Skip to main content
Log in

Chronic Disorders of Consciousness: Diagnosis and Prognosis

  • Published:
Neuroscience and Behavioral Physiology Aims and scope Submit manuscript

This review analyzes the literature on studies of states of pathological disorders (suppression) of consciousness based on the use of neuroimaging, electrophysiological, and other noninvasive methods for assessing nervous system activity. Problems of making diagnoses and prognosticating the recovery of patients with chronic disorders of consciousness are assessed. Neuroimaging, electrophysiological, physiological, and other correlates of chronic disorders of consciousness, such as the minimally conscious state and unresponsive wakefulness syndrome, are assessed. Pathways to resolving problems in diagnosis and prognostication of chronic disorders of consciousness are discussed.

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.

Institutional subscriptions

Similar content being viewed by others

References

  • Aaslid, R., Lindegaard, K. F., Sorteberg, W., and Nornes, H., “Cerebral autoregulation dynamics in humans,” Stroke, 20, No. 1, 45–52 (1989).

    Article  CAS  PubMed  Google Scholar 

  • Abdalmalak, A., Milej, D., Norton, L., et al., “Single-session communication with a locked-in patient by functional near-infrared spectroscopy,” Neurophotonics, 4, No. 04, 040501 (2017).

  • Agbangla, N. F., Audiffren, M., and Albinet, C. T., “Use of near-infrared spectroscopy in the investigation of brain activation during cognitive aging: A systematic review of an emerging area of research,” Ageing Res. Rev., 38, 52–66 (2017).

    Article  PubMed  Google Scholar 

  • Aleksandrov, M. V., Aleksandrova, T. V., and Povalyukhina, E. S., “Electroencephalographic monitoring in resuscitation and intensive care departments,” Vestn. Sev.-Zapad. Gos. Med. Univ. im. Mechnikova, 10, No. 3, 81–90 (2018).

    Google Scholar 

  • Aleksandrova, E. V., Tenedieva, V. D., and Potapov, A. A., Post-Traumatic Unconscious States, GEOTAR-Media, Moscow (2015).

    Google Scholar 

  • Andrews, K., Murphy, L., Munday, R., and Littlewood, C., “Misdiagnosis of the vegetative state: Retrospective study in a rehabilitation unit,” Br. Med. J., 313, No. 7048, 13–16 (1996).

    Article  CAS  Google Scholar 

  • Angerer, M., Schabus, M., Raml, M., et al., “Actigraphy in brain-injured patients – A valid measurement for assessing circadian rhythms?” BMC Med., 18, No. 106) (2020).

  • Bagnato, S., Boccagni, C., Sant’Angelo, A., et al., “EEG predictors of outcome in patients with disorders of consciousness admitted for intensive rehabilitation,” Clin. Neurophysiol., 126, No. 5, 959–966 (2015).

    Article  PubMed  Google Scholar 

  • Bai, Y., Xia, X., Li, X., et al., “Spinal cord stimulation modulates frontal delta and gamma in patients of minimally consciousness state,” Neuroscience, 346, 247–254 (2017a).

    Article  CAS  PubMed  Google Scholar 

  • Bai, Y., Xia, X., Liang, Z., et al., “Frontal connectivity in EEG gamma (30–45Hz) respond to spinal cord stimulation in minimally conscious state patients,” Front. Cell. Neurosci., 11, 177 (2017b).

    Article  PubMed  PubMed Central  Google Scholar 

  • Bardin, J. C., Fins, J. J., Katz, D. I., et al., “Dissociations between behavioural and functional magnetic resonance imaging-based evaluations of cognitive function after brain injury,” Brain, 134, No. 3, 769–782 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  • Bardin, J. C., Schiff, N. D., and Voss, H. U., “Pattern classifi cation of volitional functional magnetic resonance imaging responses in patients with severe brain injury,” Arch. Neurol., 69, No. 2, 176–181 (2012).

    Article  PubMed  Google Scholar 

  • Bekinschtein, T. A., Dehaene, S., Rohaut, B., et al., “Neural signature of the conscious processing of auditory regularities,” Proc. Natl. Acad. Sci. USA, 106, No. 5, 1672–7 (2009b).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bekinschtein, T. A., Golombek, D. A., Simonetta, S. H., et al., “Circadian rhythms in the vegetative state,” Brain Inj., 23, No. 11, 915–919 (2009c).

    Article  CAS  PubMed  Google Scholar 

  • Bekinschtein, T., Cologan, V., Dahmen, B., and Golombek, D., “You are only coming through in waves: wakefulness variability and assessment in patients with impaired consciousness,” Prog. Brain Res., 177, No. C, 171–189 (2009a).

    Article  PubMed  Google Scholar 

  • Bernat, J. L., “Prognostic limitations of syndromic diagnosis in disorders of consciousness,” AJOB Neurosci., 7, No. 1, 46–48 (2016).

    Article  Google Scholar 

  • Blume, C., Angerer, M., Raml, M., et al., “Healthier rhythm, healthier brain? Integrity of circadian melatonin and temperature rhythms relates to the clinical state of brain-injured patients,” Eur. J. Neurol., 26, No. 8, 1051–1059 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Blume, C., Lechinger, J., Santhi, N., et al., “Signifi cance of circadian rhythms in severely brain-injured patients,” Neurology, 88, No. 20, 1933–1941 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  • Boly, M., Faymonville, M. E., Schnakers, C., et al., “Perception of pain in the minimally conscious state with PET activation: an observational study,” Lancet Neurol., 7, No. 11, 1013–1020 (2008).

    Article  PubMed  Google Scholar 

  • Boly, M., Garrido, M. I., Gosseries, O., et al., “Preserved feedforward but impaired top-down processes in the vegetative state,” Science, 332, No. 6031, 858–862 (2011).

    Article  CAS  PubMed  Google Scholar 

  • Boly, M., Tshibanda, L., Vanhaudenhuyse, A., et al., “Functional connectivity in the default network during resting state is preserved in a vegetative but not in a brain dead patient,” Hum. Brain Mapp., 30, No. 8, 2393–2400 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bruno, M. A., Majerus, S., Boly, M., et al., “Functional neuroanatomy underlying the clinical subcategorization of minimally conscious state patients,” J. Neurol., 259, No. 6, 1087–1098 (2012).

    Article  PubMed  Google Scholar 

  • Calabrò, R. S., Naro, A., Manuli, A., et al., “Pain perception in patients with chronic disorders of consciousness: What can limbic system tell us?” Clin. Neurophysiol., 128, No. 3, 454–462 (2017).

