Diffusion weighted imaging distinguishes the vegetative state from the minimally conscious state

Functional and structural brain connectivity in disorders of consciousness

Brain connectivity, allowing information to be shared between distinct cortical areas and thus to be processed in an integrated way, has long been considered critical for consciousness. However, the relationship between functional intercortical interactions and the structural connections thought to underlie them is poorly understood. In the present work, we explore both functional (with an EEG-based metric: the median weighted symbolic mutual information in the theta band) and structural (with a brain MRI-based metric: fractional anisotropy) connectivities in a cohort of 78 patients with disorders of consciousness. Both metrics could distinguish patients in a vegetative state from patients in minimally conscious state. Crucially, we discovered a significant positive correlation between functional and structural connectivities. Furthermore, we showed that this structure-function relationship is more specifically observed when considering structural connectivity within the intra- and inter-hemispheric long-distance cortico-cortical bundles involved in the Global Neuronal Workspace (GNW) theory of consciousness, thus supporting predictions of this model. Altogether, these results support the interest of multimodal assessments of brain connectivity in refining the diagnostic evaluation of patients with disorders of consciousness.

Diagnostic value of PET imaging in clinically unresponsive patients

Rapid advancements in the critical care management of acute brain injuries have facilitated the survival of numerous patients who may have otherwise succumbed to their injuries. The probability of conscious recovery hinges on the extent of structural brain damage and the level of metabolic and functional cerebral impairment, which remain challenging to assess via laboratory, clinical, or functional tests. Current research settings and guidelines highlight the potential value of fluorodeoxyglucose-PET (FDG-PET) for diagnostic and prognostic purposes, emphasizing its capacity to consistently illustrate a metabolic reduction in cerebral glucose uptake across various disorders of consciousness. Crucially, FDG-PET might be a pivotal tool for differentiating between patients in the minimally conscious state and those in the unresponsive wakefulness syndrome, a persistent clinical challenge. In patients with disorders of consciousness, PET offers utility in evaluating the degree and spread of functional disruption, as well as identifying irreversible neural damage. Further, studies that capture responses to external stimuli can shed light on residual or revived brain functioning. Nevertheless, the validity of these findings in predicting clinical outcomes calls for additional long-term studies with larger patient cohorts suffering from consciousness impairment. Misdiagnosis of conscious illnesses during bedside clinical assessments remains a significant concern. Based on the clinical research settings, current clinical guidelines recommend PET for diagnostic and/or prognostic purposes. This review article discusses the clinical categories of conscious disorders and the diagnostic and prognostic value of PET imaging in clinically unresponsive patients, considering the known limitations of PET imaging in such contexts.

Common Data Elements for Disorders of Consciousness: Recommendations from the Electrophysiology Working Group

BACKGROUND

Electroencephalography (EEG) has long been recognized as an important tool in the investigation of disorders of consciousness (DoC). From inspection of the raw EEG to the implementation of quantitative EEG, and more recently in the use of perturbed EEG, it is paramount to providing accurate diagnostic and prognostic information in the care of patients with DoC. However, a nomenclature for variables that establishes a convention for naming, defining, and structuring data for clinical research variables currently is lacking. As such, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups composed of experts in the field to construct common data elements (CDEs) to provide recommendations for DoC, with the main goal of facilitating data collection and standardization of reporting. This article summarizes the recommendations of the electrophysiology DoC working group.

METHODS

After assessing previously published pertinent CDEs, we developed new CDEs and categorized them into "disease core," "basic," "supplemental," and "exploratory." Key EEG design elements, defined as concepts that pertained to a methodological parameter relevant to the acquisition, processing, or analysis of data, were also included but were not classified as CDEs.

RESULTS

After identifying existing pertinent CDEs and developing novel CDEs for electrophysiology in DoC, variables were organized into a framework based on the two primary categories of resting state EEG and perturbed EEG. Using this categorical framework, two case report forms were generated by the working group.

CONCLUSIONS

Adherence to the recommendations outlined by the electrophysiology working group in the resting state EEG and perturbed EEG case report forms will facilitate data collection and sharing in DoC research on an international level. In turn, this will allow for more informed and reliable comparison of results across studies, facilitating further advancement in the realm of DoC research.

Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Neuroimaging

BACKGROUND

Over the past 5 decades, advances in neuroimaging have yielded insights into the pathophysiologic mechanisms that cause disorders of consciousness (DoC) in patients with severe brain injuries. Structural, functional, metabolic, and perfusion imaging studies have revealed specific neuroanatomic regions, such as the brainstem tegmentum, thalamus, posterior cingulate cortex, medial prefrontal cortex, and occipital cortex, where lesions correlate with the current or future state of consciousness. Advanced imaging modalities, such as diffusion tensor imaging, resting-state functional magnetic resonance imaging (fMRI), and task-based fMRI, have been used to improve the accuracy of diagnosis and long-term prognosis, culminating in the endorsement of fMRI for the clinical evaluation of patients with DoC in the 2018 US (task-based fMRI) and 2020 European (task-based and resting-state fMRI) guidelines. As diverse neuroimaging techniques are increasingly used for patients with DoC in research and clinical settings, the need for a standardized approach to reporting results is clear. The success of future multicenter collaborations and international trials fundamentally depends on the implementation of a shared nomenclature and infrastructure.

METHODS

To address this need, the Neurocritical Care Society's Curing Coma Campaign convened an international panel of DoC neuroimaging experts to propose common data elements (CDEs) for data collection and reporting in this field.

RESULTS

We report the recommendations of this CDE development panel and disseminate CDEs to be used in neuroimaging studies of patients with DoC.

CONCLUSIONS

These CDEs will support progress in the field of DoC neuroimaging and facilitate international collaboration.

Prognostication in Prolonged and Chronic Disorders of Consciousness

Patients with prolonged disorders of consciousness (DOCs) longer than 28 days may continue to make significant gains and achieve functional recovery. Occasionally, this recovery trajectory may extend past 3 (for nontraumatic etiologies) and 12 months (for traumatic etiologies) into the chronic period. Prognosis is influenced by several factors including state of DOC, etiology, and demographics. There are several testing modalities that may aid prognostication under active investigation including electroencephalography, functional and anatomic magnetic resonance imaging, and event-related potentials. At this time, only one treatment (amantadine) has been routinely recommended to improve functional recovery in prolonged DOC. Given that some patients with prolonged or chronic DOC have the potential to recover both consciousness and functional status, it is important for neurologists experienced in prognostication to remain involved in their care.

