Skip to main content
SpringerLink
Log in

Electroencephalography

  • Chapter
  • First Online:
Neuroimaging Techniques in Clinical Practice

  • 917 Accesses

Abstract

This chapter summarizes the basic theoretical principles about electroencephalography (EEG) and informs about EEG recording and data analysis. Followed by two chapters that discuss clinical applications of EEG, showing some representative group- and single-case EEG results for various clinical disorders.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Berger H. Electroencephalogram in humans. Arch Psychiatr Nervenkr. 1929;87:527–70. https://doi.org/10.1007/Bf01797193.

    Article  Google Scholar 

  2. Jasper HH, Carmichael L. Electrical potentials from the intact human brain. Science. 1935;81(2089):51–3. https://doi.org/10.1126/science.81.2089.51.

    Article  CAS  PubMed  Google Scholar 

  3. Coles MD, Rugg. Electrophysiology of mind. Oxford: Oxford University Press; 1996.

    Google Scholar 

  4. Belnap WD, Toman JE, Goodman LS. Tridione-diphenylhydantoin combination therapy in grand mal with slow-wave EEG dysrhythmia. Fed Proc. 1947;6(1):308.

    CAS  PubMed  Google Scholar 

  5. Glaser MA, Irons M. Is the epileptic a safe motor vehicle driver? With some remarks relative to the clinical application of the EEG. J Nerv Ment Dis. 1946;103:21–36.

    CAS  PubMed  Google Scholar 

  6. Goodwin JE. The significance of alpha variants in the EEG, and their relationship to an epileptiform syndrome. Am J Psychiatry. 1947;104(6):369–79. https://doi.org/10.1176/ajp.104.6.369.

    Article  CAS  PubMed  Google Scholar 

  7. Bonnet H, Chabot E. EEG and clinical manifestations observed in a case of anxiety psychosis during the period of treatment with various drugs. Electroencephalogr Clin Neurophysiol. 1955;7(1):151.

    Google Scholar 

  8. Guntekin B, Emek DD, Kurt P, Yener GG, Basar E. Beta oscillatory responses in healthy subjects and subjects with mild cognitive impairment upon application of stimuli with cognitive load. Biol Psychiatry. 2013;73(9):82s.

    Google Scholar 

  9. Liddell DW. Investigations of EEG findings in presenile dementia. J Neurol Neurosurg Psychiatry. 1958;21(3):173–6. https://doi.org/10.1136/jnnp.21.3.173.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Yener GG, Kurt P, Cavusoglu B, Emek DD, Aktas G, Ada E, Guntekin B, Basar E. The auditory event-related oscillations are diminished, and correlate with hippocampal volumetry in mild cognitive impairment. Ann Neurol. 2012;72:S126.

    Google Scholar 

  11. Steriade M, Nunez A, Amzica F. A novel slow (< 1 Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components. J Neurosci. 1993;13(8):3252–65.

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Steriade M, Timofeev I, Grenier F. Natural waking and sleep states: a view from inside neocortical neurons. J Neurophysiol. 2001;85(5):1969–85. https://doi.org/10.1152/jn.2001.85.5.1969.

    Article  CAS  PubMed  Google Scholar 

  13. Gais S, Plihal W, Wagner U, Born J. Early sleep triggers memory for early visual discrimination skills. Nat Neurosci. 2000;3(12):1335–9. https://doi.org/10.1038/81881.

    Article  CAS  PubMed  Google Scholar 

  14. Huber R, Ghilardi MF, Massimini M, Tononi G. Local sleep and learning. Nature. 2004;430(6995):78–81. https://doi.org/10.1038/nature02663.

    Article  CAS  PubMed  Google Scholar 

  15. Maquet P. The role of sleep in learning and memory. Science. 2001;294(5544):1048–52. https://doi.org/10.1126/science.1062856.

    Article  CAS  PubMed  Google Scholar 

  16. Stickgold R, Whidbee D, Schirmer B, Patel V, Hobson JA. Visual discrimination task improvement: a multi-step process occurring during sleep. J Cogn Neurosci. 2000;12(2):246–54.

    CAS  PubMed  Google Scholar 

  17. Koenig T, Lehmann D, Saito N, Kuginuki T, Kinoshita T, Koukkou M. Decreased functional connectivity of EEG theta-frequency activity in first-episode, neuroleptic-naive patients with schizophrenia: preliminary results. Schizophr Res. 2001;50(1–2):55–60.

    CAS  PubMed  Google Scholar 

  18. Vertes RP. Hippocampal theta rhythm: a tag for short-term memory. Hippocampus. 2005;15(7):923–35. https://doi.org/10.1002/hipo.20118.

