Skip to main content
SpringerLink
Log in

Electroencephalography in epilepsy: look for what could be beyond the visual inspection

  • Review Article
  • Published:
Neurological Sciences Aims and scope Submit manuscript

Abstract

Since its starting point in 1929, human scalp electroencephalography (EEG) has been routinely interpreted by visual inspection of waveforms using the assumption that the activity at a given electrode is a representation of the activity of the cerebral cortex under it, but such a method has some limitations. In this review, we will discuss three advanced methods to obtain valuable information from scalp EEG in epilepsy using innovative technologies. Authors who had previous publications in the field provided a narrative review. Spike voltage topography of interictal spikes is a potential way to improve non-invasive EEG localization in focal epilepsies. Electrical source imaging is also a complementary technique in localization of the epileptogenic zone in patients who are candidates for epilepsy surgery. Quantitative EEG simplifies the large amount of information in continuous EEG by providing a static graphical display. Scalp electroencephalography has the potential to offer more spatial and temporal information than the traditional way of visual inspection alone in patients with epilepsy. Fortunately, with the help of modern digital EEG equipment and computer-assisted analysis, this information is more accessible.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Rose S, Ebersole JS (2009) Advances in spike localization with EEG dipole modeling. Clin EEG Neurosci 40:281–287

    Article  Google Scholar 

  2. Asadi-Pooya AA, Asadollahi M, Shimamoto S et al (2016) Spike voltage topography in temporal lobe epilepsy. J Neurol Sci 366:209–212

    Article  Google Scholar 

  3. Do Marcolino C, Baulac M, Samson-Dollfus D (1994) Topographic analysis of interictal spikes in the presurgical evaluation of severe partial epilepsy. Neurophysiol Clin 24:20–34 Article in French; abstract was available

    Article  Google Scholar 

  4. Ebersole JS, Wade PB (1990) Spike voltage topography and equivalent dipole localization in complex partial epilepsy. Brain Topogr 3:21–34

    Article  CAS  Google Scholar 

  5. Ebersole JS, Wade PB (1991) Spike voltage topography identifies two types of frontotemporal epileptic foci. Neurology 41:1425–1433

    Article  CAS  Google Scholar 

  6. Boon P, D'Havé M (1995) Interictal and ictal dipole modelling in patients with refractory partial epilepsy. Acta Neurol Scand 92:7–18

    Article  CAS  Google Scholar 

  7. Boon P, D’Have M, Adam C et al (1996) Dipole modeling in epilepsy surgery candidates. Epilepsia 38:208–218

    Article  Google Scholar 

  8. Cuffin BN (1996) EEG localization accuracy improvements using realistically shaped head models. IEEE Trans Biomed Eng 43:299–303

    Article  CAS  Google Scholar 

  9. Roth BJ, Ko D, von Albertini-Carletti IR et al (1997) Dipole localization in patients with epilepsy using the realistically shaped head model. Electroencephalogr Clin Neurophysiol 102:159–166

    Article  CAS  Google Scholar 

  10. Kaiboriboon K, Lüders HO, Hamaneh M et al (2012) EEG source imaging in epilepsy--practicalities and pitfalls. Nat Rev Neurol 8(9):498–507

    Article  Google Scholar 

  11. Boon P, D’Havé M, Vanrumste B et al (2002) Ictal source localization in presurgical patients with refractory epilepsy. J Clin Neurophysiol 19(5):461–468

    Article  Google Scholar 

  12. Nemtsas P, Birot G, Pittau F et al (2017) Source localization of ictal epileptic activity based on high-density scalp EEG data. Epilepsia 58(6):1027–1036

    Article  Google Scholar 

  13. Wennberg R, Cheyne D (2014) EEG source imaging of anterior temporal lobe spikes: validity and reliability. Clin Neurophysiol 125(5):886–902

    Article  Google Scholar 

  14. Abdallah C, Maillard LG, Rikir E et al (2017) Localizing value of electrical source imaging: frontal lobe, malformations of cortical development and negative MRI related epilepsies are the best candidates. Neuroimage Clin 16:319–329

    Article  Google Scholar 

  15. Brodbeck V, Spinelli L, Lascano AM, et al. Electroencephalographic source imaging: a prospective study of 52 operated epileptic patients. Brain 2011; 134 (Pt 10): 2887–2897.

    Article  Google Scholar 

  16. Mouthaan BE, Rados M, Barsi P et al (2016) Current use of imaging and electromagnetic source localization procedures in epilepsy surgery centers across Europe. Epilepsia 57(5):770–776

    Article  Google Scholar 

  17. Swisher CB, White CR, Mace BE et al (2015) Diagnostic accuracy of electrographic seizure detection by neurophysiologists and non-neurophysiologists in the adult ICU using a panel of quantitative EEG trends. J Clin Neurophysiol 32(4):324–330

    Article  Google Scholar 

  18. Moura LMVR, Shafi MM, Ng M et al (2014) Spectrogram screening of adult EEGs is sensitive and efficient. Neurology. 83(1):56–64

    Article  Google Scholar 

  19. Abend NS, Dlugos D, Herman S (2008) Neonatal seizure detection using multichannel display of envelope trend. Epilepsia 49(2):349–352

    Article  Google Scholar 

  20. Akman CI, Micic V, Thompson A et al (2011) Seizure detection using digital trend analysis: factors affecting utility. Epilepsy Res 93(1):66–72

    Article  Google Scholar 

  21. Dericioglu N, Yetim E, Bas DF et al (2015) Non-expert use of quantitative EEG displays for seizure identification in the adult neuro-intensive care unit. Epilepsy Res 109:48–56

    Article  Google Scholar 

  22. Haider HA, Esteller R, Hahn CD et al (2016) Sensitivity of quantitative EEG for seizure identification in the intensive care unit. Neurology. 87(9):935–944

    Article  Google Scholar 

  23. Pensirikul AD, Beslow LA, Kessler SK et al (2013) Density spectral array for seizure identification in critically ill children. J Clin Neurophysiol 30(4):371–375

    Article  Google Scholar 

  24. Shah DK, Mackay MT, Lavery S et al (2008) Accuracy of bedside electroencephalographic monitoring in comparison with simultaneous continuous conventional electroencephalography for seizure detection in term infants. Pediatrics. 121(6):1146–1154

    Article  Google Scholar 

  25. Stewart CP, Otsubo H, Ochi A et al (2010) Seizure identification in the ICU using quantitative EEG displays. Neurology. 75(17):1501–1508

    Article  CAS  Google Scholar 

  26. Du Pont-Thibodeau G, Sanchez SM, Jawad AF et al (2017) Seizure detection by critical care providers using amplitude-integrated electroencephalography and color density spectral array in pediatric cardiac arrest patients. Pediatr Crit Care Med 18(4):363–369

    Article  Google Scholar 

  27. Sarkis RA, Lee JW (2013) Quantitative EEG in hospital encephalopathy: review and microstate analysis. J Clin Neurophysiol 30(5):526–530

    Article  Google Scholar 

  28. Cozac VV, Gschwandtner U, Hatz F et al (2016) Quantitative EEG and cognitive decline in Parkinson’s disease. Parkinsons Dis 2016:9060649

    PubMed  PubMed Central  Google Scholar 

  29. Puskás S, Kozák N, Sulina D et al (2017) Quantitative EEG in obstructive sleep apnea syndrome: a review of the literature. Rev Neurosci 28(3):265–270

    Article  Google Scholar 

  30. Schirrmeister RT, Springenberg JT, Fiederer LDJ et al (2017) Deep learning with convolutional neural networks for EEG decoding and visualization. Hum Brain Mapp 38(11):5391–5420

    Article  Google Scholar 

  31. Iakovidou ND (2017) Graph theory at the service of electroencephalograms. Brain Connect 7(3):137–151

    Article  Google Scholar 

  32. Jaiswal AK, Banka H (2018) Epileptic seizure detection in EEG signal using machine learning techniques. Australas Phys Eng Sci Med 41(1):81–94

    Article  Google Scholar 

  33. Sharmila A Epilepsy detection from EEG signals: a review. J Med Eng Technol 2018(22):1–13

  34. Jun YH, Eom TH, Kim YH et al (2019) Source localization of epileptiform discharges in childhood absence epilepsy using a distributed source model: a standardized, low-resolution, brain electromagnetic tomography (sLORETA) study. Neurol Sci. https://doi.org/10.1007/s10072-019-03751-4 Epub ahead of print

    Article  Google Scholar 

  35. Gao J, Wu M, Wu Y, Liu P (2019) Emotional consciousness preserved in patients with disorders of consciousness? Neurol Sci. https://doi.org/10.1007/s10072-019-03848-w Epub ahead of print

    Article  Google Scholar 

  36. Comi G, Leocani L (1999) Neurophysiological imaging techniques in dementia. Ital J Neurol Sci 20(5 Suppl):S265–S269

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This review was presented at the 1st International Qatar Epilepsy School in November 2018 by the authors. We thank Hamad Medical Corporation for supporting this event.

Author information

Authors and Affiliations

  1. Hamad Medical Corporation, Doha, Qatar

    Boulenouar Mesraoua, Dirk Deleu, Hassan Al Hail & Gayane Melikyan

  2. Weill Cornell Medical College, Doha, Qatar

    Boulenouar Mesraoua, Dirk Deleu, Hassan Al Hail & Gayane Melikyan

  3. Department of Neurology, Reference Center for Refractory Epilepsy, Ghent University Hospital, Ghent, Belgium

    Paul Boon

  4. Department of Neurology, Emory University, Atlanta, GA, USA

    Hiba A. Haider

  5. Shiraz Medical School, Shiraz University of Medical Sciences, Shiraz, Iran

    Ali A. Asadi-Pooya

  6. Jefferson Comprehensive Epilepsy Center, Department of Neurology, Thomas Jefferson University, Philadelphia, USA

    Ali A. Asadi-Pooya

Authors
  1. Boulenouar Mesraoua
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dirk Deleu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hassan Al Hail
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gayane Melikyan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Paul Boon
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hiba A. Haider
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ali A. Asadi-Pooya
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors were involved in the conception, design, review process, and preparation of the manuscript. All have approved this final version and all authors agree to be accountable for all aspects of the work.

Corresponding author

Correspondence to Ali A. Asadi-Pooya.

Ethics declarations

Conflict of interest

Ali A. Asadi-Pooya, M.D., consultant: LLC and UCB Pharma; Honorarium: Cobel Daru; Royalty: Oxford University Press (Book publication). Paul Boon, M.D., has received consultancy and speaker fees from UCB Pharma, LivaNova, Medtronic, and Eisai.

Hiba A. Haider M.D., Royalties: Uptodate Inc., Demos Publishing. Others, none.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mesraoua, B., Deleu, D., Al Hail, H. et al. Electroencephalography in epilepsy: look for what could be beyond the visual inspection. Neurol Sci 40, 2287–2291 (2019). https://doi.org/10.1007/s10072-019-04026-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10072-019-04026-8

Keywords

Search

Navigation