Multi-session tDCS paired with passive mobilisation of the thumb modulates thalamo-cortical coupling during command following in the healthy brain

Therapeutic options to restore responsiveness in patients with prolonged disorder of consciousness (PDOC) are limited. We have recently shown that a single session of tDCS over M1 delivered at rest can reduce thalamic self-inhibition during motor command following. Here, we build upon this by exploring whether pairing tDCS with a concurrent passive mobilisation protocol can further influence thalamo-M1 dynamics and whether these changes are enhanced after multiple stimulation sessions. Specifically, we used Dynamic Causal Modelling (DCM) of functional magnetic resonance imaging (fMRI) data from 22 healthy participants to assess changes on effective connectivity within the motor network during active thumb movements after 1 or 5 sessions of tDCS paired with passive mobilisations of the thumb. We found that a single anodal tDCS session (paired with passive mobilisation of the thumb) decreased self-inhibition in M1, with five sessions further enhancing this effect. In addition, anodal tDCS increased thalamo-M1 excitation as compared to cathodal stimulation, with the effects maintained after 5 sessions. Together, our results suggest that pairing anodal tDCS with passive mobilisation across multiple sessions may facilitate thalamo-cortical dynamics that are relevant for behavioural responsiveness in PDOC. More broadly, they offer a mechanistic window into the neural underpinnings of the cumulative effects of multi-session tDCS.

Relationship between Coma Recovery Scale-Revised and the Thalamocortical Tract of Ascending Reticular Activating System in Hypoxic-Ischemic Brain Injury: A Pilot Study

BACKGROUND

This pilot study examined the relationship between the Coma Recovery Scale-Revised (CRS-R) and the five subparts of the thalamocortical tract in chronic patients with hypoxic-ischemic brain injury by diffusion tensor tractography (DTT).

METHODS

Seventeen consecutive chronic patients with hypoxic-ischemic brain injury were recruited. The consciousness state was evaluated using CRS-R. The five subparts of the thalamocortical tract (the prefrontal cortex, the premotor cortex, the primary motor cortex, the primary somatosensory cortex, and the posterior parietal cortex) were reconstructed using DTT. Fractional anisotropy and the tract volume of each subpart of the thalamocortical tract were estimated.

RESULTS

The CRS-R score showed a moderate positive correlation with the tract volume of the prefrontal cortex part of the thalamocortical tract (p < 0.05). In addition, the tract volume of the prefrontal cortex component of the thalamocortical tract could explain the variability in the CRS-R score (p < 0.05).

CONCLUSION

The prefrontal cortex part was closely related to the CRS-R score in chronic patients with hypoxic-ischemic brain injury. In addition, the change in the remaining number of neural fibers of the prefrontal cortex part appeared to be related to the change in conscious state.

Reduced emergent character of neural dynamics in patients with a disrupted connectome

High-level brain functions are widely believed to emerge from the orchestrated activity of multiple neural systems. However, lacking a formal definition and practical quantification of emergence for experimental data, neuroscientists have been unable to empirically test this long-standing conjecture. Here we investigate this fundamental question by leveraging a recently proposed framework known as "Integrated Information Decomposition," which establishes a principled information-theoretic approach to operationalise and quantify emergence in dynamical systems - including the human brain. By analysing functional MRI data, our results show that the emergent and hierarchical character of neural dynamics is significantly diminished in chronically unresponsive patients suffering from severe brain injury. At a functional level, we demonstrate that emergence capacity is positively correlated with the extent of hierarchical organisation in brain activity. Furthermore, by combining computational approaches from network control theory and whole-brain biophysical modelling, we show that the reduced capacity for emergent and hierarchical dynamics in severely brain-injured patients can be mechanistically explained by disruptions in the patients' structural connectome. Overall, our results suggest that chronic unresponsiveness resulting from severe brain injury may be related to structural impairment of the fundamental neural infrastructures required for brain dynamics to support emergence.

Mapping topography and network of brain injury in patients with disorders of consciousness

Background

There is a growing interest in the topography of brain regions associated with disorders of consciousness. This has caused increased research output, yielding many publications investigating the topic with varying methodologies. The objective of this study was to ascertain the topographical regions of the brain most frequently associated with disorders of consciousness.

Methods

We performed a cross-sectional text-mining analysis of disorders of consciousness studies. A text mining algorithm built in the Python programming language searched documents for anatomical brain terminology. We reviewed primary PubMed studies between January 1st 2000 to 8th February 2023 for the search query “Disorders of Consciousness.” The frequency of brain regions mentioned in these articles was recorded, ranked, then built into a graphical network. Subgroup analysis was performed by evaluating the impact on our results if analyses were based on abstracts, full-texts, or topic-modeled groups (non-negative matrix factorization was used to create subgroups of each collection based on their key topics). Brain terms were ranked by their frequency and concordance was measured between subgroups. Graphical analysis was performed to explore relationships between the anatomical regions mentioned. The PageRank algorithm (used by Google to list search results in order of relevance) was used to determine global importance of the regions.

Results

The PubMed search yielded 24,944 abstracts and 3,780 full texts. The topic-modeled subgroups contained 2015 abstracts and 283 full texts. Text Mining across all document groups concordantly ranked the thalamus the highest (Savage score = 11.716), followed by the precuneus (Savage score = 4.983), hippocampus (Savage score = 4.483). Graphical analysis had 5 clusters with the thalamus once again having the highest PageRank score (PageRank = 0.0344).

Conclusion

The thalamus, precuneus and cingulate cortex are strongly associated with disorders of consciousness, likely due to the roles they play in maintaining awareness and involvement in the default mode network, respectively. The findings also suggest that other areas of the brain like the cerebellum, cuneus, amygdala and hippocampus also share connections to consciousness should be further investigated.

Enhanced brain parcellation via abnormality inpainting for neuroimage-based consciousness evaluation of hydrocephalus patients by lumbar drainage

Brain network analysis based on structural and functional magnetic resonance imaging (MRI) is considered as an effective method for consciousness evaluation of hydrocephalus patients, which can also be applied to facilitate the ameliorative effect of lumbar cerebrospinal fluid drainage (LCFD). Automatic brain parcellation is a prerequisite for brain network construction. However, hydrocephalus images usually have large deformations and lesion erosions, which becomes challenging for ensuring effective brain parcellation works. In this paper, we develop a novel and robust method for segmenting brain regions of hydrocephalus images. Our main contribution is to design an innovative inpainting method that can amend the large deformations and lesion erosions in hydrocephalus images, and synthesize the normal brain version without injury. The synthesized images can effectively support brain parcellation tasks and lay the foundation for the subsequent brain network construction work. Specifically, the novelty of the inpainting method is that it can utilize the symmetric properties of the brain structure to ensure the quality of the synthesized results. Experiments show that the proposed brain abnormality inpainting method can effectively aid the brain network construction, and improve the CRS-R score estimation which represents the patient's consciousness states. Furthermore, the brain network analysis based on our enhanced brain parcellation method has demonstrated potential imaging biomarkers for better interpreting and understanding the recovery of consciousness in patients with secondary hydrocephalus.

Structural connectivity in recovery after coma: Connectome atlas approach

AIM

Pathological states of recovery after coma as a result of a severe brain injury are marked with changes in structural connectivity of the brain. This study aimed to identify a topological correlation between white matter integrity and the level of functional and cognitive impairment in patients recovering after coma.