    Article  PubMed  Google Scholar 

  • Casali, A. G., Gosseries, O., Rosanova, M., et al., “A theoretically based index of consciousness independent of sensory processing and behavior,” Sci. Transl. Med., 5, No. 198, 198ra105 (2013).

  • Casarotto, S., Comanducci, A., Rosanova, M., et al., “Stratifi cation of unresponsive patients by an independently validated index of brain complexity,” Ann. Neurol., 80, No. 5, 718–729 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  • Casarotto, S., Romero Lauro, L. J., Bellina, V., et al., “EEG responses to TMS are sensitive to changes in the perturbation parameters and repeatable over time,” PLoS One, 5, No. 4, e10281 (2010).

  • Cauda, F., Micon, B. M., Sacco, K., et al., “Disrupted intrinsic functional connectivity in the vegetative state,” J Neurol. Neurosurg. Psychiatry, 80, No. 4, 429–431 (2009).

    Article  CAS  PubMed  Google Scholar 

  • Celesia, G. G., “Vegetative state two decades after the multi-society task force (MSTF) report,” Brain Funct. Responsiveness Disord. Conscious., 171–184 (2016).

  • Chellappa, S. L., Morris, C. J., and Scheer, F. A. J. L., “Daily circadian misalignment impairs human cognitive performance task-dependently,” Sci. Rep., 8, No. 1, (2018).

  • Chennu, S., Annen, J., Wannez, S., et al., “Brain networks predict metabolism, diagnosis and prognosis at the bedside in disorders of consciousness,” Brain, 140, No. 8, 2120–1232 (2017).

    Article  PubMed  Google Scholar 

  • Chennu, S., Finoia, P., Kamau, E., et al., Spectral signatures of reorganised brain networks in disorders of consciousness,” PLoS Comput. Biol., 10, No. 10, e1003887 (2014).

  • Childs, N. L., Mercer, W. N., and Childs, H. W., “Accuracy of diagnosis of persistent vegetative state,” Neurology, 43, 1465–1467 (1993).

    Article  CAS  PubMed  Google Scholar 

  • Cobos, M. I., Guerra, P. M., Vila, J., and Chica, A. B., “Heart-rate modulations reveal attention and consciousness interactions,” Psychophysiology, 56, No. 3, (2019).

  • Coleman, M. R., Davis, M. H., Rodd, J. M., et al., “Towards the routine use of brain imaging to aid the clinical diagnosis of disorders of consciousness,” Brain, 132, No. 9, 2541–2452 (2009).

    Article  CAS  PubMed  Google Scholar 

  • Cortese, M. D., Riganello, F., Arcuri, F., et al., “Coma recovery scale-r: Variability in the disorder of consciousness,” BMC Neurol., 15, 186 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Coyle, D., Carroll, A., Stow, J., et al., “Enabling control in the minimally conscious state in a single session with a three channel BCI,” in: 1st Int. Decoder Workshop, April, 1–4, 2012.

  • Cruse, D., Thibaut, A., Demertzi, A., et al., “Actigraphy assessments of circadian sleep–wake cycles in the vegetative and minimally conscious states,” BMC Med., 16, No. 1, 134 (2013).

  • De Vignemont, F. and Iannetti, G. D., “How many peripersonal spaces?” Neuropsychologia, 70, 327–334 (2015).

    Article  PubMed  Google Scholar 

  • De Volder, A. G., Goffinet, A. M., Bol, A., et al., “Brain glucose metabolism in postanoxic syndrome: positron emission tomographic study,” Arch. Neurol., 47, No. 2, 197–204 (1990).

    Article  Google Scholar 

  • De Weer, A. S., Da Ros, M., Berré, J., et al., “Environmental infl uences on activity patterns in altered states of consciousness,” Eur. J. Neurol., 18, No. 12, 1432–1434 (2011).

    Article  PubMed  Google Scholar 

  • Deacon, D., Grose-Fifer, J., Hewitt, S., et al., “Physiological evidence that a masked unrelated intervening item disrupts semantic priming: Implications for theories of semantic representation and retrieval models of semantic priming,” Brain Lang., 89, No. 1, 38–46 (2004).

    Article  PubMed  Google Scholar 

  • Demertzi, A., Antonopoulos, G., Heine, L., et al., “Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients,” Brain, 138, No. 9, 2619–2631 (2015).

    Article  PubMed  Google Scholar 

  • Demertzi, A., Antonopoulos, G., Voss, H. U., et al., “Audio-visual crossmodal fMRI connectivity differentiates single patients with disorders of consciousness,” Front. Hum. Neurosci., Conference Abstract: Belgian Brain Council 2014 Modulating The Brain: Facts, Fiction, Future (2014a).

  • Demertzi, A., Gómez, F., Crone, J. S., et al., “Multiple fMRI system-level baseline connectivity is disrupted in patients with consciousness alterations,” Cortex, 52, No. 1, 35–46 (2014b).

    Article  PubMed  Google Scholar 

  • Devalle, G., Castiglioni, P., Arienti, C., et al., “Cardio-respiratory autonomic responses to nociceptive stimuli in patients with disorders of consciousness,” PLoS One, 13, No. 9, 1083–1089 (2018).

    Article  CAS  Google Scholar 

  • Di Lazzaro, V., Oliviero, A., Pilato, et al., “The physiological basis of transcranial motor cortex stimulation in conscious humans,” Clin. Neurophysiol., 115, No. 2, 255–266 (2004).

    Article  PubMed  Google Scholar 

  • Di Perri, C., Bahri, M. A., Amico, E., et al., “Neural correlates of consciousness in patients who have emerged from a minimally conscious state: A cross-sectional multimodal imaging study,” Lancet Neurol., 15, No. 8, 830–842 (2016).

    Article  PubMed  Google Scholar 

  • Dobrokhotova, T. A., Grindel’, O. M., Bragina, N. N., et al., “Recovery of consciousness after prolonged coma in patients with severe traumatic brain injury,” Zh. Nevrol. Psikhiatr., 85, No. 5, 720–726 (1985).

    CAS  Google Scholar 

  • Dobrokhotova, T. A., Potapov, A. A., Zaitsev, O. S., and Likhterman, L. B., “Reversible postcoma unconscious states,” Zh. Sotsial. Klin. Psikhiatr., 2, 26–36 (1996).

