Can human neurological tests of consciousness be applied to octopus?

If the anatomy, physiology and behaviour of a species differ substantially from our own, can we infer that the species is unconscious? In the daily clinical care of patients with disorders of consciousness we face many similar challenges: our current approach with these patients - a combination of behavioural and brain imaging-based assessments - might also be a viable route to investigating octopus consciousness

Brain-Computer Interfaces and its Place in the Management of Disorders of Consciousness

editorial reviewedBrain-computer interfaces (BCI) constitute a growing and constantly evolving field of study showing promising applications that span a multitude of potential disciplines. In this chapter, we will introduce BCIs and the roles that different technologies and paradigms play specifically for the management of patients with a disorder of consciousness (DoC). We will provide an overview of the state of the art concerning BCI research in the field of DoC by highlighting some of the most paramount works in the current literature. Contrasting the advances in research with current recommendations and applications in clinical practice exposes the severe lack of recognition that BCI usage receives in routine care for patients with a DoC. To conclude, we mention some potentially interesting future perspectives to further develop this domain

Theta network centrality correlates with tDCS response in disorders of consciousness.

peer reviewe

BCI performance and brain metabolism profile in severely brain-injured patients without response to command at bedside

peer reviewedDetection and interpretation of signs of "covert command following" in patients with disorders of consciousness (DOC) remains a challenge for clinicians. In this study, we used a tactile P3-based BCI in 12 patients without behavioral command following, attempting to establish "covert command following." These results were then confronted to cerebral metabolism preservation as measured with glucose PET (FDG-PET). One patient showed "covert command following" (i.e., above-threshold BCI performance) during the active tactile paradigm. This patient also showed a higher cerebral glucose metabolism within the language network (presumably required for command following) when compared with the other patients without "covert command-following" but having a cerebral glucose metabolism indicative of minimally conscious state. Our results suggest that the P3-based BCI might probe "covert command following" in patients without behavioral response to command and therefore could be a valuable addition in the clinical assessment of patients with DOC

Mapping the functional connectome traits of levels of consciousness

Examining task-free functional connectivity (FC) in the human brain offers insights on how spontaneous integration and segregation of information relate to human cognition, and how this organization may be altered in different conditions, and neurological disorders. This is particularly relevant for patients in disorders of consciousness (DOC) following severe acquired brain damage and coma, one of the most devastating conditions in modern medical care. We present a novel data-driven methodology, connICA, which implements Independent Component Analysis (ICA) for the extraction of robust independent FC patterns (FC-traits) from a set of individual functional connectomes, without imposing any a priori data stratification into groups. We here apply connICA to investigate associations between network traits derived from task-free FC and cognitive/clinical features that define levels of consciousness. Three main independent FC-traits were identified and linked to consciousness-related clinical features. The first one represents the functional configuration it is associated to a sedative (sevoflurane), the overall effect of the pathology and the level of arousal. The second FC-trait reflects the disconnection of the visual and sensory-motor connectivity patterns. It also relates to the time since the insult and to the ability of communicating with the external environment. The third FC-trait isolates the connectivity pattern encompassing the fronto-parietal and the default-mode network areas as well as the interaction between left and right hemispheres, which are also associated to the awareness of the self and its surroundings. Each FC-trait represents a distinct functional process with a role in the degradation of conscious states of functional brain networks, shedding further light on the functional subcircuits that get disrupted in severe brain-damage

Auditory and somatosensory p3 are complementary for the assessment of patients with disorders of consciousness

The evaluation of the level of consciousness in patients with disorders of consciousness (DOC) is primarily based on behavioural assessments. Patients with unresponsive wakefulness syndrome (UWS) do not show any sign of awareness of their environment, while minimally conscious state (MCS) patients show reproducible but fluctuating signs of awareness. Some patients, although with remaining cognitive abilities, are not able to exhibit overt voluntary responses at the bedside and may be misdiagnosed as UWS. Several studies investigated functional neuroimaging and neurophysiology as an additional tool to evaluate the level of consciousness and to detect covert command following in DOC. Most of these studies are based on auditory stimulation, neglecting patients suffering from decreased or absent hearing abilities. In the present study, we aim to assess the response to a P3-based paradigm in 40 patients with DOC and 12 healthy participants using auditory (AEP) and vibrotactile (VTP) stimulation. To this end, an EEG-based brain-computer interface was used at DOC patient’s bedside. We compared the significance of the P3 performance (i.e., the interpretation of significance of the evoked P3 response) as obtained by ‘direct processing’ (i.e., theoretical-based significance threshold) and ‘offline processing’ (i.e., permutation-based single subject level threshold). We evaluated whether the P3 performances were dependent on clinical variables such as diagnosis (UWS and MCS), aetiology and time since injury. Last we tested the dependency of AEP and VTP performances at the single subject level. Direct processing tends to overestimate P3 performance. We did not find any difference in the presence of a P3 performance according to the level of consciousness (UWS vs. MCS) or the aetiology (traumatic vs. non-traumatic brain injury). The performance achieved at the AEP paradigm was independent from what was achieved at the VTP paradigm, indicating that some patients performed better on the AEP task while others performed better on the VTP task. Our results support the importance of using multimodal approaches in the assessment of DOC patients in order to optimise the evaluation of patient’s abilities. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

Resting-state functional connectivity and cortical thickness characterization of a patient with Charles Bonnet syndrome

Charles Bonnet syndrome (CBS) is a rare condition characterized by visual impairment associated with complex visual hallucinations in elderly people. Although studies suggested that visual hallucinations may be caused by brain damage in the visual system in CBS patients, alterations in specific brain regions in the occipital cortex have not been studied. Functional connectivity during resting-state functional magnetic resonance imaging (rs-fMRI; without hallucinations) in CBS patients, has never been explored. We aimed to investigate brain structural and functional changes in a patient with CBS, as compared with late blind (LB) and normally sighted subjects. We employed voxel-based morphometry and cortical thickness analyses to investigate alterations in grey matter characteristics, and rs-fMRI to study changes in functional brain connectivity. Decreased grey matter volume was observed in the middle occipital gyrus and in the cuneus in the CBS patient and in the middle occipital gyrus and in the lingual gyrus within LB subjects, compared to their respective control groups. Reductions in cortical thickness in associative and multimodal cortices were observed in the CBS patient when comparing with LB subjects. The precuneus exhibited increased functional connectivity with the secondary visual cortex in the CBS patient compared to the controls. In contrast, LB patients showed decreased functional connectivity compared to sighted controls between the DMN and the temporo-occipital fusiform gyrus, a region known to support hallucinations. Our findings suggest a reorganization of the functional connectivity between regions involved in self-awareness and in visual and salience processing in CBS that may contribute to the appearance of visual hallucinations

Mapping the functional brain state of a world champion freediver in static dry apnea

peer reviewedVoluntary apnea showcases extreme human adaptability in trained individuals like professional free divers. We evaluated the psychological and physiological adaptation and the functional cerebral changes using electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) to 6.5 min of dry static apnea performed by a world champion free diver. Compared to resting state at baseline, breath holding was characterized by increased EEG power and functional connectivity in the alpha band, along with decreased delta band connectivity. fMRI connectivity was increased within the default mode network (DMN) and visual areas but decreased in pre- and postcentral cortices. While these changes occurred in regions overlapping with cerebral signatures of several meditation practices, they also display some unique features that suggest an altered somatosensory integration. As suggested by self-reports, these findings could reflect the ability of elite free divers to create a state of sensory dissociation when performing prolonged apnea

Needs and quality of life in caregivers of patients with prolonged disorders of consciousness

peer reviewe

Brain networks predict metabolism, diagnosis and prognosis at the bedside in disorders of consciousness

peer reviewedRecent advances in functional neuroimaging have demonstrated novel potential for informing diagnosis and prognosis in the unresponsive wakeful syndrome and minimally conscious states. However, these technologies come with considerable expense and difficulty, limiting the possibility of wider clinical application in patients. Here, we show that high density electroencephalography, collected from 104 patients measured at rest, can provide valuable information about brain connectivity that correlates with behaviour and functional neuroimaging. Using graph theory, we visualize and quantify spectral connectivity estimated from electroencephalography as a dense brain network. Our findings demonstrate that key quantitative metrics of these networks correlate with the continuum of behavioural recovery in patients, ranging from those diagnosed as unresponsive, through those who have emerged from minimally conscious, to the fully conscious locked-in syndrome. In particular, a network metric indexing the presence of densely interconnected central hubs of connectivity discriminated behavioural consciousness with accuracy comparable to that achieved by expert assessment with positron emission tomography. We also show that this metric correlates strongly with brain metabolism. Further, with classification analysis, we predict the behavioural diagnosis, brain metabolism and 1-year clinical outcome of individual patients. Finally, we demonstrate that assessments of brain networks show robust connectivity in patients diagnosed as unresponsive by clinical consensus, but later rediagnosed as minimally conscious with the Coma Recovery Scale-Revised. Classification analysis of their brain network identified each of these misdiagnosed patients as minimally conscious, corroborating their behavioural diagnoses. If deployed at the bedside in the clinical context, such network measurements could complement systematic behavioural assessment and help reduce the high misdiagnosis rate reported in these patients. These metrics could also identify patients in whom further assessment is warranted using neuroimaging or conventional clinical evaluation. Finally, by providing objective characterization of states of consciousness, repeated assessments of network metrics could help track individual patients longitudinally, and also assess their neural responses to therapeutic and pharmacological interventions