    Article  CAS  PubMed  Google Scholar 

  19. von Stein A, Sarnthein J. Different frequencies for different scales of cortical integration: from local gamma to long range alpha/theta synchronization. Int J Psychophysiol. 2000;38(3):301–13.

    Google Scholar 

  20. Buzsaki G. Theta oscillations in the hippocampus. Neuron. 2002;33(3):325–40. https://doi.org/10.1016/S0896-6273(02)00586-X.

    Article  CAS  PubMed  Google Scholar 

  21. Buzsaki G. Theta rhythm of navigation: Link between path integration and landmark navigation, episodic and semantic memory. Hippocampus. 2005;15(7):827–40. https://doi.org/10.1002/hipo.20113.

    Article  PubMed  Google Scholar 

  22. Vanderwolf CH. Hippocampal electrical activity and voluntary movement in rat. Electroencephalogr Clin Neurophysiol. 1969;26(4):407–18. https://doi.org/10.1016/0013-4694(69)90092-3.

    Article  CAS  PubMed  Google Scholar 

  23. Bland BH, Oddie SD. Theta band oscillation and synchrony in the hippocampal formation and associated structures: the case for its role in sensorimotor integration. Behav Brain Res. 2001;127(1–2):119–36. https://doi.org/10.1016/S0166-4328(01)00358-8.

    Article  CAS  PubMed  Google Scholar 

  24. Palva S, Palva JM. New vistas for alpha-frequency band oscillations. Trends Neurosci. 2007;30(4):150–8. https://doi.org/10.1016/j.tins.2007.02.001.

    Article  CAS  PubMed  Google Scholar 

  25. Kolev V, Basar-Eroglu C, Aksu F, Basar E. EEG rhythmicities evoked by visual stimuli in three-year-old children. Int J Neurosci. 1994;75(3–4):257–70.

    CAS  PubMed  Google Scholar 

  26. Daniel RS. Alpha and theta EEG in vigilance. Percept Mot Skills. 1967;25(3):697–703. https://doi.org/10.2466/pms.1967.25.3.697.

    Article  CAS  PubMed  Google Scholar 

  27. Mulholland T. The concept of attention and the EEG alpha-rhythm. Electroencephalogr Clin Neurophysiol. 1968;24(2):188.

    CAS  PubMed  Google Scholar 

  28. Gale A, Spratt G, Christie B, Smallbone A. Stimulus complexity, EEG abundance gradients, and detection efficiency in a visual recognition task. Br J Psychol. 1975;66(3):289–98.

    CAS  PubMed  Google Scholar 

  29. Jasper HH, Penfield W. Electrocorticograms in man: effect of voluntary movement upon the electrical activity of the precentral gyrus. Arch Psychiatr Zeitschr Neurol. 1949;83:163–74.

    Google Scholar 

  30. Baumeister J, Barthel T, Geiss KR, Weiss M. Influence of phosphatidylserine on cognitive performance and cortical activity after induced stress. Nutr Neurosci. 2008;11(3):103–10. https://doi.org/10.1179/147683008X301478.

    Article  CAS  PubMed  Google Scholar 

  31. Baker SN. Oscillatory interactions between sensorimotor cortex and the periphery. Curr Opin Neurobiol. 2007;17(6):649–55. https://doi.org/10.1016/j.conb.2008.01.007.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Lalo E, Gilbertson T, Doyle L, Di Lazzaro V, Cioni B, Brown P. Phasic increases in cortical beta activity are associated with alterations in sensory processing in the human. Exp Brain Res. 2007;177(1):137–45. https://doi.org/10.1007/s00221-006-0655-8.

    Article  PubMed  Google Scholar 

  33. Zhang Y, Chen Y, Bressler SL, Ding M. Response preparation and inhibition: the role of the cortical sensorimotor beta rhythm. Neuroscience. 2008;156(1):238–46. https://doi.org/10.1016/j.neuroscience.2008.06.061.

    Article  CAS  PubMed  Google Scholar 

  34. Pogosyan A, Gaynor LD, Eusebio A, Brown P. Boosting cortical activity at beta-band frequencies slows movement in humans. Curr Biol. 2009;19(19):1637–41. https://doi.org/10.1016/j.cub.2009.07.074.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Singer W, Gray CM. Visual feature integration and the temporal correlation hypothesis. Annu Rev Neurosci. 1995;18:555–86. https://doi.org/10.1146/annurev.ne.18.030195.003011.

