The neuronal connectivity patterns that differentiate consciousness from unconsciousness remain unclear. Previous studies have demonstrated that effective connectivity, as assessed by transcranial ...magnetic stimulation combined with electroencephalography (TMS-EEG), breaks down during the loss of consciousness. This study investigated changes in EEG connectivity associated with consciousness during non-rapid eye movement (NREM) sleep following parietal TMS. Compared with unconsciousness, conscious experiences during NREM sleep were associated with reduced phase-locking at low frequencies (<4 Hz). Transitivity and clustering coefficient in the delta and theta bands were also significantly lower during consciousness compared to unconsciousness, with differences in the clustering coefficient observed in scalp electrodes over parietal-occipital regions. There were no significant differences in Granger-causality patterns in frontal-to-parietal or parietal-to-frontal connectivity between reported unconsciousness and reported consciousness. Together these results suggest that alterations in spectral and spatial characteristics of network properties in posterior brain areas, in particular decreased local (segregated) connectivity at low frequencies, is a potential indicator of consciousness during sleep.
Summary Background Bedside clinical examinations can have high rates of misdiagnosis of unresponsive wakefulness syndrome (vegetative state) or minimally conscious state. The diagnostic and ...prognostic usefulness of neuroimaging-based approaches has not been established in a clinical setting. We did a validation study of two neuroimaging-based diagnostic methods: PET imaging and functional MRI (fMRI). Methods For this clinical validation study, we included patients referred to the University Hospital of Liège, Belgium, between January, 2008, and June, 2012, who were diagnosed by our unit with unresponsive wakefulness syndrome, locked-in syndrome, or minimally conscious state with traumatic or non-traumatic causes. We did repeated standardised clinical assessments with the Coma Recovery Scale–Revised (CRS–R), cerebral18 F-fluorodeoxyglucose (FDG) PET, and fMRI during mental activation tasks. We calculated the diagnostic accuracy of both imaging methods with CRS–R diagnosis as reference. We assessed outcome after 12 months with the Glasgow Outcome Scale–Extended. Findings We included 41 patients with unresponsive wakefulness syndrome, four with locked-in syndrome, and 81 in a minimally conscious state (48=traumatic, 78=non-traumatic; 110=chronic, 16=subacute).18 F-FDG PET had high sensitivity for identification of patients in a minimally conscious state (93%, 95% CI 85–98) and high congruence (85%, 77–90) with behavioural CRS–R scores. The active fMRI method was less sensitive at diagnosis of a minimally conscious state (45%, 30–61) and had lower overall congruence with behavioural scores (63%, 51–73) than PET imaging.18 F-FDG PET correctly predicted outcome in 75 of 102 patients (74%, 64–81), and fMRI in 36 of 65 patients (56%, 43–67). 13 of 41 (32%) of the behaviourally unresponsive patients (ie, diagnosed as unresponsive with CRS–R) showed brain activity compatible with (minimal) consciousness (ie, activity associated with consciousness, but diminished compared with fully conscious individuals) on at least one neuroimaging test; 69% of these (9 of 13) patients subsequently recovered consciousness. Interpretation Cerebral18 F-FDG PET could be used to complement bedside examinations and predict long-term recovery of patients with unresponsive wakefulness syndrome. Active fMRI might also be useful for differential diagnosis, but seems to be less accurate. Funding The Belgian National Funds for Scientific Research (FNRS), Fonds Léon Fredericq, the European Commission, the James McDonnell Foundation, the Mind Science Foundation, the French Speaking Community Concerted Research Action, the University of Copenhagen, and the University of Liège.
Transcranial magnetic stimulation (TMS) of human occipital and posterior parietal cortex can give rise to visual sensations called phosphenes. We used near-threshold TMS with concurrent EEG ...recordings to measure how oscillatory brain dynamics covary, on single trials, with the perception of phosphenes after occipital and parietal TMS. Prestimulus power and phase, predominantly in the alpha band (8-13 Hz), predicted occipital TMS phosphenes, whereas higher-frequency beta-band (13-20 Hz) power (but not phase) predicted parietal TMS phosphenes. TMS-evoked responses related to phosphene perception were similar across stimulation sites and were characterized by an early (200 ms) posterior negativity and a later (>300 ms) parietal positivity in the time domain and an increase in low-frequency (∼5-7 Hz) power followed by a broadband decrease in alpha/beta power in the time-frequency domain. These correlates of phosphene perception closely resemble known electrophysiological correlates of conscious perception of near-threshold visual stimuli. The regionally differential pattern of prestimulus predictors of phosphene perception suggests that distinct frequencies may reflect cortical excitability in occipital versus posterior parietal cortex, calling into question the broader assumption that the alpha rhythm may serve as a general index of cortical excitability.
Alpha-band oscillations are thought to reflect cortical excitability and are therefore ascribed an important role in gating information transmission across cortex. We probed cortical excitability directly in human occipital and parietal cortex and observed that, whereas alpha-band dynamics indeed reflect excitability of occipital areas, beta-band activity was most predictive of parietal cortex excitability. Differences in the state of cortical excitability predicted perceptual outcomes (phosphenes), which were manifest in both early and late patterns of evoked activity, revealing the time course of phosphene perception. Our findings prompt revision of the notion that alpha activity reflects excitability across all of cortex and suggest instead that excitability in different regions is reflected in distinct frequency bands.
Consciousness can be defined by two components: arousal (wakefulness) and awareness (subjective experience). However, neurophysiological consciousness metrics able to disentangle between these ...components have not been reported. Here, we propose an explainable consciousness indicator (ECI) using deep learning to disentangle the components of consciousness. We employ electroencephalographic (EEG) responses to transcranial magnetic stimulation under various conditions, including sleep (n = 6), general anesthesia (n = 16), and severe brain injury (n = 34). We also test our framework using resting-state EEG under general anesthesia (n = 15) and severe brain injury (n = 34). ECI simultaneously quantifies arousal and awareness under physiological, pharmacological, and pathological conditions. Particularly, ketamine-induced anesthesia and rapid eye movement sleep with low arousal and high awareness are clearly distinguished from other states. In addition, parietal regions appear most relevant for quantifying arousal and awareness. This indicator provides insights into the neural correlates of altered states of consciousness.
Significant advances have been made in the behavioral assessment and clinical management of disorders of consciousness (DOC). In addition, functional neuroimaging paradigms are now available to help ...assess consciousness levels in this challenging patient population. The success of these neuroimaging approaches as diagnostic markers is, however, intrinsically linked to understanding the relationships between consciousness and the brain. In this context, a combined theoretical approach to neuroimaging studies is needed. The promise of such theoretically based markers is illustrated by recent findings that used a perturbational approach to assess the levels of consciousness. Further research on the contents of consciousness in DOC is also needed.
Despite the absence of responsiveness during anesthesia, conscious experience may persist. However, reliable, easily acquirable and interpretable neurophysiological markers of the presence of ...consciousness in unresponsive states are still missing. A promising marker is based on the decay-rate of the power spectral density (PSD) of the resting EEG.
We acquired resting electroencephalogram (EEG) in three groups of healthy participants (n = 5 each), before and during anesthesia induced by either xenon, propofol or ketamine. Dosage of each anesthetic agent was tailored to yield unresponsiveness (Ramsay score = 6). Delayed subjective reports assessed whether conscious experience was present (‘Conscious report’) or absent/inaccessible to recall (‘No Report’). We estimated the decay of the PSD of the resting EEG—after removing oscillatory peaks—via the spectral exponent β, for a broad band (1–40 Hz) and narrower sub-bands (1–20 Hz, 20–40 Hz). Within-subject anesthetic changes in β were assessed. Furthermore, based on β, ‘Conscious report’ states were discriminated against ‘no report’ states. Finally, we evaluated the correlation of the resting spectral exponent with a recently proposed index of consciousness, the Perturbational Complexity Index (PCI), derived from a previous TMS-EEG study.
The spectral exponent of the resting EEG discriminated states in which consciousness was present (wakefulness, ketamine) from states where consciousness was reduced or abolished (xenon, propofol). Loss of consciousness substantially decreased the (negative) broad-band spectral exponent in each subject undergoing xenon or propofol anesthesia—indexing an overall steeper PSD decay. Conversely, ketamine displayed an overall PSD decay similar to that of wakefulness—consistent with the preservation of consciousness—yet it showed a flattening of the decay in the high-frequencies (20–40 Hz)—consistent with its specific mechanism of action. The spectral exponent was highly correlated to PCI, corroborating its interpretation as a marker of the presence of consciousness. A steeper PSD of the resting EEG reliably indexed unconsciousness in anesthesia, beyond sheer unresponsiveness.
•Unconsciousness does not imply unresponsiveness.•Consciousness is abolished during xenon and propofol, yet preserved during ketamine.•EEG Spectral exponent indexes the 1/f-like decay of non-oscillatory PSD background.•Xenon and propofol steepen broad-band decay; ketamine flattens high-frequency decay.•Spectral exponent separates un/consciousness in anesthesia-induced unresponsiveness.
One challenging aspect of the clinical assessment of brain-injured, unresponsive patients is the lack of an objective measure of consciousness that is independent of the subject's ability to interact ...with the external environment. Theoretical considerations suggest that consciousness depends on the brain's ability to support complex activity patterns that are, at once, distributed among interacting cortical areas (integrated) and differentiated in space and time (information-rich). We introduce and test a theory-driven index of the level of consciousness called the perturbational complexity index (PCI). PCI is calculated by (i) perturbing the cortex with transcranial magnetic stimulation (TMS) to engage distributed interactions in the brain (integration) and (ii) compressing the spatiotemporal pattern of these electrocortical responses to measure their algorithmic complexity (information). We test PCI on a large data set of TMS-evoked potentials recorded in healthy subjects during wakefulness, dreaming, nonrapid eye movement sleep, and different levels of sedation induced by anesthetic agents (midazolam, xenon, and propofol), as well as in patients who had emerged from coma (vegetative state, minimally conscious state, and locked-in syndrome). PCI reliably discriminated the level of consciousness in single individuals during wakefulness, sleep, and anesthesia, as well as in patients who had emerged from coma and recovered a minimal level of consciousness. PCI can potentially be used for objective determination of the level of consciousness at the bedside.
A common endpoint of general anesthetics is behavioral unresponsiveness 1, which is commonly associated with loss of consciousness. However, subjects can become disconnected from the environment ...while still having conscious experiences, as demonstrated by sleep states associated with dreaming 2. Among anesthetics, ketamine is remarkable 3 in that it induces profound unresponsiveness, but subjects often report “ketamine dreams” upon emergence from anesthesia 4–9. Here, we aimed at assessing consciousness during anesthesia with propofol, xenon, and ketamine, independent of behavioral responsiveness. To do so, in 18 healthy volunteers, we measured the complexity of the cortical response to transcranial magnetic stimulation (TMS)—an approach that has proven helpful in assessing objectively the level of consciousness irrespective of sensory processing and motor responses 10. In addition, upon emergence from anesthesia, we collected reports about conscious experiences during unresponsiveness. Both frontal and parietal TMS elicited a low-amplitude electroencephalographic (EEG) slow wave corresponding to a local pattern of cortical activation with low complexity during propofol anesthesia, a high-amplitude EEG slow wave corresponding to a global, stereotypical pattern of cortical activation with low complexity during xenon anesthesia, and a wakefulness-like, complex spatiotemporal activation pattern during ketamine anesthesia. Crucially, participants reported no conscious experience after emergence from propofol and xenon anesthesia, whereas after ketamine they reported long, vivid dreams unrelated to the external environment. These results are relevant because they suggest that brain complexity may be sensitive to the presence of disconnected consciousness in subjects who are considered unconscious based on behavioral responses.
•The perturbational complexity index (PCI) in propofol and xenon anesthesia is low•Both these anesthetics are associated with the lack of post-anesthesia reports•Ketamine is associated with high PCI and by vivid post-anesthesia dream reports•PCI may index the presence of disconnected consciousness during unresponsiveness
Sarasso, Boly, et al. show that the complexity of the cortical response to TMS is low during propofol and xenon anesthesia but high during ketamine. Crucially, no reports are obtained upon awakening from both propofol and xenon while after ketamine, all subjects report long, vivid dreams, possibly indicating a state of disconnected consciousness.
Objective
Validating objective, brain‐based indices of consciousness in behaviorally unresponsive patients represents a challenge due to the impossibility of obtaining independent evidence through ...subjective reports. Here we address this problem by first validating a promising metric of consciousness—the Perturbational Complexity Index (PCI)—in a benchmark population who could confirm the presence or absence of consciousness through subjective reports, and then applying the same index to patients with disorders of consciousness (DOCs).
Methods
The benchmark population encompassed 150 healthy controls and communicative brain‐injured subjects in various states of conscious wakefulness, disconnected consciousness, and unconsciousness. Receiver operating characteristic curve analysis was performed to define an optimal cutoff for discriminating between the conscious and unconscious conditions. This cutoff was then applied to a cohort of noncommunicative DOC patients (38 in a minimally conscious state MCS and 43 in a vegetative state VS).
Results
We found an empirical cutoff that discriminated with 100% sensitivity and specificity between the conscious and the unconscious conditions in the benchmark population. This cutoff resulted in a sensitivity of 94.7% in detecting MCS and allowed the identification of a number of unresponsive VS patients (9 of 43) with high values of PCI, overlapping with the distribution of the benchmark conscious condition.
Interpretation
Given its high sensitivity and specificity in the benchmark and MCS population, PCI offers a reliable, independently validated stratification of unresponsive patients that has important physiopathological and therapeutic implications. In particular, the high‐PCI subgroup of VS patients may retain a capacity for consciousness that is not expressed in behavior. Ann Neurol 2016;80:718–729
Abstract
Background: Spasticity following a stroke occurs in about 30% of patients. The mechanisms underlying this disorder, however, are not well understood.
Method: This review aims to define ...spasticity, describe hypotheses explaining its development after a stroke, give an overview of related neuroimaging studies as well as a description of the most common scales used to quantify the degree of spasticity and finally explore which treatments are currently being used to treat this disorder.
Results: The lack of consensus is highlighted on the basis of spasticity and the associated absence of guidelines for treatment, use of drugs and rehabilitation programmes.
Conclusions: Future studies require controlled protocols to determine the efficiency of pharmacological and non-pharmacological treatments for spasticity. Neuroimaging may help predict the occurrence of spasticity and could provide insight into its neurological basis.
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