Cruse, Damian, Chennu, Srivas, Fernández-Espejo, Davinia, Payne, William L., Young, G. Bryan, Owen, Adrian M. (2012) Detecting Awareness in the Vegetative State: Electroencephalographic Evidence for Attempted Movements to Command. PLoS ONE, 7 (11). e49933. ISSN 1932-6203. E-ISSN 1932-6203. (doi:10.1371/journal.pone.0049933) (KAR id:54643)
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Official URL: http://dx.doi.org/10.1371%2Fjournal.pone.0049933 |
Abstract
Patients in the Vegetative State (VS) do not produce overt motor behavior to command and are therefore considered to be unaware of themselves and of their environments. However, we recently showed that high-density electroencephalography (EEG) can be used to detect covert command-following in some VS patients. Due to its portability and inexpensiveness, EEG assessments of awareness have the potential to contribute to a standard clinical protocol, thus improving diagnostic accuracy. However, this technique requires refinement and optimization if it is to be used widely as a clinical tool. We asked a patient who had been repeatedly diagnosed as VS for 12-years to try to move his left and right hands, between periods of rest, while EEG was recorded from four scalp electrodes. We identified appropriate and statistically reliable modulations of sensorimotor beta rhythms following commands to try to move, which could be significantly classified at a single-trial level. These reliable effects indicate that the patient attempted to follow the commands, and was therefore aware, but was unable to execute an overtly discernable action. The cognitive demands of this novel task are lower than those used previously and, crucially, allow for awareness to be determined on the basis of a 20-minute EEG recording made with only four electrodes. This approach makes EEG assessments of awareness clinically viable, and therefore has potential for inclusion in a standard assessment of awareness in the VS.
Item Type: | Article |
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DOI/Identification number: | 10.1371/journal.pone.0049933 |
Subjects: | B Philosophy. Psychology. Religion > BF Psychology |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Srivas Chennu |
Date Deposited: | 13 Apr 2016 09:28 UTC |
Last Modified: | 05 Nov 2024 10:43 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/54643 (The current URI for this page, for reference purposes) |
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