    Article  CAS  PubMed  Google Scholar 

  36. Tallon-Baudry C, Bertrand O, Delpuech C, Permier J. Oscillatory gamma-band (30-70 Hz) activity induced by a visual search task in humans. J Neurosci. 1997;17(2):722–34.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Howard MW, Rizzuto DS, Caplan JB, Madsen JR, Lisman J, Aschenbrenner-Scheibe R, Schulze-Bonhage A, Kahana MJ. Gamma oscillations correlate with working memory load in humans. Cereb Cortex. 2003;13(12):1369–74.

    PubMed  Google Scholar 

  38. Tallon-Baudry C, Bertrand O, Peronnet F, Pernier J. Induced gamma-band activity during the delay of a visual short-term memory task in humans. J Neurosci. 1998;18(11):4244–54.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Tallon-Baudry C, Bertrand O. Oscillatory gamma activity in humans and its role in object representation. Trends Cogn Sci. 1999;3(4):151–62.

    CAS  PubMed  Google Scholar 

  40. Basar-Eroglu C, Brand A, Hildebrandt H, Karolina Kedzior K, Mathes B, Schmiedt C. Working memory related gamma oscillations in schizophrenia patients. Int J Psychophysiol. 2007;64(1):39–45. https://doi.org/10.1016/j.ijpsycho.2006.07.007.

    Article  PubMed  Google Scholar 

  41. Kissler J, Muller MM, Fehr T, Rockstroh B, Elbert T. MEG gamma band activity in schizophrenia patients and healthy subjects in a mental arithmetic task and at rest. Clin Neurophysiol. 2000;111(11):2079–87.

    CAS  PubMed  Google Scholar 

  42. Jasper HH. The ten-twenty electrode system of the international federation. Electroencephalogr Clin Neurophysiol Suppl. 1958;10:371–75.

    Google Scholar 

  43. Galambos R, Sheatz GC. An electroencephalograph study of classical conditioning. Am J Phys. 1962;203:173–84. https://doi.org/10.1152/ajplegacy.1962.203.1.173.

    Article  CAS  Google Scholar 

  44. Polich J. Neuropsychology of P300. In: Kappenman ES, Luck SJ (eds.), The oxford handbook of event-related potential components. Oxford University Press, 2012; pp. 159–88.

    Google Scholar 

  45. Haig AR, Gordon E, Wright JJ, Meares RA, Bahramali H. Synchronous cortical gamma-band activity in task-relevant cognition. Neuroreport. 2000;11(4):669–75.

    CAS  PubMed  Google Scholar 

  46. Hanslmayr S, Aslan A, Staudigl T, Klimesch W, Herrmann CS, Bauml KH. Prestimulus oscillations predict visual perception performance between and within subjects. NeuroImage. 2007;37(4):1465–73. https://doi.org/10.1016/j.neuroimage.2007.07.011.

    Article  PubMed  Google Scholar 

  47. Michels L, Muthuraman M, Anwar AR, Kollias S, Leh SE, Riese F, Unschuld PG, Siniatchkin M, Gietl AF, Hock C. Changes of functional and directed resting-state connectivity are associated with neuronal oscillations, ApoE genotype and amyloid deposition in mild cognitive impairment. Front Aging Neurosci. 2017;9:304. https://doi.org/10.3389/fnagi.2017.00304.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Michels L, Muthuraman M, Luchinger R, Martin E, Anwar AR, Raethjen J, Brandeis D, Siniatchkin M. Developmental changes of functional and directed resting-state connectivities associated with neuronal oscillations in EEG. NeuroImage. 2013;81:231–42. https://doi.org/10.1016/j.neuroimage.2013.04.030.

    Article  PubMed  Google Scholar 

  49. Schelter B, Sommerlade L, Platt B, Plano A, Thiel M, Timmer J. Multivariate analysis of dynamical processes with applications to the neurosciences. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:5931–4. https://doi.org/10.1109/IEMBS.2011.6091467.

    Article  Google Scholar 

  50. Koenig T, Lehmann D, Merlo MC, Kochi K, Hell D, Koukkou M. A deviant EEG brain microstate in acute, neuroleptic-naive schizophrenics at rest. Eur Arch Psychiatry Clin Neurosci. 1999;249(4):205–11.

    CAS  PubMed  Google Scholar 

  51. Van de Ville D, Britz J, Michel CM. EEG microstate sequences in healthy humans at rest reveal scale-free dynamics. Proc Natl Acad Sci U S A. 2010;107(42):18179–84. https://doi.org/10.1073/pnas.1007841107.

