Minds and Machines

, Volume 28, Issue 1, pp 173–189 | Cite as

No-report Paradigmatic Ascription of the Minimally Conscious State: Neural Signals as a Communicative Means for Operational Diagnostic Criteria



The minimally conscious state (MCS) is usually ascribed when a patient with brain damage exhibits observable volitional behaviors that predict recovery of cognitive functions. Nevertheless, a patient with brain damage who lacks motor capacity might nonetheless be in MCS. For this reason, some clinicians use neural signals as a communicative means for MCS ascription. For instance, a vegetative state patient is diagnosed with MCS if activity in the motor area is observed when the instruction to imagine wiggling toes is given. The validity of using neural signals in ascribing MCS requires a special sort of inference. That is, no-report paradigmatic assessments must have inductively strong ways of inferring a purported informational content from the observed neural signal that grounds the fact that the patient has top-down cognitive control (or residual volition). Shannon’s mathematical theory of communication and Bayes’ theorem reveals the formal structure of neural communication. On the basis of relevant data from the neuroscience literature, I conclude that the formal structure combined with the data shows that neural signals can be used as a communicative means for operational diagnostic criteria for MCS ascription.


Minimally conscious state Mental motor action Neural signal Informational content Shannon information Bayes’ theorem Residual volition No-report paradigm 



I am indebted to Carrie Figdor for many fruitful discussions and her invaluable comments made on earlier drafts. I am also grateful to Gregory Landini, Richard Fumerton, as well as two anonymous reviewers of this journal for their well-placed suggestions on previous versions. Many thanks to Seung Wook Kim, David Redmond, and members of the University of Iowa Graduate Philosophical Society for helpful discussions.


  1. Andrews, K., et al. (1996). Misdiagnosis of the vegetative state: Retrospective study in a rehabilitation unit. The British Medical Journal, 313, 13–16.CrossRefGoogle Scholar
  2. Ansell, B. J. (1993). Slow-to-recover patients: Improvement to rehabilitation readiness. The Journal of Head Trauma Rehabilitation, 8(3), 88–98.CrossRefGoogle Scholar
  3. Ansell, B. J. (1995). Visual tracking behavior in low functioning head-injured adults. Archives of Physical Medicine and Rehabilitation, 76(8), 726–731.CrossRefGoogle Scholar
  4. Armstrong, D. M. (1980). The nature of mind and other essays. Ithaca, NY: Cornell University Press.Google Scholar
  5. Bargh, J. A., & Chartland, T. L. (1999). The unbearable automaticity of being. American Psychologist, 54(7), 467–479.CrossRefGoogle Scholar
  6. Cruse, D., et al. (2011). Bedside detection of awareness in the vegetative state: a cohort study. The Lancet, 378, 2088–2094.CrossRefGoogle Scholar
  7. Drayson, Z. (2014). Intentional action and the post-coma patient. Topoi, 33, 23–31.CrossRefGoogle Scholar
  8. Ehrsson, H. H., Geyer, S., & Naito, E. (2003). Imagery of voluntary movement of fingers, toes, and tongue activates corresponding body-part–specific motor representations. Journal of Neurophysiology, 90, 3304–3316.CrossRefGoogle Scholar
  9. Frith, C. D., Blakemore, D., & Wolpert, D. M. (2000). Abnormalities in the awareness and control of action. Philosophical Transactions of the Royal Society of London. Series B, 355, 1771–1788.CrossRefGoogle Scholar
  10. Giacino, J. T., & Kalmar, K. K. (1997). The vegetative and minimally conscious states: A comparison of clinical features and functional outcome. The Journal of Head Trauma Rehabilitation, 12(4), 36–51.CrossRefGoogle Scholar
  11. Giacino, J. T., Kalmar, K., & Whyte, J. (2004). The JFK coma recovery scale-revised: Measurement characteristics and diagnostic utility. Archives of Physical Medicine and Rehabilitation, 85(12), 2020–2029.CrossRefGoogle Scholar
  12. Giacino, J. T., et al. (2002). The minimally conscious state: Definition and diagnostic criteria. American Academy of Neurology, 58, 349–353.CrossRefGoogle Scholar
  13. Godfrey-Smith, P. (2012). Review of brian Skyrms’s signals. Mind, 120, 1288–1297.CrossRefGoogle Scholar
  14. Grafton, S. T., et al. (1991). Somatotopic mapping of the primary motor cortex in humans: Activation studies with cerebral blood flow and positron emission tomography. Journal of Neurophysiology, 66(3), 735–743.CrossRefGoogle Scholar
  15. Haibo, D., et al. (2008). Neuroimaging activation studies in the vegetative state: predictors of recovery? Clinical Medicine, 8(5), 502–507.CrossRefGoogle Scholar
  16. Harms, W. F. (2006). What is information? Three concepts. Biological Theory, 1(3), 230–242.CrossRefGoogle Scholar
  17. Hohwy, J. (2009). The neural correlates of consciousness: New experimental approaches needed? Consciousness and Cognition, 18, 428–438.CrossRefGoogle Scholar
  18. Isaac, A. M. C. (2010). The Informational Content of Perceptual Experience. Unpublished dissertation.Google Scholar
  19. Isaac, A. M. C. (forthcoming). The Semantic Latent in Shannon Information. The British Journal for the Philosophy of Science.Google Scholar
  20. Laureys, S., et al. (2000). Restoration of thalamocortical connectivity after recovery from persistent vegetative state. The Lancet, 335, 1790–1791.CrossRefGoogle Scholar
  21. Monti, M. M., Laureys, S., & Owen, A. M. (2010a). The vegetative state. The British Medical Journal, 341, 292–296.CrossRefGoogle Scholar
  22. Monti, M. M., et al. (2010b). Willful modulation of brain activity in disorders of consciousness. The New England Journal of Medicine, 362(7), 579–589.CrossRefGoogle Scholar
  23. Naci, L., Sinai, L., & Owen, A. M. (2015). Detecting and interpreting conscious experience in behaviorally non-responsive patients. NeuroImage. http://dx.doi.org/10/1016/j.neuroimage.2015.11.059.
  24. Naci, L., et al. (2014). A common neural code for similar conscious experiences in different individuals. PNAS, 111(39), 14277–14282.CrossRefGoogle Scholar
  25. Neuper, C., et al. (2005). Imagery of motor actions: Differential effects of kinesthetic and visual–motor mode of imagery in single-trial EEG. Cognitive Brain Research, 25, 668–677.CrossRefGoogle Scholar
  26. Overgaard, M. (2015). Behavioral Methods in Consciousness Research. Oxford: Oxford University Press.CrossRefGoogle Scholar
  27. Owen, A. M. (2013). Detecting consciousness: A unique role for neuroimaging. Annual Review of Psychology, 64, 109–133.CrossRefGoogle Scholar
  28. Owen, A. M., et al. (2006). Detecting awareness in the vegetative state. Science, 313, 1402.CrossRefGoogle Scholar
  29. Owen, A. M., et al. (2007). Response to comments on “detecting awareness in the vegetative state”. Science, 315(5816), 1221.CrossRefGoogle Scholar
  30. Pattamadilok, C., et al. (2017). Automaticity of phonological and semantic processing during visual word recognition. NeuroImage, 149, 244–255.CrossRefGoogle Scholar
  31. Pfurtscheller, G., & Neuper, C. (1997). Motor imagery activates primary sensorimotor area in humans. Neuroscience Letters, 239, 65–68.CrossRefGoogle Scholar
  32. Poldrack, R. A. (2006). Can cognitive processes be inferred from neuroimaging data? Trends in Cognitive Sciences, 10(2), 59–63.CrossRefGoogle Scholar
  33. Porro, C. A., et al. (1996). Primary motor and sensory cortex activation during motor performance and motor imagery: A functional magnetic resonance imaging study. The Journal of Neuroscience, 16(23), 7688–7698.Google Scholar
  34. Pulvermüller, F. (2005). Brain mechanisms linking language and action. Nature Reviews Neuroscience, 6, 576–582.CrossRefGoogle Scholar
  35. Raposo, A., et al. (2009). Modulation of motor and premotor cortices by actions, action words and action sentences. Neuropsycologia, 47, 388–396.CrossRefGoogle Scholar
  36. Schnakers, C., et al. (2009). Diagnostic accuracy of the vegetative and minimally conscious state: Clinical consensus versus standardized neurobehavioral assessment. BMC Neurology, 9, 35.CrossRefGoogle Scholar
  37. Shannon, C. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27(379–423), 623–656.MathSciNetCrossRefMATHGoogle Scholar
  38. Shea, N., & Bayne, T. (2010). The vegetative state and the science of consciousness. The British Journal for the Philosophy of Science, 61, 459–484.CrossRefGoogle Scholar
  39. Shea, N., Godfrey-Smith, P., & Cao, R. (2017). Content in Simple Signalling Systems. The British Journal for the Philosophy of Science, in press.Google Scholar
  40. Shewmon, D. A. (2004). THE ABC OF PVS: Problems of definition. In C. Machado & D. A. Shewmon (Eds.), Brain death and disorders of consciousness. New York: Kluwer Academic/Plenum Publishers.Google Scholar
  41. Skyrms, B. (2010). Signals: Evolution, learning, and information. Oxford: Oxford University Press.CrossRefGoogle Scholar
  42. Stender, J., et al. (2016). The minimal energetic requirement of sustained awareness after brain injury. Current Biology, 26, 1494–1499.CrossRefGoogle Scholar
  43. Stins, J. F. (2009). Establishing consciousness in non-communicative patients: A modern-day version of the Turing test. Consciousness and Cognition, 18, 187–192.CrossRefGoogle Scholar
  44. Tsuchiya, N., et al. (2015). No-report paradigms: Extracting the true neural correlates of consciousness. Trends in Cognitive Sciences, 19(12), 757–770.CrossRefGoogle Scholar
  45. Wegner, D. M., & Wheatley, T. (1999). Apparent mental causation: Sources of the experience of will. American Psychologist, 54(7), 480–492.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  1. 1.Department of PhilosophyThe University of IowaIowa CityUSA

Personalised recommendations