Considering the entire lifespan, Goodin et al. [62] showed the natural evolution of latency decrease and amplitude increase in young subjects and that of latency increase and amplitude decrease in elderly subjects. A considerable number of publications have been focused on studying this component in other species. This component or similar waves have been described in rats [63], cats [64], monkeys [65], or mice [66], among other studies.

P3 latency peaks around 350 ms and, in particular, P3a and P3b are around 240 ms and 350 ms, respectively [67]. However, it is possible to find a P3 peak in a range that goes from 300 to 500 ms depending on many variables (type of task, difficulty…, and so forth). [55]. With regard to topography, the maximum amplitude of the P3 wave is seen at the parieto-occipital area for P3b and as fronto-central derivations for P3a [57]. With aging, the topography can change with a more frontal distribution; however, the scalp distribution is defined similarly by task requirements when it is compared with young subjects [68]. Concerning neural sources for this component, multiple studies have described controversial results about them. In particular, diverse cortical lobes (frontal, parietal, and temporal) or the hippocampus are defined as relevant for the generation of the P3 component (see Ref. [69] for a review).

4.3. Psychological meaning and pathology

Nowadays, there are many suggestions about the psychological meaning of this component: (1) inhibition that ends the activation related to stimulus processing [70]; (2) expectation and relevancy of the stimulus [71]; (3) selective attention [72]; (4) updating of working memory [73]; (5) activation generated by the sequence of frequent stimuli [74]; (6) speed of cognitive processing and allocation of brain energy resources [75]; (7) difficulty of the task [76]; (8) emotion and motivation [77, 78]. As was pointed out previously, it can be asserted that P3 comprises multiple processes and its modulation can be determined by different variables in different ways, sometimes increasing/decreasing either the latency or amplitude and sometimes opposing some variables to others.

In the clinical field, P3 has been used extensively in many diseases. Our group has referred in some studies to alterations of the amplitude (decrease) and latency (increase) of P3 in multiple sclerosis [79, 80] (see Figure 8). Comi et al. [81] has shown that a longer latency in P3 may be related to demyelination. An increased latency is also observed in diverse types of dementia (Alzheimer, multiinfarction dementia, and lacunar dementia); on the other hand, in pseudodementia, the altered parameter is amplitude, which is flattened [82].

Figure 8.

P3 component modulations at Pz electrode and topographic maps for ANT test. Note the reduction in the amplitude for multiple sclerosis patients in both conditions (congruent and incongruent). Adapted from Vazquez-Marrufo [80].

In Parkinson’s disease, an amplitude decrease has also been observed by O'Donnel et al. [83]. However, other authors suggest that this reduction is more related to the dementia associated with the disease, rather than Parkinson itself [84].

P3 has also been useful as an indicator of the presence of a traumatic lesion (e.g., prefrontal cortex). It has been related to P3a and behavioral responses indicating a reduced attentional shift toward novel stimuli [85]. It is also possible to assess the evolution in the subacute phase of a stroke from changes in the P3 component [86].

In the psychopathology field, schizophrenia has received a remarkable attention with P3 studies. One general finding is decreased amplitude, which seems to be correlated to the presence of negative symptoms [87, 88]. Another potential application of P3 consists of assessing the neurodegenerative process in this pathology. Martin-Loeches showed a negative correlation between P3 amplitude and prefrontal CSF volume in these patients [89].

Advertisement

5. Conclusion

As a general conclusion, the ERP literature presented in this chapter shows an amazing field to explore, which relates the electric activity of the brain to the cognitive processes. It seems that a vast number of applications could be developed in the next few years, in our understanding of how information is processed in the brain, identifying anatomical structures where these processes occur, and their hierarchical organization.

However, one of the main challenges for this field is to study reliability tests that guarantee the health professionals that the assessment is reproducible and valid to be applied in the clinical field.

References

  1. 1. Chapman RM & Bragdon HR. Evoked responses to numerical and non-numerical visual stimuli while problem solving. Nature. 1964;203:1155-1157. DOI: 10.1038/2031155a0
  2. 2. Walter WG, Cooper R, Aldridge VJ, McCallum WC, Winter AL. Contingent negative variation: An electric sign of sensorimotor association and expectancy in the human brain. Nature. 1964;203(4943):380-384. DOI: 10.1038/203380a0
  3. 3. Näätänen R, Gaillard AW, Mäntysalo S. Early selective-attention effect on evoked potential reinterpreted. Acta Psychologica. 1978;42(4):313-329
  4. 4. Galvao-Carmona A, González-Rosa JJ, Hidalgo-Muñoz AR, Páramo D, Benítez ML, Izquierdo G, Vazquez-Marrufo M. Disentangling the attention network test: Behavioral, event related potentials, and neural source analyses. Frontiers in Human Neuroscience. 2014 Oct 13;8:813. DOI: 10.3389/fnhum.2014.00813
  5. 5. Bostanov V, Keune PM, Kotchoubey B, Hautzinger M. Event-related brain potentials reflect increased concentration ability after mindfulness-based cognitive therapy for depression: A randomized clinical trial. Psychiatry Research. 2012 Oct 30;199(3):174-180. DOI: 10.1016/j.psychres.2012.05.031. Epub Jul 6, 2012
  6. 6. Arjona A, Escudero M, Gómez CM. Cue validity probability influences neural processing of targets. Biological Psychology. 2016 Sep;119:171-183. DOI: 10.1016/j.biopsycho.2016.07.001
  7. 7. Lytnev V, Fujiwara K, Kiyota N, Irei M, Toyama H, Yaguchi C. Postural control and contingent negative variation during transient floor translation while standing with the ankle fixed. Journal of Physiological Anthropology. 2016 Jul 25;36(1):7. DOI: 10.1186/s40101-016-0104-8
  8. 8. Fan J, McCandliss BD, Sommer T, Raz A and Posner MI. Testing the efficiency and independence of attentional networks. Journal Cognitive Neuroscience. 2002;14:340-347. DOI: 10.1162/089892902317361886
  9. 9. Callejas A, Lupiáñez J, Tudela P. The three attentional networks: On their independence and interactions. Brain and Cognition. 2004 Apr;54(3):225-227
  10. 10. Fuentes LJ, Campoy G. The time course of alerting effect over orienting in the attention network test. Experimental Brain Research. 2008 Mar;185(4):667-672
  11. 11. Kratz O, Studer P, Baack J, Malcherek S, Erbe K, Moll GH, Heinrich H. Differential effects of methylphenidate and atomoxetine on attentional processes in children with ADHD: An event-related potential study using the attention network test. Progress in Neuropsychopharmacology and Biological Psychiatry. 2012 Apr 27;37(1):81-89. DOI: 10.1016/j.pnpbp.2011.12.008. Epub Dec 29, 2011
  12. 12. Tecce JJ. Contingent negative variation (CNV) and psychological processes in man. Psychological Bulletin. 1972;77(2):73-108. DOI: 10.1037/h0032177
  13. 13. Frost BG, Neill RA, Fenelon B. The determinants of the non-motoric CNV in a complex, variable foreperiod, information processing paradigm. Biological Psychology. 1988;27(1):1-21. DOI: 10.1016/0301-0511(88)90002
  14. 14. Segalowitz SJ, Davies PL. Charting the maturation of the frontal lobe: An electrophysiological strategy. Brain and Cognition. 2004 Jun;55(1):116-133
  15. 15. Schmitt H, Ferdinand NK, Kray J. Age-differential effects on updating cue information: Evidence from event-related potentials. Cognitive, Affective, & Behavioral Neuroscience. 2014 Sep;14(3):1115-1131. DOI: 10.3758/s13415-014-0268-9
  16. 16. Weerts TC, Lang PJ. The effects of eye fixation and stimulus and response location on the contingent negative variation (CNV). Biological Psychology. 1973;1(1):1-19. DOI: 10.1016/0301-0511(73)90010-0
  17. 17. Giard MH, Perrin F, Pernier J & Bouchet P. Brain generators implicated in the processing of auditory stimulus deviance: A topographic event-related potential study. Psychophysiology. 1990;27:627-640. DOI: 10.1111/j.1469-8986.1990.tb03184.x
  18. 18. Knott VJ, Lapierre YD, De Lugt D, Griffiths L, Bakish D, Browne M & Horn E. Preparatory brain potentials in major depressive disorder. Progress in Neuro-Psychopharmacology & Biological Psychiatry. 1991;15:257-262. DOI: 10.1016/0278-5846(91)90089-J
  19. 19. Gaillard AW. Effects of warning-signal modality on the contingent negative variation (CNV). Biological Psychology. 1976 Jun;4(2):139-154
  20. 20. Hultin L, Rossini P, Romani GL, Högstedt P, Tecchio F, Pizzella V. Neuromagnetic localization of the late component of the contingent negative variation. Electroencephalography and Clinical Neurophysiology. 1996;98:425-448
  21. 21. Zappoli, R. Permanent or transitory effects on neurocognitive components of the CNV complex induced by brain dysfunctions, lesions, and ablations in humans. International Journal of Psychophysiology. 2003;48(2):189-220. DOI: 10.1016/S0167-8760(03)00054-0
  22. 22. de Tommaso M, Difruscolo O, Sciruicchio V, Specchio N, Livrea P. Abnormalities of the contingent negative variation in Huntington's disease: Correlations with clinical features. Journal of Neurological Sciences. 2007 Mar 15;254(1-2):84-89. Epub Feb 14, 2007
  23. 23. Zappoli R, Versari A, Arnetoli G, Paganini M, Muscas GC, Arneodo MG, Gangemi PF, Bartelli M. Topographic CNV activity mapping, presenile mild primary cognitive decline and Alzheimer-type dementia. Neurophysiologie Clinique. 1991 Dec;21(5-6):473-483
  24. 24. van Deursen JA, Vuurman EF, Smits LL, Verhey FR, Riedel WJ. Response speed, contingent negative variation and P300 in Alzheimer’s disease and MCI. Brain and Cognition. 2009 Apr;69(3):592-599. DOI: 10.1016/j.bandc.2008.12.007. Epub Jan 29, 2009
  25. 25. Kuoppamäki M, Rothwell JC, Brown RG, Quinn N, Bhatia KP, Jahanshahi M. Parkinsonism following bilateral lesions of the globus pallidus: Performance on a variety of motor tasks shows similarities with Parkinson's disease. Journal of Neurology, Neurosurgery and Psychiatry. 2005 Apr;76(4):482-490
  26. 26. Vázquez-Marrufo M, Galvao-Carmona A, González-Rosa JJ, Hidalgo-Muñoz AR, Borges M, Ruiz-Peña JL, Izquierdo G. Neural correlates of alerting and orienting impairment in multiple sclerosis patients. PLoS One. 2014 May 12;9(5):e97226. DOI: 10.1371/journal.pone.0097226. eCollection 2014
  27. 27. Kirenskaya AV, Kamenskov MY, Myamlin VV, Novototsky-Vlasov VY, Tkachenko AA. The antisaccade task performance deficit and specific CNV abnormalities in patients with stereotyped paraphilia and schizophrenia. Journal of Forensic Science. 2013 Sep;58(5):1219-1226. DOI: 10.1111/1556-4029.12241. Epub Jul 30, 2013
  28. 28. Oke S, Saatchi R, Allen E, Hudson NR, Jervis BW. The contingent negative variation in positive and negative types of schizophrenia. American Journal of Psychiatry. 1994 Mar;151(3):432-433
  29. 29. Siniatchkin M, Gerber WD, Kropp P, Vein A. Contingent negative variation in patients with chronic daily headache. Cephalalgia. 1998 Oct;18(8):565-569; discussion 531
  30. 30. Vazquez-Marrufo M, González-Rosa JJ, Vaquero E, Duque P, Escera C, Borges M, Izquierdo G, Gómez CM. Abnormal ERPs and high frequency bands power in multiple sclerosis. International Journal of Neuroscience. 2008 Jan;118(1):27-38
  31. 31. Kane NM, Butler SR, Simpson T. Coma outcome prediction using event-related potentials: P(3) and mismatch negativity. Audiology & Neuro-Otology. 2000 May–Aug;5(3–4):186-191
  32. 32. Näätänen R, Paavilainen, P, Titinen H, Jiang D, Alho D. Attention and mismatch negativity. Psychophysiology. 1993;30(5):436-450
  33. 33. Schröger E, Winkler I. Presentation rate and magnitude of stimulus deviance effects on human pre-attentive change detection. Neuroscience Letters. 1995 Jul 7;193(3):185-188
  34. 34. Mullens D, Woodley J, Whitson L, Provost A, Heathcote A, Winkler I & Todd J. Altering the primacy bias – How does a prior task affects mismatch negativity? Psychophysiology. 2014;51:437-445
  35. 35. Pazo-Alvarez P, Cadaveira F & Amenedo E. MMN in the visual modality: A review. Biological Psychology. 2003;63:199-236
  36. 36. Kremláček J, Kreegipuu K, Tales A, Astikainen P, Põldver N, Näätänen R, Stefanics G. Visual mismatch negativity (vMMN): A review and meta-analysis of studies in psychiatric and neurological disorders. Cortex. 2016 Jul;80:76-112. DOI: 10.1016/j.cortex.2016.03.017
  37. 37. Strömmer JM, Tarkka IM, Astikainen P. Somatosensory mismatch response in young and elderly adults. Frontiers in Aging Neuroscience. 2014 Oct 27;6:293. DOI: 10.3389/fnagi.2014.00293
  38. 38. Cheour-Luhtanen M, Alho K, Kujala T, Sainio K, Reinikainen K, Renlund M, Aaltonen O, Eerola O, Näätänen R. Mismatch negativity indicates vowel discrimination in newborns. Hearing Research. 1995 Jan;82(1):53-58
  39. 39. Cleary KM, Donkers FC, Evans AM, Belger A. Investigating developmental changes in sensory processing: Visual mismatch response in healthy children. Frontiers in Human Neuroscience. 2013 Dec 30;7:922. DOI: 10.3389/fnhum.2013.00922
  40. 40. Cooper RJ, Todd J, McGill K and Michie PT. Auditory sensory memory and the aging brain: A mismatch negativity study. Neurobiology of Aging. 2006;27:752-762. DOI: 10.1016/j.neurobiolaging.2005.03.012
  41. 41. Gaeta H, Friedman D, Ritter W, Cheng J. An event-related potential evaluation of involuntary attentional shifts in young and older adults. Psychology and Aging. 2001 Mar;16(1):55-68
  42. 42. Alho K. Cerebral generators of mismatch negativity (MMN) and its magnetic counterpart (MMNm) elicited by sound changes. Ear and Hearing. 1995 Feb;16(1):38-51
  43. 43. Lang HA, Nyrke T, Ek M, Aaltonen O, Raimo I, Naatanen R. Pitch discrimination performance and auditory event-related potentials. In: Brunia CHM, Gaillard AWK, Kok A, Mulder G, Verbaten MN, editors. Psychophysiological Brain Research. Vol. 1. Tilburg: Tilburg University Press; 1990; pp. 294-298
  44. 44. Kraus N, McGee T, Carrell TD, Sharma A. Neurophysiologic bases of speech discrimination. Ear and Hearing. 1995 Feb;16(1):19-37
  45. 45. Näätänen R, Sussman ES, Salisbury D, Shafer VL. Mismatch negativity (MMN) as an index of cognitive dysfunction. Brain Topography. 2014 Jul;27(4):451-466. DOI: 10.1007/s10548-014-0374-6
  46. 46. Salisbury DF, Shenton ME, Griggs CB, Bonner-Jackson A, McCarley RW. Mismatch negativity in chronic schizophrenia and first-episode schizophrenia. Archives of General Psychiatry. 2002 Aug;59(8):686-694
  47. 47. Oades RD, Wild-Wall N, Juran SA, Sachsse J, Oknina LB, Röpcke B. Auditory change detection in schizophrenia: Sources of activity, related neuropsychological function and symptoms in patients with a first episode in adolescence, and patients 14 years after an adolescent illness-onset. BMC Psychiatry. 2006 Feb 8;6:7
  48. 48. Jung J, Morlet D, Mercier B, Confavreux C, Fischer C. Mismatch negativity (MMN) in multiple sclerosis: An event-related potentials study in 46 patients. Clinical Neurophysiology. 2006 Jan;117(1):85-93. Epub Dec 1, 2005
  49. 49. Ilvonen TM, Kujala T, Kiesiläinen A, Salonen O, Kozou H, Pekkonen E, Roine RO, Kaste M, Näätänen R. Auditory discrimination after left-hemisphere stroke: A mismatch negativity follow-up study. Stroke. 2003 Jul;34(7):1746-1751. Epub Jun 19, 2003
  50. 50. Särkämö T, Tervaniemi M, Laitinen S, Forsblom A, Soinila S, Mikkonen M, Autti T, Silvennoinen HM, Erkkilä J, Laine M, Peretz I, Hietanen M. Music listening enhances cognitive recovery and mood after middle cerebral artery stroke. Brain. 2008 Mar;131(Pt 3):866-876. DOI: 10.1093/brain/awn013
  51. 51. Shafer VL, Morr ML, Datta H, Kurtzberg D, Schwartz RG. Neurophysiological indexes of speech processing deficits in children with specific language impairment. Journal Cognitive Neuroscience. 2005 Jul;17(7):1168-1180
  52. 52. Gomot M, Giard MH, Adrien JL, Barthelemy C, Bruneau N. Hypersensitivity to acoustic change in children with autism: Electrophysiological evidence of left frontal cortex dysfunctioning. Psychophysiology. 2002 Sep;39(5):577-584
  53. 53. Kuhl PK, Coffey-Corina S, Padden D, Dawson G. Links between social and linguistic processing of speech in preschool children with autism: Behavioral and electrophysiological measures. Developmental Science. 2005 Jan;8(1):F1-F12
  54. 54. Vazquez-Marrufo M, González-Rosa JJ, Galvao-Carmona A, Hidalgo-Muñoz A, Borges M, Peña JL, Izquierdo G. Retest reliability of individual p3 topography assessed by high density electroencephalography. PLoS One. 2013 May 1;8(5):e62523. DOI: 10.1371/journal.pone.0062523
  55. 55. Hruby T, Marsalek P. Event-related potentials--the P3 wave. Acta Neurobiologiae Experimentalis (Wars). 2003;63(1):55-63
  56. 56. Sutton S, Tueting P, Zubin J. Information delivery and the sensory evoked potential. Science. 1967;155:1436-1439
  57. 57. Polich J. P300 in clinical applications. In: Niedermayer E and Lopes de la Silva F, editors. Electroencephalography: Basic Principles, Clinical Applications and Related Fields. Baltimore-Munich: Urban and Schwartzenberger. 1999. pp. 1073-1091
  58. 58. Katayama J, Polich J. Auditory and visual P300 topography from a 3 stimulus paradigm. Clinical Neurophysiology. 1999;110:463-468
  59. 59. Polich J, Howard L, Starr A. Stimulus frequency and masking as determinants of P300 latency in event-related potentials from auditory stimuli. Biological Psychology. 1985 Dec;21(4):309-318
  60. 60. Kutas M, McCarthy G, Donchin E. Augmenting mental chronometry: The P300 as a measure of stimulus evaluation time. Science. 1977;197:792-795
  61. 61. Ohlrich ES, Barnet AB, Weiss IP, Shanks BL. Auditory evoked potential development in early childhood: A longitudinal study. Electroencephalography and Clinical Neurophysiology. 1978 Apr;44(4):411-423
  62. 62. Goodin DS, Squires KC, Henderson BH, Starr A. Age-related variations in evoked potentials to auditory stimuli in normal human subjects. Electroencephalography and Clinical Neurophysiology. 1978 Apr;44(4):447-458
  63. 63. O'Brien JH. P300 wave elicited by a stimulus-change paradigm in acutely prepared rats. Physiology & Behavior. 1982;28:711-713
  64. 64. Harrison J, Buchwald J. Aging changes in the cat ‘P300’ mimic the human. Electroencephalography and Clinical Neurophysiology. 1985;62:227-234
  65. 65. Paller, KA, Zola-Morgan, S, Squire, LR, Hillyard, SA. P3-like brain waves in normal monkeys and monkeys with medial temporal lesions. Journal of Behavioral Neuroscience. 1988;102:714-725
  66. 66. Ehlers CL, Somes C. Long latency event-related potentials in mice: Effects of stimulus characteristics and strain. Brain Research. 2002 Dec 6;957(1):117-128
  67. 67. Squires NK, Squires KC, Hillyard SA. Two varieties of long-latency positive waves evoked by unpredictable auditory stimuli in man. Electroencephalography and Clinical Neurophysiology. 1975 Apr;38(4):387-401
  68. 68. Friedman D, Kazmerski V, Fabiani M. An overview of age-related changes in the scalp distribution of P3b. Electroencephalography and Clinical Neurophysiology. 1997 Nov;104(6):498-513
  69. 69. Huang WJ, Chen WW, Zhang X. The neurophysiology of P300 – an integrated review. European Review for Medical and Pharmacological Sciences. 2015 Apr;19(8):1480-1488
  70. 70. Desmedt JE. P300 in serial tasks: An essential post-decision closure mechanism. Progress in Brain Research. 1980;54:682-686
  71. 71. Wickens C, Kramer A, Vanasse L, Donchin E. Performance of concurrent task: A psychophysiological analysis of the reciprocity of information-processing resources. Science. 1983;221:1080-1082
  72. 72. Johnson VS, Miller DR, Burleson MH. Multiple P3s to emotional stimuli and their theoretical significance. Psychophysiology. 1986;23:684-694
  73. 73. Donchin E, Coles MGH. Is the P300 manifestation of context updating? Behavioral and Brain Sciences. 1988;11:357-374
  74. 74. Verleger R. Event-related potentials and cognition: A critique of the context updating hypothesis and an alternative interpretation of P3. Behavioral and Brain Sciences. 1988;11:343-427
  75. 75. Kok A. Event-related potentials (ERP) reflections of mental resources: A review and synthesis. Biological Psychology. 1997;45:19-56
  76. 76. Polich J. P300 clinical utility and control of variability. Journal of Clinical Neurophysiology. 1998;15:14-33
  77. 77. Carretié L, Iglesias J, García T, Ballesteros M. N300, P300 and the emotional processing of visual stimuli. Electroencephalography and Clinical Neurophysiology. 1997 Aug;103(2):298-303
  78. 78. Carillo-de-la Pena MT, Cadaveira F. The effect of motivational instructions on P300 amplitude. Neurophysiologie Clinique. 2000;30:232-239
  79. 79. Vázquez-Marrufo M, González-Rosa J, Vaquero-Casares E, Duque P, Borges M, Izquierdo G. Cognitive evoked potentials in remitting-relapsing and benign forms of multiple sclerosis. Revista de Neurologia. 2009 May 1–15;48(9):453-458
  80. 80. Vázquez-Marrufo M, Galvao-Carmona A, González-Rosa JJ, Hidalgo-Muñoz AR, Borges M, Ruiz-Peña JL, Izquierdo G. Neural correlates of alerting and orienting impairment in multiple sclerosis patients. PLoS One. 2014 May 12;9(5):e97226. DOI: 10.1371/journal.pone.0097226
  81. 81. Comi G, Leocani L, Locatelli T, Medaglini S, Martinelli V. Electrophysiological investigations in multiple sclerosis dementia. Electroencephalography and Clinical Neurophysiology. Supplement. 1999;50:480-485
  82. 82. Polich J, Ladish C, Bloom F. P3 assessment of early Alzheimer’s disease. Electroencephalography and Clinical Neurophysiology. 1990;77:1
  83. 83. O'Donnel BF, Squires NK, Martz MJ, Chen JR, Phay JR. Evoked potential changes and neuropsychological performance in Parkinson’s disease. Biological Psychology. 1987;24:23-37
  84. 84. Tanaka H, Koenig T, Pascual-Marqui RD, Hirata K, Kochi K, Lehmann D. Event-related potential and EEG measures in Parkinson’s disease without and with dementia. Dementia and Geriatric Cognitive Disorders. 2000;11:39-45
  85. 85. Daffner K, Mesulam M, Holcomb P, Calvo V, Acar D, Chabrerie A, Kikinis R, Jolesz F, Rentz D, Seinto L. Disruption of attention to novel events after frontal lobe injury in humans. Journal of Neurology, Neurosurgery and Psychiatry. 2000;68:18-24
  86. 86. Alonso-Prieto E, Lvarez-Gonzalez Ma, Reyes-Verazain A. Use of event related potentials for the diagnosis and follow up of subclinical disorders of sustained attention in ischemic cerebrovascular disease. Revista de Neurologia. 2002;34:1017-1020
  87. 87. Pritchard WS. Cognitive event-related potentials correlates of schizophrenia. Psychological Bulletin. 1986;100:43-66
  88. 88. O'Donnel BF, McCarley R, Potts G, Salisbury D, Nestor P, Hirayasu Y. Identification of neural circuit underlying P300 abnormalities in schizophrenia. Psychophysiology. 1999;36:388-398
  89. 89. Martín-Loeches M, Molina V, Munoz F, Hinojosa JA, Reig S, Desco M, Benito C, Sanz J, Gabiri A, Sarramea F, Santos A, Palomo T. P300 amplitude as a possible correlate of frontal degeneration in schizophrenia. Schizophrenia Research. 2001;49:121-128

Written By

Manuel Vazquez-Marrufo

Submitted: September 29th, 2016 Reviewed: April 19th, 2017 Published: November 29th, 2017