    Article  PubMed  Google Scholar 

  52. Kikuchi M, Koenig T, Munesue T, Hanaoka A, Strik W, Dierks T, Koshino Y, Minabe Y. EEG microstate analysis in drug-naive patients with panic disorder. PLoS One. 2011;6(7):e22912. https://doi.org/10.1371/journal.pone.0022912.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Lehmann D, Faber PL, Galderisi S, Herrmann WM, Kinoshita T, Koukkou M, Mucci A, Pascual-Marqui RD, Saito N, Wackermann J, Winterer G, Koenig T. EEG microstate duration and syntax in acute, medication-naive, first-episode schizophrenia: a multi-center study. Psychiatry Res. 2005;138(2):141–56. https://doi.org/10.1016/j.pscychresns.2004.05.007.

    Article  PubMed  Google Scholar 

  54. Soni S, Muthukrishnan SP, Sood M, Kaur S, Sharma R. Hyperactivation of left inferior parietal lobule and left temporal gyri shortens resting EEG microstate in schizophrenia. Schizophr Res. 2018;201:204–7. https://doi.org/10.1016/j.schres.2018.06.020.

    Article  PubMed  Google Scholar 

  55. Strelets V, Faber PL, Golikova J, Novototsky-Vlasov V, Koenig T, Gianotti LR, Gruzelier JH, Lehmann D. Chronic schizophrenics with positive symptomatology have shortened EEG microstate durations. Clin Neurophysiol. 2003;114(11):2043–51.

    CAS  PubMed  Google Scholar 

  56. Strik WK, Chiaramonti R, Muscas GC, Paganini M, Mueller TJ, Fallgatter AJ, Versari A, Zappoli R. Decreased EEG microstate duration and anteriorisation of the brain electrical fields in mild and moderate dementia of the Alzheimer type. Psychiatry Res. 1997;75(3):183–91.

    CAS  PubMed  Google Scholar 

  57. Raj VK, Rajagopalan SS, Bhardwaj S, Panda R, Reddam VR, Ganne C, Kenchaiah R, Mundlamuri RC, Kandavel T, Majumdar KK, Parthasarathy S, Sinha S, Bharath RD. Machine learning detects EEG microstate alterations in patients living with temporal lobe epilepsy. Seizure. 2018;61:8–13. https://doi.org/10.1016/j.seizure.2018.07.007.

    Article  Google Scholar 

  58. Yoshimura M, Pascual-Marqui RD, Nishida K, Kitaura Y, Mii H, Saito Y, Ikeda S, Katsura K, Ueda S, Minami S, Isotani T, Kinoshita T. Hyperactivation of the frontal control network revealed by symptom provocation in obsessive-compulsive disorder using EEG microstate and sLORETA analyses. Neuropsychobiology. 2019;77:176–85. https://doi.org/10.1159/000491719.

    Article  PubMed  Google Scholar 

  59. Schirrmeister RT, Springenberg JT, Fiederer LDJ, Glasstetter M, Eggensperger K, Tangermann M, Hutter F, Burgard W, Ball T. Deep learning with convolutional neural networks for EEG decoding and visualization. Hum Brain Mapp. 2017;38(11):5391–420. https://doi.org/10.1002/hbm.23730.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Tjepkema-Cloostermans MC, de Carvalho RCV, van Putten M. Deep learning for detection of focal epileptiform discharges from scalp EEG recordings. Clin Neurophysiol. 2018;129(10):2191–6. https://doi.org/10.1016/j.clinph.2018.06.024.

    Article  PubMed  Google Scholar 

  61. van Putten M, Olbrich S, Arns M. Predicting sex from brain rhythms with deep learning. Sci Rep. 2018;8(1):3069. https://doi.org/10.1038/s41598-018-21495-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Jirayucharoensak S, Pan-Ngum S, Israsena P. EEG-based emotion recognition using deep learning network with principal component based covariate shift adaptation. ScientificWorldJournal. 2014;2014:627892. https://doi.org/10.1155/2014/627892.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Chiarelli AM, Croce P, Merla A, Zappasodi F. Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification. J Neural Eng. 2018;15(3):036028. https://doi.org/10.1088/1741-2552/aaaf82.

    Article  PubMed  Google Scholar 

  64. Dakun T, Rui Z, Jinbo S, Wei Q. Sleep spindle detection using deep learning: a validation study based on crowdsourcing. Conf Proc IEEE Eng Med Biol Soc. 2015;2015:2828–31. https://doi.org/10.1109/EMBC.2015.7318980.

    Article  Google Scholar 

  65. Pascual-Marqui RD, Lehmann D, Koukkou M, Kochi K, Anderer P, Saletu B, Tanaka H, Hirata K, John ER, Prichep L, Biscay-Lirio R, Kinoshita T. Assessing interactions in the brain with exact low-resolution electromagnetic tomography. Philos Trans A Math Phys Eng Sci. 2011;369(1952):3768–84. https://doi.org/10.1098/rsta.2011.0081.

    Article  PubMed  Google Scholar 

  66. Pascual-Marqui RD, Michel CM, Lehmann D. Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol. 1994;18(1):49–65.

    CAS  PubMed  Google Scholar 

  67. Dale AM, Liu AK, Fischl BR, Buckner RL, Belliveau JW, Lewine JD, Halgren E. Dynamic statistical parametric mapping: combining fMRI and MEG for high-resolution imaging of cortical activity. Neuron. 2000;26(1):55–67.

    CAS  PubMed  Google Scholar 

  68. Pascual Marqui RD. Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find Exp Clin Pharmacol. 2002;24(Suppl C):5–12.

    PubMed  Google Scholar 

  69. Sekihara K, Sahani M, Nagarajan SS. Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction. NeuroImage. 2005;25(4):1056–67. https://doi.org/10.1016/j.neuroimage.2004.11.051.

    Article  PubMed  Google Scholar 

  70. Michel C, Koenig T, Brandeis D, Gianotti LR, Wackermann J. Electrical neuroimaging. Cambridge: Cambridge University Press; 2009.

    Google Scholar 

  71. Van Boxtel A, Jessurun M. Amplitude and bilateral coherency of facial and jaw-elevator EMG activity as an index of effort during a two-choice serial reaction task. Psychophysiology. 1993;30(6):589–604.

    PubMed  Google Scholar 

  72. Al-Asmi A, Benar CG, Gross DW, Khani YA, Andermann F, Pike B, Dubeau F, Gotman J. fMRI activation in continuous and spike-triggered EEG-fMRI studies of epileptic spikes. Epilepsia. 2003;44(10):1328–39.

    PubMed  Google Scholar 

  73. Bagshaw AP, Aghakhani Y, Benar CG, Kobayashi E, Hawco C, Dubeau F, Pike GB, Gotman J. EEG-fMRI of focal epileptic spikes: analysis with multiple haemodynamic functions and comparison with gadolinium-enhanced MR angiograms. Hum Brain Mapp. 2004;22(3):179–92. https://doi.org/10.1002/hbm.20024.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Hamandi K, Salek-Haddadi A, Laufs H, Liston A, Friston K, Fish DR, Duncan JS, Lemieux L. EEG-fMRI of idiopathic and secondarily generalized epilepsies. NeuroImage. 2006;31(4):1700–10. https://doi.org/10.1016/j.neuroimage.2006.02.016.

    Article  PubMed  Google Scholar 

  75. Kang JK, Benar C, Al-Asmi A, Khani YA, Pike GB, Dubeau F, Gotman J. Using patient-specific hemodynamic response functions in combined EEG-fMRI studies in epilepsy. NeuroImage. 2003;20(2):1162–70.

    PubMed  Google Scholar 

  76. Liechti MD, Valko L, Müller UC, Döhnert M, Drechsler R, Steinhausen Hans-Christoph, Brandeis D. Diagnostic value of resting electroencephalogram in attention-deficit/hyperactivity disorder across the lifespan. Brain Topogr. 2013;26(1):135–51. https://doi.org/10.1007/s10548-012-0258-6.

  77. Barry RJ, Stuart JJ, Clarke AR. A review of electrophysiology in attention-deficit/hyperactivity disorder: II. event-related potentials. Clin Neurophysiol. 2003;114(2):184–98. https://doi.org/10.1016/s1388-2457(02)00363-2.

  78. Barry RJ, Clarke AR, Stuart JJ. A review of electrophysiology in attention-deficit/hyperactivity disorder: I. Qualitative and Quantitative Electroencephalography. Clin Neurophysiol. 2003;114(2):171–83. https://doi.org/10.1016/s1388-2457(02)00362-0.

  79. Prichep LS, John ER, Ferris SH, Reisberg B, Almas M, Alper K, Cancro R. Quantitative EEG correlates of cognitive deterioration in the elderly. Neurobiol Aging. 1994;15(1):85–90.

    CAS  PubMed  Google Scholar 

  80. Stevens A, Kircher T, Nickola M, Bartels M, Rosellen N, Wormstall H. Dynamic regulation of EEG power and coherence is lost early and globally in probable DAT. Eur Arch Psychiatry Clin Neurosci. 2001;251(5):199–204.

