Olivia Gosseries

A Theoretically Based Index of Consciousness Independent of Sensory Processing and Behavior

A theory-derived index of consciousness, which quantifies the complexity of the brain’s response to a stimulus, measures the level of consciousness in awake, sleeping, anesthetized, and brain-damaged subjects. Quantifying the Unquantifiable Manipulation of consciousness is an everyday medical trick—think anesthesia—but physicians have only the crudest of tools to detect when a person is not aware. The usual question or physical stimulus does not always provide reliable reactions, and a more precise index is needed to avoid, for example, the conclusion that people who have locked-in syndrome (in which they are aware but cannot respond) are unconscious. Here, Casali et al. have extended their previous work on electrical correlates of consciousness to define an electroencephalographic-derived index of human consciousness [the perturbational complexity index (PCI)] that reflects the information content of the brain’s response to a magnetic stimulus. The PCI could allow tracking of consciousness in individual patients. The authors used data already collected from previous experiments, in which they had stimulated people’s brains with transcranial magnetic stimulation. By calculating the likely brain regional sources of the signals and then comparing the unique information in each, the authors derived PCI values. The values ranged from 0.44 to 0.67 in 32 awake healthy people, but fell to 0.18 to 0.28 during nonrapid eye movement (NREM) sleep. Then, to see whether a completely different way of inducing unconsciousness had the same effect on PCI, the authors assessed data from patients given various amounts of the anesthetics midazolam, xenon, and propofol. These agents too caused low “unconscious” values for the PCI: midazolam deep sedation, 0.23 to 0.31; propofol, 0.13 to 0.30; and xenon, 0.12 to 0.31. However, what about patients who suffer brain damage and who exhibit various levels of consciousness by conventional assessment methods? In these people, consciousness varies widely, as does the underlying damage from stroke or trauma. Here, too, the authors found promising results in those who had emerged from coma but were in a vegetative state or minimally conscious state, or exhibited locked-in syndrome. The PCI values from these patients clearly reflected the state of their consciousness, with the six patients in a vegetative state clearly unconscious (0.19 to 0.31), the two with locked-in syndrome clearly aware (0.51 to 0.62), and those in a minimally conscious state showing intermediate values (0.32 to 0.49). The validity of PCI for clinical application will need to be assessed in prospective trials, but it has the advantage of being derived from a simple noninvasive measurement. The new index reported by Casali et al. appears to be a robust measure that distinguishes conscious from unconscious states well enough to be used on an individual basis, a prerequisite for deployment in the clinic. 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.

Preserved Feedforward But Impaired Top-Down Processes in the Vegetative State

Discerning the neural correlates of (un)consciousness sheds light on the mechanisms underlying vegetative states. Frontoparietal cortex is involved in the explicit processing (awareness) of stimuli. Frontoparietal activation has also been found in studies of subliminal stimulus processing. We hypothesized that an impairment of top-down processes, involved in recurrent neuronal message-passing and the generation of long-latency electrophysiological responses, might provide a more reliable correlate of consciousness in severely brain-damaged patients, than frontoparietal responses. We measured effective connectivity during a mismatch negativity paradigm and found that the only significant difference between patients in a vegetative state and controls was an impairment of backward connectivity from frontal to temporal cortices. This result emphasizes the importance of top-down projections in recurrent processing that involve high-order associative cortices for conscious perception.

Recovery of cortical effective connectivity and recovery of consciousness in vegetative patients.

Patients surviving severe brain injury may regain consciousness without recovering their ability to understand, move and communicate. Recently, electrophysiological and neuroimaging approaches, employing simple sensory stimulations or verbal commands, have proven useful in detecting higher order processing and, in some cases, in establishing some degree of communication in brain-injured subjects with severe impairment of motor function. To complement these approaches, it would be useful to develop methods to detect recovery of consciousness in ways that do not depend on the integrity of sensory pathways or on the subjects ability to comprehend or carry out instructions. As suggested by theoretical and experimental work, a key requirement for consciousness is that multiple, specialized cortical areas can engage in rapid causal interactions (effective connectivity). Here, we employ transcranial magnetic stimulation together with high-density electroencephalography to evaluate effective connectivity at the bedside of severely brain injured, non-communicating subjects. In patients in a vegetative state, who were open-eyed, behaviourally awake but unresponsive, transcranial magnetic stimulation triggered a simple, local response indicating a breakdown of effective connectivity, similar to the one previously observed in unconscious sleeping or anaesthetized subjects. In contrast, in minimally conscious patients, who showed fluctuating signs of non-reflexive behaviour, transcranial magnetic stimulation invariably triggered complex activations that sequentially involved distant cortical areas ipsi- and contralateral to the site of stimulation, similar to activations we recorded in locked-in, conscious patients. Longitudinal measurements performed in patients who gradually recovered consciousness revealed that this clear-cut change in effective connectivity could occur at an early stage, before reliable communication was established with the subject and before the spontaneous electroencephalogram showed significant modifications. Measurements of effective connectivity by means of transcranial magnetic stimulation combined with electroencephalography can be performed at the bedside while by-passing subcortical afferent and efferent pathways, and without requiring active participation of subjects or language comprehension; hence, they offer an effective way to detect and track recovery of consciousness in brain-injured patients who are unable to exchange information with the external environment.

Diagnostic precision of PET imaging and functional MRI in disorders of consciousness: a clinical validation study

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), cerebral (18)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 Cerebral (18)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.

Spasticity after stroke: physiology, assessment and treatment.

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.

METABOLIC ACTIVITY IN EXTERNAL AND INTERNAL AWARENESS NETWORKS IN SEVERELY BRAIN-DAMAGED PATIENTS

OBJECTIVE An extrinsic cerebral network (encompassing lateral frontoparietal cortices) related to external/sensory awareness and an intrinsic midline network related to internal/self-awareness have been identified recently. This study measured brain metabolism in both networks in patients with severe brain damage. DESIGN Prospective [18F]-fluorodeoxyglucose-positron emission tomography and Coma Recovery Scale-Revised assessments in a university hospital setting. SUBJECTS Healthy volunteers and patients in vegetative state/unresponsive wakefulness syndrome (VS/UWS), minimally conscious state (MCS), emergence from MCS (EMCS), and locked-in syndrome (LIS). RESULTS A total of 70 patients were included in the study: 24 VS/UWS, 28 MCS, 10 EMCS, 8 LIS and 39 age-matched controls. VS/UWS showed metabolic dysfunction in extrinsic and intrinsic networks and thalami. MCS showed dysfunction mostly in intrinsic network and thalami. EMCS showed impairment in posterior cingulate/retrosplenial cortices. LIS showed dysfunction only in infratentorial regions. Coma Recovery Scale-Revised total scores correlated with metabolic activity in both extrinsic and part of the intrinsic network and thalami. CONCLUSION Progressive recovery of extrinsic and intrinsic awareness network activity was observed in severely brain-damaged patients, ranging from VS/UWS, MCS, EMCS to LIS. The predominance of intrinsic network impairment in MCS could reflect altered internal/self-awareness in these patients, which is difficult to quantify at the bedside.

Electrophysiological correlates of behavioural changes in vigilance in vegetative state and minimally conscious state

The existence of normal sleep in patients in a vegetative state is still a matter of debate. Previous electrophysiological sleep studies in patients with disorders of consciousness did not differentiate patients in a vegetative state from patients in a minimally conscious state. Using high-density electroencephalographic sleep recordings, 11 patients with disorders of consciousness (six in a minimally conscious state, five in a vegetative state) were studied to correlate the electrophysiological changes associated with sleep to behavioural changes in vigilance (sustained eye closure and muscle inactivity). All minimally conscious patients showed clear electroencephalographic changes associated with decreases in behavioural vigilance. In the five minimally conscious patients showing sustained behavioural sleep periods, we identified several electrophysiological characteristics typical of normal sleep. In particular, all minimally conscious patients showed an alternating non-rapid eye movement/rapid eye movement sleep pattern and a homoeostatic decline of electroencephalographic slow wave activity through the night. In contrast, for most patients in a vegetative state, while preserved behavioural sleep was observed, the electroencephalographic patterns remained virtually unchanged during periods with the eyes closed compared to periods of behavioural wakefulness (eyes open and muscle activity). No slow wave sleep or rapid eye movement sleep stages could be identified and no homoeostatic regulation of sleep-related slow wave activity was observed over the night-time period. In conclusion, we observed behavioural, but no electrophysiological, sleep wake patterns in patients in a vegetative state, while there were near-to-normal patterns of sleep in patients in a minimally conscious state. These results shed light on the relationship between sleep electrophysiology and the level of consciousness in severely brain-damaged patients. We suggest that the study of sleep and homoeostatic regulation of slow wave activity may provide a complementary tool for the assessment of brain function in minimally conscious state and vegetative state patients.

Dynamic Change of Global and Local Information Processing in Propofol-Induced Loss and Recovery of Consciousness

Whether unique to humans or not, consciousness is a central aspect of our experience of the world. The neural fingerprint of this experience, however, remains one of the least understood aspects of the human brain. In this paper we employ graph-theoretic measures and support vector machine classification to assess, in 12 healthy volunteers, the dynamic reconfiguration of functional connectivity during wakefulness, propofol-induced sedation and loss of consciousness, and the recovery of wakefulness. Our main findings, based on resting-state fMRI, are three-fold. First, we find that propofol-induced anesthesia does not bear differently on long-range versus short-range connections. Second, our multi-stage design dissociated an initial phase of thalamo-cortical and cortico-cortical hyperconnectivity, present during sedation, from a phase of cortico-cortical hypoconnectivity, apparent during loss of consciousness. Finally, we show that while clustering is increased during loss of consciousness, as recently suggested, it also remains significantly elevated during wakefulness recovery. Conversely, the characteristic path length of brain networks (i.e., the average functional distance between any two regions of the brain) appears significantly increased only during loss of consciousness, marking a decrease of global information-processing efficiency uniquely associated with unconsciousness. These findings suggest that propofol-induced loss of consciousness is mainly tied to cortico-cortical and not thalamo-cortical mechanisms, and that decreased efficiency of information flow is the main feature differentiating the conscious from the unconscious brain.

Thalamus, Brainstem and Salience Network Connectivity Changes During Propofol-Induced Sedation and Unconsciousness

In this functional magnetic resonance imaging study, we examined the effect of mild propofol sedation and propofol-induced unconsciousness on resting state brain connectivity, using graph analysis based on independent component analysis and a classical seed-based analysis. Contrary to previous propofol research, which mainly emphasized the importance of connectivity in the default mode network (DMN) and external control network (ECN), we focused on the salience network, thalamus, and brainstem. The importance of these brain regions in brain arousal and organization merits a more detailed examination of their connectivity response to propofol. We found that the salience network disintegrated during propofol-induced unconsciousness. The thalamus decreased connectivity with the DMN, ECN, and salience network, while increasing connectivity with sensorimotor and auditory/insular cortices. Brainstem regions disconnected from the DMN with unconsciousness, while the pontine tegmental area increased connectivity with the insulae during mild sedation. These findings illustrate that loss of consciousness is associated with a wide variety of decreases and increases of both cortical and subcortical connectivity. It furthermore stresses the necessity of also examining resting state connectivity in networks representing arousal, not only those associated with awareness.

Measuring Consciousness in Severely Damaged Brains

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.