Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies

Nature Reviews Neurology volume 17, pages 135–156 (2021)Cite this article

Subjects

Abstract

Substantial progress has been made over the past two decades in detecting, predicting and promoting recovery of consciousness in patients with disorders of consciousness (DoC) caused by severe brain injuries. Advanced neuroimaging and electrophysiological techniques have revealed new insights into the biological mechanisms underlying recovery of consciousness and have enabled the identification of preserved brain networks in patients who seem unresponsive, thus raising hope for more accurate diagnosis and prognosis. Emerging evidence suggests that covert consciousness, or cognitive motor dissociation (CMD), is present in up to 15–20% of patients with DoC and that detection of CMD in the intensive care unit can predict functional recovery at 1 year post injury. Although fundamental questions remain about which patients with DoC have the potential for recovery, novel pharmacological and electrophysiological therapies have shown the potential to reactivate injured neural networks and promote re-emergence of consciousness. In this Review, we focus on mechanisms of recovery from DoC in the acute and subacute-to-chronic stages, and we discuss recent progress in detecting and predicting recovery of consciousness. We also describe the developments in pharmacological and electrophysiological therapies that are creating new opportunities to improve the lives of patients with DoC.

Key points

  • A common pathophysiological mechanism underlying disorders of consciousness (DoC) is the withdrawal of excitatory synaptic activity across the cerebrum produced by deafferentation or disfacilitation of neocortical, thalamic and striatal neurons.

  • Recovery from coma involves various mechanisms, culminating in the restoration of excitatory neurotransmission across long-range corticocortical, thalamocortical and thalamostriatal connections.

  • The re-emergence of consciousness is associated with a shift in patterns of neuronal activity across the corticothalamic system that can be measured with EEG, PET or resting-state functional MRI.

  • Task-based functional MRI and EEG can reveal cognitive motor dissociation in up to 15–20% of patients who seem unresponsive on behavioural examination, and emerging evidence suggests that early detection of cognitive motor dissociation in the intensive care unit predicts 1-year functional outcomes.

  • Amantadine is the only therapy that has been associated with the acceleration of recovery of consciousness in a randomized controlled trial of patients with subacute traumatic DoC, but multiple pharmacological and neuromodulatory therapies are now being tested.

  • Emerging advances in diagnostic and prognostic techniques provide new opportunities to detect consciousness, monitor its recovery, elucidate its neuronal substrate and identify the therapeutic potential of promoting re-emergence of consciousness in a subset of patients with DoC.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Multidimensional assessment of consciousness.
Fig. 2: Diffusion tractography detects acute disconnection of the ascending arousal network.
Fig. 3: Mapping loss of consciousness to a common brain network using the human connectome.
Fig. 4: Task-based functional MRI detects cognitive motor dissociation in the intensive care unit.
Fig. 5: EEG detection of cognitive motor dissociation in the intensive care unit predicts 1-year functional recovery.

Similar content being viewed by others

References

  1. Giacino, J. T., Fins, J. J., Laureys, S. & Schiff, N. D. Disorders of consciousness after acquired brain injury: the state of the science. Nat. Rev. Neurol. 10, 99–114 (2014).

    PubMed  Google Scholar 

  2. Giacino, J. T. et al. Practice guideline update recommendations summary: disorders of consciousness: report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology; the American Congress of Rehabilitation Medicine; and the National Institute on Disability, Independent Living, and Rehabilitation Research. Neurology 91, 450–460 (2018).

    PubMed  PubMed Central  Google Scholar 

  3. Teasdale, G. & Jennett, B. Assessment of coma and impaired consciousness. A practical scale. Lancet 2, 81–84 (1974).

    CAS  PubMed  Google Scholar 

  4. Laureys, S. et al. Unresponsive wakefulness syndrome: a new name for the vegetative state or apallic syndrome. BMC Med. 8, 68 (2010).

    PubMed  PubMed Central  Google Scholar 

  5. Jennett, B. & Plum, F. Persistent vegetative state after brain damage. A syndrome in search of a name. Lancet 1, 734–737 (1972).

    CAS  PubMed  Google Scholar 

  6. Multi-Society Task Force on PVS. Medical aspects of the persistent vegetative state (1). N. Engl. J. Med. 330, 1499–1508 (1994).

    Google Scholar 

  7. Giacino, J. T. et al. The minimally conscious state: definition and diagnostic criteria. Neurology 58, 349–353 (2002).

    PubMed  Google Scholar 

  8. Bruno, M. A., Vanhaudenhuyse, A., Thibaut, A., Moonen, G. & Laureys, S. From unresponsive wakefulness to minimally conscious PLUS and functional locked-in syndromes: recent advances in our understanding of disorders of consciousness. J. Neurol. 258, 1373–1384 (2011).

    PubMed  Google Scholar 

  9. Thibaut, A., Bodien, Y. G., Laureys, S. & Giacino, J. T. Minimally conscious state “plus”: diagnostic criteria and relation to functional recovery. J. Neurol. 267, 1245–1254 (2020).

    PubMed  Google Scholar 

  10. Giacino, J. T. et al. Behavioral recovery and early decision making in patients with prolonged disturbance in consciousness after traumatic brain injury. J. Neurotrauma 37, 357–365 (2020).

    PubMed  Google Scholar 

  11. Schiff, N. D. Cognitive motor dissociation following severe brain injuries. JAMA Neurol. 72, 1413–1415 (2015).

    PubMed  Google Scholar 

  12. Hemphill, J. C. 3rd & White, D. B. Clinical nihilism in neuroemergencies. Emerg. Med. Clin. North Am. 27, 27–37 (2009).

    PubMed  PubMed Central  Google Scholar 

  13. Leblanc, G. et al. Incidence and impact of withdrawal of life-sustaining therapies in clinical trials of severe traumatic brain injury: a systematic review. Clin. Trials 15, 398–412 (2018).

    PubMed  Google Scholar 

  14. Elmer, J. et al. Association of early withdrawal of life-sustaining therapy for perceived neurological prognosis with mortality after cardiac arrest. Resuscitation 102, 127–135 (2016).

    PubMed  PubMed Central  Google Scholar 

  15. Posner, J. B., Saper, C. B., Schiff, N. D. & Claassen, J. Plum and Posner’s Diagnosis and Treatment of Stupor and Coma 5th edn (Oxford Univ. Press, 2019).

  16. Parvizi, J. & Damasio, A. R. Neuroanatomical correlates of brainstem coma. Brain 126, 1524–1536 (2003).

    PubMed  Google Scholar 

  17. Fischer, D. B. et al. A human brain network derived from coma-causing brainstem lesions. Neurology 87, 2427–2434 (2016).

    PubMed  PubMed Central  Google Scholar 

  18. Schiff, N. D. Resolving the role of the paramedian thalamus in forebrain arousal mechanisms. Ann. Neurol. 84, 812–813 (2018).

    PubMed  Google Scholar 

  19. Steriade, M., Nunez, A. & Amzica, F. A novel slow (<1 Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components. J. Neurosci. 13, 3252–3265 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Timofeev, I., Grenier, F., Bazhenov, M., Sejnowski, T. J. & Steriade, M. Origin of slow cortical oscillations in deafferented cortical slabs. Cereb. Cortex 10, 1185–1199 (2000).

    CAS  PubMed  Google Scholar 

  21. Gold, L. & Lauritzen, M. Neuronal deactivation explains decreased cerebellar blood flow in response to focal cerebral ischemia or suppressed neocortical function. Proc. Natl Acad. Sci. USA 99, 7699–7704 (2002).

    CAS  PubMed  Google Scholar 

  22. Timofeev, I., Grenier, F. & Steriade, M. Disfacilitation and active inhibition in the neocortex during the natural sleep–wake cycle: an intracellular study. Proc. Natl Acad. Sci. USA 98, 1924–1929 (2001).

    CAS  PubMed  Google Scholar 

  23. Blumenfeld, H. et al. Ictal neocortical slowing in temporal lobe epilepsy. Neurology 63, 1015–1021 (2004).

    CAS  PubMed  Google Scholar 

  24. Brown, E. N., Lydic, R. & Schiff, N. D. General anesthesia, sleep, and coma. N. Engl. J. Med. 363, 2638–2650 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Fridman, E. A., Beattie, B. J., Broft, A., Laureys, S. & Schiff, N. D. Regional cerebral metabolic patterns demonstrate the role of anterior forebrain mesocircuit dysfunction in the severely injured brain. Proc. Natl Acad. Sci. USA 111, 6473–6478 (2014).

    CAS  PubMed  Google Scholar 

  26. Stender, J. et al. The minimal energetic requirement of sustained awareness after brain injury. Curr. Biol. 26, 1494–1499 (2016).

    CAS  PubMed  Google Scholar 

  27. Schiff, N. D. Recovery of consciousness after brain injury: a mesocircuit hypothesis. Trends Neurosci. 33, 1–9 (2010).

    CAS  PubMed  Google Scholar 

  28. Laureys, S. & Schiff, N. D. Coma and consciousness: paradigms (re)framed by neuroimaging. NeuroImage 61, 478–491 (2012).