    CAS  PubMed  Google Scholar 

  81. Prichep LS, John ER, Ferris SH, Rausch L, Fang Z, Cancro R, Torossian C, Reisberg B. Prediction of longitudinal cognitive decline in normal elderly with subjective complaints using electrophysiological imaging. Neurobiol Aging. 2006;27(3):471–81. https://doi.org/10.1016/j.neurobiolaging.2005.07.021.

    Article  CAS  PubMed  Google Scholar 

  82. Mathalon DH, Bennett A, Askari N, Gray EM, Rosenbloom MJ, Ford JM. Response-monitoring dysfunction in aging and Alzheimer’s disease: an event-related potential study. Neurobiol Aging. 2003;24(5):675–85.

    PubMed  Google Scholar 

  83. Ryzhenkova YY, Ponomarev VA, Anichkov AD, Konenkov SY, Polyakov YI, Melnichuk KV, Kropotov JD. P3 monitoring component decrease after bilateral crio-cingulotomy in heroin drug addicts. Int J Psychophysiol. 2008;69(3):314. https://doi.org/10.1016/j.ijpsycho.2008.05.334.

    Article  Google Scholar 

  84. Peniston EG, Kulkosky PJ. Alpha-theta-brainwave training and beta-endorphin levels in alcoholics. Alcohol Clin Exp Res. 1989;13(2):271–9. https://doi.org/10.1111/j.1530-0277.1989.tb00325.x.

    Article  CAS  PubMed  Google Scholar 

  85. Saxby E, Peniston EG. Alpha-theta brainwave neurofeedback training—an effective treatment for male and female alcoholics with depressive symptoms. J Clin Psychol. 1995;51(5):685–93. https://doi.org/10.1002/1097-4679(199509)51:5<685::Aid-Jclp2270510514>3.0.Co;2-K.

    Article  CAS  PubMed  Google Scholar 

  86. Prashad S, Dedrick ES, Filbey FM. Cannabis users exhibit increased cortical activation during resting state compared to non-users. NeuroImage. 2018;179:176–86. https://doi.org/10.1016/j.neuroimage.2018.06.031.

    Article  PubMed  Google Scholar 

  87. Herning RI, Jones RT, Hooker WD, Mendelson J, Blackwell L. Cocaine increases EEG beta: a replication and extension of Hans Berger’s historic experiments. Electroencephalogr Clin Neurophysiol. 1985;60(6):470–7.

    CAS  PubMed  Google Scholar 

  88. Bucci P, Mucci A, Volpe U, Merlotti E, Galderisi S, Maj M. Executive hypercontrol in obsessive-compulsive disorder: electrophysiological and neuropsychological indices. Clin Neurophysiol. 2004;115(6):1340–8. https://doi.org/10.1016/j.clinph.2003.12.031.

    Article  PubMed  Google Scholar 

  89. Herrmann MJ, Jacob C, Unterecker S, Fallgatter AJ. Reduced response-inhibition in obsessive-compulsive disorder measured with topographic evoked potential mapping. Psychiatry Res. 2003;120(3):265–71.

    PubMed  Google Scholar 

  90. Henriques JB, Davidson RJ. Regional brain electrical asymmetries discriminate between previously depressed and healthy control subjects. J Abnorm Psychol. 1990;99(1):22–31.

    CAS  PubMed  Google Scholar 

  91. Henriques JB, Davidson RJ. Brain electrical asymmetries during cognitive task performance in depressed and nondepressed subjects. Biol Psychiatry. 1997;42(11):1039–50.

    CAS  PubMed  Google Scholar 

  92. Sumich AL, Kumari V, Heasman BC, Gordon E, Brammer M. Abnormal asymmetry of N200 and P300 event-related potentials in subclinical depression. J Affect Disord. 2006;92(2–3):171–83. https://doi.org/10.1016/j.jad.2006.01.006.

    Article  PubMed  Google Scholar 

  93. Lee SH, Wynn JK, Green MF, Kim H, Lee KJ, Nam M, Park JK, Chung YC. Quantitative EEG and low resolution electromagnetic tomography (LORETA) imaging of patients with persistent auditory hallucinations. Schizophr Res. 2006;83(2–3):111–9. https://doi.org/10.1016/j.schres.2005.11.025.

    Article  PubMed  Google Scholar 

  94. McCarley RW, ODonnell BF, Niznikiewicz MA, Salisbury DF, Potts GF, Hirayasu Y, Nestor PG, Shenton ME. Update on electrophysiology in schizophrenia. Int Rev Psychiatry. 1997;9(4):373–86.

