Elsevier

Clinical Neurophysiology

Volume 131, Issue 11, November 2020, Pages 2736-2765
Clinical Neurophysiology

Clinical and advanced neurophysiology in the prognostic and diagnostic evaluation of disorders of consciousness: review of an IFCN-endorsed expert group

https://doi.org/10.1016/j.clinph.2020.07.015Get rights and content
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Highlights

  • We provide an overview of EEG-based techniques in the prognostic and diagnostic assessment of DoC.

  • We highlight bridging principles between conventional and investigational approaches.

  • We share expert opinions and considerations on the technical and conceptual caveats.

Abstract

The analysis of spontaneous EEG activity and evoked potentials is a cornerstone of the instrumental evaluation of patients with disorders of consciousness (DoC). The past few years have witnessed an unprecedented surge in EEG-related research applied to the prediction and detection of recovery of consciousness after severe brain injury, opening up the prospect that new concepts and tools may be available at the bedside. This paper provides a comprehensive, critical overview of both consolidated and investigational electrophysiological techniques for the prognostic and diagnostic assessment of DoC. We describe conventional clinical EEG approaches, then focus on evoked and event-related potentials, and finally we analyze the potential of novel research findings. In doing so, we (i) draw a distinction between acute, prolonged and chronic phases of DoC, (ii) attempt to relate both clinical and research findings to the underlying neuronal processes and (iii) discuss technical and conceptual caveats. The primary aim of this narrative review is to bridge the gap between standard and emerging electrophysiological measures for the detection and prediction of recovery of consciousness. The ultimate scope is to provide a reference and common ground for academic researchers active in the field of neurophysiology and clinicians engaged in intensive care unit and rehabilitation.

Keywords

disorders of consciousness
EEG
evoked potentials
event-related potentials
vegetative state
minimally conscious state
coma

Abbreviations

α
alpha
β
beta
δ
delta
γ
gamma
θ
theta
AAN
American Academy of Neurology
BCI
Brain-Computer Interface
CI
confidence intervals
CMD
cognitive motor dissociation
CPC
cerebral performance category
CRS-R
Coma-Recovery Scale-revised
cEEG
continuous electroencephalography
CSD
cortical spread depolarization
DoC
disorders of consciousness
EAN
European Academy of Neurology
EEG
electroencephalography
EMCS
emergence from minimally conscious state
EP
evoked potential
ERD
event-related desynchronization
ERP
event-related potential
ERSP
event-related spectral perturbation
GOS
Glasgow Outcome Scale
GOS-E
Glasgow Outcome Scale Extended
FDG-PET
fluorodeoxyglucose positron emission tomography
fMRI
functional magnetic resonance imaging
FPR
false positive rate
HIE
hypoxic-ischemic encephalopathy
HMD
higher-order cortex motor dissociation
ICU
intensive care unit
IIC
ictal-interictal continuum
K
Kolmogorov complexity
LIS
locked-in syndrome
LFP
local field potential
MCS
minimally conscious state
ML
machine learning
MMN
mismatch negativity
NCSz
non-convulsive seizures
NCSE
non-convulsive status epilepticus
NREM
non-rapid eye movement
OPJ
occipito-parietal junction
PCI
perturbational complexity index
PHG
parahippocampal gyrus
PLF
phase locking factor
PMC
premotor cortex
PPV
positive predictive value
PSD
power spectral density
qEEG
quantitative EEG
REM
rapid eye movement
SAH
subarachnoid hemorrhage
SEP
somatosensory evoked potential
SIRPIDs
stimulus-induced rhythmic, periodic, or ictal discharges
SMA
supplementary motor area
SPES
single pulse electrical stimulation
TEP
TMS-evoked potential
TBI
traumatic brain injury
TMS
transcranial magnetic stimulation
TMS/EEG
TMS combined with EEG
TTM
targeted temperature management
UWS
unresponsive wakefulness syndrome
VS
vegetative state
wSMI
weighted symbolic mutual information

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