    PubMed  Google Scholar 

  29. Williams, S. T. et al. Common resting brain dynamics indicate a possible mechanism underlying zolpidem response in severe brain injury. eLife 2, e01157 (2013).

    PubMed  PubMed Central  Google Scholar 

  30. Vanhaudenhuyse, A. et al. Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients. Brain 133, 161–171 (2010).

    PubMed  Google Scholar 

  31. Wu, X. et al. Intrinsic functional connectivity patterns predict consciousness level and recovery outcome in acquired brain injury. J. Neurosci. 35, 12932–12946 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Buckner, R. L. & DiNicola, L. M. The brain’s default network: updated anatomy, physiology and evolving insights. Nat. Rev. Neurosci. 20, 593–608 (2019).

    CAS  PubMed  Google Scholar 

  33. Raichle, M. E. & Snyder, A. Z. A default mode of brain function: a brief history of an evolving idea. NeuroImage 37, 1083–1090 (2007).

    PubMed  Google Scholar 

  34. Seeley, W. W. et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J. Neurosci. 27, 2349–2356 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Thibaut, A. et al. Clinical response to tDCS depends on residual brain metabolism and grey matter integrity in patients with minimally conscious state. Brain Stimul. 8, 1116–1123 (2015).

    PubMed  Google Scholar 

  36. Threlkeld, Z. D. et al. Functional networks reemerge during recovery of consciousness after acute severe traumatic brain injury. Cortex 106, 299–308 (2018).

    PubMed  PubMed Central  Google Scholar 

  37. Lant, N. D., Gonzalez-Lara, L. E., Owen, A. M. & Fernandez-Espejo, D. Relationship between the anterior forebrain mesocircuit and the default mode network in the structural bases of disorders of consciousness. Neuroimage Clin. 10, 27–35 (2016).

    PubMed  Google Scholar 

  38. Redinbaugh, M. J. et al. Thalamus modulates consciousness via layer-specific control of cortex. Neuron 106, 66–75.e12 (2020).

    CAS  PubMed  Google Scholar 

  39. Schiff, N. D. Central lateral thalamic nucleus stimulation awakens cortex via modulation of cross-regional, laminar-specific activity during general anesthesia. Neuron 106, 1–3 (2020).

    CAS  PubMed  Google Scholar 

  40. Schiff, N. D. Central thalamic contributions to arousal regulation and neurological disorders of consciousness. Ann. N. Y. Acad. Sci. 1129, 105–118 (2008).

    PubMed  Google Scholar 

  41. Edlow, B. L. et al. Neuroanatomic connectivity of the human ascending arousal system critical to consciousness and its disorders. J. Neuropathol. Exp. Neurol. 71, 531–546 (2012).

    PubMed  PubMed Central  Google Scholar 

  42. Snider, S. B. et al. Disruption of the ascending arousal network in acute traumatic disorders of consciousness. Neurology 93, e1281–e1287 (2019).

    PubMed  PubMed Central  Google Scholar 

  43. Steriade, M. Arousal: revisiting the reticular activating system. Science 272, 225–226 (1996).

    CAS  PubMed  Google Scholar 

  44. Moruzzi, G. & Magoun, H. W. Brain stem reticular formation and activation of the EEG. Electroencephalogr. Clin. Neurophysiol. 1, 455–473 (1949).

    CAS  PubMed  Google Scholar 

  45. Berlingeri, M., Magnani, F. G., Salvato, G., Rosanova, M. & Bottini, G. Neuroimaging studies on disorders of consciousness: a meta-analytic evaluation. J. Clin. Med. 8, 516 (2019).

    PubMed Central  Google Scholar 

  46. Rudolph, M., Pelletier, J. G., Pare, D. & Destexhe, A. Characterization of synaptic conductances and integrative properties during electrically induced EEG-activated states in neocortical neurons in vivo. J. Neurophysiol. 94, 2805–2821 (2005).

    PubMed  Google Scholar 

  47. Schiff, N. D. in Brain Function and Responsiveness in Disorders of Consciousness Ch. 15 (eds Monti, M. M. & Sannita, W. G.) 195–204 (Springer International, 2016).

  48. Schiff, N. D., Nauvel, T. & Victor, J. D. Large-scale brain dynamics in disorders of consciousness. Curr. Opin. Neurobiol. 25, 7–14 (2014).

    CAS  PubMed  Google Scholar 

  49. Becker, D. A. et al. A major miss in prognostication after cardiac arrest: burst suppression and brain healing. Epilepsy Behav. Case Rep. 7, 1–5 (2017).

    CAS  PubMed  Google Scholar 

  50. Ching, S., Purdon, P. L., Vijayan, S., Kopell, N. J. & Brown, E. N. A neurophysiological–metabolic model for burst suppression. Proc. Natl Acad. Sci. USA 109, 3095–3100 (2012).

    CAS  PubMed  Google Scholar 

  51. Silva, L. R., Amitai, Y. & Connors, B. W. Intrinsic oscillations of neocortex generated by layer 5 pyramidal neurons. Science 251, 432–435 (1991).

    CAS  Google Scholar 

  52. Llinas, R. R., Ribary, U., Jeanmonod, D., Kronberg, E. & Mitra, P. P. Thalamocortical dysrhythmia: a neurological and neuropsychiatric syndrome characterized by magnetoencephalography. Proc. Natl Acad. Sci. USA 96, 15222–15227 (1999).

    CAS  PubMed  Google Scholar 

  53. Llinas, R., Urbano, F. J., Leznik, E., Ramirez, R. R. & van Marle, H. J. Rhythmic and dysrhythmic thalamocortical dynamics: GABA systems and the edge effect. Trends Neurosci. 28, 325–333 (2005).

    CAS  PubMed  Google Scholar 

  54. Drover, J. D. & Schiff, N. D. A method for decomposing multivariate time series into a causal hierarchy within specific frequency bands. J. Comput. Neurosci. 45, 59–82 (2018).

    PubMed  Google Scholar 

  55. Steriade, M., Timofeev, I. & Grenier, F. Natural waking and sleep states: a view from inside neocortical neurons. J. Neurophysiol. 85, 1969–1985 (2001).

    CAS  PubMed  Google Scholar 

  56. Forgacs, P. B. et al. Dynamic regimes of neocortical activity linked to corticothalamic integrity correlate with outcomes in acute anoxic brain injury after cardiac arrest. Ann. Clin. Transl Neurol. 4, 119–129 (2017).

    PubMed  PubMed Central  Google Scholar 

  57. Claassen, J. et al. Bedside quantitative electroencephalography improves assessment of consciousness in comatose subarachnoid hemorrhage patients. Ann. Neurol. 80, 541–553 (2016).

    PubMed  PubMed Central  Google Scholar 

  58. Shah, S. A. et al. Executive attention deficits after traumatic brain injury reflect impaired recruitment of resources. Neuroimage Clin. 14, 233–241 (2017).

    PubMed  PubMed Central  Google Scholar 

  59. Shah, S. A. et al. Focal electroencephalographic changes index post-traumatic confusion and outcome. J. Neurotrauma 34, 2691–2699 (2017).

    PubMed  Google Scholar 

  60. Chatelle, C. et al. Changes in cerebral metabolism in patients with a minimally conscious state responding to zolpidem. Front. Hum. Neurosci. 8, 917 (2014).

    PubMed  PubMed Central  Google Scholar 

  61. Destexhe, A., Rudolph, M. & Pare, D. The high-conductance state of neocortical neurons in vivo. Nat. Rev. Neurosci. 4, 739–751 (2003).

    CAS  PubMed  Google Scholar 

  62. Dikmen, S. S. et al. Cognitive outcome following traumatic brain injury. J. Head. Trauma. Rehabil. 24, 430–438 (2009).

    PubMed  Google Scholar 

  63. Newcombe, V. F. et al. Aetiological differences in neuroanatomy of the vegetative state: insights from diffusion tensor imaging and functional implications. J. Neurol. Neurosurg. Psychiatry 81, 552–561 (2010).

    PubMed  Google Scholar 

  64. Hammond, F. M. et al. Disorders of consciousness due to traumatic brain injury: functional status ten years post-injury. J. Neurotrauma 36, 1136–1146 (2019).

    PubMed  Google Scholar 

  65. Edlow, B. L. et al. Unexpected recovery of function after severe traumatic brain injury: the limits of early neuroimaging-based outcome prediction. Neurocrit Care 19, 364–375 (2013).

    PubMed  PubMed Central  Google Scholar 

  66. Edlow, B. L., Threlkeld, Z. D., Fehnel, K. P. & Bodien, Y. G. Recovery of functional independence after traumatic transtentorial herniation with Duret hemorrhages. Front. Neurol. 10, 1077 (2019).

    PubMed  PubMed Central  Google Scholar 

  67. Muccio, C. F. et al. Reversible post-traumatic bilateral extensive restricted diffusion of the brain. A case study and review of the literature. Brain Inj. 23, 466–472 (2009).

    PubMed  Google Scholar 

  68. Stiver, S. I., Gean, A. D. & Manley, G. T. Survival with good outcome after cerebral herniation and Duret hemorrhage caused by traumatic brain injury. J. Neurosurg. 110, 1242–1246 (2009).

    PubMed  Google Scholar 

  69. Wijdicks, E. F. et al. Recommendations for the management of cerebral and cerebellar infarction with swelling: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 45, 1222–1238 (2014).

    PubMed  Google Scholar 

  70. Lord, A. S., Gilmore, E., Choi, H. A., Mayer, S. A. & VISTA-ICH Collaboration. Time course and predictors of neurological deterioration after intracerebral hemorrhage. Stroke 46, 647–652 (2015).

    PubMed  PubMed Central  Google Scholar 

  71. Rosengart, A. J., Schultheiss, K. E., Tolentino, J. & Macdonald, R. L. Prognostic factors for outcome in patients with aneurysmal subarachnoid hemorrhage. Stroke 38, 2315–2321 (2007).

    PubMed  Google Scholar 

  72. Wijdicks, E. F. et al. 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 (2006).

    CAS  PubMed  Google Scholar 

  73. Hemphill, J. C. 3rd, Bonovich, D. C., Besmertis, L., Manley, G. T. & Johnston, S. C. The ICH score: a simple, reliable grading scale for intracerebral hemorrhage. Stroke 32, 891–897 (2001).

    PubMed  Google Scholar 

  74. Turgeon, A. F. et al. Mortality associated with withdrawal of life-sustaining therapy for patients with severe traumatic brain injury: a Canadian multicentre cohort study. CMAJ 183, 1581–1588 (2011).

    PubMed  PubMed Central  Google Scholar 

  75. Peberdy, M. A. et al. Cardiopulmonary resuscitation of adults in the hospital: a report of 14720 cardiac arrests from the National Registry of Cardiopulmonary Resuscitation. Resuscitation 58, 297–308 (2003).

    PubMed  Google Scholar 

  76. Izzy, S., Compton, R., Carandang, R., Hall, W. & Muehlschlegel, S. Self-fulfilling prophecies through withdrawal of care: do they exist in traumatic brain injury, too? Neurocrit Care 19, 347–363 (2013).

    PubMed  Google Scholar 

  77. Wijdicks, E. F., Bamlet, W. R., Maramattom, B. V., Manno, E. M. & McClelland, R. L. Validation of a new coma scale: the FOUR score. Ann. Neurol. 58, 585–593 (2005).

    PubMed  Google Scholar 

  78. Foo, C. C., Loan, J. J. M. & Brennan, P. M. The relationship of the FOUR score to patient outcome: a systematic review. J. Neurotrauma 36, 2469–2483 (2019).

    PubMed  PubMed Central  Google Scholar 

  79. Teasdale, G. M. et al. A universal subarachnoid hemorrhage scale: report of a committee of the World Federation of Neurosurgical Societies. J. Neurol. Neurosurg. Psychiatry 51, 1457 (1988).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. de Oliveira Manoel, A. L. et al. Functional outcome after poor-grade subarachnoid hemorrhage: a single-center study and systematic literature review. Neurocrit Care 25, 338–350 (2016).

    PubMed  Google Scholar 

  81. Rittenberger, J. C., Tisherman, S. A., Holm, M. B., Guyette, F. X. & Callaway, C. W. An early, novel illness severity score to predict outcome after cardiac arrest. Resuscitation 82, 1399–1404 (2011).

    PubMed  PubMed Central  Google Scholar 

  82. Coppler, P. J. et al. Validation of the Pittsburgh Cardiac Arrest Category illness severity score. Resuscitation 89, 86–92 (2015).

    PubMed  PubMed Central  Google Scholar 

  83. Steyerberg, E. W. et al. Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLoS Med. 5, e165 (2008).

    PubMed  PubMed Central  Google Scholar 

  84. Suys, T. et al. Automated quantitative pupillometry for the prognostication of coma after cardiac arrest. Neurocrit Care 21, 300–308 (2014).

    PubMed  Google Scholar 

  85. Solari, D. et al. Early prediction of coma recovery after cardiac arrest with blinded pupillometry. Ann. Neurol. 81, 804–810 (2017).

    PubMed  Google Scholar 

  86. Oddo, M. et al. Quantitative versus standard pupillary light reflex for early prognostication in comatose cardiac arrest patients: an international prospective multicenter double-blinded study. Intensive Care Med. 44, 2102–2111 (2018).

    PubMed  PubMed Central  Google Scholar 

  87. Maciel, C. B. et al. Corneal reflex testing in the evaluation of a comatose patient: an ode to precise semiology and examination skills. Neurocrit Care 33, 399–404 (2020).

    PubMed  Google Scholar 

  88. Acosta, M. C., Tan, M. E., Belmonte, C. & Gallar, J. Sensations evoked by selective mechanical, chemical, and thermal stimulation of the conjunctiva and cornea. Invest. Ophthalmol. Vis. Sci. 42, 2063–2067 (2001).

    CAS  PubMed  Google Scholar 

  89. Greer, D. M. et al. Clinical examination for outcome prediction in nontraumatic coma. Crit. Care Med. 40, 1150–1156 (2012).

    PubMed  Google Scholar 

  90. Nolan, J. P. et al. European Resuscitation Council and European Society of Intensive Care Medicine 2015 guidelines for post-resuscitation care. Intensive Care Med. 41, 2039–2056 (2015).

    PubMed  Google Scholar 

  91. Greer, D. M., Rosenthal, E. S. & Wu, O. Neuroprognostication of hypoxic–ischaemic coma in the therapeutic hypothermia era. Nat. Rev. Neurol. 10, 190–203 (2014).

    CAS  PubMed  Google Scholar 

  92. Giacino, J. T., Kalmar, K. & Whyte, J. The JFK Coma Recovery Scale — Revised: measurement characteristics and diagnostic utility. Arch. Phys. Med. Rehabil. 85, 2020–2029 (2004).

    PubMed  Google Scholar 

  93. Schnakers, C. et al. Diagnostic accuracy of the vegetative and minimally conscious state: clinical consensus versus standardized neurobehavioral assessment. BMC Neurol. 9, 35 (2009).

    PubMed  PubMed Central  Google Scholar 

  94. Giacino, J. T. & Kalmar, K. The vegetative and minimally conscious states: a comparison of clinical features and functional outcome. J. Head. Trauma. Rehabil. 12, 36–51 (1997).

    Google Scholar 

  95. Claassen, J. et al. Detection of brain activation in unresponsive patients with acute brain injury. N. Engl. J. Med. 380, 2497–2505 (2019).

    PubMed  Google Scholar 

  96. Faugeras, F. et al. Survival and consciousness recovery are better in the minimally conscious state than in the vegetative state. Brain Inj. 32, 72–77 (2018).

    PubMed  Google Scholar 

  97. Fins, J. J. Rights Come to Mind: Brain Injury, Ethics, and the Struggle for Consciousness (Cambridge Univ. Press, 2015).

  98. Metter, R. B., Rittenberger, J. C., Guyette, F. X. & Callaway, C. W. Association between a quantitative CT scan measure of brain edema and outcome after cardiac arrest. Resuscitation 82, 1180–1185 (2011).

    PubMed  PubMed Central  Google Scholar 

  99. Claassen, J. et al. Global cerebral edema after subarachnoid hemorrhage: frequency, predictors, and impact on outcome. Stroke 33, 1225–1232 (2002).

    Google Scholar 

  100. Gentry, L. R., Godersky, J. C., Thompson, B. & Dunn, V. D. Prospective comparative study of intermediate-field MR and CT in the evaluation of closed head trauma. Am. J. Roentgenol. 150, 673–682 (1988).

    CAS  Google Scholar 

  101. Skandsen, T. et al. Prevalence and impact of diffuse axonal injury in patients with moderate and severe head injury: a cohort study of early magnetic resonance imaging findings and 1-year outcome. J. Neurosurg. 113, 556–563 (2010).

    PubMed  Google Scholar 

  102. Wu, O. et al. Comatose patients with cardiac arrest: predicting clinical outcome with diffusion-weighted MR imaging. Radiology 252, 173–181 (2009).

    PubMed  PubMed Central  Google Scholar 

  103. Wijman, C. A. et al. Prognostic value of brain diffusion-weighted imaging after cardiac arrest. Ann. Neurol. 65, 394–402 (2009).

    PubMed  PubMed Central  Google Scholar 

  104. Greer, D. M. et al. Hippocampal magnetic resonance imaging abnormalities in cardiac arrest are associated with poor outcome. J. Stroke Cerebrovasc. Dis. 22, 899–905 (2013).

    PubMed  Google Scholar 

  105. Tong, K. A. et al. Diffuse axonal injury in children: clinical correlation with hemorrhagic lesions. Ann. Neurol. 56, 36–50 (2004).

    PubMed  Google Scholar 

  106. Yanagawa, Y. et al. A quantitative analysis of head injury using T2*-weighted gradient-echo imaging. J. Trauma. 49, 272–277 (2000).

    CAS  PubMed  Google Scholar 

  107. Griffin, A. D. et al. Traumatic microbleeds suggest vascular injury and predict disability in traumatic brain injury. Brain 142, 3550–3564 (2019).

    PubMed  PubMed Central  Google Scholar 

  108. Izzy, S. et al. Revisiting grade 3 diffuse axonal injury: not all brainstem microbleeds are prognostically equal. Neurocrit Care 27, 199–207 (2017).

    PubMed  PubMed Central  Google Scholar 

  109. Edlow, B. L. et al. Disconnection of the ascending arousal system in traumatic coma. J. Neuropathol. Exp. Neurol. 72, 505–523 (2013).

    PubMed  PubMed Central  Google Scholar 

  110. McNab, J. A. et al. The human connectome project and beyond: initial applications of 300 mT/m gradients. NeuroImage 80, 234–245 (2013).

    PubMed  Google Scholar 

  111. Smith, D. H., Hicks, R. & Povlishock, J. T. Therapy development for diffuse axonal injury. J. Neurotrauma 30, 307–323 (2013).

    PubMed  PubMed Central  Google Scholar 

  112. Diaz-Arrastia, R. et al. Pharmacotherapy of traumatic brain injury: state of the science and the road forward: report of the Department of Defense Neurotrauma Pharmacology Workgroup. J. Neurotrauma 31, 135–158 (2014).

    PubMed  PubMed Central  Google Scholar 

  113. Sair, H. I. et al. Early functional connectome integrity and 1-year recovery in comatose survivors of cardiac arrest. Radiology 287, 247–255 (2018).

    PubMed  Google Scholar 

  114. Koenig, M. A. et al. MRI default mode network connectivity is associated with functional outcome after cardiopulmonary arrest. Neurocrit Care 20, 348–357 (2014).

    PubMed  PubMed Central  Google Scholar 

  115. Norton, L. et al. Disruptions of functional connectivity in the default mode network of comatose patients. Neurology 78, 175–181 (2012).

    CAS  PubMed  Google Scholar 

  116. Pugin, D. et al. Resting-state brain activity for early prediction outcome in postanoxic patients in a coma with indeterminate clinical prognosis. AJNR Am. J. Neuroradiol. 41, 1022–1030 (2020).

    CAS  PubMed  Google Scholar 

  117. Silva, S. et al. Disruption of posteromedial large-scale neural communication predicts recovery from coma. Neurology 85, 2036–2044 (2015).

    PubMed  PubMed Central  Google Scholar 

  118. Velly, L. et al. Use of brain diffusion tensor imaging for the prediction of long-term neurological outcomes in patients after cardiac arrest: a multicentre, international, prospective, observational, cohort study. Lancet Neurol. 17, 317–326 (2018).

    PubMed  Google Scholar 

  119. Galanaud, D. et al. Assessment of white matter injury and outcome in severe brain trauma: a prospective multicenter cohort. Anesthesiology 117, 1300–1310 (2012).

    PubMed  Google Scholar 

  120. Basser, P. J. & Pierpaoli, C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J. Magn. Reson. B 111, 209–219 (1996).

    CAS  PubMed  Google Scholar 

  121. Wang, J. Y. et al. Longitudinal changes of structural connectivity in traumatic axonal injury. Neurology 77, 818–826 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  122. Edlow, B. L. et al. Diffusion tensor imaging in acute-to-subacute traumatic brain injury: a longitudinal analysis. BMC Neurol. 16, 2 (2016).

    PubMed  PubMed Central  Google Scholar 

  123. Warner, M. A. et al. Assessing spatial relationships between axonal integrity, regional brain volumes, and neuropsychological outcomes after traumatic axonal injury. J. Neurotrauma 27, 2121–2130 (2010).

    PubMed  PubMed Central  Google Scholar 

  124. Edlow, B. L. et al. Personalized connectome mapping to guide targeted therapy and promote recovery of consciousness in the intensive care unit. Neurocrit Care 33, 364–375 (2020).

    PubMed  Google Scholar 

  125. Yue, J. K. et al. Transforming research and clinical knowledge in traumatic brain injury pilot: multicenter implementation of the common data elements for traumatic brain injury. J. Neurotrauma 30, 1831–1844 (2013).

    PubMed  PubMed Central  Google Scholar 

  126. Maas, A. I. R. et al. Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research. Lancet Neurol. 16, 987–1048 (2017).

    PubMed  Google Scholar 

  127. Haacke, E. M. et al. Common data elements in radiologic imaging of traumatic brain injury. J. Magn. Reson. Imaging 32, 516–543 (2010).

    PubMed  Google Scholar 

  128. Nichols, T. E. et al. Best practices in data analysis and sharing in neuroimaging using MRI. Nat. Neurosci. 20, 299–303 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  129. Fox, M. D. Mapping symptoms to brain networks with the human connectome. N. Engl. J. Med. 379, 2237–2245 (2018).

    CAS  PubMed  Google Scholar 

  130. Crossley, N. A. et al. The hubs of the human connectome are generally implicated in the anatomy of brain disorders. Brain 137, 2382–2395 (2014).

    PubMed  PubMed Central  Google Scholar 

  131. Achard, S. et al. Hubs of brain functional networks are radically reorganized in comatose patients. Proc. Natl Acad. Sci. USA 109, 20608–20613 (2012).

    CAS  PubMed  Google Scholar 

  132. Sharp, D. J., Scott, G. & Leech, R. Network dysfunction after traumatic brain injury. Nat. Rev. Neurol. 10, 156–166 (2014).

    PubMed  Google Scholar 

  133. Snider, S. B. et al. Cortical lesions causing loss of consciousness are anticorrelated with the dorsal brainstem. Hum. Brain Mapp. 41, 1520–1531 (2020).

    PubMed  PubMed Central  Google Scholar 

  134. Thengone, D. J., Voss, H. U., Fridman, E. A. & Schiff, N. D. Local changes in network structure contribute to late communication recovery after severe brain injury. Sci. Transl Med. 8, 368re365 (2016).

    Google Scholar 

  135. Voss, H. U. et al. Possible axonal regrowth in late recovery from the minimally conscious state. J. Clin. Invest. 116, 2005–2011 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  136. Bodien, Y. G., Chatelle, C. & Edlow, B. L. Functional networks in disorders of consciousness. Semin. Neurol. 37, 485–502 (2017).

    PubMed  PubMed Central  Google Scholar 

  137. Kondziella, D. et al. Functional MRI for assessment of the default mode network in acute brain injury. Neurocrit Care 27, 401–406 (2017).

    PubMed  Google Scholar 

  138. Fischer, D. et al. Intact brain network function in an unresponsive patient with COVID-19. Ann. Neurol. 88, 851–854 (2020).

    CAS  PubMed  Google Scholar 

  139. Comanducci, A. et al. Basic and advanced neurophysiology in the prognostic and diagnostic evaluation of disorders of consciousness: review of an IFCN-endorsed expert group. Clin Neurophysiol. 131, 2736–2765 (2020).

    CAS  PubMed  Google Scholar 

  140. Towne, A. R. et al. Prevalence of nonconvulsive status epilepticus in comatose patients. Neurology 54, 340–345 (2000).

    CAS  PubMed  Google Scholar 

  141. Claassen, J., Mayer, S. A., Kowalski, R. G., Emerson, R. G. & Hirsch, L. J. Detection of electrographic seizures with continuous EEG monitoring in critically ill patients. Neurology 62, 1743–1748 (2004).

    CAS  PubMed  Google Scholar 

  142. Young, G. B., McLachlan, R. S., Kreeft, J. H. & Demelo, J. D. An electroencephalographic classification for coma. Can. J. Neurol. Sci. 24, 320–325 (1997).

    CAS  PubMed  Google Scholar 

  143. Husari, K. S., Johnson, E. L. & Ritzl, E. K. Acute and long-term outcomes of lateralized rhythmic delta activity (LRDA) versus lateralized periodic discharges (LPDs) in critically ill patients. Neurocrit. Care https://doi.org/10.1007/s12028-020-01017-y (2020).

  144. Tabaeizadeh, M. et al. Burden of epileptiform activity predicts discharge neurologic outcomes in severe acute ischemic stroke. Neurocrit Care 32, 697–706 (2020).

    PubMed  Google Scholar 

  145. Oddo, M., Carrera, E., Claassen, J., Mayer, S. A. & Hirsch, L. J. Continuous electroencephalography in the medical intensive care unit. Crit. Care Med. 37, 2051–2056 (2009).

    PubMed  Google Scholar 

  146. De Marchis, G. M. et al. Seizure burden in subarachnoid hemorrhage associated with functional and cognitive outcome. Neurology 86, 253–260 (2016).

    PubMed  PubMed Central  Google Scholar 

  147. Claassen, J. et al. Electrographic seizures and periodic discharges after intracerebral hemorrhage. Neurology 69, 1356–1365 (2007).