    Google Scholar 

  95. Umbricht DS, Bates JA, Lieberman JA, Kane JM, Javitt DC. Electrophysiological indices of automatic and controlled auditory information processing in first-episode, recent-onset and chronic schizophrenia. Biol Psychiatry. 2006;59(8):762–72. https://doi.org/10.1016/j.biopsych.2005.08.030.

    Article  PubMed  Google Scholar 

  96. Boord P, Siddall PJ, Tran Y, Herbert D, Middleton J, Craig A. Electroencephalographic slowing and reduced reactivity in neuropathic pain following spinal cord injury. Spinal Cord. 2008;46(2):118–23. https://doi.org/10.1038/sj.sc.3102077.

    Article  CAS  PubMed  Google Scholar 

  97. Schmidt S, Naranjo JR, Brenneisen C, Gundlach J, Schultz C, Kaube H, Hinterberger T, Jeanmonod D. Pain ratings, psychological functioning and quantitative EEG in a controlled study of chronic back pain patients. PLoS One. 2012;7(3):e31138. https://doi.org/10.1371/journal.pone.0031138.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Stern J, Jeanmonod D, Sarnthein J. Persistent EEG overactivation in the cortical pain matrix of neurogenic pain patients. NeuroImage. 2006;31(2):721–31. https://doi.org/10.1016/j.neuroimage.2005.12.042.

    Article  PubMed  Google Scholar 

  99. Bjork MH, Stovner LJ, Engstrom M, Stjern M, Hagen K, Sand T. Interictal quantitative EEG in migraine: a blinded controlled study. J Headache Pain. 2009;10(5):331–9. https://doi.org/10.1007/s10194-009-0140-4.

    Article  PubMed  PubMed Central  Google Scholar 

  100. Sarnthein J, Stern J, Aufenberg C, Rousson V, Jeanmonod D. Increased EEG power and slowed dominant frequency in patients with neurogenic pain. Brain. 2006;129(Pt 1):55–64. https://doi.org/10.1093/brain/awh631.

    Article  PubMed  Google Scholar 

  101. Vuckovic A, Hasan MA, Fraser M, Conway BA, Nasseroleslami B, Allan DB. Dynamic oscillatory signatures of central neuropathic pain in spinal cord injury. J Pain. 2014;15(6):645–55. https://doi.org/10.1016/j.jpain.2014.02.005.

    Article  PubMed  PubMed Central  Google Scholar 

  102. van den Broeke EN, Wilder-Smith OHG, van Goor H, Vissers KCP, van Rijn CM. Patients with persistent pain after breast cancer treatment show enhanced alpha activity in spontaneous EEG. Pain Med. 2013;14(12):1893–9. https://doi.org/10.1111/pme.12216.

    Article  PubMed  Google Scholar 

  103. Bjork M, Hagen K, Stovner L, Sand T. Photic EEG-driving responses related to ictal phases and trigger sensitivity in migraine: a longitudinal, controlled study. Cephalalgia. 2011;31(4):444–55. https://doi.org/10.1177/0333102410385582.

    Article  CAS  PubMed  Google Scholar 

  104. Gonzalez-Roldan AM, Munoz MA, Cifre I, Sitges C, Montoya P. Altered psychophysiological responses to the view of others’ pain and anger faces in fibromyalgia patients. J Pain. 2013;14(7):709–19. https://doi.org/10.1016/j.jpain.2013.01.775.

    Article  PubMed  Google Scholar 

  105. Mendonca-de-Souza M, Monteiro UM, Bezerra AS, Silva-de-Oliveira AP, Ventura-da-Silva BR, Barbosa MS, de Souza JA, Criado EC, Ferrarezi MC, Alencar Gde A, Lins OG, Coriolano M, Costa BL, Rodrigues MC. Resilience in migraine brains: decrease of coherence after photic stimulation. Front Hum Neurosci. 2012;6:207. https://doi.org/10.3389/fnhum.2012.00207.

    Article  PubMed  PubMed Central  Google Scholar 

  106. Sitges C, Bornas X, Llabres J, Noguera M, Montoya P. Linear and nonlinear analyses of EEG dynamics during non-painful somatosensory processing in chronic pain patients. Int J Psychophysiol. 2010;77(2):176–83. https://doi.org/10.1016/j.ijpsycho.2010.05.010.

    Article  PubMed  Google Scholar 

  107. Sitges C, Garcia-Herrera M, Pericas M, Collado D, Truyols M, Montoya P. Abnormal brain processing of affective and sensory pain descriptors in chronic pain patients. J Affect Disord. 2007;104(1–3):73–82. https://doi.org/10.1016/j.jad.2007.02.024.

    Article  PubMed  Google Scholar 

  108. Veldhuijzen DS, Kenemans JL, van Wijck AJ, Olivier B, Kalkman CJ, Volkerts ER. Processing capacity in chronic pain patients: a visual event-related potentials study. Pain. 2006;121(1–2):60–8. https://doi.org/10.1016/j.pain.2005.12.004.

    Article  CAS  PubMed  Google Scholar 

  109. Stein MB, Uhde TW. Infrequent occurrence of EEG abnormalities in panic disorder. Am J Psychiatry. 1989;146(4):517–20. https://doi.org/10.1176/ajp.146.4.517.

    Article  CAS  PubMed  Google Scholar 

  110. Knott VJ, Bakish D, Lusk S, Barkely J, Perugini M. Quantitative EEG correlates of panic disorder. Psychiatry Res. 1996;68(1):31–9.

    CAS  PubMed  Google Scholar 

  111. Hughes JR, Zak SM. EEG and clinical changes in patients with chronic seizures associated with slowly growing brain tumors. Arch Neurol. 1987;44(5):540–3.

    CAS  PubMed  Google Scholar 

  112. Fukushima T. Application of EEG-interval-spectrum-analysis (EISA) to the study of photic driving responses. A preliminary report. Arch Psychiatr Nervenkr (1970). 1975;220(2):99–105.

    CAS  Google Scholar 

  113. Melamed E, Lavy S, Portnoy Z, Sadan S, Carmon A. Correlation between regional cerebral blood flow and eeg frequency in the contralateral hemisphere in acute cerebral infarction. J Neurol Sci. 1975;26(1):21–7. https://doi.org/10.1016/0022-510x(75)90110-0.

  114. Hossmann KA, Heiss WD, Bewermeyer H, Mies G. EEG frequency analysis in the course of acute ischemic stroke. Neurosurg Rev. 1980;3(1):31–6.

    CAS  PubMed  Google Scholar 

  115. Rogers JM, Bechara J, Middleton S, Johnstone SJ. Acute EEG patterns associated with transient ischemic attack. Clin EEG Neurosci. 2018. https://doi.org/10.1177/1550059418790708.

  116. Tedesco Triccas L, Meyer S, Mantini D, Camilleri K, Falzon O, Camilleri T, Verheyden G. A systematic review investigating the relationship of electroencephalography and magnetoencephalography measurements with sensorimotor upper limb impairments after stroke. J Neurosci Methods. 2019;311:318–30. https://doi.org/10.1016/j.jneumeth.2018.08.009.

    Article  CAS  PubMed  Google Scholar 

  117. Chen CC, Lee SH, Wang WJ, Lin YC, Su MC. EEG-based motor network biomarkers for identifying target patients with stroke for upper limb rehabilitation and its construct validity. PLoS One. 2017;12(6):e0178822. https://doi.org/10.1371/journal.pone.0178822.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Zappasodi F, Tombini M, Milazzo D, Rossini PM, Tecchio F. Delta dipole density and strength in acute monohemispheric stroke. Neurosci Lett. 2007;416(3):310–4. https://doi.org/10.1016/j.neulet.2007.02.017.

    Article  CAS  PubMed  Google Scholar 

  119. Tecchio F, Zappasodi F, Pasqualetti P, Tombini M, Salustri C, Oliviero A, Pizzella V, Vernieri F, Rossini PM. Rhythmic brain activity at rest from rolandic areas in acute mono-hemispheric stroke: a magnetoencephalographic study. NeuroImage. 2005;28(1):72–83. https://doi.org/10.1016/j.neuroimage.2005.05.051.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Neuroradiology, University Hospital of Zurich, Zurich, Switzerland

    L. Michels

Authors
  1. L. Michels
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to L. Michels .

Editor information

Editors and Affiliations

  1. University Clinic for Radiology, University Hospital of Münster, Münster, Germany

    Manoj Mannil

  2. Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland

    Sebastian F.-X. Winklhofer

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Michels, L. (2020). Electroencephalography. In: Mannil, M., Winklhofer, SX. (eds) Neuroimaging Techniques in Clinical Practice. Springer, Cham. https://doi.org/10.1007/978-3-030-48419-4_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-48419-4_21

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-48418-7

  • Online ISBN: 978-3-030-48419-4

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation