Increasing evidence from studies of brain responses to subject's own name (SON) indicates that residual consciousness is preserved in patients with disorders of consciousness (DOC) and that specific network activation might provide evidence of consciousness. However, it remains unclear whether SON is suitable for detection of emotional consciousness; moreover, the particular aspects of brain network organization that are critical for consciousness are unknown. The present study used an innovative approach to explore affective consciousness in patients with DOC during emotional stimuli. EEG data were acquired from 15 patients and 15 healthy volunteers. We analyzed brain potentials and functional network connectivity with a passive emotional paradigm based on graph theoretical methods. Larger N1 or P3a was detected in patients upon exposure to emotional sound, relative to neutral stimuli. Brain topology revealed that emotional sound evoked significantly stronger network linkages in healthy controls; additionally, it evoked several connectivity changes in patients with DOC. In conclusion, emotional consciousness might be partially preserved in patients with DOC; moreover, EEG network patterns could provide new insights into the neural activity of emotional perception in these patients.

Consciousness is something we experience in our everyday life, more especially between the time we wake up in the morning and go to sleep at night, but also during the rapid eye movement (REM) sleep stage. Disorders of consciousness (DoC) are states in which a person's consciousness is damaged, possibly after a traumatic brain injury. Completely locked-in syndrome (CLIS) patients, on the other hand, display covert states of consciousness. Although they appear unconscious, their cognitive functions are mostly intact. Only, they cannot externally display it due to their quadriplegia and inability to speak. Determining these patients' states constitutes a challenging task. The ultimate goal of the approach presented in this paper is to assess these CLIS patients consciousness states. EEG data from DoC patients are used here first, under the assumption that if the proposed approach is able to accurately assess their consciousness states, it will assuredly do so on CLIS patients too. This method combines different sets of features consisting of spectral, complexity and connectivity measures in order to increase the probability of correctly estimating their consciousness levels. The obtained results showed that the proposed approach was able to correctly estimate several DoC patients' consciousness levels. This estimation is intended as a step prior attempting to communicate with them, in order to maximise the efficiency of brain-computer interfaces (BCI)-based communication systems.

The natural evolution of consciousness in different animal species mandates that conscious experiences are causally potent in order to confer any advantage in the struggle for survival. Any endeavor to construct a physical theory of consciousness based on emergence within the framework of classical physics, however, leads to causally impotent conscious experiences in direct contradiction to evolutionary theory since epiphenomenal consciousness cannot evolve through natural selection. Here, we review recent theoretical advances in describing sentience and free will as fundamental aspects of reality granted by quantum physical laws. Modern quantum information theory considers quantum states as a physical resource that endows quantum systems with the capacity to perform physical tasks that are classically impossible. Reductive identification of conscious experiences with the quantum information comprised in quantum brain states allows for causally potent consciousness that is capable of performing genuine choices for future courses of physical action. The consequent evolution of brain cortical networks contributes to increased computational power, memory capacity, and cognitive intelligence of the living organisms.

We assessed the relationship between consciousness level and values of cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and time to peak (TTP) obtained by whole-brain perfusion computed tomography (pCT) in patients with prolonged disorders of consciousness (pDOC).

Anesthetic manipulations provide much-needed causal evidence for neural correlates of consciousness, but non-specific drug effects complicate their interpretation. Evidence suggests that thalamic deep brain stimulation (DBS) can either increase or decrease consciousness, depending on the stimulation target and parameters. The putative role of the central lateral thalamus (CL) in consciousness makes it an ideal DBS target to manipulate circuit-level mechanisms in cortico-striato-thalamic (CST) systems, thereby influencing consciousness and related processes. We used multi-microelectrode DBS targeted to CL in macaques while recording from frontal, parietal, and striatal regions. DBS induced episodes of abnormally long, vacant staring with low-frequency oscillations here termed vacant, perturbed consciousness (VPC). DBS modulated VPC likelihood in a frequency-specific manner. VPC events corresponded to decreases in measures of neural complexity (entropy) and integration (Φ*), proposed indices of consciousness, and substantial changes to communication in CST circuits. During VPC, power spectral density and coherence at low frequencies increased across CST circuits, especially in thalamo-parietal and cortico-striatal pathways. Decreased consciousness and neural integration corresponded to shifts in cortico-striatal network configurations that dissociated parietal and subcortical structures. Overall, the features of VPC and implicated networks were similar to those of absence epilepsy. As this same multi-microelectrode DBS method-but at different stimulation frequencies-can also increase consciousness in anesthetized macaques, it can be used to flexibly address questions of consciousness with limited confounds, as well as inform clinical investigations of other consciousness disorders.

No abstract available

Background: Spasticity is a motor disorder frequently encountered after a lesion involving the central nervous system. It is hypothesized to arise from an anarchic reorganization of the pyramidal and parapyramidal fibers and leads to hypertonia and hyperreflexia of the affected muscular groups. While this symptom and its management is well-known in patients suffering from stroke, multiple sclerosis or spinal cord lesion, little is known regarding its appropriate management in patients presenting disorders of consciousness after brain damage. Objectives: Our aim was to review the occurrence of spasticity in patients with disorders of consciousness and the therapeutic interventions used to treat it. Methods: We conducted a systematic review using the PubMed online database. It returned 157 articles. After applying our inclusion criteria (i.e., studies about patients in coma, unresponsive wakefulness syndrome or minimally conscious state, with spasticity objectively reported as a primary or secondary outcome), 18 studies were fully reviewed. Results: The prevalence of spasticity in patients with disorders of consciousness ranged from 59% to 89%. Current treatment options include intrathecal baclofen and soft splints. Several treatment options still need further investigation; including acupuncture, botulin toxin or cortical activation by thalamic stimulation. Conclusion: The small number of articles available in the current literature highlights that spasticity is poorly studied in patients with disorders of consciousness although it is one of the most common motor disorders. While treatments such as intrathecal baclofen and soft splints seem effective, large randomized controlled trials have to be done and new therapeutic options should be explored.

This systematic review analysed the evidence for the effect of head-up tilt (passive-standing) on consciousness among persons in prolonged disorders of consciousness.

Our knowledge grows as we integrate events experienced at different points in time. We may or may not become aware of events, their integration, and their impact on our knowledge and decisions. But can we mentally integrate two events, if they are experienced at different time points and at different levels of consciousness? In this study, an event consisted of the presentation of two unrelated words. In the stream of events, half of events shared one component ("tree desk" … "desk fish") to facilitate event integration. We manipulated the amount of time and trials that separated two corresponding events. The contents of one event were presented subliminally (invisible) and the contents of the corresponding overlapping event supraliminally (visible). Hence, event integration required the binding of contents between consciousness levels and between time points. At the final test of integration, participants judged whether two supraliminal test words ("tree fish") fit together semantically or not. Unbeknown to participants, half of test words were episodically related through an overlap ("desk"; experimental condition) and half were not (control condition). Participants judged episodically related test words to be closer semantically than unrelated test words. This subjective decrease in the semantic distance between test words was both independent of whether the invisible event was encoded first or second in order and independent of the number of trials and the time that separated two corresponding events. Hence, conscious and unconscious memories were mentally integrated into a linked mnemonic representation.

Typical consciousness can be defined as an individual-specific stream of experiences. Modern consciousness research on dynamic functional connectivity uses clustering techniques to create common bases on which to compare different individuals. We propose an alternative approach by combining modern theories of consciousness and insights arising from phenomenology and dynamical systems theory. This approach enables a representation of an individual's connectivity dynamics in an intrinsically-defined, individual-specific landscape. Given the wealth of evidence relating functional connectivity to experiential states, we assume this landscape is a proxy measure of an individual's stream of consciousness. By investigating the properties of this landscape in individuals in different states of consciousness, we show that consciousness is associated with short term transitions that are less predictable, quicker, but, on average, more constant. We also show that temporally-specific connectivity states are less easily describable by network patterns that are distant in time, suggesting a richer space of possible states. We show that the cortex, cerebellum and subcortex all display consciousness-relevant dynamics and discuss the implication of our results in forming a point of contact between dynamical systems interpretations and phenomenology.

The amount of knowledge on human consciousness has created a multitude of viewpoints and it is difficult to compare and synthesize all the recent scientific perspectives. Indeed, there are many definitions of consciousness and multiple approaches to study the neural correlates of consciousness (NCC). Therefore, the main aim of this article is to collect data on the various theories of consciousness published between 2007-2017 and to synthesize them to provide a general overview of this topic. To describe each theory, we developed a thematic grid called the dimensional model, which qualitatively and quantitatively analyzes how each article, related to one specific theory, debates/analyzes a specific issue. Among the 1130 articles assessed, 85 full texts were included in the prefinal step. Finally, this scoping review analyzed 68 articles that described 29 theories of consciousness. We found heterogeneous perspectives in the theories analyzed. Those with the highest grade of variability are as follows: subjectivity, NCC, and the consciousness/cognitive function. Among sub-cortical structures, thalamus, basal ganglia, and the hippocampus were the most indicated, whereas the cingulate, prefrontal, and temporal areas were the most reported for cortical ones also including the thalamo-cortical system. Moreover, we found several definitions of consciousness and 21 new sub-classifications.

During the last years, functional magnetic resonance imaging (fMRI) of the brain has been introduced as a new tool to measure consciousness, both in a clinical setting and in a basic neurocognitive research. Moreover, advanced mathematical methods and theories have arrived the field of fMRI (e.g. computational neuroimaging), and functional and structural brain connectivity can now be assessed non-invasively.

The brain is possibly the most complex system known to mankind, and its complexity has been called upon to explain the emergence of consciousness. However, complexity has been defined in many ways by multiple different fields: here, we investigate measures of algorithmic and process complexity in both the temporal and topological domains, testing them on functional MRI BOLD signal data obtained from individuals undergoing various levels of sedation with the anaesthetic agent propofol, replicating our results in two separate datasets. We demonstrate that the various measures are differently able to discriminate between levels of sedation, with temporal measures showing higher sensitivity. Further, we show that all measures are strongly related to a single underlying construct explaining most of the variance, as assessed by Principal Component Analysis, which we interpret as a measure of "overall complexity" of our data. This overall complexity was also able to discriminate between levels of sedation and serum concentrations of propofol, supporting the hypothesis that consciousness is related to complexity - independent of how the latter is measured.

The mismatch negativity (MMN) index has been used to evaluate consciousness levels in patients with disorders of consciousness (DoC). Indeed, MMN has been validated for the diagnosis of vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state (MCS). In this study, we evaluated the accuracy of different MMN amplitude representations in predicting levels of consciousness.

Consciousness is comprised of arousal (i.e., wakefulness) and awareness. Substantial progress has been made in mapping the cortical networks that modulate awareness in the human brain, but knowledge about the subcortical networks that sustain arousal is lacking. We integrated data from ex vivo diffusion MRI, immunohistochemistry, and in vivo 7 Tesla functional MRI to map the connectivity of a subcortical arousal network that we postulate sustains wakefulness in the resting, conscious human brain, analogous to the cortical default mode network (DMN) that is believed to sustain self-awareness. We identified nodes of the proposed default ascending arousal network (dAAN) in the brainstem, hypothalamus, thalamus, and basal forebrain by correlating ex vivo diffusion MRI with immunohistochemistry in three human brain specimens from neurologically normal individuals scanned at 600-750 μm resolution. We performed deterministic and probabilistic tractography analyses of the diffusion MRI data to map dAAN intra-network connections and dAAN-DMN internetwork connections. Using a newly developed network-based autopsy of the human brain that integrates ex vivo MRI and histopathology, we identified projection, association, and commissural pathways linking dAAN nodes with one another and with cortical DMN nodes, providing a structural architecture for the integration of arousal and awareness in human consciousness. We release the ex vivo diffusion MRI data, corresponding immunohistochemistry data, network-based autopsy methods, and a new brainstem dAAN atlas to support efforts to map the connectivity of human consciousness.

The generation and maintenance of consciousness are fundamental but difficult subjects in the fields of psychology, philosophy, neuroscience, and medicine. However, recent developments in neuro-imaging techniques coupled with network analysis have greatly advanced our understanding of consciousness. The present review focuses on large-scale functional brain networks based on neuro-imaging data to explain the awareness (contents) and wakefulness of consciousness. Despite limitations, neuroimaging data suggests brain maps for important psychological and cognitive processes such as attention, language, self-referential, emotion, motivation, social behavior, and wakefulness. We considered a review of these advancements would provide new insights into research on the neural correlates of consciousness.

Psychedelics have been recognized as model interventions for studying altered states of consciousness. However, few empirical studies of the shamanic state of consciousness, which is anecdotally similar to the psychedelic state, exist. We investigated the neural correlates of shamanic trance using high-density electroencephalography (EEG) in 24 shamanic practitioners and 24 healthy controls during rest, shamanic drumming, and classical music listening, followed by an assessment of altered states of consciousness. EEG data were used to assess changes in absolute power, connectivity, signal diversity, and criticality, which were correlated with assessment measures. We also compared assessment scores to those of individuals in a previous study under the influence of psychedelics. Shamanic practitioners were significantly different from controls in several domains of altered states of consciousness, with scores comparable to or exceeding that of healthy volunteers under the influence of psychedelics. Practitioners also displayed increased gamma power during drumming that positively correlated with elementary visual alterations. Furthermore, shamanic practitioners had decreased low alpha and increased low beta connectivity during drumming and classical music and decreased neural signal diversity in the gamma band during drumming that inversely correlated with insightfulness. Finally, criticality in practitioners was increased during drumming in the low and high beta and gamma bands, with increases in the low beta band correlating with complex imagery and elementary visual alterations. These findings suggest that psychedelic drug-induced and non-pharmacologic alterations in consciousness have overlapping phenomenal traits but are distinct states of consciousness, as reflected by the unique brain-related changes during shamanic trance compared to previous literature investigating the psychedelic state.

Interoceptive signals, such as the heartbeat, are processed in a network of brain regions including the insular cortex. Recent studies have shown that such signals modulate perceptual and cognitive processing, and that they impact visual awareness. For example, visual stimuli presented synchronously to the heartbeat take longer to enter visual awareness than the same stimuli presented asynchronously to the heartbeat, and this is reflected in anterior insular activation. This finding demonstrated a link between the processing of interoceptive and exteroceptive signals as well as visual awareness in the insular cortex. The advantage for visual stimuli which are asynchronous to the heartbeat to enter visual consciousness may indicate a role for the anterior insula in the suppression of the sensory consequences of cardiac signals. Here, we present data from the detailed investigation of two patients with insular lesions (as well as four patients with non-insular lesions and healthy age matched controls) indicating that a lesion of the anterior insular cortex, but not of other regions, abolished this cardio-visual suppression effect. The present data provide causal evidence for the role of the anterior insula in the integration of internal interoceptive and external sensory signals for visual awareness.

(1) Background: Sustained axonal degeneration may play a critical role in prolonged disorder of consciousness (DOCs) pathophysiology. We evaluated levels of neurofilament light chain (NFL), an axonal injury marker, in patients with unresponsive wakefulness syndrome (UWS) and in the minimally conscious state (MCS) after traumatic brain injury (TBI) and hypoxic-ischemic brain injury (HIBI). (2) Methods: This prospective multicenter blinded study involved 70 patients with prolonged DOC and 70 sex-/age-matched healthy controls. Serum NFL levels were evaluated at 1-3 and 6 months post-injury and compared with those of controls. NFL levels were compared by DOC severity (UWS vs. MCS) and etiology (TBI vs. HIBI). (3) Results: Patients' serum NFL levels were significantly higher than those of controls at 1-3 and 6 months post-injury (medians, 1729 and 426 vs. 90 pg/mL; both p < 0.0001). NFL levels were higher in patients with UWS than in those in MCS at 1-3 months post-injury (p = 0.008) and in patients with HIBI than in those with TBI at 6 months post-injury (p = 0.037). (4) Conclusions: Patients with prolonged DOC present sustained axonal degeneration that is affected differently over time by brain injury severity and etiology.

In this narrative review, we focus on the role of quantitative EEG technology in the diagnosis and prognosis of patients with unresponsive wakefulness syndrome and minimally conscious state. This paper is divided into two main parts, i.e., diagnosis and prognosis, each consisting of three subsections, namely, (i) resting-state EEG, including spectral power, functional connectivity, dynamic functional connectivity, graph theory, microstates and nonlinear measurements, (ii) sleep patterns, including rapid eye movement (REM) sleep, slow-wave sleep and sleep spindles and (iii) evoked potentials, including the P300, mismatch negativity, the N100, the N400 late positive component and others. Finally, we summarize our findings and conclude that QEEG is a useful tool when it comes to defining the diagnosis and prognosis of DOC patients.