    Google Scholar 

  • Dobronravova, I. S., Reorganization of Human Brain Electrical Activity on Depression and Recovery of Consciousness (cerebral coma): Dissert. Doct. Biol. Sci., 03.00.13, Moscow (1996).

  • Ernst, G., “Heart-rate variability – more than heart beats?” Front. Public Health, 5, 240 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  • Faugeras, F., Rohaut, B., Weiss, N., et al., “Probing consciousness with event-related potentials in the vegetative state,” Neurology, 77, No. 3, 264–268 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fellinger, R., Klimesch, W., Schnakers, C., et al., “Cognitive processes in disorders of consciousness as revealed by EEG time-frequency analyses,” Clin. Neurophysiol., 122, No. 11, 2177–2184 (2011).

    Article  CAS  PubMed  Google Scholar 

  • Fernández-Espejo, D., Bekinschtein, T., Monti, M. M., et al., “Diffusion weighted imaging distinguishes the vegetative state from the minimally conscious state,” Neuroimage, 54, No. 1, 103–112 (2011).

    Article  PubMed  Google Scholar 

  • Fernández-Espejo, D., Soddu, A., Cruse, D., et al., “A role for the default mode network in the bases of disorders of consciousness,” Ann. Neurol., 72, No. 3, 335–343 (2012).

    Article  PubMed  Google Scholar 

  • Ferrarelli, F., Massimini, M., Sarasso, S., et al., “Breakdown in cortical effective connectivity during midazolam-induced loss of consciousness,” Proc. Natl. Acad. Sci. USA, 107, No. 6, 2681–2686 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fingelkurts, A. A., Fingelkurts, A. A., Bagnato, et al., “Life or death: Prognostic value of a resting EEG with regards to survival in patients in vegetative and minimally conscious states,” PLoS One, 6, No. 10, e25967 (2011).

  • Fischer, D. B., Boes, A. D., Demertzi, A., et al., “A human brain network derived from coma-causing brainstem lesions,” Neurology, 87, No. 23, 2427–2434 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  • Formisano, R., D’Ippolito, M., and Catani, S., “Functional locked-in syndrome as recovery phase of vegetative state,” Brain Inj., 27, No. 11, 1332 (2013).

  • Friston, K., “Beyond phrenology: What can neuroimaging tell us about distributed circuitry?” Annu. Rev. Neurosci., 25, 221–250 (2002).

    Article  CAS  PubMed  Google Scholar 

  • Fukudome, Y., Abe, I., Saku, Y., et al., “Circadian blood pressure in patients in a persistent vegetative state,” Am. J. Physiol., 270, No. 5, Pt. 2, R1109–1114 (1996).

  • Galanaud, D., Perlbarg, V., Gupta, R., et al., “Assessment of white matter injury and outcome in severe brain trauma: A prospective multicenter cohort,” Anesthesiology, 117, No. 6, 1300–1310 (2012).

    Article  PubMed  Google Scholar 

  • Gallegos-Ayala, G., Furdea, A., Takano, K., et al., “Brain communication in a completely locked-in patient using bedside near-infrared spectroscopy,” Neurology, 82, No. 21, 1930–1932 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  • Giacino, J. T., Kalmar, K., and Whyte, J., “The JFK Coma Recovery Scale – Revised: Measurement characteristics and diagnostic utility,” Arch. Phys. Med. Rehabil., 85, No. 12, 2020–2029 (2004).

    Article  PubMed  Google Scholar 

  • Giacino, J. T., Schnakers, C., Rodriguez-Moreno, D., et al., “Behavioral assessment in patients with disorders of consciousness: gold standard or fool’s gold?” Prog. Brain Res., 177, No. C, 33–48 (2009).

  • Gnezditskii, V. V. and Piradov, M. A., The Neurophysiology of Coma and Impaired Consciousness (analysis and interpretation of clinical observations), PresSto, Ivanovo (2015).

    Google Scholar 

  • Golkowski, D., Merz, K., Mlynarcik, C., et al., “Simultaneous EEG-PETfMRI measurements in disorders of consciousness: an exploratory study on diagnosis and prognosis,” J. Neurol., 264, No. 9, 1986– 1995 (2017).

    Article  CAS  PubMed  Google Scholar 

  • Gosseries, O., Zasler, N. D., and Laureys, S., “Recent advances in disorders of consciousness: Focus on the diagnosis,” Brain Inj., 28, No. 9, 1141–1150 (2014).

    Article  PubMed  Google Scholar 

  • Graham, D. I., Adams, J. H., Murray, L. S., and Jennett, B., “Neuropathology of the vegetative state after head injury,” Neuropsychol. Rehabil., 15, No. 3–4, 198–213 (2005).

    Article  CAS  PubMed  Google Scholar 

  • Graziano, M. S. A. and Cooke, D. F., “Parieto-frontal interactions, personal space, and defensive behavior,” Neuropsychologia, 44, No. 13, 2621–2635 (2006).

    Article  PubMed  Google Scholar 

  • Grindel’, O. M., Human Electroencephalography in Traumatic Brain Injury, Nauka, Moscow (1988).

  • Grindel’, O. M., Romanova, N. V., Zaitsev, O. S., et al., “Mathematical analysis of electroencephalograms in the recovery of consciousness after severe traumatic brain injury,” Zh. Nevrol. Psikhiatr., 12, 47–51 (2006).

    Google Scholar 

  • Guaraldi, P., Sancisi, E., La Morgia, C., et al., “Nocturnal melatonin regulation in post-traumatic vegetative state: A possible role for melatonin supplementation?” Chronobiol. Int., 31, No. 5, 741–745 (2014).

    Article  CAS  PubMed  Google Scholar 

  • Hagoort, P. and Brown, C., “The Processing nature of the N400: Evidence from masked priming,” J. Cogn. Neurosci., 5, No. 1, 34–44 (1993).

    Article  PubMed  Google Scholar 

  • Hauger, S. L., Schanke, A. K., Andersson, S., et al., “The clinical diagnostic utility of electrophysiological techniques in assessment of patients with disorders of consciousness following acquired brain injury: A systematic review,” J. Head Trauma Rehabil., 32, No. 3, 185–196 (2017).

    Article  CAS  PubMed  Google Scholar 

  • He, J. H., Cui, Y., Song, M., et al., “Decreased functional connectivity between the mediodorsal thalamus and default mode network in patients with disorders of consciousness,” Acta Neurol. Scand., 131, No. 3, 145–151 (2015).