    CAS  PubMed  Google Scholar 

  148. Zafar, S. F. et al. Effect of epileptiform abnormality burden on neurologic outcome and antiepileptic drug management after subarachnoid hemorrhage. Clin. Neurophysiol. 129, 2219–2227 (2018).

    PubMed  PubMed Central  Google Scholar 

  149. Rossetti, A. O., Rabinstein, A. A. & Oddo, M. Neurological prognostication of outcome in patients in coma after cardiac arrest. Lancet Neurol. 15, 597–609 (2016).

    PubMed  Google Scholar 

  150. Rossetti, A. O. et al. Electroencephalography predicts poor and good outcomes after cardiac arrest: a two-center study. Crit. Care Med. 45, e674–e682 (2017).

    PubMed  Google Scholar 

  151. Rossetti, A. O., Oddo, M., Liaudet, L. & Kaplan, P. W. Predictors of awakening from postanoxic status epilepticus after therapeutic hypothermia. Neurology 72, 744–749 (2009).

    PubMed  Google Scholar 

  152. Elmer, J. et al. Clinically distinct electroencephalographic phenotypes of early myoclonus after cardiac arrest. Ann. Neurol. 80, 175–184 (2016).

    PubMed  PubMed Central  Google Scholar 

  153. Bekinschtein, T. A. et al. Neural signature of the conscious processing of auditory regularities. Proc. Natl Acad. Sci. USA 106, 1672–1677 (2009).

    CAS  PubMed  Google Scholar 

  154. Amorim, E. et al. Estimating the false positive rate of absent somatosensory evoked potentials in cardiac arrest prognostication. Crit. Care Med. 46, e1213–e1221 (2018).

    PubMed  PubMed Central  Google Scholar 

  155. Carter, B. G. & Butt, W. Review of the use of somatosensory evoked potentials in the prediction of outcome after severe brain injury. Crit. Care Med. 29, 178–186 (2001).

    CAS  PubMed  Google Scholar 

  156. Forgacs, P. B. et al. Preservation of electroencephalographic organization in patients with impaired consciousness and imaging-based evidence of command-following. Ann. Neurol. 76, 869–879 (2014).

    PubMed  PubMed Central  Google Scholar 

  157. Estraneo, A. et al. Standard EEG in diagnostic process of prolonged disorders of consciousness. Clin. Neurophysiol. 127, 2379–2385 (2016).

    PubMed  Google Scholar 

  158. Jorgensen, E. O. & Holm, S. The natural course of neurological recovery following cardiopulmonary resuscitation. Resuscitation 36, 111–122 (1998).

    CAS  PubMed  Google Scholar 

  159. Engemann, D. A. et al. Robust EEG-based cross-site and cross-protocol classification of states of consciousness. Brain 141, 3179–3192 (2018).

    PubMed  Google Scholar 

  160. Sitt, J. D. et al. Large scale screening of neural signatures of consciousness in patients in a vegetative or minimally conscious state. Brain 137, 2258–2270 (2014).

    PubMed  PubMed Central  Google Scholar 

  161. Gosseries, O. et al. Automated EEG entropy measurements in coma, vegetative state/unresponsive wakefulness syndrome and minimally conscious state. Funct. Neurol. 26, 25–30 (2011).

    PubMed  PubMed Central  Google Scholar 

  162. Mikell, C. B. et al. Frontal networks associated with command following after hemorrhagic stroke. Stroke 46, 49–57 (2015).

    PubMed  Google Scholar 

  163. Streitberger, K. J. et al. Neuron-specific enolase predicts poor outcome after cardiac arrest and targeted temperature management: a multicenter study on 1,053 patients. Crit. Care Med. 45, 1145–1151 (2017).

    PubMed  Google Scholar 

  164. Mattsson, N. et al. Serum Tau and neurological outcome in cardiac arrest. Ann. Neurol. 82, 665–675 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  165. Moseby-Knappe, M. et al. Serum neurofilament light chain for prognosis of outcome after cardiac arrest. JAMA Neurol. 76, 64–71 (2019).

    PubMed  Google Scholar 

  166. Owen, A. M. et al. Detecting awareness in the vegetative state. Science 313, 1402 (2006).

    CAS  PubMed  Google Scholar 

  167. Schnakers, C. et al. Preserved covert cognition in noncommunicative patients with severe brain injury? Neurorehabil. Neural Repair. 29, 308–317 (2015).

    PubMed  Google Scholar 

  168. Gosseries, O., Zasler, N. D. & Laureys, S. Recent advances in disorders of consciousness: focus on the diagnosis. Brain Inj. 28, 1141–1150 (2014).

    PubMed  Google Scholar 

  169. Edlow, B. L. et al. Early detection of consciousness in patients with acute severe traumatic brain injury. Brain 140, 2399–2414 (2017).

    PubMed  PubMed Central  Google Scholar 

  170. Bodien, Y. G., Giacino, J. T. & Edlow, B. L. Functional MRI motor imagery tasks to detect command following in traumatic disorders of consciousness. Front. Neurol. 8, 688 (2017).

    PubMed  PubMed Central  Google Scholar 

  171. Kondziella, D., Friberg, C. K., Frokjaer, V. G., Fabricius, M. & Moller, K. Preserved consciousness in vegetative and minimal conscious states: systematic review and meta-analysis. J. Neurol. Neurosurg. Psychiatry 87, 485–492 (2016).

    PubMed  Google Scholar 

  172. Cruse, D. et al. Bedside detection of awareness in the vegetative state: a cohort study. Lancet 378, 2088–2094 (2011).

    PubMed  Google Scholar 

  173. Bodien, Y. G., Threlkeld, Z. D. & Edlow, B. L. Default mode network dynamics in covert consciousness. Cortex 117, 571–574 (2019).

    Google Scholar 

  174. Goldfine, A. M. et al. Reanalysis of “Bedside detection of awareness in the vegetative state: a cohort study”. Lancet 381, 289–291 (2013).

    PubMed  PubMed Central  Google Scholar 

  175. Chatelle, C., Spencer, C. A., Cash, S. S., Hochberg, L. R. & Edlow, B. L. Feasibility of an EEG-based brain–computer interface in the intensive care unit. Clin. Neurophysiol. 129, 1519–1525 (2018).

    PubMed  PubMed Central  Google Scholar 

  176. Rohaut, B., Eliseyev, A. & Claassen, J. Uncovering consciousness in unresponsive ICU patients: technical, medical and ethical considerations. Crit. Care 23, 78 (2019).

    PubMed  PubMed Central  Google Scholar 

  177. Menon, D. K. et al. Cortical processing in persistent vegetative state. Lancet 352, 200 (1998).

    CAS  PubMed  Google Scholar 

  178. Schiff, N. D. & Plum, F. Cortical function in the persistent vegetative state. Trends Cogn. Sci. 3, 43–44 (1999).

    CAS  PubMed  Google Scholar 

  179. Coleman, M. R. et al. Towards the routine use of brain imaging to aid the clinical diagnosis of disorders of consciousness. Brain 132, 2541–2552 (2009).

    CAS  PubMed  Google Scholar 

  180. Fernandez-Espejo, D. et al. Cerebral response to speech in vegetative and minimally conscious states after traumatic brain injury. Brain Inj. 22, 882–890 (2008).

    PubMed  Google Scholar 

  181. Di, H. B. et al. Cerebral response to patient’s own name in the vegetative and minimally conscious states. Neurology 68, 895–899 (2007).

    CAS  PubMed  Google Scholar 

  182. Kondziella, D. et al. European Academy of Neurology guideline on the diagnosis of coma and other disorders of consciousness. Eur. J. Neurol. 27, 741–756 (2020).

    CAS  PubMed  Google Scholar 

  183. Braiman, C. et al. Cortical response to the natural speech envelope correlates with neuroimaging evidence of cognition in severe brain injury. Curr. Biol. 28, 3833–3839.e3 (2018).

    CAS  PubMed  Google Scholar 

  184. Chatelle, C. et al. EEG correlates of language function in traumatic disorders of consciousness. Neurocrit Care 33, 449–457 (2020).

    PubMed  Google Scholar 

  185. Macdonald, R. L. Delayed neurological deterioration after subarachnoid haemorrhage. Nat. Rev. Neurol. 10, 44–58 (2014).

    CAS  PubMed  Google Scholar 

  186. Diringer, M. N. et al. Critical care management of patients following aneurysmal subarachnoid hemorrhage: recommendations from the Neurocritical Care Society’s Multidisciplinary Consensus Conference. Neurocrit Care 15, 211–240 (2011).

    Google Scholar 

  187. Bernard, S. A. et al. Treatment of comatose survivors of out-of-hospital cardiac arrest with induced hypothermia. N. Engl. J. Med. 346, 557–563 (2002).

    PubMed  Google Scholar 

  188. Nielsen, N. et al. Targeted temperature management at 33°C versus 36°C after cardiac arrest. N. Engl. J. Med. 369, 2197–2206 (2013).

    CAS  PubMed  Google Scholar 

  189. Lascarrou, J. B. et al. Targeted temperature management for cardiac arrest with nonshockable rhythm. N. Engl. J. Med. 381, 2327–2337 (2019).

    PubMed  Google Scholar 

  190. Andrews, P. J. et al. Hypothermia for intracranial hypertension after traumatic brain injury. N. Engl. J. Med. 373, 2403–2412 (2015).

    CAS  PubMed  Google Scholar 

  191. Cooper, D. J. et al. Effect of early sustained prophylactic hypothermia on neurologic outcomes among patients with severe traumatic brain injury: the POLAR randomized clinical trial. JAMA 320, 2211–2220 (2018).

    PubMed  PubMed Central  Google Scholar 

  192. Clifton, G. L. et al. Lack of effect of induction of hypothermia after acute brain injury. N. Engl. J. Med. 344, 556–563 (2001).

    CAS  PubMed  Google Scholar 

  193. Dietrich, W. D. & Bramlett, H. M. Therapeutic hypothermia and targeted temperature management in traumatic brain injury: clinical challenges for successful translation. Brain Res. 1640, 94–103 (2016).

    CAS  PubMed  Google Scholar 

  194. Hutchinson, P. J. et al. Trial of decompressive craniectomy for traumatic intracranial hypertension. N. Engl. J. Med. 375, 1119–1130 (2016).

    PubMed  Google Scholar 

  195. Meythaler, J. M., Brunner, R. C., Johnson, A. & Novack, T. A. Amantadine to improve neurorecovery in traumatic brain injury-associated diffuse axonal injury: a pilot double-blind randomized trial. J. Head. Trauma. Rehabil. 17, 300–313 (2002).

    PubMed  Google Scholar 

  196. Ghalaenovi, H. et al. The effects of amantadine on traumatic brain injury outcome: a double-blind, randomized, controlled, clinical trial. Brain Inj. 32, 1050–1055 (2018).

    PubMed  Google Scholar 

  197. Barra, M. E. et al. Stimulant therapy in acute traumatic brain injury: prescribing patterns and adverse event rates at 2 Level 1 trauma centers. J. Intensive. Care Med. 35, 11196–1202 (2020).

    Google Scholar 

  198. Alkhachroum, A. et al. EEG to detect early recovery of consciousness in amantadine-treated acute brain injury patients. J. Neurol. Neurosurg. Psychiatry 91, 675–676 (2020).

    PubMed  Google Scholar 

  199. Monti, M. M., Schnakers, C., Korb, A. S., Bystritsky, A. & Vespa, P. M. Non-invasive ultrasonic thalamic stimulation in disorders of consciousness after severe brain injury: a first-in-man report. Brain Stimul. 9, 940–941 (2016).

    PubMed  Google Scholar 

  200. American Congress of Rehabilitation Medicine, Brain Injury-Interdisciplinary Special Interest Group, Disorders of Consciousness Task Force, et al. Assessment scales for disorders of consciousness: evidence-based recommendations for clinical practice and research. Arch. Phys. Med. Rehabil. 91, 1795–1813 (2010).

    Google Scholar 

  201. Wannez, S. et al. The repetition of behavioral assessments in diagnosis of disorders of consciousness. Ann. Neurol. 81, 883–889 (2017).

    PubMed  Google Scholar 

  202. Pincherle, A. et al. Motor behavior unmasks residual cognition in disorders of consciousness. Ann. Neurol. 85, 443–447 (2019).

    PubMed  Google Scholar 

  203. Johr, J. et al. Recovery in cognitive motor dissociation after severe brain injury: a cohort study. PLoS ONE 15, e0228474 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  204. Estraneo, A. et al. Late recovery after traumatic, anoxic, or hemorrhagic long-lasting vegetative state. Neurology 75, 239–245 (2010).

    CAS  PubMed  Google Scholar 

  205. Giacino, J. T. et al. Practice guideline update recommendations summary: disorders of consciousness: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology; the American Congress of Rehabilitation Medicine; and the National Institute on Disability, Independent Living, and Rehabilitation Research. Arch. Phys. Med. Rehabil. 99, 1699–1709 (2018).

    PubMed  Google Scholar 

  206. Laureys, S. et al. Impaired effective cortical connectivity in vegetative state: preliminary investigation using PET. NeuroImage 9, 377–382 (1999).

    CAS  PubMed  Google Scholar 

  207. Laureys, S. et al. Restoration of thalamocortical connectivity after recovery from persistent vegetative state. Lancet 355, 1790–1791 (2000).

    CAS  PubMed  Google Scholar 

  208. Owen, A. M. et al. Residual auditory function in persistent vegetative state: a combined PET and fMRI study. Neuropsychol. Rehabil. 15, 290–306 (2005).

    PubMed  Google Scholar 

  209. Sharp, D. J. et al. Default mode network functional and structural connectivity after traumatic brain injury. Brain 134, 2233–2247 (2011).

    PubMed  Google Scholar 

  210. Hillary, F. G. et al. Changes in resting connectivity during recovery from severe traumatic brain injury. Int. J. Psychophysiol. 82, 115–123 (2011).

    CAS  PubMed  Google Scholar 

  211. Bonnelle, V. et al. Default mode network connectivity predicts sustained attention deficits after traumatic brain injury. J. Neurosci. 31, 13442–13451 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  212. Bonnelle, V. et al. Salience network integrity predicts default mode network function after traumatic brain injury. Proc. Natl Acad. Sci. USA 109, 4690–4695 (2012).

    CAS  PubMed  Google Scholar 

  213. Cauda, F. et al. Disrupted intrinsic functional connectivity in the vegetative state. J. Neurol. Neurosurg. Psychiatry 80, 429–431 (2009).

    CAS  PubMed  Google Scholar 

  214. Soddu, A. et al. Identifying the default-mode component in spatial IC analyses of patients with disorders of consciousness. Hum. Brain Mapp. 33, 778–796 (2012).

    PubMed  Google Scholar 

  215. Demertzi, A. et al. Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients. Brain 138, 2619–2631 (2015).

    PubMed  Google Scholar 

  216. Demertzi, A. et al. Multiple fMRI system-level baseline connectivity is disrupted in patients with consciousness alterations. Cortex 52, 35–46 (2014).

    PubMed  Google Scholar 

  217. Qin, P. et al. How are different neural networks related to consciousness? Ann. Neurol. 78, 594–605 (2015).

    PubMed  Google Scholar 

  218. Song, M. et al. Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics. eLife 7, e36173 (2018).

    PubMed  PubMed Central  Google Scholar 

  219. Fernandez-Espejo, D. et al. A role for the default mode network in the bases of disorders of consciousness. Ann. Neurol. 72, 335–343 (2012).

    PubMed  Google Scholar 

  220. Golland, Y. et al. Extrinsic and intrinsic systems in the posterior cortex of the human brain revealed during natural sensory stimulation. Cereb. Cortex 17, 766–777 (2007).

    PubMed  Google Scholar 

  221. Fox, M. D. & Raichle, M. E. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat. Rev. Neurosci. 8, 700–711 (2007).

    CAS  PubMed  Google Scholar 

  222. Fox, M. D. et al. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl Acad. Sci. USA 102, 9673–9678 (2005).

    CAS  PubMed  Google Scholar 

  223. Demertzi, A. et al. Human consciousness is supported by dynamic complex patterns of brain signal coordination. Sci. Adv. 5, eaat7603 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  224. Brooks, J. C., Faull, O. K., Pattinson, K. T. & Jenkinson, M. Physiological noise in brainstem FMRI. Front. Hum. Neurosci. 7, 623 (2013).

    PubMed  PubMed Central  Google Scholar 

  225. Beissner, F., Schumann, A., Brunn, F., Eisentrager, D. & Bar, K. J. Advances in functional magnetic resonance imaging of the human brainstem. NeuroImage 86, 91–98 (2014).

    PubMed  Google Scholar 

  226. Bianciardi, M. et al. In vivo functional connectome of human brainstem nuclei of the ascending arousal, autonomic, and motor systems by high spatial resolution 7-Tesla fMRI. MAGMA 29, 451–462 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  227. Bar, K. J. et al. Functional connectivity and network analysis of midbrain and brainstem nuclei. NeuroImage 134, 53–63 (2016).

    PubMed  Google Scholar 

  228. Curley, W. H., Forgacs, P. B., Voss, H. U., Conte, M. M. & Schiff, N. D. Characterization of EEG signals revealing covert cognition in the injured brain. Brain 141, 1404–1421 (2018).

    PubMed  PubMed Central  Google Scholar 

  229. Rosanova, M. et al. Sleep-like cortical OFF-periods disrupt causality and complexity in the brain of unresponsive wakefulness syndrome patients. Nat. Commun. 9, 4427 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  230. Arnaldi, D. et al. The prognostic value of sleep patterns in disorders of consciousness in the sub-acute phase. Clin. Neurophysiol. 127, 1445–1451 (2016).

    PubMed  Google Scholar 

  231. Kang, X. G. et al. Development of a simple score to predict outcome for unresponsive wakefulness syndrome. Crit. Care 18, R37 (2014).

    PubMed  PubMed Central  Google Scholar 

  232. Chennu, S. et al. Brain networks predict metabolism, diagnosis and prognosis at the bedside in disorders of consciousness. Brain 140, 2120–2132 (2017).

    PubMed  Google Scholar 

  233. Schomer, D. L. & Lopes da Silva, F. H. Niedermeyer’s Electroencephalography: Basic Principles, Clinical Applications, and Related Fields 7th edn (Oxford Univ. Press, 2017).

  234. Boly, M. et al. Preserved feedforward but impaired top-down processes in the vegetative state. Science 332, 858–862 (2011).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  236. Cavinato, M. et al. Post-acute P300 predicts recovery of consciousness from traumatic vegetative state. Brain Inj. 23, 973–980 (2009).

    PubMed  Google Scholar 

  237. Daltrozzo, J., Wioland, N., Mutschler, V. & Kotchoubey, B. Predicting coma and other low responsive patients outcome using event-related brain potentials: a meta-analysis. Clin. Neurophysiol. 118, 606–614 (2007).

    CAS  PubMed  Google Scholar 

  238. Steppacher, I. et al. N400 predicts recovery from disorders of consciousness. Ann. Neurol. 73, 594–602 (2013).

    PubMed  Google Scholar 

  239. Garrido, M. I., Kilner, J. M., Stephan, K. E. & Friston, K. J. The mismatch negativity: a review of underlying mechanisms. Clin. Neurophysiol. 120, 453–463 (2009).

    PubMed  PubMed Central  Google Scholar 

  240. Qin, P. et al. Mismatch negativity to the patient’s own name in chronic disorders of consciousness. Neurosci. Lett. 448, 24–28 (2008).

    CAS  PubMed  Google Scholar 

  241. Tzovara, A. et al. Prediction of awakening from hypothermic postanoxic coma based on auditory discrimination. Ann. Neurol. 79, 748–757 (2016).

    PubMed  Google Scholar 

  242. Raimondo, F. et al. Brain–heart interactions reveal consciousness in noncommunicating patients. Ann. Neurol. 82, 578–591 (2017).

    PubMed  Google Scholar 

  243. O’Kelly, J. et al. Neurophysiological and behavioral responses to music therapy in vegetative and minimally conscious states. Front. Hum. Neurosci. 7, 884 (2013).

    PubMed  PubMed Central  Google Scholar 

  244. Casali, A. G. et al. A theoretically based index of consciousness independent of sensory processing and behavior. Sci. Transl Med. 5, 198ra105 (2013).

    PubMed  Google Scholar 

  245. Casarotto, S. et al. Stratification of unresponsive patients by an independently validated index of brain complexity. Ann. Neurol. 80, 718–729 (2016).

    PubMed  PubMed Central  Google Scholar 

  246. Tononi, G., Boly, M., Massimini, M. & Koch, C. Integrated information theory: from consciousness to its physical substrate. Nat. Rev. Neurosci. 17, 450–461 (2016).

    CAS  PubMed  Google Scholar 

  247. Comolatti, R. et al. A fast and general method to empirically estimate the complexity of brain responses to transcranial and intracranial stimulations. Brain Stimul. 12, 1280–1289 (2019).

    PubMed  Google Scholar 

  248. Belardinelli, P. et al. Reproducibility in TMS–EEG studies: a call for data sharing, standard procedures and effective experimental control. Brain Stimul. 12, 787–790 (2019).

    PubMed  Google Scholar 

  249. Monti, M. M. et al. Willful modulation of brain activity in disorders of consciousness. N. Engl. J. Med. 362, 579–589 (2010).

    CAS  PubMed  Google Scholar 

  250. Stender, J. et al. Diagnostic precision of PET imaging and functional MRI in disorders of consciousness: a clinical validation study. Lancet 384, 514–522 (2014).

    PubMed  Google Scholar 

  251. Goldfine, A. M., Victor, J. D., Conte, M. M., Bardin, J. C. & Schiff, N. D. Determination of awareness in patients with severe brain injury using EEG power spectral analysis. Clin. Neurophysiol. 122, 2157–2168 (2011).

    PubMed  PubMed Central  Google Scholar 

  252. Monti, M. M., Pickard, J. D. & Owen, A. M. Visual cognition in disorders of consciousness: from V1 to top-down attention. Hum. Brain Mapp. 34, 1245–1253 (2013).

    PubMed  Google Scholar 

  253. Bardin, J. C. et al. Dissociations between behavioural and functional magnetic resonance imaging-based evaluations of cognitive function after brain injury. Brain 134, 769–782 (2011).

    PubMed  PubMed Central  Google Scholar 

  254. Naci, L. & Owen, A. M. Making every word count for nonresponsive patients. JAMA Neurol. 70, 1235–1241 (2013).

    PubMed  Google Scholar 

  255. Gibson, R. M. et al. Multiple tasks and neuroimaging modalities increase the likelihood of detecting covert awareness in patients with disorders of consciousness. Front. Hum. Neurosci. 8, 950 (2014).

    PubMed  PubMed Central  Google Scholar 

  256. Pisa, F. E., Biasutti, E., Drigo, D. & Barbone, F. The prevalence of vegetative and minimally conscious states: a systematic review and methodological appraisal. J. Head. Trauma. Rehabil. 29, E23–E30 (2014).

    PubMed  Google Scholar 

  257. van Erp, W. S. et al. The vegetative state/unresponsive wakefulness syndrome: a systematic review of prevalence studies. Eur. J. Neurol. 21, 1361–1368 (2014).

    PubMed  Google Scholar 

  258. Di Perri, C. 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, 830–842 (2016).

    PubMed  Google Scholar 

  259. Iotzov, I. et al. Divergent neural responses to narrative speech in disorders of consciousness. Ann. Clin. Transl Neurol. 4, 784–792 (2017).

    PubMed  PubMed Central  Google Scholar 

  260. Fridman, E. A. & Schiff, N. D. Neuromodulation of the conscious state following severe brain injuries. Curr. Opin. Neurobiol. 29, 172–177 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  261. Giacino, J. T. et al. Placebo-controlled trial of amantadine for severe traumatic brain injury. N. Engl. J. Med. 366, 819–826 (2012).

    CAS  PubMed  Google Scholar 

  262. Kim, Y. W., Shin, J. C. & An, Y. S. Effects of methylphenidate on cerebral glucose metabolism in patients with impaired consciousness after acquired brain injury. Clin. Neuropharmacol. 32, 335–339 (2009).

    CAS  PubMed  Google Scholar 

  263. Krimchansky, B. Z., Keren, O., Sazbon, L. & Groswasser, Z. Differential time and related appearance of signs, indicating improvement in the state of consciousness in vegetative state traumatic brain injury (VS-TBI) patients after initiation of dopamine treatment. Brain Inj. 18, 1099–1105 (2004).

    PubMed  Google Scholar 

  264. Passler, M. A. & Riggs, R. V. Positive outcomes in traumatic brain injury-vegetative state: patients treated with bromocriptine. Arch. Phys. Med. Rehabil. 82, 311–315 (2001).

    CAS  PubMed  Google Scholar 

  265. Fridman, E. A. et al. Continuous subcutaneous apomorphine for severe disorders of consciousness after traumatic brain injury. Brain Inj. 24, 636–641 (2010).

    PubMed  Google Scholar 

  266. Manganotti, P. et al. Effect of high-frequency repetitive transcranial magnetic stimulation on brain excitability in severely brain-injured patients in minimally conscious or vegetative state. Brain Stimul. 6, 913–921 (2013).

    PubMed  Google Scholar 

  267. Thibaut, A., Bruno, M. A., Ledoux, D., Demertzi, A. & Laureys, S. tDCS in patients with disorders of consciousness: sham-controlled randomized double-blind study. Neurology 82, 1112–1118 (2014).

    PubMed  Google Scholar 

  268. Corazzol, M. et al. Restoring consciousness with vagus nerve stimulation. Curr. Biol. 27, R994–R996 (2017).

    CAS  PubMed  Google Scholar 

  269. Pape, T. L. et al. Placebo-controlled trial of familiar auditory sensory training for acute severe traumatic brain injury: a preliminary report. Neurorehabil Neural Repair. 29, 537–547 (2015).

    PubMed  Google Scholar 

  270. Schnakers, C., Magee, W. L. & Harris, B. Sensory stimulation and music therapy programs for treating disorders of consciousness. Front. Psychol. 7, 297 (2016).

    PubMed  PubMed Central  Google Scholar 

  271. Whyte, J. et al. Zolpidem and restoration of consciousness. Am. J. Phys. Med. Rehabil. 93, 101–113 (2014).

    PubMed  Google Scholar 

  272. Schiff, N. D. et al. Behavioural improvements with thalamic stimulation after severe traumatic brain injury. Nature 448, 600–603 (2007).

