Skip to main content

Advertisement

Log in

The Objective Assessment of Event-Related Potentials: An Influence of Chronic Pain on ERP Parameters

  • Original Article
  • Published:
Neuroscience Bulletin Aims and scope Submit manuscript

Abstract

The article presents an original method for the automatic assessment of the quality of event-related potentials (ERPs), based on the calculation of the coefficient ε, which describes the compliance of recorded ERPs with some statistically significant parameters. This method was used to analyze the neuropsychological EEG monitoring of patients suffering from migraines. The frequency of migraine attacks was correlated with the spatial distribution of the coefficients ε, calculated for EEG channels. More than 15 migraine attacks per month was accompanied by an increase in calculated values in the occipital region. Patients with infrequent migraines exhibited maximum quality in the frontal areas. The automatic analysis of spatial maps of the coefficient ε demonstrated a statistically significant difference between the two analyzed groups with different means of migraine attack numbers per month.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Duncan CC, Barry RJ, Connolly JF, Fischer C, Michie PT, Näätänen R. Event-related potentials in clinical research: Guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. Clin Neurophysiol 2009, 120: 1883–1908.

    Article  PubMed  Google Scholar 

  2. Hillyard SA, Hinrichs H, Tempelmann C, Morgan ST, Hansen JC, Scheich H, et al. Combining steady-state visual evoked potentials and fMRI to localize brain activity during selective attention. Hum Brain Mapp 1997, 5: 287–292.

    Article  CAS  PubMed  Google Scholar 

  3. Makeig S, Westerfield M, Jung TP, Enghoff S, Townsend J, Courchesne E, et al. Dynamic brain sources of visual evoked responses. Science 2002, 295: 690–694.

    Article  CAS  PubMed  Google Scholar 

  4. Chen Y, Ni Y, Zhou J, Zhou H, Zhong Q, Li X, et al. The amygdala responds rapidly to flashes linked to direct retinal innervation: A flash-evoked potential study across cortical and subcortical visual pathways. Neurosci Bull 2021, 37: 1107–1118.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Lepock JR, Mizrahi R, Korostil M, Bagby RM, Pang EW, Kiang M. Event-related potentials in the clinical high-risk (CHR) state for psychosis: A systematic review. Clin EEG Neurosci 2018, 49: 215–225.

    Article  PubMed  Google Scholar 

  6. Hajcak G, Klawohn J, Meyer A. The utility of event-related potentials in clinical psychology. Annu Rev Clin Psychol 2019, 15: 71–95.

    Article  PubMed  Google Scholar 

  7. Penengo C, Colli C, Bonivento C, Boscutti A, Balestrieri M, Delvecchio G, et al. Auditory event-related electroencephalographic potentials in borderline personality disorder. J Affect Disord 2022, 296: 454–464.

    Article  PubMed  Google Scholar 

  8. Javanbakht A, Liberzon I, Amirsadri A, Gjini K, Boutros NN. Event-related potential studies of post-traumatic stress disorder: A critical review and synthesis. Biol Mood Anxiety Disord 2011, 1: 5.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Tokuda K, Maruta M, Shimokihara S, Han G, Tomori K, Tabira T. Self-selection of interesting occupation facilitates cognitive response to the task: An event-related potential study. Front Hum Neurosci 2020, 14: 299.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Hyun KY, Lee GH. Analysis of change of event related potential in escape test using virtual reality technology. Biomed Sci Lett 2019, 25: 139–148.

    Article  Google Scholar 

  11. Suchotzki K, Crombez G, Smulders FT, Meijer E, Verschuere B. The cognitive mechanisms underlying deception: An event-related potential study. Int J Psychophysiol 2015, 95: 395–405.

    Article  PubMed  Google Scholar 

  12. Homan RW. The 10–20 electrode system and cerebral location. Am J EEG Technol 1988, 28: 269–279.

    Article  Google Scholar 

  13. Hajcak G, Meyer A, Kotov R. Psychometrics and the neuroscience of individual differences: Internal consistency limits between-subjects effects. J Abnorm Psychol 2017, 126: 823–834.

    Article  PubMed  Google Scholar 

  14. Polikar R, Topalis A, Green D, Kounios J, Clark CM. Comparative multiresolution wavelet analysis of ERP spectral bands using an ensemble of classifiers approach for early diagnosis of Alzheimer’s disease. Comput Biol Med 2007, 37: 542–558.

    Article  PubMed  Google Scholar 

  15. Kropotov JD, Mueller A, Ponomarev VA. ERP-based endophenotypes: Application in diagnosis and neurotherapy. In: Neurofeedback and Neuromodulation Techniques and Applications. Amsterdam: Elsevier, 2011: 47–77.

  16. Olvet DM, Hajcak G. Reliability of error-related brain activity. Brain Res 2009, 1284: 89–99.

    Article  CAS  PubMed  Google Scholar 

  17. Olvet DM, Hajcak G. The stability of error-related brain activity with increasing trials. Psychophysiology 2009, 46: 957–961.

    Article  PubMed  Google Scholar 

  18. Meyer A, Bress JN, Proudfit GH. Psychometric properties of the error-related negativity in children and adolescents. Psychophysiology 2014, 51: 602–610.

    Article  PubMed  Google Scholar 

  19. Weinberg A, Hajcak G. Longer term test-retest reliability of error-related brain activity. Psychophysiology 2011, 48: 1420–1425.

    Article  PubMed  Google Scholar 

  20. Kothari R, Bokariya P, Singh S, Singh R. A comprehensive review on methodologies employed for visual evoked potentials. Scientifica 2016, 2016: 9852194.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Plourde G. Auditory evoked potentials. Best Pract Res Clin Anaesthesiol 2006, 20: 129–139.

    Article  CAS  PubMed  Google Scholar 

  22. Arpaia P, Cataldo A, Criscuolo S, De Benedetto E, Masciullo A, Schiavoni R. Assessment and scientific progresses in the analysis of olfactory evoked potentials. Bioengineering (Basel) 2022, 9: 252.

    Article  PubMed  Google Scholar 

  23. García-Larrea L, Lukaszewicz AC, Mauguiére F. Revisiting the oddball paradigm. Non-target vs neutral stimuli and the evaluation of ERP attentional effects. Neuropsychologia 1992, 30: 723–741.

    Article  PubMed  Google Scholar 

  24. Keil A, Debener S, Gratton G, Junghöfer M, Kappenman ES, Luck SJ, et al. Committee report: Publication guidelines and recommendations for studies using electroencephalography and magnetoencephalography. Psychophysiology 2014, 51: 1–21.

    Article  PubMed  Google Scholar 

  25. Wang K, Xu M, Wang Y, Zhang S, Chen L, Ming D. Enhance decoding of pre-movement EEG patterns for brain-computer interfaces. J Neural Eng 2020, 17: 016033.

    Article  PubMed  Google Scholar 

  26. Han CH, Kim YW, Kim DY, Kim SH, Nenadic Z, Im CH. Electroencephalography-based endogenous brain-computer interface for online communication with a completely locked-in patient. J Neuroeng Rehabil 2019, 16: 18.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Zhang Y, Xie SQ, Wang H, Zhang Z. Data analytics in steady-state visual evoked potential-based brain–computer interface: A review. IEEE Sens J 2021, 21: 1124–1138.

    Article  CAS  Google Scholar 

  28. Li J, Yu ZL, Gu Z, Tan M, Wang Y, Li Y. Spatial–temporal discriminative restricted boltzmann machine for event-related potential detection and analysis. IEEE Trans Neural Syst Rehabil Eng 2019, 27: 139–151.

    Article  PubMed  Google Scholar 

  29. Ramele R, Villar AJ, Santos JM. EEG waveform analysis of P300 ERP with applications to brain computer interfaces. Brain Sci 2018, 8: 199.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Hu L, Mouraux A, Hu Y, Iannetti GD. A novel approach for enhancing the signal-to-noise ratio and detecting automatically event-related potentials (ERPs) in single trials. NeuroImage 2010, 50: 99–111.

    Article  CAS  PubMed  Google Scholar 

  31. Hruby T, Marsalek P. Event-related potentials—the P3 wave. Acta Neurobiol Exp (Wars) 2003, 63: 55–63.

    PubMed  Google Scholar 

  32. Braverman ER, Blum K. P300 (latency) event-related potential: An accurate predictor of memory impairment. Clin Electroencephalogr 2003, 34: 124–139.

    Article  PubMed  Google Scholar 

  33. Klochkova O, Gnezditsky V. Cognitive evoked potentials (P300): Is the decision to press a button always conscious? Kne Life Sci 2018, 4: 481–494.

    Google Scholar 

  34. Hafer CL, Weissflog M, Drolet CE, Segalowitz SJ. The relation between belief in a just world and early processing of deserved and undeserved outcomes: An ERP study. Soc Neurosci 2022, 17: 95–116.

    Article  PubMed  Google Scholar 

  35. Higuchi S, Liu Y, Yuasa T, Maeda A, Motohashi Y. Diurnal variation in the P300 component of human cognitive event-related potential. Chronobiol Int 2000, 17: 669–678.

    Article  CAS  PubMed  Google Scholar 

  36. Patel SH, Azzam PN. Characterization of N200 and P300: Selected studies of the event-related potential. Int J Med Sci 2005, 2: 147–154.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Picton TW. The P300 wave of the human event-related potential. J Clin Neurophysiol 1992, 9: 456–479.

    Article  CAS  PubMed  Google Scholar 

  38. Guo F, Du Y, Qu FH, Lin SD, Chen Z, Zhang SH. Dissecting the neural circuitry for pain modulation and chronic pain: Insights from optogenetics. Neurosci Bull 2022, 38: 440–452.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Wang HR, Hu SW, Zhang S, Song Y, Wang XY, Wang L, et al. KCNQ channels in the mesolimbic reward circuit regulate nociception in chronic pain in mice. Neurosci Bull 2021, 37: 597–610.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Ma KY, Cai XY, Wang XT, Wang ZX, Huang WM, Wu ZY, et al. Three-dimensional heterogeneity of cerebellar interposed nucleus-recipient zones in the thalamic nuclei. Neurosci Bull 2021, 37: 1529–1541.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Helfrich RF, Knight RT. Cognitive neurophysiology: Event-related potentials. Handb Clin Neurol 2019, 160: 543–558.

    Article  PubMed  Google Scholar 

  42. Sokhadze EM, Casanova MF, Casanova EL, Lamina E, Kelly DP, Khachidze I. Event-related potentials (ERP) in cognitive neuroscience research and applications. NeuroRegulation 2017, 4: 14–27.

    Article  Google Scholar 

  43. Iturrate I, Chavarriaga R, Montesano L, Minguez J, Millán J. Latency correction of event-related potentials between different experimental protocols. J Neural Eng 2014, 11: 036005.

    Article  CAS  PubMed  Google Scholar 

  44. Bruno RS, Oppitz SJ, Garcia MV, Biaggio EPV. Long latency auditory evoked potential: Differences in count form of rare stimulus. Rev CEFAC 2016, 18: 14–26.

    Article  Google Scholar 

  45. Mast J, Victor JD. Fluctuations of steady-state VEPs: Interaction of driven evoked potentials and the EEG. Electroencephalogr Clin Neurophysiol 1991, 78: 389–401.

    Article  CAS  PubMed  Google Scholar 

  46. Schack B, Klimesch W. Frequency characteristics of evoked and oscillatory electroencephalic activity in a human memory scanning task. Neurosci Lett 2002, 331: 107–110.

    Article  CAS  PubMed  Google Scholar 

  47. Oostenveld R, Fries P, Maris E, Schoffelen JM. FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput Intell Neurosci 2011, 2011: 156869.

    Article  PubMed  Google Scholar 

  48. Odom JV, Bach M, Brigell M, Holder GE, McCulloch DL, Mizota A, et al. ISCEV standard for clinical visual evoked potentials: (2016 update). Doc Ophthalmol 2016, 133: 1–9.

    Article  PubMed  Google Scholar 

  49. Huang Z, Li M, Yang S, Ma Y, Zhou C. A novel single-trial event-related potential estimation method based on compressed sensing. Neurosci Bull 2013, 29: 788–797.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Zhu B, Coppola G, Shoaran M. Migraine classification using somatosensory evoked potentials. Cephalalgia 2019, 39: 1143–1155.

    Article  PubMed  Google Scholar 

  51. Coppola G, Di Lorenzo C, Parisi V, Lisicki M, Serrao M, Pierelli F. Clinical neurophysiology of migraine with aura. J Headache Pain 2019, 20: 42.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Evers S, Bauer B, Suhr B, Husstedt IW, Grotemeyer KH. Cognitive processing in primary headache: A study on event-related potentials. Neurology 1997, 48: 108–113.

    Article  CAS  PubMed  Google Scholar 

  53. Huang L, Dong HJ, Wang X, Wang Y, Xiao Z. Duration and frequency of migraines affect cognitive function: Evidence from neuropsychological tests and event-related potentials. J Headache Pain 2017, 18: 54.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Titlic M, Mise NI, Pintaric I, Rogosic V, Vanjaka-Rogosic L, Mihalj M, et al. The event-related potential P300 in patients with migraine. Acta Inform Med 2015, 23: 339–342.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Raggi A, Ferri R. Information processing in migraine: A review of studies on P300. Appl Psychophysiol Biofeedback 2020, 45: 131–144.

    Article  PubMed  Google Scholar 

  56. Steppacher I, Schindler S, Kissler J. Higher, faster, worse? An event-related potentials study of affective picture processing in migraine. Cephalalgia 2016, 36: 249–257.

    Article  PubMed  Google Scholar 

  57. Guo Y, Tian Q, Xu S, Han M, Sun Y, Hong Y, et al. The impact of attack frequency and duration on neurocognitive processing in migraine sufferers: Evidence from event-related potentials using a modified oddball paradigm. BMC Neurol 2019, 19: 73.

    Article  PubMed  PubMed Central  Google Scholar 

  58. de Tommaso M, Ambrosini A, Brighina F, Coppola G, Perrotta A, Pierelli F, et al. Altered processing of sensory stimuli in patients with migraine. Nat Rev Neurol 2014, 10: 144–155.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was partially supported by the Russian Federation Government Grant No. 075-15-2022-1094 (clinical data processing). Another part of this work (developing the numeric method of data processing) was supported by the Ministry of Science and Higher Education of the Russian Federation in the framework of the state assignment (FSRR-2020-0003). The clinical experimental work was partially supported by the Russian Foundation for Basic Research (20-02-00752).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Maksim Zhuravlev.

Ethics declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 263 kb)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhuravlev, M., Novikov, M., Parsamyan, R. et al. The Objective Assessment of Event-Related Potentials: An Influence of Chronic Pain on ERP Parameters. Neurosci. Bull. 39, 1105–1116 (2023). https://doi.org/10.1007/s12264-023-01035-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12264-023-01035-8

Keywords

Navigation