    Article  CAS  PubMed  Google Scholar 

  • Hofmeijer, J. and van Putten, M., “EEG in postanoxic coma: Prognostic and diagnostic value,” Clin. Neurophysiol., 127, No. 4, 2047–2055 (2016).

    Article  CAS  PubMed  Google Scholar 

  • Höller, Y., Thomschewski, A., Bergmann, J., et al., “Connectivity biomarkers can differentiate patients with different levels of consciousness,” Clin. Neurophysiol., 125, No. 8, 1545–1455 (2014).

    Article  PubMed  Google Scholar 

  • Ilmoniemi, R. J. and Kičić, D., “Methodology for combined TMS and EEG,” Brain Topogr., 22, No. 4, 233–248 (2010).

    Article  PubMed  Google Scholar 

  • Irani, F., Platek, S. M., Bunce, S., et al., “Functional near infrared spectroscopy (fNIRS, an emerging neuroimaging technology with important applications for the study of brain disorders,” Clin. Neuropsychol., 21, No. 1, 9–37 (2007).

  • Jennett, B. and Bond, M., “Assessment of outcome after severe brain damage,” Lancet, 1, No. 7905, 480–484 (1975).

    Article  CAS  PubMed  Google Scholar 

  • Jennett, B., “Thirty years of the vegetative state: Clinical, ethical and legal problems,” Prog. Brain Res., 150, 537–543 (2005).

    Article  PubMed  Google Scholar 

  • Jöbsis, F. F., “Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters,” Science, 198, No. 4323, 1264–1267 (1977).

    Article  PubMed  Google Scholar 

  • Jox, R. J., Bernat, J. L., Laureys, S., and Racine, E., “Disorders of consciousness: Responding to requests for novel diagnostic and therapeutic interventions,” Lancet Neurol., 11, No. 8, 732–738 (2012).

    Article  PubMed  Google Scholar 

  • Kamper, J. E., Garofano, J., Schwartz, D. J., et al., “Concordance of actigraphy with polysomnography in traumatic brain injury neurorehabilitation admissions,” J. Head Trauma Rehabil., 31, No. 2, 117–125 (2016).

    Article  PubMed  Google Scholar 

  • Kang, X. G., Li, L., Wei, D., et al., “Development of a simple score to predict outcome for unresponsive wakefulness syndrome,” Crit. Care, 18, No. 1, R37 (2014).

  • Kempny, A. M., James, L., Yelden, K., et al., “Functional near infrared spectroscopy as a probe of brain function in people with prolonged disorders of consciousness,” Neuroimage Clin., 12, 312–319 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  • King, J. R., Sitt, J. D., Faugeras, F., et al., “Information sharing in the brain indexes consciousness in noncommunicative patients,” Curr. Biol., 23, No. 19, 1914–1919 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Koch, C., Massimini, M., Boly, M., and Tononi, G., “Neural correlates of consciousness: Progress and problems,” Nat. Rev. Neurosci., 17, No. 5, 307–321 (2016).

    Article  CAS  PubMed  Google Scholar 

  • Komssi, S., Kähkönen, S., and Ilmoniemi, R. J., “The effect of stimulus intensity on brain responses evoked by transcranial magnetic stimulation,” Hum. Brain Mapp., 21, No. 3, 154–164 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  • Kondrat’eva, E. A., Avdyunina, I. A., Kondrat’ev, A. N., et al., “Determination of signs of consciousness and prognostication of outcomes in patients in vegetative states,” Aktual. Vopr. Anesteziol. Reanimatol., 71, No. 4, 273–280 (2016).

    Google Scholar 

  • Kotchoubey, B., Vogel, D., Lang, S., and Müller, F., “What kind of consciousness is minimal?” Brain Inj., 28, No. 9, 1156–1163 (2014).

    Article  PubMed  Google Scholar 

  • Kurganskii, A. V., “Functional organization of the human brain in the resting state,” Zh. Vyssh. Nerv. Deyat., 68, No. 5, 567–580 (2018).

    Google Scholar 

  • Kutas, M. and Hillyard, S. A., “Reading senseless sentences: Brain potentials refl ect semantic incongruity,” Science, 207, No. 4427, 203–205 (1980).

    Article  CAS  PubMed  Google Scholar 

  • Landsness, E., Bruno, M. A., Noirhomme, Q., et al., “Electrophysiological correlates of behavioural changes in vigilance in vegetative state and minimally conscious state,” Brain, 134, No. 8, 2222–2232 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  • Lassen, N. A., Ingvar, D. H., and Skinhøj, E., “Brain function and blood fl ow,” Sci. Am., 239, No. 4, 62–71 (1978).

    Article  CAS  PubMed  Google Scholar 

  • Laureys, S. and Schiff, N. D., “Coma and consciousness: Paradigms (re) framed by neuroimaging,” Neuroimage, 61, No. 2, 478–491 (2012).

    Article  PubMed  Google Scholar 

  • Laureys, S., Faymonville, M. E., Luxen, A., et al., “Restoration of thalamocortical connectivity after recovery from persistent vegetative state,” Lancet, 355, No. 9217, 1790–1791 (2000).

    Article  CAS  PubMed  Google Scholar 

  • Laureys, S., Faymonville, M. E., Peigneux, P., et al., “Cortical processing of noxious somatosensory stimuli in the persistent vegetative state,” Neuroimage, 17, No. 2, 732–741 (2002).

    Article  CAS  PubMed  Google Scholar 

  • Laureys, S., Goldman, S., Phillips, C., et al., “Impaired effective cortical connectivity in vegetative state: Preliminary investigation using PET,” Neuroimage, 9, No. 4, 377–382 (1999a).

    Article  CAS  PubMed  Google Scholar 

  • Laureys, S., Lemaire, C., Maquet, P., et al., “Cerebral metabolism during vegetative state and after recovery to consciousness,” J Neurol. Neurosurg. Psychiatry, 67, No. 1, 121 (1999b).

  • Laureys, S., Perrin, F., Faymonville, M. E., et al., “Cerebral processing in the minimally conscious state,” Neurology, 63, No. 5, 916–918 (2004).

    Article  CAS  PubMed  Google Scholar 

  • León-Carrión, J., Eeckhout, P., van Domínguez-Morales, M., del, R., and Pérez-Santamaría, F. J., “Survey: The locked-in syndrome: a syndrome looking for a therapy,” Brain Inj., 16, No. 7, 571–582 (2002).

    Article  PubMed  Google Scholar 

  • Liang, X., Zou, Q., He, Y., and Yang, Y., “Coupling of functional connectivity and regional cerebral blood fl ow reveals a physiological basis for network hubs of the human brain,” Proc. Natl. Acad. Sci. USA, 110, No. 5, 1929–1934 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Løvstad, M., Frøslie, K. F., Giacino, J. T., et al., “Reliability and diagnostic characteristics of the JFK Coma Recovery Scale – Revised: Exploring the infl uence of raters level of experience,” J. Head Trauma Rehabil., 25, No. 5, 349–356 (2010).

    Article  PubMed  Google Scholar 

  • Lucca, L. F., Lofaro, D., Pignolo, L., et al., “Outcome prediction in disorders of consciousness: the role of coma recovery scale revised,” BMC Neurol., 19, No. 1, 68 (2019).

  • Lulé, D., Noirhomme, Q., Kleih, S. C., et al., “Probing command following in patients with disorders of consciousness using a brain–computer interface,” Clin. Neurophysiol., 124, No. 1, 101–106 (2013).

    Article  PubMed  Google Scholar 

  • Majerus, S., Bruno, M. A., Schnakers, C., et al., “The problem of aphasia in the assessment of consciousness in brain-damaged patients,” Prog. Brain Res., 177, No. C, 49–61 (2009).

  • Matsumoto, M., Sugama, J., Okuwa, M., et al., “Non-invasive monitoring of core body temperature rhythms over 72 h in 10 bedridden elderly patients with disorders of consciousness in a Japanese hospital: A pilot study,” Arch. Gerontol. Geriatr., 57, No. 3, 428–432 (2013).

    Article  PubMed  Google Scholar 

  • Monti, M. M., Rosenberg, M., Finoia, P., et al., “Thalamo-frontal connectivity mediates top-down cognitive functions in disorders of consciousness,” Neurology, 84, No. 2, 167–173 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  • Monti, M. M., Vanhaudenhuyse, A., Coleman, M. R., et al., “Willful modulation of brain activity in disorders of consciousness,” N. Engl. J. Med., 362, No. 7, 579–589 (2010).

    Article  CAS  PubMed  Google Scholar 

  • Moody, M., Panerai, R. B., Eames, P. J., and Potter, J. F., “Cerebral and systemic hemodynamic changes during cognitive and motor activation paradigms,” Am. J. Physiol., 288, No. 657-6, R1581–1588 (2005).

    CAS  Google Scholar 

  • Moskała, M., Krupa, M., Gościński, I., and Traczewski, W., “Circadian rhythms of melatonin of patients with severe traumatic brain injury,” Neurol. Neurochir. Pol., 38, No. 5, 401–404 (2004).

    PubMed  Google Scholar 

  • Naito, M., Michioka, Y., Ozawa, K., et al., “A communication means for totally locked-in ALS patients based on changes in cerebral blood volume measured with near-infrared light,” IEICE Trans. Inf. Syst., E90-D (7), 1028–1037 (2007).

  • Naro, A., Bramanti, P., Leo, A., et al., “Transcranial alternating current stimulation in patients with chronic disorder of consciousness: A possible way to cut the diagnostic Gordian knot?” Brain Topogr., 29, No. 4, 623–644 (2016a).

    Article  PubMed  Google Scholar 

  • Naro, A., Russo, M., Leo, A., et al., “Cortical connectivity modulation induced by cerebellar oscillatory transcranial direct current stimulation in patients with chronic disorders of consciousness: A marker of covert cognition?” Clin. Neurophysiol., 127, No. 3, 1845–1854 (2016b).

    Article  PubMed  Google Scholar 

  • Obrig, H. and Villringer, A., “Beyond the visible imaging the human brain with light,” J. Cereb. Blood Flow Metab., 23 No. 1, 1–18 (2003).

    Article  PubMed  Google Scholar 

  • Oknina, L., Zaitsev, O., Masherow, E., et al., “The use of event-related potentials for predicting the degree of mental recovery in patients with severe brain injury – a prospective study,” J. Adv. Med. Med. Res., 27, No. 4, 1–13 (2018).

    Article  Google Scholar 

  • Owen, A. M., Coleman, M. R., Boly, M., et al., “Detecting awareness in the vegetative state,” Science, 313, No. 5792, 1402 (2006).

  • Pan, J., Xie, Q., He, Y., et al., “Detecting awareness in patients with disorders of consciousness using a hybrid brain–computer interface,” J. Neural Eng., 11, No. 5, 56007 (2014), accessed online.

  • Paparrigopoulos, T., Melissaki, A., Tsekou, H., et al., “Melatonin secretion after head injury: A pilot study,” Brain Inj., 20, No. 8, 873–8 (2006).

    Article  PubMed  Google Scholar 

  • Pattoneri, P., Tirabassi, G., Pelá, G., et al., “Circadian blood pressure and heart rate changes in patients in a persistent vegetative state after traumatic brain injury,” J. Clin. Hypertens. (Greenwich), 7, No. 12, 734–739 (2005).

    Article  Google Scholar 

  • Piradov, M. A., Suponeva, N. A., Sergeev, D. V., et al., “Structural-functional bases of chronic impairments to consciousness,” Ann. Klin. Eksperim. Nevrol., 12, 6–15 (2018).

    Google Scholar 

  • Pokorny, C., Klobassa, D. S., Pichler, G., et al., “The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients,” Artif. Intell. Med., 59, No. 2, 81–90 (2013).

    Article  PubMed  Google Scholar 

  • Potapov, A. A., Danilov, G. V., Sychev, A. A., et al., “Clinical and magnetic resonance tomography predictors of the duration of coma and the volume of intensive care and outcomes in traumatic brain injury,” Vopr. Neirokhirurg., 84, No. 4, 5–16 (2020).

    Article  CAS  Google Scholar 

  • Potapov, A. A., Krylov, V. V., Gavrilov, A. G., et al., “Recommendations for the diagnosis and treatment of severe traumatic brain injury. Part 1. Organization of medical care and diagnosis,” Vopr. Neirokhirurg., 79, No. 6, 100–106 (2015). Practice Guideline Update: Disorders of Consciousness (2018), https://www.aan.com/Guidelines/home/GuidelineDetail/926, acc. Dec. 15, 2020.

  • Qin, P., Wu, X., Huang, Z., et al., “How are different neural networks related to consciousness?” Ann. Neurol., [access online], 78, No. 4, 594– 605 (2015).

  • Ragazzoni, A., Cincotta, M., Giovannelli, F., et al., “Clinical neurophysiology of prolonged disorders of consciousness: From diagnostic stimulation to therapeutic neuromodulation,” Clin. Neurophysiol., 128, No. 9, 1629–1646 (2017).

    Article  PubMed  Google Scholar 

  • Ragazzoni, A., Pirulli, C., Veniero, D., et al., “Vegetative versus minimally conscious states: A study using TMS-EEG, sensory and event-related potentials,” PLoS One, 8, No. 2, e57069 (2013).

  • Riganello, F., Chatelle, C., Schnakers, C., and Laureys, S., “Heart rate variability as an indicator of nociceptive pain in disorders of consciousness?” J. Pain Symptom Manage., 57, No. 1, 47–56 (2019).

    Article  PubMed  Google Scholar 

  • Riganello, F., Cortese, M., Dolce, G., and Sannita, W., “Visual pursuit response in the severe disorder of consciousness: Modulation by the central autonomic system and a predictive model,” BMC Neurol., 13, 164 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  • Riganello, F., Larroque, S. K., Bahri, M. A., et al., “A heartbeat away from consciousness: Heart rate variability entropy can discriminate disorders of consciousness and is correlated with resting-state fMRI brain connectivity of the central autonomic network,” Front. Neurol., 9, 769 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  • Rosanova, M., Gosseries, O., Casarotto, S., et al., “Recovery of cortical effective connectivity and recovery of consciousness in vegetative patients,” Brain, 135, No. 4, 1308–1320 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  • Rosengarten, B., Deppe, M., Kaps, M., and Klingelhöfer, J., “Methodological aspects of functional transcranial doppler sonography and recommendations for simultaneous EEG recording,” Ultrasound Med. Biol., 38, No. 6, 989–996 (2012).

    Article  PubMed  Google Scholar 

  • Rossetti, A. O., Rabinstein, A. A., and Oddo, M., “Neurological prognostication of outcome in patients in coma after cardiac arrest,” Lancet Neurol., 15, No. 6, 597–609 (2016).

    Article  PubMed  Google Scholar 

  • Rundgren, M., Karlsson, T., Nielsen, N., et al., “Neuron specifi c enolase and S-100B as predictors of outcome after cardiac arrest and induced hypothermia,” Resuscitation, 80, No. 7, 784–789 (2009).

    Article  CAS  PubMed  Google Scholar 

  • Salinet, A. S. M., Panerai, R. B., and Robinson, T. G., “Effects of active, passive and motor imagery paradigms on cerebral and peripheral hemodynamics in older volunteers: A functional TCD study,” Ultrasound Med. Biol., 38, No. 6, 997–1003 (2012).

    Article  PubMed  Google Scholar 

  • Salinet, A. S. M., Robinson, T. G., and Panerai, R. B., “Active, passive, and motor imagery paradigms: Component analysis to assess neurovascular coupling,” J. Appl. Physiol., 114, No. 10, 1406–1412 (2013).

    Article  CAS  PubMed  Google Scholar 

  • Sambo, C. F., Forster, B., Williams, S. C., and Iannetti, G. D., “To blink or not to blink: Fine cognitive tuning of the defensive peripersonal space,” J. Neurosci., 32, No. 37, 12921–12927 (2012a).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sambo, C. F., Liang, M., Cruccu, G., and Iannetti, G. D., “Defensive peripersonal space: The blink refl ex evoked by hand stimulation is increased when the hand is near the face,” J. Neurophysiol., 107, No. 3, 880–889 (2012b).

    Article  CAS  PubMed  Google Scholar 

  • Santhi, N., Horowitz, T. S., Duffy, J. F., and Czeisler, C. A., “Acute sleep deprivation and circadian misalignment associated with transition onto the fi rst night of work impairs visual selective attention,” PLoS One, 2, No. 11, e1233 (2007).

  • Sarà, M., Pistoia, F., Pasqualetti, P., et al., “Functional isolation within the cerebral cortex in the vegetative state: A nonlinear method to predict clinical outcomes,” Neurorehabil. Neural Repair, 25, No. 1, 35–42 (2011).

    Article  PubMed  Google Scholar 

  • Schabus, M., Wislowska, M., Angerer, M., and Blume, C., “Sleep and circadian rhythms in severely brain-injured patients – A comment,” Clin. Neurophysiol., 129, No. 8, 1780–1784 (2018).

    Article  PubMed  Google Scholar 

  • Schartner, M., Seth, A., Noirhomme, Q., et al., “Complexity of multi-dimensional spontaneous EEG decreases during propofol induced general anaesthesia,” PLoS One, 10, No. 8) (2015).

  • Schiff, N. D., “Cognitive motor dissociation following severe brain injuries,” JAMA Neurol., 72, No. 12, 1413–1415 (2015).

    Article  PubMed  Google Scholar 

  • Schiff, N. D., “Recovery of consciousness after brain injury: a mesocircuit hypothesis,” Trends Neurosci., 33, No. 1, 1–9 (2010).

    Article  CAS  PubMed  Google Scholar 

  • Schnakers, C., Chatelle, C., Majerus, S., et al., “Assessment and detection of pain in noncommunicative severely brain-injured patients,” Expert Rev. Neurother., 10, No. 11, 1725–1731 (2010).

    Article  PubMed  Google Scholar 

  • Schnakers, C., Vanhaudenhuyse, A., Giacino, J., et al., “Diagnostic accuracy of the vegetative and minimally conscious state: Clinical consensus versus standardized neurobehavioral assessment,” BMC Neurol., 9, Art. 35 (2009).

  • Schorr, B., Schlee, W., Arndt, M., and Bender, A., “Coherence in resting- state EEG as a predictor for the recovery from unresponsive wakefulness syndrome,” J. Neurol., 263, No. 5, 937–953 (2016).

    Article  PubMed  Google Scholar 

  • Seel, R. T., Sherer, M., Whyte, J., et al., “Assessment scales for disorders of consciousness: Evidence-based recommendations for clinical practice and research,” Arch. Phys. Med. Rehabil., 91, No. 12, 1795– 1813 (2010).

    Article  PubMed  Google Scholar 

  • Sharova, E. V. and Romanova, N. V., “The EEG in traumatic brain injury,” in: Neurophysiological Investigations in Clinical Practice, Burdenko National Medical Research Center of Neurosurgery, Moscow (2019), 2nd ed., pp. 87–101.

  • Sharova, E. V., “Electrographic correlates of cerebral reactions to afferent stimuli in post-coma unconscious states in patients with severe traumatic brain injury,” Fiziol. Cheloveka, 31, No. 3, 5–15 (2005).

    CAS  PubMed  Google Scholar 

  • Sharova, E. V., Chelyapina, M. V., Korobkova, E. V., et al., “EEG correlates of the recovery of consciousness after severe traumatic brain injury,” Vopr. Neirokhirurg., 78, No. 1, 14–25 (2014).

    CAS  Google Scholar 

  • Sharova, E. V., Kotovich, J. V., Deza-Araujo, Y. I., et al., “FMRI resting state networks visualization in patients with severe traumatic brain injury,” Med. Vis., 24, No. 1, 68–84 (2020).

    Google Scholar 

  • Sharova, E. V., Shchekut’ev, G. A., Oknina, L. B., et al., “Prognostic signifi cance of brain electrical activity (EEG and ERP) in poersistent post-traumatic unconscious states,” Doktor Ru, 4, 30–37 (2008).

    Google Scholar 

  • Sharova, E., Pogosbekyan, E., Korobkova, E., et al., “Inter hemispheric connectivity and attention in patients with disorders of consciousness after severe traumatic brain injury,” J. Neurol. Stroke, 8, No. 4 (2018).

  • Shchekut’ev, G. A., Potapov, A. A., Bragina, N. N., and Manevich, A. Z., “Event-related potentials,” in: Clinical Guidelines for Traumatic Brain Injury, Konovalova, A. N. et al. (eds.), Antidor, Moscow (1998), pp. 387–394.

    Google Scholar 

  • Shea, N. and Bayne, T., “The vegetative state and the science of consciousness,” Br. J. Philos. Sci., 61, No. 3, 459–484 (2010).

    Article  PubMed  Google Scholar 

  • Shekleton, J. A., Parcell, D. L., Redman, J. R., et al., “Sleep disturbance and melatonin levels following traumatic brain injury,” Neurology, 74, No. 21, 1732–1738 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Shi, H., Yang, L., Zhao, L., et al., “Differences of heart rate variability between happiness and sadness emotion states: A pilot study,” J. Med. Biol. Eng., 37, No. 4, 527–539 (2017).

    Article  Google Scholar 

  • Si, J., Zhao, R., Zhang, Y., et al., “A portable fNIRS system with eight channels,” Opt. Tech. Neurosurg. Neurophot. Optogen., II, 9305: 93051B (2015).

    Google Scholar 

  • Siclari, F., Baird, B., Perogamvros, L., et al., “The neural correlates of dreaming,” BioRxiv, 012443 (2014).

  • Silva, S., De Pasquale, F., Vuillaume, C., et al., “Disruption of posteromedial large-scale neural communication predicts recovery from coma,” Neurology, 85, No. 23, 2036–2044 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  • Sinitsyn, D. O., Legostaeva, L. A., Kremneva, E. I., et al., “Degrees of functional connectome abnormality in disorders of consciousness,” Hum. Brain Mapp., 39, No. 7, 2929–2940 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  • Sitt, J. D., King, J. R., El Karoui, I., et al., “Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state,” Brain, 137, No. 8, 2258–2270 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  • Smith, E. and Delargy, M., “Locked-in syndrome,” Br. Med. J., 330, No. 7488, 406–409 (2005).

    Article  Google Scholar 

  • Song, M., Yang, Y., He, J., et al., “Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics,” eLife, 7, e36173 (2018a).

    Article  PubMed  PubMed Central  Google Scholar 

  • Song, M., Zhang, Y., Cui, Y., et al., “Brain network studies in chronic disorders of consciousness: Advances and perspectives,” Neurosci. Bull., 34, No. 4, 592–604 (2018b).

    Article  PubMed  PubMed Central  Google Scholar 

  • Stender, J., Gosseries, O., Bruno, M. A., et al., “Diagnostic precision of PET imaging and functional MRI in disorders of consciousness: A clinical validation study,” Lancet, 384, No. 9942, 514–522 (2014).

    Article  PubMed  Google Scholar 

  • Steppacher, I., Eickhoff, S., Jordanov, T., et al., “N400 predicts recovery from disorders of consciousness,” Ann. Neurol., 73, No. 5, 594–602 (2013).

    Article  PubMed  Google Scholar 

  • Steppacher, I., Fuchs, P., Kaps, M., et al., “A Tree of Life? Multivariate logistic outcome-prediction in disorders of consciousness,” Brain Inj., 34, No. 3, 399–406 (2020).

    Article  PubMed  Google Scholar 

  • Stevens, R. D. and Sutter, R., “Prognosis in severe brain injury,” Crit. Care Med., 41, No. 4, 1104–1123 (2013).

    Article  PubMed  Google Scholar 

  • Sussman, T. J., Jin, J., and Mohanty, A., “Top-down and bottom-up factors in threat-related perception and attention in anxiety,” Biol. Psychol., 121, 160–172 (2016).

    Article  PubMed  Google Scholar 

  • Troshina, E. M., Oknina, L. B., and Kopachka, M. M., “Use of ERP in Clinical Practice,” in: Neurophysiological Investigations in Clinical Practice, Burdenko National Medical Research Center of Neurosurgery, Moscow (2019), 2nd ed., pp. 209–223.

  • Van Der Eerden, A. W., Khalilzadeh, O., Perlbarg, V., et al., “White matter changes in comatose survivors of anoxic ischemic encephalopathy and traumatic brain injury: Comparative diffusion-tensor imaging study,” Radiology, 270, No. 2, 506–516 (2014).

    Article  PubMed  Google Scholar 

  • van Erp, W. S., Lavrijsen, J. C. M., Vos, P. E., et al., “The vegetative state: Prevalence, misdiagnosis, and treatment limitations,” J. Am. Med. Dir. Assoc., 16, No. 1, 85, e9-85.e14 (2015).

  • Vanhaudenhuyse, A., Demertzi, A., Schabus, M., et al., “Two distinct neuronal networks mediate the awareness of environment and of self,” J. Cogn. Neurosci., 23, No. 3, 570–578 (2011).

    Article  PubMed  Google Scholar 

  • Vanhaudenhuyse, A., Laureys, S., and Perrin, F., “Cognitive event-related potentials in comatose and post-comatose states,” Neurocrit. Care, 8, No. 2, 262–270 (2008).

    Article  PubMed  Google Scholar 

  • Varotto, G., Fazio, P., Rossi Sebastiano, D., et al., “Altered resting state effective connectivity in long-standing vegetative state patients: An EEG study,” Clin. Neurophysiol., 125, No. 1, 63–68 (2014).

    Article  PubMed  Google Scholar 

  • Veniero, D., Maioli, C., and Miniussi, C., “Potentiation of short-latency cortical responses by high-frequency repetitive transcranial magnetic stimulation,” J. Neurophysiol., 104, No. 3, 1578–1588 (2010).

    Article  PubMed  Google Scholar 

  • Villringer, A. and Dirnagl, U., “Coupling of brain activity and cerebral blood fl ow: Basis of functional neuroimaging,” Cerebrovasc. Brain Metab. Rev., 7, No. 3, 240–276 (1995).

    CAS  PubMed  Google Scholar 

  • Wang, F., He, Y., Pan, J., et al., “A novel audiovisual brain–computer interface and its application in awareness detection,” Sci. Rep., 5, Art. 9962 (2015).

    Article  Google Scholar 

  • Wannez, S., Heine, L., Thonnard, M., et al., “The repetition of behavioral assessments in diagnosis of disorders of consciousness,” Ann. Neurol., 81, No. 6, 883–889 (2017).

    Article  PubMed  Google Scholar 

  • Wijnen, V., Heutink, M., Boxtel, G. J. M., et al., “Autonomic reactivity to sensory stimulation is related to consciousness level after severe traumatic brain injury,” Clin. Neurophysiol., 117, No. 8, 1794–1807 (2006).

    Article  PubMed  Google Scholar 

  • Wijnen, V., van Boxtel, G., Eilander, H., and de Gelder, B., “Mismatch negativity predicts recovery from the vegetative state,” Clin. Neurophysiol., 118, No. 3, 597–605 (2007).

    Article  CAS  PubMed  Google Scholar 

  • Wilson, C., “Aetiological differences in neuroanatomy of the vegetative state: Insights from diffusion tensor imaging and functional implications,” J Neurol. Neurosurg. Psychiatry, 81, No. 5, 475–476 (2010).

    Article  PubMed  Google Scholar 

  • Wolpaw, J. R. and Birbaumer, N., “Brain–computer interfaces for communication and control,” Textb. Neural Repair Rehabil., 602–614 (2012).

  • Wright, J. E., Vogel, J. A., Sampson, J. B., et al., “Effects of travel across time zones (jet-lag) on exercise capacity and performance,” Aviat. Space Environ. Med., 54, No. 2, 132–137 (1983).

    CAS  PubMed  Google Scholar 

  • Wu, X., Zhang, J., Cui, Z., et al., “White matter deficits underlie the loss of consciousness level and predict recovery outcome in disorders of consciousness,” arXiv preprint, arXiv:1611.08310 (2016).

  • Wu, X., Zou, Q., Hu, J., et al., “Intrinsic functional connectivity patterns predict consciousness level and recovery outcome in acquired brain injury,” J. Neurosci., 35, No. 37, 12932–12946 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Xu, W., Jiang, G., Chen, Y., et al., “Prediction of minimally conscious state with somatosensory evoked potentials in long-term unconscious patients after traumatic brain injury,” J. Trauma Acute Care Surg., 72, No. 4, 1024–1030 (2012).

    Article  PubMed  Google Scholar 

  • Yamamoto, T., Katayama, Y., Kobayashi, K., et al., “Deep brain stimulation for the treatment of vegetative state,” Eur. J. Neurosci., 32, No. 7, 1145–1151 (2010).

    Article  PubMed  Google Scholar 

  • Yao, S., Song, J., Gao, L., et al., “Thalamocortical sensorimotor circuit damage associated with disorders of consciousness for diffuse axonal injury patients,” J. Neurol. Sci., 356, No. 1–2, 168–174 (2015).

    Article  PubMed  Google Scholar 

  • Zaitsev, O. S., The Psychopathology of Traumatic Brain Injury, Medpress- Inform, Moscow (2014).

    Google Scholar 

  • Zakharova, N. E., Potapov, A. A., Kornienko, V. N., et al., “Dynamic studies of the structure of the corpus callosum and the corticospinal tracts using diffusion tensor MRI in diffuse axonal injury,” Vopr. Neirokhirurg., 3, 3–10 (2010).

    Google Scholar 

  • Zakharova, N., Kornienko, V., Potapov, A., and Pronin, I., “Neuroimaging of traumatic brain injury,”in: Neuroimaging of Traumatic Brain Injury, Springer, ISBN 978-3-319-04355-5: 1-159 (2014).

  • Zhang, J., Wei, R. L., Peng, G. P., et al., “Correlations between diffusion tensor imaging and levels of consciousness in patients with traumatic brain injury: A systematic review and meta-analysis,” Sci. Rep., 7, No. 1, 2793 (2017).

  • Zhang, Y., Yang, Y., Si, J., et al., “Influence of inter-stimulus interval of spinal cord stimulation in patients with disorders of consciousness: A preliminary functional near-infrared spectroscopy study,” Neuroimage Clin., 17, 1–9 (2018).

    Article  PubMed  Google Scholar 

  • Zheng, Z. S., Reggente, N., Lutkenhoff, E., et al., “Disentangling disorders of consciousness: Insights from diffusion tensor imaging and machine learning,” Hum. Brain Mapp., 38, No. 1, 431–443 (2017).

    Article  CAS  PubMed  Google Scholar 

  • Zigmantovich, A., Oknina, L., Kopachka, M., et al., “Task-related reorganization of functional connectivity in early detection of consciousness in patients with severe brain injury,” Arch. Clin. Biomed. Res., 3, 374–385 (2019).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to L. A. Mayorova.

Additional information

Translated from Zhurnal Vysshei Nervnoi Deyatel’nosti imeni I. P. Pavlova, Vol. 71, No. 2, pp. 213–236, March–April, 2021.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mayorova, L.A., Petrova, M.V., Pryanikov, I.V. et al. Chronic Disorders of Consciousness: Diagnosis and Prognosis. Neurosci Behav Physi 51, 1132–1147 (2021). https://doi.org/10.1007/s11055-021-01173-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11055-021-01173-4

Keywords

Navigation