    CAS  PubMed  Google Scholar 

  273. Provencio, J. J. et al. The Curing Coma Campaign: framing initial scientific challenges — proceedings of the first Curing Coma Campaign Scientific Advisory Council Meeting. Neurocrit Care 33, 1–12 (2020).

    PubMed  PubMed Central  Google Scholar 

  274. Jenkins, P. O. et al. Stratifying drug treatment of cognitive impairments after traumatic brain injury using neuroimaging. Brain 142, 2367–2379 (2019).

    PubMed  Google Scholar 

  275. Fridman, E. A., Osborne, J. R., Mozley, P. D., Victor, J. D. & Schiff, N. D. Presynaptic dopamine deficit in minimally conscious state patients following traumatic brain injury. Brain 142, 1887–1893 (2019).

    PubMed  PubMed Central  Google Scholar 

  276. Simon, D. W. et al. The far-reaching scope of neuroinflammation after traumatic brain injury. Nat. Rev. Neurol. 13, 171–191 (2017).

    PubMed  PubMed Central  Google Scholar 

  277. Shlosberg, D., Benifla, M., Kaufer, D. & Friedman, A. Blood–brain barrier breakdown as a therapeutic target in traumatic brain injury. Nat. Rev. Neurol. 6, 393–403 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  278. Johnson, V. E. et al. Inflammation and white matter degeneration persist for years after a single traumatic brain injury. Brain 136, 28–42 (2013).

    PubMed  PubMed Central  Google Scholar 

  279. Scott, G. et al. Minocycline reduces chronic microglial activation after brain trauma but increases neurodegeneration. Brain 141, 459–471 (2018).

    PubMed  Google Scholar 

  280. Edlow, B. L. et al. Multimodal characterization of the late effects of traumatic brain injury: a methodological overview of the Late Effects of Traumatic Brain Injury project. J. Neurotrauma 35, 1604–1619 (2018).

    PubMed  PubMed Central  Google Scholar 

  281. Walker, W. C. et al. The Chronic Effects of Neurotrauma Consortium (CENC) multi-centre observational study: description of study and characteristics of early participants. Brain Inj. 30, 1469–1480 (2016).

    CAS  PubMed  Google Scholar 

  282. Mez, J. et al. Assessing clinicopathological correlation in chronic traumatic encephalopathy: rationale and methods for the UNITE study. Alzheimers Res. Ther. 7, 62 (2015).

    PubMed  PubMed Central  Google Scholar 

  283. Smith, D. H., Johnson, V. E., Trojanowski, J. Q. & Stewart, W. Chronic traumatic encephalopathy — confusion and controversies. Nat. Rev. Neurol. 15, 179–183 (2019).

    PubMed  PubMed Central  Google Scholar 

  284. Schiff, N. D. et al. in Fifth Annual Brain Initiative Investigators Meeting Abstract book [abstract S-124]. 250 (National Institute of Mental Health, 2019).

  285. Kotchoubey, B. & Pavlov, Y. G. A systematic review and meta-analysis of the relationship between brain data and the outcome in disorders of consciousness. Front. Neurol. 9, 315 (2018).

    PubMed  PubMed Central  Google Scholar 

  286. Edlow, B. L. & Fins, J. J. Assessment of covert consciousness in the intensive care unit: clinical and ethical considerations. J. Head. Trauma. Rehabil. 33, 424–434 (2018).

    PubMed  PubMed Central  Google Scholar 

  287. Fins, J. J. & Bernat, J. L. Ethical, palliative, and policy considerations in disorders of consciousness. Neurology 91, 471–475 (2018).

    PubMed  Google Scholar 

  288. Cincotta, M. et al. No effects of 20 Hz-rTMS of the primary motor cortex in vegetative state: a randomised, sham-controlled study. Cortex 71, 368–376 (2015).

    PubMed  Google Scholar 

  289. Parvizi, J. & Damasio, A. Consciousness and the brainstem. Cognition 79, 135–160 (2001).

    CAS  PubMed  Google Scholar 

  290. Baker, J. L. et al. Robust modulation of arousal regulation, performance, and frontostriatal activity through central thalamic deep brain stimulation in healthy nonhuman primates. J. Neurophysiol. 116, 2383–2404 (2016).

    PubMed  PubMed Central  Google Scholar 

  291. Liu, J. et al. Frequency-selective control of cortical and subcortical networks by central thalamus. eLife 4, e09215 (2015).

    PubMed  PubMed Central  Google Scholar 

  292. Bernander, O., Douglas, R. J., Martin, K. A. & Koch, C. Synaptic background activity influences spatiotemporal integration in single pyramidal cells. Proc. Natl Acad. Sci. USA 88, 11569–11573 (1991).

    CAS  PubMed  Google Scholar 

  293. Thibaut, A., Schiff, N., Giacino, J., Laureys, S. & Gosseries, O. Therapeutic interventions in patients with prolonged disorders of consciousness. Lancet Neurol. 18, 600–614 (2019).

    PubMed  Google Scholar 

  294. Edlow, B. L. et al. 7 Tesla MRI of the ex vivo human brain at 100 micron resolution. Sci. Data 6, 244 (2019).

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors’ work is supported by the National Institutes of Health (NIH) National Institute of Neurological Disorders and Stroke (R01NS102574, R01NS106014, R03NS112760, R21NS109627, RF1NS115268, UH3NS95554), NIH Director’s Office (DP2HD101400), James S. McDonnell Foundation, DANA Foundation, Jerold B. Katz and Lenny Katz Foundations, Rappaport Foundation and Tiny Blue Dot Foundation. The authors thank S.B. Snider for assistance with the creation of Fig. 3.

Author information

Authors and Affiliations

  1. Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA

    Brian L. Edlow

  2. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA

    Brian L. Edlow

  3. Department of Neurology, Columbia University Medical Center, New York Presbyterian Hospital, New York, NY, USA

    Jan Claassen

  4. Feil Family Brain Mind Research Institute, Weill Cornell Medical College, New York, NY, USA

    Nicholas D. Schiff

  5. Department of Neurology, Boston University School of Medicine, Boston, MA, USA

    David M. Greer

Authors
  1. Brian L. Edlow
    View author publications

    Search author on:PubMed Google Scholar

  2. Jan Claassen
    View author publications

    Search author on:PubMed Google Scholar

  3. Nicholas D. Schiff
    View author publications

    Search author on:PubMed Google Scholar

  4. David M. Greer
    View author publications

    Search author on:PubMed Google Scholar

Contributions

The authors contributed equally to all aspects of the manuscript.

Corresponding author

Correspondence to David M. Greer.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information

Nature Reviews Neurology thanks R. Geocardin, J. Pickard, M. Oddo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note

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

Review criteria

We selected articles for this Review from a MEDLINE search and from our personal reference libraries. The MEDLINE search included the following terms: ‘disorders of consciousness’, ‘coma’, ‘vegetative state’, ‘unresponsive wakefulness syndrome’, ‘minimally conscious state’, ‘confusional state’, ‘cognitive motor dissociation’, ‘covert consciousness’, ‘neurologic examination’, ‘prognosis’, ‘functional MRI’, ‘diffusion tensor imaging’, ‘EEG’, ‘evoked potentials’, ‘P300’ and ‘mismatch negativity’. The search was from 2006 to 2020 and was exclusive to English language publications. Full-text papers were used for further leads.

Glossary

Disfacilitation

The downregulation of neuronal firing rates due to deafferentation and/or functional withdrawal of excitatory neurotransmission.

Reafferentation

The re-establishment of afferent neuronal inputs, such as occurs during the process of neuronal plasticity that contributes to recovery of consciousness after a severe brain injury.

Deafferentation

The disruption or disconnection of afferent neuronal inputs, such as when cortical neurons lose their neuronal inputs in the setting of thalamic injury.

Dynamic range

In neocortical neurons, the nominal span of the absolute firing rate, specific patterns of firing and the differential ability of individual neurons to integrate synaptic information, all of which vary as a function of membrane potential that is, in turn, controlled by background synaptic input.

EEG complexity

The complexity of the electrophysiological signal recorded by EEG reflects the integrity of cortico-cortical and thalamocortical networks that support human consciousness.

EEG spectrogram

A visual representation of the time-varying EEG power at each frequency plotted in two dimensions as frequency (y axis) over time (x axis).

Motor imagery

In a motor imagery task, a patient is instructed to imagine performing a motor task, such as “imagine opening and closing your hand”; evidence for volitional modulation of brain activity during this task is measured using functional MRI or EEG and contrasted with brain activity during a period of rest, when the patient is instructed to stop imagining the motor task.

Natural speech envelope

An EEG measurement that is based upon the amplitude and latency of cortical responses to spoken language; a normal cortical response to language does not prove the presence of consciousness but indicates the preservation of thalamocortical circuits and association regions of the cerebral cortex.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Edlow, B.L., Claassen, J., Schiff, N.D. et al. Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies. Nat Rev Neurol 17, 135–156 (2021). https://doi.org/10.1038/s41582-020-00428-x

Download citation

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41582-020-00428-x

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing