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Brain Electrophysiology in Disorders of Consciousness: Diagnostic and Prognostic Utility

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Brain Function and Responsiveness in Disorders of Consciousness

Abstract

Electroencephalography (EEG) is a powerful and inexpensive bedside tool for the assessment of residual brain function in prolonged disorders of consciousness. Here we review a range of methods for EEG interpretation, including reactivity, perturbation by transcranial magnetic stimulation, evoked potentials, and oscillatory changes. We show that, in combination, these methods can form a reliable picture of each patient’s structural impairments and residual sensory and cognitive functioning, thereby leading to more accurate diagnoses and prognoses and stratification of patients for experimental neuro-stimulation therapies.

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References

  1. Gutling E, Gonser A, Imhof HG, Landis T (1995) EEG reactivity in the prognosis of severe head injury. Neurology 45:915–918. doi:10.1212/WNL.45.5.915

    Article  CAS  PubMed  Google Scholar 

  2. Kobylarz E, Schiff N (2005) Neurophysiological correlates of persistent vegetative and minimally conscious states. Neuropsychol Rehabil 15:323–332. doi:10.1080/09602010443000605

    Article  PubMed  Google Scholar 

  3. Thenayan Al E, Savard M, Sharpe M et al (2008) Predictors of poor neurologic outcome after induced mild hypothermia following cardiac arrest. Neurology 71:1535–1537. doi:10.1212/01.wnl.0000334205.81148.31

    Article  Google Scholar 

  4. Guerit JM, Amantini A, Amodio P et al (2009) Consensus on the use of neurophysiological tests in the intensive care unit (ICU): Electroencephalogram (EEG), evoked potentials (EP), and electroneuromyography (ENMG). Neurophysiol Clin 39:71–83. doi:10.1016/j.neucli.2009.03.002

    Article  PubMed  Google Scholar 

  5. Kaplan PW, Genoud D, Ho TW, Jallon P (2000) Clinical correlates and prognosis in early spindle coma. Clin Neurophysiol 111:584–590. doi:10.1016/S1388-2457(99)00303-X

    Article  CAS  PubMed  Google Scholar 

  6. RamachandranNair R, Sharma R, Weiss SK, Cortez MA (2005) Reactive EEG Patterns in Pediatric Coma. Pediatr Neurol 33:345–349. doi:10.1016/j.pediatrneurol.2005.05.007

    Article  PubMed  Google Scholar 

  7. Rossetti AO, Urbano LA, Delodder F, Kaplan PW (2010) Prognostic value of continuous EEG monitoring during therapeutic hypothermia after cardiac arrest. Crit Care 14(5):R173

    Article  PubMed Central  PubMed  Google Scholar 

  8. Logi F, Pasqualetti P, Tomaiuolo F (2011) Predict recovery of consciousness in post-acute severe brain injury: the role of EEG reactivity. Brain Inj 25:972–979. doi:10.3109/02699052.2011.589795

    Article  PubMed  Google Scholar 

  9. Hansotia PL (1985) Persistent vegetative state. Arch Neurol 42:1048–1052. doi:10.1001/archneur.1985.04060100030015

    Article  CAS  PubMed  Google Scholar 

  10. Bagnato S, Boccagni C, Sant’Angelo A et al (2015) EEG predictors of outcome in patients with disorders of consciousness. Clin Neurophysiol 126(5):959–966. doi:10.1016/j.clinph.2014.08.005

    Article  PubMed  Google Scholar 

  11. Ragazzoni A, Pirulli C, Veniero D et al (2013) Vegetative versus minimally conscious states: a study using TMS-EEG, sensory and event-related potentials. PLoS One 8, e57069. doi:10.1371/journal.pone.0057069

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  12. Wennervirta JE, Ermes MJ, Tiainen SM et al (2009) Hypothermia-treated cardiac arrest patients with good neurological outcome differ early in quantitative variables of EEG suppression and epileptiform activity. Crit Care Med 37:2427–2435. doi:10.1097/CCM.0b013e3181a0ff84

    Article  PubMed  Google Scholar 

  13. Rundgren M, Rosén I, Friberg H (2006) Amplitude-integrated EEG (aEEG) predicts outcome after cardiac arrest and induced hypothermia. Intensive Care Med 32:836–842. doi:10.1007/s00134-006-0178-6

    Article  PubMed  Google Scholar 

  14. Rundgren M, Westhall E, Cronberg T et al (2010) Continuous amplitude-integrated electroencephalogram predicts outcome in hypothermia-treated cardiac arrest patients. Crit Care Med 38:1838–1844. doi:10.1097/CCM.0b013e3181eaa1e7

    Article  PubMed  Google Scholar 

  15. Noirhomme Q, Lehembre R, Zdel RL et al (2014) Automated analysis of background EEG and reactivity during therapeutic hypothermia in comatose patients after cardiac arrest. Clin EEG Neurosci 45:6–13. doi:10.1177/1550059413509616

    Article  PubMed  Google Scholar 

  16. Zandbergen EG, de Haan RJ, Stoutenbeek CP et al (1998) Systematic review of early prediction of poor outcome in anoxicischaemic coma. Lancet 352:1808–1812. doi:10.1016/S0140-6736(98)04076-8

    Article  CAS  PubMed  Google Scholar 

  17. Young GB, Doig G, Ragazzoni A (2005) Anoxic-ischemic encephalopathy: clinical and Electrophysiological Associations with outcome. Neurocrit Care 2:159–164. doi:10.1385/NCC:2:2:159

    Article  PubMed  Google Scholar 

  18. Cruse D, Norton L, Gofton T et al (2014) Positive prognostication from median-nerve somatosensory evoked cortical potentials. Neurocrit Care 21:238–244. doi:10.1007/s12028-014-9982-y

    Article  PubMed  Google Scholar 

  19. Wijdicks EF, Hijdra A, Young GB et al (2006) Practice parameter: prediction of outcome in comatose survivors after cardiopulmonary resuscitation (an evidence-based review): report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 67:203–210. doi:10.1212/01.wnl.0000227183.21314.cd

    Article  CAS  PubMed  Google Scholar 

  20. Jones SJ (2000) Auditory evoked potentials to spectro-temporal modulation of complex tones in normal subjects and patients with severe brain injury. Brain 123:1007–1016. doi:10.1093/brain/123.5.1007

    Article  PubMed  Google Scholar 

  21. Kotchoubey B, Lang S, Baales R et al (2001) Brain potentials in human patients with extremely severe diffuse brain damage. Neurosci Lett 301:37–40

    Article  CAS  PubMed  Google Scholar 

  22. Fischer C, Luaute J, Morlet D (2010) Event-related potentials (MMN and novelty P3) in permanent vegetative or minimally conscious states. Clin Neurophysiol 121:1032–1042. doi:10.1016/j.clinph.2010.02.005

    Article  PubMed  Google Scholar 

  23. Cavinato M, Freo U, Ori C et al (2009) Post-acute P300 predicts recovery of consciousness from traumatic vegetative state. Brain Inj. 23(12):973–980. doi:10.3109/02699050903373493

    Article  PubMed  Google Scholar 

  24. Luaute J, Maucort-Boulch D, Tell L et al (2010) Long-term outcomes of chronic minimally conscious and vegetative states. Neurology 75:246–252.

    Article  CAS  PubMed  Google Scholar 

  25. Estraneo A, Moretta P, Loreto V et al (2013) Predictors of recovery of responsiveness in prolonged anoxic vegetative state. Neurology 80:464–470. doi:10.1212/WNL.0b013e31827f0f31

    Article  PubMed  Google Scholar 

  26. Wijnen VJ, Eilander HJ, de Gelder B, van Boxtel GJ (2014) Repeated measurements of the auditory oddball paradigm is related to recovery from the vegetative state. J Clin Neurophysiol 31:65–80. doi:10.1097/01.wnp.0000436894.17749.0c

    Article  PubMed  Google Scholar 

  27. Hildebrandt H, Happe S, Deutschmann A et al (2007) Brain perfusion and VEP reactivity in occipital and parietal areas are associated to recovery from hypoxic vegetative state. J Neurol Sci 260:150–158. doi:10.1016/j.jns.2007.04.035

    Article  PubMed  Google Scholar 

  28. Vogel EK, Luck SJ, Shapiro KL (1998) Electrophysiological evidence for a postperceptual locus of suppression during the attentional blink. J Exp Psychol Hum Percept Perform 24:1656–1674. doi:10.1037/0096-1523.24.6.1656

    Article  CAS  PubMed  Google Scholar 

  29. Dehaene S, Sergent C, Changeux JP (2003) A neuronal network model linking subjective reports and objective physiological data during conscious perception. Proc Natl Acad Sci U S A 100:8520–8525. doi:10.1073/pnas.1332574100

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  30. Lamy D, Salti M, Bar-Haim Y (2009) Neural correlates of subjective awareness and unconscious processing: an ERP study. J Cogn Neurosci 21:1435–1446. doi:10.1016/j.neulet.2003.09.060

    Article  PubMed  Google Scholar 

  31. Verleger R (2010) Markers of awareness? EEG potentials evoked by faint and masked events, with special reference to the “attentional blink“. In: Czigler I, Winkler I (eds) Unconscious memory representations in perception: processes and mechanisms in the brain. John Benjamin Publishing Company, Amsterdam, pp 37–70

    Chapter  Google Scholar 

  32. Owen AM, Coleman MR, Boly M et al (2006) Detecting awareness in the vegetative state. Science 313:1402

    Article  CAS  PubMed  Google Scholar 

  33. Goldfine AM, Victor JD, Conte MM et al (2011) Determination of awareness in patients with severe brain injury using EEG power spectral analysis. Clin Neurophysiol 122:2157–2168. doi:10.1016/j.clinph.2011.03.022

    Article  PubMed Central  PubMed  Google Scholar 

  34. Cruse D, Chennu S, Fernandez-Espejo D et al (2012) Detecting awareness in the vegetative state: electroencephalographic evidence for attempted movements to command. PLoS One 7, e49933. doi:10.1371/journal.pone.0049933

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  35. Guger C, Edlinger G, Harkam W et al (2003) How many people are able to operate an EEG-based brain-computer interface (BCI)? IEEE Trans Neural Syst Rehabil Eng 11:145–147

    Article  CAS  PubMed  Google Scholar 

  36. Cruse D, Chennu S, Chatelle C et al (2011) Bedside detection of awareness in the vegetative state: a cohort study. Lancet 378:2088–2094. doi:10.1016/S0140-6736(11)61224-5

    Article  PubMed  Google Scholar 

  37. Cruse D, Chennu S, Chatelle C et al (2012) Relationship between etiology and covert cognition in the minimally conscious state. Neurology 78:816–822. doi:10.1212/WNL.0b013e318249f764

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  38. Cruse D, Chennu S, Chatelle C et al (2012) Bedside detection of awareness in the vegetative state - Authors’ reply. Lancet 379:1702. doi:10.1016/S0140-6736(12)60715-6

    Article  Google Scholar 

  39. Goldfine AM, Bardin JC, Noirhomme Q et al (2013) Reanalysis of “Bedside detection of awareness in the vegetative state: a cohort study”. Lancet 381:289–291. doi:10.1016/S0140-6736(13)60125-7

    Article  PubMed Central  PubMed  Google Scholar 

  40. Cruse D, Chennu S, Chatelle C et al (2013) Reanalysis of “Bedside detection of awareness in the vegetative state: a cohort study” – Authors’ reply. Lancet 381:291–292. doi:10.1016/S0140-6736(13)60126-9

    Article  PubMed  Google Scholar 

  41. Owen AM, Coleman MR, Boly M et al (2007) Response to comments on “Detecting awareness in the vegetative state”. Science 315:1221c. doi:10.1126/science.1135583

    Article  Google Scholar 

  42. Noirhomme Q, Lesenfants D, Gomez F et al (2014) Biased binomial assessment of cross-validated estimation of classification accuracies illustrated in diagnosis predictions. NeuroImage Clin. doi:10.1016/j.nicl.2014.04.004

    PubMed Central  PubMed  Google Scholar 

  43. Cruse D, Gantner I, Soddu A, Owen AM (2014) Lies, damned lies, and diagnoses: estimating the clinical utility of assessments of covert awareness in the vegetative state. Brain Inj 28(9):1197–1201. doi: 10.3109/02699052.2014.920517

    Article  PubMed  Google Scholar 

  44. Peterson A, Cruse D, Naci L et al (2015) Risk, diagnostic error, and the clinical science of consciousness. Neuroimage Clin 7:588–597. doi:10.1016/j.nicl.2015.02.008

    Article  PubMed Central  PubMed  Google Scholar 

  45. Gibson RM, Fernández-Espejo D, Gonzalez-Lara LE, Kwan BY, Lee DH, Owen AM, Cruse D (2014) Multiple tasks and neuroimaging modalities increase the likelihood of detecting covert awareness in patients with disorders of consciousness. Front Hum Neurosci. doi:10.3389/fnhum.2014.00950

    PubMed Central  PubMed  Google Scholar 

  46. Horki P, Bauernfeind G, Klobassa DS, Pokorny C, Pichler G, Schippinger W, Müller-Putz GR (2014) Detection of mental imagery and attempted movements in patients with disorders of consciousness using EEG. Front Hum Neurosci. doi:10.3389/fnhum.2014.01

    PubMed Central  PubMed  Google Scholar 

  47. Cruse D, Thibaut A, Demertzi A et al (2013) Actigraphy assessments of circadian sleep-wake cycles in the vegetative and minimally conscious states. BMC Med 11:18. doi:10.1097/00001199-200501000-00005

    Article  PubMed Central  PubMed  Google Scholar 

  48. Isono M, Wakabayashi Y, Fujiki MM et al (2002) Sleep cycle in patients in a state of permanent unconsciousness. Brain Inj 16:705–712. doi:10.1080/02699050210127303

    Article  PubMed  Google Scholar 

  49. Landsness EC, Bruno M-A, Noirhomme Q et al (2011) Electrophysiological correlates of behavioural changes in vigilance in vegetative state and minimally conscious state. Brain 134:2222–2232. doi:10.1093/brain/awr152

    Article  PubMed Central  PubMed  Google Scholar 

  50. de Biase S, Gigli GL, Lorenzut S et al (2014) The importance of polysomnography in the evaluation of prolonged disorders of consciousness: sleep recordings more adequately correlate than stimulus-related evoked potentials with patients’ clinical status. Sleep Med 15:393–400. doi:10.1016/j.sleep.2013.09.026

    Article  PubMed  Google Scholar 

  51. Schiff ND (2012) Moving toward a generalizable application of central thalamic deep brain stimulation for support of forebrain arousal regulation in the severely injured brain. Ann N Y Acad Sci 1265:56–68. doi:10.1111/j.1749-6632.2012.06712.x

    Article  PubMed  Google Scholar 

  52. Espejo DF, Soddu A, Cruse D et al (2012) A role for the default mode network in the bases of disorders of consciousness. Ann Neurol 72(3):335–343

    Article  Google Scholar 

  53. Tononi G (2004) An information integration theory of consciousness. BMC Neurosci 5:42. doi:10.1186/1471-2202-5-42

    Article  PubMed Central  PubMed  Google Scholar 

  54. Rosanova M, Gosseries O, Casarotto S et al (2012) Recovery of cortical effective connectivity and recovery of consciousness in vegetative patients. Brain 135:1308–1320. doi:10.1093/brain/awr340

    Article  PubMed Central  PubMed  Google Scholar 

  55. Ferrarelli F, Massimini M, Sarasso S et al (2010) Breakdown in cortical effective connectivity during midazolam-induced loss of consciousness. Proc Natl Acad Sci U S A 107:2681–2686. doi:10.1073/pnas.0913008107

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  56. Massimini M, Ferrarelli F, Murphy MJ et al (2010) Cortical reactivity and effective connectivity during REM sleep in humans. Cogn Neurosci 1:176–183. doi:10.1080/17588921003731578

    Article  PubMed Central  PubMed  Google Scholar 

  57. Casali AG, Gosseries O, Rosanova M (2013) A theoretically based index of consciousness independent of sensory processing and behavior. Sci Transl Med 5(198):198ra105

    Article  PubMed  Google Scholar 

  58. Azila Noh N, Fuggetta G (2011) Human cortical theta reactivity to high-frequency repetitive transcranial magnetic stimulation. Hum Brain Mapp 33:2224–2237. doi:10.1002/hbm.21355

    Article  PubMed  Google Scholar 

  59. Fuggetta G, Pavone EF, Fiaschi A, Manganotti P (2008) Acute modulation of cortical oscillatory activities during short trains of high-frequency repetitive transcranial magnetic stimulation of the human motor cortex: a combined EEG and TMS study. Hum Brain Mapp 29:1–13. doi:10.1002/hbm.20371

    Article  PubMed  Google Scholar 

  60. Calvo-Merino B, Haggard P (2004) Transcranial magnetic stimulation. Applications in cognitive neuroscience. Rev Neurol 38:374–380

    CAS  PubMed  Google Scholar 

  61. Nitsche MA, Seeber A, Frommann K et al (2005) Modulating parameters of excitability during and after transcranial direct current stimulation of the human motor cortex. J Physiol 568:291–303. doi:10.1113/jphysiol.2005.092429

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  62. Louise-Bender Pape T, Rosenow J, Lewis G et al (2009) Repetitive transcranial magnetic stimulation-associated neurobehavioral gains during coma recovery. Brain Stimul 2:22–35. doi:10.1016/j.brs.2008.09.004

    Article  PubMed  Google Scholar 

  63. Strafella AP, Paus T, Fraraccio M, Dagher A (2003) Striatal dopamine release induced by repetitive transcranial magnetic stimulation of the human motor cortex. Brain 126(Pt 12):2609–2615

    Article  PubMed  Google Scholar 

  64. King JR, Sitt JD, Faugeras F et al (2013) Information sharing in the brain indexes consciousness in noncommunicative patients. Curr Biol 23:1914–1919. doi:10.1016/j.cub.2013.07.075

    Article  CAS  PubMed  Google Scholar 

  65. Chennu S, Finoia P, Kamau E et al (2014) Spectral signatures of reorganised brain networks in disorders of consciousness. PLoS Comput Biol 10(10):e1003887. doi:10.1371/journal.pcbi.1003887

    Article  PubMed Central  PubMed  Google Scholar 

  66. Piccione F, Cavinato M, Manganotti P et al (2010) Behavioral and neurophysiological effects of repetitive transcranial magnetic stimulation on the minimally conscious state: a case study. Neurorehabil Neural Repair 25:98–102. doi:10.1177/1545968310369802

    Article  PubMed  Google Scholar 

  67. Gabriel D, Henriques J, Comte A et al (2015) Substitute or complement? Defining the relative place of EEG and fMRI in the detection of voluntary brain reactions. Neuroscience 290:435–444. doi:10.1016/j.neuroscience.2015.01.053

    Article  CAS  PubMed  Google Scholar 

  68. Kotchoubey B, Lang S, Mezger G et al (2005) Information processing in severe disorders of consciousness: vegetative state and minimally conscious state. Clin Neurophysiol 116:2441–2453

    Article  CAS  PubMed  Google Scholar 

  69. Perrin F, Schnakers C, Schabus M et al (2006) Brain response to one’s own name in vegetative state, minimally conscious state, and locked-in syndrome. Arch Neurol 63:562–569

    Article  PubMed  Google Scholar 

  70. Schnakers C, Perrin F, Schabus M et al (2008) Voluntary brain processing in disorders of consciousness. Neurology 71:1614–1620

    Article  CAS  PubMed  Google Scholar 

  71. Bekinschtein TA, Dehaene S, Rohaut B et al (2009) Neural signature of the conscious processing of auditory regularities. Proc Natl Acad Sci U S A 106:1672–1677

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  72. Cavinato M, Volpato C, Silvoni S et al (2011) Event-related brain potential modulation in patients with severe brain damage. Clin Neurophysiol 122:719–724. doi:10.1016/j.clinph.2010.08.024

    Article  CAS  PubMed  Google Scholar 

  73. Boly M, Garrido MI, Gosseries O et al (2011) Preserved feedforward but impaired top-down processes in the vegetative state. Science 332:858–862. doi:10.1126/science.1202043

    Article  CAS  PubMed  Google Scholar 

  74. Höller Y, Bergmann J, Kronbichler M et al (2011) Preserved oscillatory response but lack of mismatch negativity in patients with disorders of consciousness. Clin Neurophysiol 122:1744–1754. doi:10.1016/j.clinph.2011.02.009

    Article  PubMed  Google Scholar 

  75. faugeras F, Rohaut B, Weiss N et al (2012) Event related potentials elicited by violations of auditory regularities in patients with impaired consciousness. Neuropsychologia 50:403–418. doi:10.1016/j.neuropsychologia.2011.12.015

    Article  PubMed  Google Scholar 

  76. Chennu S, Finoia P, Kamau E et al (2013) Dissociable endogenous and exogenous attention in disorders of consciousness. Neuroimage Clin 3:450–461. doi:10.1016/j.nicl.2013.10.008

    Article  PubMed Central  PubMed  Google Scholar 

  77. Steppacher I, Eickhoff S, Jordanov T et al (2013) N400 predicts recovery from disorders of consciousness. Annals of Neurol. doi:10.1002/ana.23835

    Google Scholar 

  78. Rohaut B, Faugeras F, Chausson N et al (2015) Probing ERP correlates of verbal semantic processing in patients with impaired consciousness. Neuropsychologia 66:279–292. doi: 10.1016/j.neuropsychologia.2014.10.014

    Article  PubMed  Google Scholar 

  79. Wijnen VJM, van Boxtel GJM, Eilander HJ, de Gelder B (2007) Mismatch negativity predicts recovery from the vegetative state. Clin Neurophysiol 118:597–605. doi:10.1016/j.clinph.2006.11.020

    Article  CAS  PubMed  Google Scholar 

  80. Qin PM, Di HB, Yan X et al (2008) Mismatch negativity to the patient’s own name in chronic disorders of consciousness. Neurosci Lett 448:24–28

    Article  CAS  PubMed  Google Scholar 

  81. Wijnen VJM, Eilander HJ, de Gelder B, van Boxtel GJM (2014) Visual processing during recovery from vegetative state to consciousness: Comparing behavioral indices to brain responses. Neurophysiol Clin 44:457–469. doi:10.1016/j.neucli.2014.08.008

    Article  CAS  PubMed  Google Scholar 

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Cruse, D., Young, G.B., Piccione, F., Cavinato, M., Ragazzoni, A. (2016). Brain Electrophysiology in Disorders of Consciousness: Diagnostic and Prognostic Utility. In: Monti, M., Sannita, W. (eds) Brain Function and Responsiveness in Disorders of Consciousness. Springer, Cham. https://doi.org/10.1007/978-3-319-21425-2_9

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