METHODS

Structural connectomes were computed based on fractional anisotropy maps from 40 patients using a probabilistic human connectome atlas. We used a network based statistics approach to identify potential brain networks associated with a more favorable outcome, assessed with clinical neurobehavioral scores at the patient's discharge from the acute neurorehabilitation unit.

RESULTS

We identified a subnetwork whose strength of connectivity correlated with a more favorable outcome as measured with the Disability Rating Scale (network based statistics: t >3.5, P =.010). The subnetwork predominated in the left hemisphere and included the thalamic nuclei, putamen, precentral and postcentral gyri, and medial parietal regions. Spearman correlation between the mean fractional anisotropy value of the subnetwork and the score was ρ = -0.60 (P <.0001). A less extensive overlapping subnetwork correlated with the Coma Recovery Scale Revised score, consisting mostly of the left hemisphere connectivity between the thalamic nuclei and pre- and post-central gyri (network based statistics: t >3.5, P =.033; Spearman's ρ = 0.58, P <.0001).

CONCLUSION

The present findings suggest an important role of structural connectivity between the thalamus, putamen and somatomotor cortex in the recovery from coma as evaluated with neurobehavioral scores. These structures are part of the motor circuit involved in the generation and modulation of voluntary movement, as well as the forebrain mesocircuit supposedly underlying the maintenance of consciousness. As behavioural assessment of consciousness depends heavily on the signs of voluntary motor behaviour, further work will elucidate whether the identified subnetwork reflects the structural architecture underlying the recovery of consciousness or rather the ability to communicate its content.

Cortical and thalamic connections of the human globus pallidus: Implications for disorders of consciousness

A dominant framework for understanding loss and recovery of consciousness in the context of severe brain injury, the mesocircuit hypothesis, focuses on the role of cortico-subcortical recurrent interactions, with a strong emphasis on excitatory thalamofugal projections. According to this view, excess inhibition from the internal globus pallidus (GPi) on central thalamic nuclei is key to understanding prolonged disorders of consciousness (DOC) and their characteristic, brain-wide metabolic depression. Recent work in healthy volunteers and patients, however, suggests a previously unappreciated role for the external globus pallidus (GPe) in maintaining a state of consciousness. This view is consistent with empirical findings demonstrating the existence of “direct” (i.e., not mediated by GPi/substantia nigra pars reticulata) GPe connections with cortex and thalamus in animal models, as well as their involvement in modulating arousal and sleep, and with theoretical work underscoring the role of GABA dysfunction in prolonged DOC. Leveraging 50 healthy subjects' high angular resolution diffusion imaging (HARDI) dataset from the Human Connectome Project, which provides a more accurate representation of intravoxel water diffusion than conventional diffusion tensor imaging approaches, we ran probabilistic tractography using extensive a priori exclusion criteria to limit the influence of indirect connections in order to better characterize “direct” pallidal connections. We report the first in vivo evidence of highly probable “direct” GPe connections with prefrontal cortex (PFC) and central thalamic nuclei. Conversely, we find direct connections between the GPi and PFC to be sparse (i.e., less likely indicative of true “direct” connectivity) and restricted to the posterior border of PFC, thus reflecting an extension from the cortical motor zones (i.e., motor association areas). Consistent with GPi's preferential connections with sensorimotor cortices, the GPi appears to predominantly connect with the sensorimotor subregions of the thalamus. These findings are validated against existing animal tracer studies. These findings suggest that contemporary mechanistic models of loss and recovery of consciousness following brain injury must be updated to include the GPe and reflect the actual patterns of GPe and GPi connectivity within large-scale cortico-thalamo-cortical circuits.

The importance of instrumental assessment in disorders of consciousness: a comparison between American, European, and UK International recommendations

The use of instrumental tools for improving both the diagnostic accuracy and the prognostic soundness in patients with disorders of consciousness (DOC) plays an important role. However, the most recent international guidelines on DOC published by the American and the European Academies of Neurology and by the UK Royal College of Physicians contain heterogeneous recommendations on the implementation of these techniques in the clinical routine for both diagnosis and prognosis. With the present work, starting from the comparison of the DOC guidelines’ recommendations, we look for possible explanations behind such discrepancies considering the adopted methodologies and the reference health systems that could have affected the guidelines’ perspectives. We made a provocative argument about the need to find the most appropriate common methodology to retrieve and grade the evidence, increase the meta-analytic studies, and reduce the health policies that influence on the guidelines development that, in turn, should inform the health policies with the strongest scientific evidence.

Altered Intestinal Microbiomes and Lipid Metabolism in Patients With Prolonged Disorders of Consciousness

The intestinal microbiota regulate the brain function of the host through the production of a myriad of metabolites and are associated with various neurological diseases. Understanding the intestinal microbiome of patients with prolonged disorders of consciousness (DoC) is important for the evaluation and treatment of the disease. To investigate the differences in the intestinal microbiome and short-chain fatty acids (SCFAs) among patients in a vegetative state (VS), a minimally conscious state (MCS), and emerged from MCS (EMCS), as well as the influence of antibiotics on these patients, 16S ribosomal RNA (16S rRNA) sequencing and targeted lipidomics were performed on fecal samples from patients; in addition, analysis of the electroencephalogram (EEG) signals was performed to evaluate the brain function of these patients. The results showed that the intestinal microbiome of the three groups differed greatly, and some microbial communities showed a reduced production of SCFAs in VS patients compared to the other two groups. Moreover, reduced microbial communities and five major SCFAs, along with attenuated brain functional connectivity, were observed in MCS patients who were treated with antibiotics compared to those who did not receive antibiotic treatment, but not in the other pairwise comparisons. Finally, three genus-level microbiota—Faecailbacterium, Enterococcus, and Methanobrevibacter—were considered as potential biomarkers to distinguish MCS from VS patients, with high accuracy both in the discovery and validation cohorts. Together, our findings improved the understanding of patients with prolonged DoC from the intestinal microbiome perspective and provided a new reference for the exploration of therapeutic targets.

The Value of First-Order Features Based on the Apparent Diffusion Coefficient Map in Evaluating the Therapeutic Effect of Low-Intensity Pulsed Ultrasound for Acute Traumatic Brain Injury With a Rat Model

Purpose

In order to evaluate the neuroprotective effect of low-intensity pulsed ultrasound (LIPUS) for acute traumatic brain injury (TBI), we studied the potential of apparent diffusion coefficient (ADC) values and ADC-derived first-order features regarding this problem.

Methods

Forty-five male Sprague Dawley rats (sham group: 15, TBI group: 15, LIPUS treated: 15) were enrolled and underwent magnetic resonance imaging. Scanning layers were acquired using a multi-shot readout segmentation of long variable echo trains (RESOLVE) to decrease distortion. The ultrasound transducer was applied to the designated region in the injured cortical areas using a conical collimator and was filled with an ultrasound coupling gel. Regions of interest were manually delineated in the center of the damaged cortex on the diffusion weighted images (b = 800 s/mm²) layer by layer for the TBI and LIPUS treated groups using the open-source software ITK-SNAP. Before analysis and modeling, the features were normalized using a z-score method, and a logistic regression model with a backward filtering method was employed to perform the modeling. The entire process was completed using the R language.

Results

During the observation time, the ADC values ipsilateral to the trauma in the TBI and LIPUS groups increased rapidly up to 24 h. After statistical analysis, the 10th percentile, 90th percentile, mean, skewness, and uniformity demonstrated a significant difference among three groups. The receiver operating characteristic curve (ROC) analysis shows that the combined LR model exhibited the highest area under the curve value (AUC: 0.96).

Conclusion

The combined LR model of first-order features based on the ADC map can acquire a higher diagnostic performance than each feature only in evaluating the neuroprotective effect of LIPUS for TBI. Models based on first-order features may have potential value in predicting the therapeutic effect of LIPUS in clinical practice in the future.

Whole-brain modelling identifies distinct but convergent paths to unconsciousness in anaesthesia and disorders of consciousness

The human brain entertains rich spatiotemporal dynamics, which are drastically reconfigured when consciousness is lost due to anaesthesia or disorders of consciousness (DOC). Here, we sought to identify the neurobiological mechanisms that explain how transient pharmacological intervention and chronic neuroanatomical injury can lead to common reconfigurations of neural activity. We developed and systematically perturbed a neurobiologically realistic model of whole-brain haemodynamic signals. By incorporating PET data about the cortical distribution of GABA receptors, our computational model reveals a key role of spatially-specific local inhibition for reproducing the functional MRI activity observed during anaesthesia with the GABA-ergic agent propofol. Additionally, incorporating diffusion MRI data obtained from DOC patients reveals that the dynamics that characterise loss of consciousness can also emerge from randomised neuroanatomical connectivity. Our results generalise between anaesthesia and DOC datasets, demonstrating how increased inhibition and connectome perturbation represent distinct neurobiological paths towards the characteristic activity of the unconscious brain.

Thalamo-Prefrontal Connectivity Correlates With Early Command-Following After Severe Traumatic Brain Injury

Recovery of consciousness after traumatic brain injury (TBI) is heterogeneous and difficult to predict. Structures such as the thalamus and prefrontal cortex are thought to be important in facilitating consciousness. We sought to investigate whether the integrity of thalamo-prefrontal circuits, assessed via diffusion tensor imaging (DTI), was associated with the return of goal-directed behavior after severe TBI. We classified a cohort of severe TBI patients (N = 25, 20 males) into Early and Late/Never outcome groups based on their ability to follow commands within 30 days post-injury. We assessed connectivity between whole thalamus, and mediodorsal thalamus (MD), to prefrontal cortex (PFC) subregions including dorsolateral PFC (dlPFC), medial PFC (mPFC), anterior cingulate (ACC), and orbitofrontal (OFC) cortices. We found that the integrity of thalamic projections to PFC subregions (L OFC, L and R ACC, and R mPFC) was significantly associated with Early command-following. This association persisted when the analysis was restricted to prefrontal-mediodorsal (MD) thalamus connectivity. In contrast, dlPFC connectivity to thalamus was not significantly associated with command-following. Using the integrity of thalamo-prefrontal connections, we created a linear regression model that demonstrated 72% accuracy in predicting command-following after a leave-one-out analysis. Together, these data support a role for thalamo-prefrontal connectivity in the return of goal-directed behavior following TBI.

tDCS modulates effective connectivity during motor command following; a potential therapeutic target for disorders of consciousness

Transcranial direct current stimulation (tDCS) is attracting increasing interest as a potential therapeutic route for unresponsive patients with prolonged disorders of consciousness (PDOC). However, research to date has had mixed results. Here, we propose a new direction by directly addressing the mechanisms underlying lack of responsiveness in PDOC, and using these to define our targets and the success of our intervention in the healthy brain first. We report 2 experiments that assess whether tDCS to the primary motor cortex (M1-tDCS; Experiment 1) and the cerebellum (cb-tDCS; Experiment 2) administered at rest modulate thalamo-cortical coupling in a subsequent command following task typically used to clinically assess awareness. Both experiments use sham- and polarity-controlled, randomised, double-blind, crossover designs. In Experiment 1, 22 participants received anodal, cathodal, and sham M1-tDCS sessions while in the MRI scanner. A further 22 participants received the same protocol with cb-tDCS in Experiment 2. We used Dynamic Causal Modelling of fMRI to characterise the effects of tDCS on brain activity and dynamics during simple thumb movements in response to command. We found that M1-tDCS increased thalamic excitation and that Cathodal cb-tDCS increased excitatory coupling from thalamus to M1. All these changes were polarity specific. Combined, our experiments demonstrate that tDCS can successfully modulate long range thalamo-cortical dynamics during command following via targeting of cortical regions. This suggests that M1- and cb-tDCS may allow PDOC patients to overcome the motor deficits at the root of their reduced responsiveness, improving their rehabilitation options and quality of life as a result.

Difference in the ascending reticular activating system between vegetative and minimally conscious states following traumatic brain injury

OBJECTIVES

We investigated differences in the ascending reticular activating system (ARAS) between vegetative state (VS) and minimally conscious state (MCS) in patients with traumatic brain injury (TBI) by using diffusion tensor tractography.

METHODS

We recruited TBI patients and normal subjects. We reconstructed the lower ARAS and five parts of upper ARAS [prefrontal cortex (PFC), premotor cortex, primary motor cortex, primary somatosensory cortex, and posterior parietal cortex].

RESULTS

Significant differences were observed in the fractional anisotropy (FA) and fiber number (FN) values of the five parts of upper ARAS between the VS and control groups and between the MCS and control groups (P < 0.05), but no differences were detected in the lower ARAS (P > 0.05). The FA and FN values of the PFC in the upper ARAS were significantly different between the VS and MCS groups (P < 0.05). No other significant differences in FA and FN values were detected among the other segments of the upper ARAS or in the lower ARAS (P > 0.05).

CONCLUSION

The results indicate that the prefrontal portion of the upper ARAS is the critical area for distinguishing between VS and MCS in patients with TBI.

Structural and functional connectivity of the ascending arousal network for prediction of outcome in patients with acute disorders of consciousness

To determine the role of early acquisition of blood oxygen level-dependent (BOLD) signals and diffusion tensor imaging (DTI) for analysis of the connectivity of the ascending arousal network (AAN) in predicting neurological outcomes after acute traumatic brain injury (TBI), cardiopulmonary arrest (CPA), or stroke. A prospective analysis of 50 comatose patients was performed during their ICU stay. Image processing was conducted to assess structural and functional connectivity of the AAN. Outcomes were evaluated after 3 and 6 months. Nineteen patients (38%) had stroke, 18 (36%) CPA, and 13 (26%) TBI. Twenty-three patients were comatose (44%), 11 were in a minimally conscious state (20%), and 16 had unresponsive wakefulness syndrome (32%). Univariate analysis demonstrated that measurements of diffusivity, functional connectivity, and numbers of fibers in the gray matter, white matter, whole brain, midbrain reticular formation, and pontis oralis nucleus may serve as predictive biomarkers of outcome depending on the diagnosis. Multivariate analysis demonstrated a correlation of the predicted value and the real outcome for each separate diagnosis and for all the etiologies together. Findings suggest that the above imaging biomarkers may have a predictive role for the outcome of comatose patients after acute TBI, CPA, or stroke.

Microstructural profiles of thalamus and thalamocortical connectivity in patients with disorder of consciousness

Thalamus and thalamocortical connectivity are crucial for consciousness; however, their microstructural changes in patients with a disorder of consciousness (DOC) have not yet been thoroughly characterized. In the present study, we applied the novel fixel-based analysis to comprehensively investigate the thalamus-related microstructural abnormalities in 10 patients with DOC using 7-T diffusion-weighted imaging data. We found that compared to healthy controls, patients with DOC showed reduced fiber density (FD) and fiber density and cross-section (FDC) in the mediodorsal, anterior, and ventral anterior thalamic nuclei, while fiber-bundle cross-section (FC) was not significantly altered in the thalamus. Impaired thalamocortical connectivity in the DOC cohort was mainly connected to the middle frontal gyrus, anterior cingulate gyrus, fusiform gyrus, and sensorimotor cortices, including the precentral gyrus and postcentral gyrus, with predominant microstructural abnormalities in FD and FDC. Correlation analysis showed that FC of the right mediodorsal thalamus was negatively correlated with the level of consciousness. Our results suggest that microstructural abnormalities of thalamus and thalamocortical connectivity in DOC were mainly attributed to axonal injury. In particular, the microstructural integrity of the thalamus is a vital factor in consciousness generation.

Electrocorticography reveals thalamic control of cortical dynamics following traumatic brain injury

The return of consciousness after traumatic brain injury (TBI) is associated with restoring complex cortical dynamics; however, it is unclear what interactions govern these complex dynamics. Here, we set out to uncover the mechanism underlying the return of consciousness by measuring local field potentials (LFP) using invasive electrophysiological recordings in patients recovering from TBI. We found that injury to the thalamus, and its efferent projections, on MRI were associated with repetitive and low complexity LFP signals from a highly structured phase space, resembling a low-dimensional ring attractor. But why do thalamic injuries in TBI patients result in a cortical attractor? We built a simplified thalamocortical model, which connotes that thalamic input facilitates the formation of cortical ensembles required for the return of cognitive function and the content of consciousness. These observations collectively support the view that thalamic input to the cortex enables rich cortical dynamics associated with consciousness.

Insights of neurophysiology on unconscious state using combined transcranial magnetic stimulation and electroencephalography: A systematic review

Unconscious state has been investigated in numerous studies so far, but pathophysiology of this state is not fully understood. Recently, combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has been developed to allow for non-invasive assessment of neurophysiology in the cerebral cortex. We conducted a systematic literature search for TMS-EEG studies on human unconscious state using PubMed with cross-reference and manual searches. The initial search yielded 137 articles, and 19 of them were identified as relevant, including one article found by manual search. This review included 10 studies for unresponsive wakefulness syndrome (UWS), 9 for minimally conscious states (MCS), 5 for medication-induced unconscious states, and 6 for natural non-rapid eye movement states. These studies analyzed TMS-evoked potential to calculate perturbational complexity index (PCI) and OFF-periods. In particular, PCI was found to be a potentially useful marker to differentiate between UWS and MCS. This review demonstrated that TMS-EEG could represent a promising neuroscientific tool to investigate various unconscious states. Further TMS-EEG research may help elucidate the neural basis of unconscious state.

Quantitative multimodal imaging in traumatic brain injuries producing impaired cognition

PURPOSE OF REVIEW

Cognitive impairments are a devastating long-term consequence following traumatic brain injury (TBI). This review provides an update on the quantitative mutimodal neuroimaging studies that attempt to elucidate the mechanism(s) underlying cognitive impairments and their recovery following TBI.

RECENT FINDINGS

Recent studies have linked individual specific behavioural impairments and their changes over time to physiological activity and structural changes using EEG, PET and MRI. Multimodal studies that combine measures of physiological activity with knowledge of neuroanatomical and connectivity damage have also illuminated the multifactorial function-structure relationships that underlie impairment and recovery following TBI.

SUMMARY

The combined use of multiple neuroimaging modalities, with focus on individual longitudinal studies, has the potential to accurately classify impairments, enhance sensitivity of prognoses, inform targets for interventions and precisely track spontaneous and intervention-driven recovery.

Disruptions in Effective Connectivity within and between Default Mode Network and Anterior Forebrain Mesocircuit in Prolonged Disorders of Consciousness

Recent research indicates prolonged disorders of consciousness (PDOC) result from structural and functional impairments to key cortical and subcortical networks, including the default mode network (DMN) and the anterior forebrain mesocircuit (AFM). However, the specific mechanisms which underpin such impairments remain unknown. It is known that disruptions in the striatal-pallidal pathway can result in the over inhibition of the thalamus and lack of excitation to the cortex that characterizes PDOC. Here, we used spectral dynamic causal modelling and parametric empirical Bayes on rs-fMRI data to assess whether DMN changes in PDOC are caused by disruptions in the AFM. PDOC patients displayed overall reduced coupling within the AFM, and specifically, decreased self-inhibition of the striatum, paired with reduced coupling from striatum to thalamus. This led to loss of inhibition from AFM to DMN, mostly driven by posterior areas including the precuneus and inferior parietal cortex. In turn, the DMN showed disruptions in self-inhibition of the precuneus and medial prefrontal cortex. Our results provide support for the anterior mesocircuit model at the subcortical level but highlight an inhibitory role for the AFM over the DMN, which is disrupted in PDOC.

Preserved fractal character of structural brain networks is associated with covert consciousness after severe brain injury

Self-similarity is ubiquitous throughout natural phenomena, including the human brain. Recent evidence indicates that fractal dimension of functional brain networks, a measure of self-similarity, is diminished in patients diagnosed with disorders of consciousness arising from severe brain injury. Here, we set out to investigate whether loss of self-similarity is observed in the structural connectome of patients with disorders of consciousness. Using diffusion MRI tractography from N = 11 patients in a minimally conscious state (MCS), N = 10 patients diagnosed with unresponsive wakefulness syndrome (UWS), and N = 20 healthy controls, we show that fractal dimension of structural brain networks is diminished in DOC patients. Remarkably, we also show that fractal dimension of structural brain networks is preserved in patients who exhibit evidence of covert consciousness by performing mental imagery tasks during functional MRI scanning. These results demonstrate that differences in fractal dimension of structural brain networks are quantitatively associated with chronic loss of consciousness induced by severe brain injury, highlighting the close connection between structural organisation of the human brain and its ability to support cognitive function.

Therapeutic Use of Transcranial Direct Current Stimulation in the Rehabilitation of Prolonged Disorders of Consciousness

Patients with Prolonged Disorders of Consciousness (PDOC) have catastrophic disabilities and very complex needs for care. Therapeutic options are very limited, and patients often show little functional improvement over time. Neuroimaging studies have demonstrated that a significant number of PDOC patients retain a high level of cognitive functioning, and in some cases even awareness, and are simply unable to show this with their external behavior - a condition known as cognitive-motor dissociation (CMD). Despite vast implications for diagnosis, the discovery of covert cognition in PDOC patients is not typically associated with a more favorable prognosis, and the majority of patients will remain in a permanent state of low responsiveness. Recently, transcranial direct current stimulation (tDCS) has attracted attention as a potential therapeutic tool in PDOC. Research to date suggests that tDCS can lead to clinical improvements in patients with a minimally conscious state (MCS), especially when administered over multiple sessions. While promising, the outcomes of these studies have been highly inconsistent, partially due to small sample sizes, heterogeneous methodologies (in terms of both tDCS parameters and outcome measures), and limitations related to electrode placement and heterogeneity of brain damage inherent to PDOC. In addition, we argue that neuroimaging and electrophysiological assessments may serve as more sensitive biomarkers to identify changes after tDCS that are not yet apparent behaviorally. Finally, given the evidence that concurrent brain stimulation and physical therapy can enhance motor rehabilitation, we argue that future studies should focus on the integration of tDCS with conventional rehabilitation programmes from the subacute phase of care onwards, to ascertain whether any synergies exist.

Metabolic Abnormalities in Patients with Chronic Disorders of Consciousness

The vegetative state (VS) and minimally conscious state (MCS) are two major types of chronic disorders of consciousness (DoC). The assessment of these two consciousness states generally relies on the Coma Recovery Scale-Revised (CRS-R) score, but a high misdiagnosis rate limits the generalized use of this score. To identify metabolites in human plasma that can accurately distinguish VS from MCS patients, comprehensive plasma metabolic profiles were obtained with targeted metabolomics analysis and untargeted and targeted lipidomics analysis. Univariate and multivariate analyses were used to assess the significance of differences. Compared with healthy controls (HCs), the DoC groups, Emerged from Minimally Conscious State (EMCS) group and Alzheimer’s disease (AD) group had significantly different metabolic profiles. Purine metabolism pathway differed the most between the DoC (MCS and VS) and HC groups. In this pathway, adenosine, ADP, and AMP, which are the derived products of ATP degradation, were decreased in the MCS and VS groups compared to healthy controls. More importantly, we identified certain lipids for which the levels were enriched in the VS or MCS groups. Specifically, phosphatidylcholine, (38:5)-H (PC(38:5)-H), and arachidonic acid (AA) differed substantially between the VS and MCS groups and may be used to distinguish these two groups of patients. Together, our findings suggest that metabolic profiling is significantly altered in patients with chronic DoC.

Discriminating cognitive motor dissociation from disorders of consciousness using structural MRI

An accurate evaluation and detection of awareness after a severe brain injury is crucial to a patient's diagnosis, therapy, and end-of-life decisions. Misdiagnosis is frequent as behavior-based assessments often overlook subtle signs of consciousness. This study aimed to identify brain MRI characteristics of patients with residual consciousness after a severe brain injury and to develop a simple MRI-based scoring system according to the findings. We retrieved data from 128 patients and split them into a development or validation set. Structural brain MRIs were qualitatively assessed for lesions in 18 brain regions. We used logistic regression and support vector machine algorithms to first identify the most relevant brain regions predicting a patient's outcome in the development set. We next built a diagnostic MRI-based score and estimated its optimal diagnostic cut-off point. The classifiers were then tested on the validation set and their performance compared using the receiver operating characteristic curve. Relevant brain regions predicting negative outcome highly overlapped between both classifiers and included the left mesencephalon, right basal ganglia, right thalamus, right parietal cortex, and left frontal cortex. The support vector machine classifier showed higher accuracy (0.93, 95% CI: 0.81-0.96) and specificity (0.97, 95% CI: 0.85-1) than logistic regression (accuracy: 0.87, 95% CI: 0.73 - 0.95; specificity: 0.90, 95% CI: 0.75-0.97), but equal sensitivity (0.67, 95% CI: 0.24-0.94 and 0.22-0.96, respectively) for distinguishing patients with and without residual consciousness. The novel MRI-based score assessing brain lesions in patients with disorders of consciousness accurately detects patients with residual consciousness. It could complement valuably behavioral evaluation as it is time-efficient and requires only conventional MRI.

The prognostic value of resting-state EEG in acute post-traumatic unresponsive states

Accurate early prognostication is vital for appropriate long-term care decisions after traumatic brain injury. While measures of resting-state EEG oscillations and their network properties, derived from graph theory, have been shown to provide clinically useful information regarding diagnosis and recovery in patients with chronic disorders of consciousness, little is known about the value of these network measures when calculated from a standard clinical low-density EEG in the acute phase post-injury. To investigate this link, we first validated a set of measures of oscillatory network features between high-density and low-density resting-state EEG in healthy individuals, thus ensuring accurate estimation of underlying cortical function in clinical recordings from patients. Next, we investigated the relationship between these features and the clinical picture and outcome of a group of 18 patients in acute post-traumatic unresponsive states who were not following commands 2 days+ after sedation hold. While the complexity of the alpha network, as indexed by the standard deviation of the participation coefficients, was significantly related to the patients' clinical picture at the time of EEG, no network features were significantly related to outcome at 3 or 6 months post-injury. Rather, mean relative alpha power across all electrodes improved the accuracy of outcome prediction at 3 months relative to clinical features alone. These results highlight the link between the alpha rhythm and clinical signs of consciousness and suggest the potential for simple measures of resting-state EEG band power to provide a coarse snapshot of brain health for stratification of patients for rehabilitation, therapy and assessments of both covert and overt cognition.

Long-term recovery from a minimally responsive state with recovery of an injured ascending reticular activating system: A case report

We report on a patient with hypoxic-ischemic brain injury (HI-BI) who showed recovery from a minimally consciousness state over 6 years concurrent with recovery of an injured ascending reticular activating system (ARAS), which was demonstrated on diffusion tensor tractography (DTT).A 31-year-old female patient, who suffered from HI-BI, showed impaired consciousness with a minimally conscious state: intermittently obeying simple motor tasks, such as "please grasp my hand." Her consciousness showed recovery with the passage of time; rapid recovery was observed during the recent 2 years.In the upper ARAS, the neural connectivity to both the basal forebrain and prefrontal cortex had increased on 8-year DTT compared with 1.5-year DTT. In the lower dorsal and ventral ARAS, no significant change was observed between 1.5 and 8 years DTTs.Recovery of an injured ARAS was demonstrated in a patient who showed recovery from a minimally consciousness state over 6 years following HI-BI. Our results suggest the brain target areas for recovery of impaired awareness in patients with disorders of consciousness.

Whole-Brain Models to Explore Altered States of Consciousness from the Bottom Up

The scope of human consciousness includes states departing from what most of us experience as ordinary wakefulness. These altered states of consciousness constitute a prime opportunity to study how global changes in brain activity relate to different varieties of subjective experience. We consider the problem of explaining how global signatures of altered consciousness arise from the interplay between large-scale connectivity and local dynamical rules that can be traced to known properties of neural tissue. For this purpose, we advocate a research program aimed at bridging the gap between bottom-up generative models of whole-brain activity and the top-down signatures proposed by theories of consciousness. Throughout this paper, we define altered states of consciousness, discuss relevant signatures of consciousness observed in brain activity, and introduce whole-brain models to explore the biophysics of altered consciousness from the bottom-up. We discuss the potential of our proposal in view of the current state of the art, give specific examples of how this research agenda might play out, and emphasize how a systematic investigation of altered states of consciousness via bottom-up modeling may help us better understand the biophysical, informational, and dynamical underpinnings of consciousness.

The subcortical basis of outcome and cognitive impairment in TBI: A longitudinal cohort study

OBJECTIVE

To understand how, biologically, the acute event of traumatic brain injury gives rise to a long-term disease, we address the relationship between evolving cortical and subcortical brain damage and measures of functional outcome and cognitive functioning at 6 months after injury.

METHODS

For this longitudinal analysis, clinical and MRI data were collected in a tertiary neurointensive care setting in a continuous sample of 157 patients surviving moderate to severe traumatic brain injury between 2000 and 2018. For each patient, we collected T1- and T2-weighted MRI data acutely and at the 6-month follow-up, as well as acute measures of injury severity (Glasgow Coma Scale), follow-up measures of functional impairment (Glasgow Outcome Scale-extended), and, in a subset of patients, neuropsychological measures of attention, executive functions, and episodic memory.

RESULTS

In the final cohort of 113 subcortical and 92 cortical datasets that survived (blind) quality control, extensive atrophy was observed over the first 6 months after injury across the brain. However, only atrophy within subcortical regions, particularly in the left thalamus, was associated with functional outcome and neuropsychological measures of attention, executive functions, and episodic memory. Furthermore, when brought together in an analytical model, longitudinal brain measurements could distinguish good from bad outcome with 90% accuracy, whereas acute brain and clinical measurements alone could achieve only 20% accuracy.

CONCLUSION

Despite great injury heterogeneity, secondary thalamic pathology is a measurable minimum common denominator mechanism directly relating biology to clinical measures of outcome and cognitive functioning, potentially linking the acute event and the longer-term disease of traumatic brain injury.

Two Coarse Spatial Patterns of Altered Brain Microstructure Predict Post-traumatic Amnesia in the Subacute Stage of Severe Traumatic Brain Injury

Introduction: Diffuse traumatic axonal injury (TAI) is one of the key mechanisms leading to impaired consciousness after severe traumatic brain injury (TBI). In addition, preferential regional expression of TAI in the brain may also influence clinical outcome. Aim: We addressed the question whether the regional expression of microstructural changes as revealed by whole-brain diffusion tensor imaging (DTI) in the subacute stage after severe TBI may predict the duration of post-traumatic amnesia (PTA). Method: Fourteen patients underwent whole-brain DTI in the subacute stage after severe TBI. Mean fractional anisotropy (FA) and mean diffusivity (MD) were calculated for five bilateral brain regions: fronto-temporal, parieto-occipital, and midsagittal hemispheric white matter, as well as brainstem and basal ganglia. Region-specific calculation of mean FA and MD only considered voxels that showed no tissue damage, using an exclusive mask with all voxels that belonged to local brain lesions or microbleeds. Mean FA or MD of the five brain regions were entered in separate partial least squares (PLS) regression analyses to identify patterns of regional microstructural changes that account for inter-individual variations in PTA. Results: For FA, PLS analysis revealed two spatial patterns that significantly correlated with individual PTA. The lower the mean FA values in all five brain regions, the longer that PTA lasted. A pattern characterized by lower FA values in the deeper brain regions relative to the FA values in the hemispheric regions also correlated with longer PTA. Similar trends were found for MD, but opposite in sign. The spatial FA changes as revealed by PLS components predicted the duration of PTA. Individual PTA duration, as predicted by a leave-one-out cross-validation analysis, correlated with true PTA values (Spearman r = 0.68, p permutation = 0.008). Conclusion: Two coarse spatial patterns of microstructural damage, indexed as reduction in FA, were relevant to recovery of consciousness after TBI. One pattern expressed was consistent with diffuse microstructural damage across the entire brain. A second pattern was indicative of a preferential damage of deep midline brain structures.

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

The analysis of spontaneous EEG activity and evoked potentialsis a cornerstone of the instrumental evaluation of patients with disorders of consciousness (DoC). Thepast 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 bothconsolidated and investigational electrophysiological techniquesfor 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.

Subcortical atrophy correlates with the perturbational complexity index in patients with disorders of consciousness

BACKGROUND

The complexity of neurophysiological brain responses to direct cortical stimulation, referred to as the perturbational complexity index (PCI), has been shown able to discriminate between consciousness and unconsciousness in patients surviving severe brain injury as well as several other conditions (e.g., wake, dreamless sleep, sleep and ketamine dreaming, anesthesia).

OBJECTIVE

This study asks whether, in patients with a disorder of consciousness (DOC), the complexity of the neurophysiological response to cortical stimulation is preferentially associated with atrophy within specific brain structures.

METHODS

We perform a retrospective analysis of 40 DOC patients and correlate their maximal PCI to MR-based measurements of cortical thinning and subcortical atrophy.

RESULTS

PCI was systematically and inversely associated with the degree of local atrophy within the globus pallidus, a region previously linked to electrocortical and behavioral arousal. Conversely, we fail to detect any association between variance in cortical ribbon thickness and PCI.

CONCLUSION

These findings corroborate the previously reported association between pallidal atrophy and low behavioral arousal and suggest that this region's role in maintaining the overall balance of excitation and inhibition may critically affect the emergence of complex cortical interactions in chronic disorders of consciousness. This finding thus also suggests a target for potential neuromodulatory intervention in DOC patients.

Modelling effects of consciousness disorders in brainstem computational model – Preliminary findings

Objectives

Disorders of consciousness are very big medical and social problem. Their variability, problems in precise definition and proper diagnosis make difficult assessing their causes and effectiveness of the therapy. In the paper we present our point of view to a problem of consciousness and its most common disorders.

Methods

For this moment scientists do not know exactly, if these disorders can be a result of simple but general mechanism, or a complex set of mechanisms, both on neural, molecular or system level. Presented in the paper simulations using neural network models, including biologically relevant consciousness’ modelling, help assess influence of specified causes.

Results

Nonmotoric brain activity can play important role within diagnostic process as a supplementary method for motor capabilities. Simple brain sensory (e.g. visual) processing of both healthy subject and people with consciousness disorders help checking hypotheses in the area of consciousness’ disorders’ mechanisms, including associations between consciousness and its neural correlates.

Conclusions

The results are promising. Project announced herein will be developed and its next result will be presented in subsequent articles.

Outcome prediction with resting-state functional connectivity after cardiac arrest

Predicting outcome in comatose patients after successful cardiopulmonary resuscitation is challenging. Our primary aim was to assess the potential contribution of resting-state-functional magnetic resonance imaging (RS-fMRI) in predicting neurological outcome. RS-fMRI was used to evaluate functional and effective connectivity within the default mode network in a cohort of 90 comatose patients and their impact on functional neurological outcome after 3 months. The RS-fMRI processing protocol comprises the evaluation of functional and effective connectivity within the default mode network. Seed-to-voxel and ROI-to-ROI feature analysis was performed as starting point for a supervised machine-learning approach. Classification of the Cerebral Performance Category (CPC) 1–3 (good to acceptable outcome) versus CPC 4–5 (adverse outcome) achieved a positive predictive value of 91.7%, sensitivity of 90.2%, and accuracy of 87.8%. A direct link to the level of consciousness and outcome after 3 months was identified for measures of segregation in the precuneus, in medial and right frontal regions. Thalamic connectivity appeared significantly reduced in patients without conscious response. Decreased within-network connectivity in the default mode network and within cortico-thalamic circuits correlated with clinical outcome after 3 months. Our results indicate a potential role of these markers for decision-making in comatose patients early after cardiac arrest.

Neuroimage-Based Consciousness Evaluation of Patients with Secondary Doubtful Hydrocephalus Before and After Lumbar Drainage

Hydrocephalus is often treated with a cerebrospinal fluid shunt (CFS) for excessive amounts of cerebrospinal fluid in the brain. However, it is very difficult to distinguish whether the ventricular enlargement is due to hydrocephalus or other causes, such as brain atrophy after brain damage and surgery. The non-trivial evaluation of the consciousness level, along with a continuous drainage test of the lumbar cistern is thus clinically important before the decision for CFS is made. We studied 32 secondary mild hydrocephalus patients with different consciousness levels, who received T1 and diffusion tensor imaging magnetic resonance scans before and after lumbar cerebrospinal fluid drainage. We applied a novel machine-learning method to find the most discriminative features from the multi-modal neuroimages. Then, we built a regression model to regress the JFK Coma Recovery Scale-Revised (CRS-R) scores to quantify the level of consciousness. The experimental results showed that our method not only approximated the CRS-R scores but also tracked the temporal changes in individual patients. The regression model has high potential for the evaluation of consciousness in clinical practice.

Habituation of auditory startle reflex is a new sign of minimally conscious state

Neurological examination of non-communicating patients relies on a few decisive items that enable the crucial distinction between vegetative state (VS)-also coined unresponsive wakefulness syndrome (UWS)-and minimally conscious state. Over the past 10 years, this distinction has proven its diagnostic value as well as its important prognostic value on consciousness recovery. However, clinicians are currently limited by three factors: (i) the current behavioural repertoire of minimally conscious state items is limited and restricted to a few cognitive domains in the goldstandard revised version of the Coma Recovery Scale; (ii) a proportion of ∼15-20% clinically VS/UWS patients are actually in a richer state than VS/UWS as evidenced by functional brain imaging; and (iii) the neurophysiological and cognitive interpretation of each minimally conscious state item is still unclear and debated. In the current study we demonstrate that habituation of the auditory startle reflex (hASR) tested at bedside constitutes a novel, simple and powerful behavioural sign that can accurately distinguish minimally conscious state from VS/UWS. In addition to enlarging the minimally conscious state items repertoire, and therefore decreasing the low sensitivity of current behavioural measures, we also provide an original and rigorous description of the neurophysiological basis of hASR through a combination of functional (high density EEG and 18F-fluorodeoxyglucose PET imaging) and structural (diffusion tensor imaging MRI) measures. We show that preservation of hASR is associated with the functional and structural integrity of a brain-scale fronto-parietal network, including prefrontal regions related to control of action and inhibition, and meso-parietal areas associated with minimally conscious and conscious states. Lastly, we show that hASR predicts 6-month improvement of consciousness. Taken together, our results show that hASR is a cortically-mediated behaviour, and suggest that it could be a new clinical item to clearly and accurately identify non-communicating patients who are in the minimally conscious state.

Decoding the circuitry of consciousness: From local microcircuits to brain-scale networks

Identifying the physiological processes underlying the emergence and maintenance of consciousness is one of the most fundamental problems of neuroscience, with implications ranging from fundamental neuroscience to the treatment of patients with disorders of consciousness (DOCs). One major challenge is to understand how cortical circuits at drastically different spatial scales, from local networks to brain-scale networks, operate in concert to enable consciousness, and how those processes are impaired in DOC patients. In this review, we attempt to relate available neurophysiological and clinical data with existing theoretical models of consciousness, while linking the micro- and macrocircuit levels. First, we address the relationships between awareness and wakefulness on the one hand, and cortico-cortical and thalamo-cortical connectivity on the other hand. Second, we discuss the role of three main types of GABAergic interneurons in specific circuits responsible for the dynamical reorganization of functional networks. Third, we explore advances in the functional role of nested oscillations for neural synchronization and communication, emphasizing the importance of the balance between local (high-frequency) and distant (low-frequency) activity for efficient information processing. The clinical implications of these theoretical considerations are presented. We propose that such cellular-scale mechanisms could extend current theories of consciousness.

Combined behavioral and electrophysiological evidence for a direct cortical effect of prefrontal tDCS on disorders of consciousness

Severe brain injuries can lead to long-lasting disorders of consciousness (DoC) such as vegetative state/unresponsive wakefulness syndrome (VS/UWS) or minimally conscious state (MCS). While behavioral assessment remains the gold standard to determine conscious state, EEG has proven to be a promising complementary tool to monitor the effect of new therapeutics. Encouraging results have been obtained with invasive electrical stimulation of the brain, and recent studies identified transcranial direct current stimulation (tDCS) as an effective approach in randomized controlled trials. This non-invasive and inexpensive tool may turn out to be the preferred treatment option. However, its mechanisms of action and physiological effects on brain activity remain unclear and debated. Here, we stimulated 60 DoC patients with the anode placed over left-dorsolateral prefrontal cortex in a prospective open-label study. Clinical behavioral assessment improved in twelve patients (20%) and none deteriorated. This behavioral response after tDCS coincided with an enhancement of putative EEG markers of consciousness: in comparison with non-responders, responders showed increases of power and long-range cortico-cortical functional connectivity in the theta-alpha band, and a larger and more sustained P300 suggesting improved conscious access to auditory novelty. The EEG changes correlated with electric fields strengths in prefrontal cortices, and no correlation was found on the scalp. Taken together, this prospective intervention in a large cohort of DoC patients strengthens the validity of the proposed EEG signatures of consciousness, and is suggestive of a direct causal effect of tDCS on consciousness.

Longitudinal increases in structural connectome segregation and functional connectome integration are associated with better recovery after mild TBI

Traumatic brain injury damages white matter pathways that connect brain regions, disrupting transmission of electrochemical signals and causing cognitive and emotional dysfunction. Connectome-level mechanisms for how the brain compensates for injury have not been fully characterized. Here, we collected serial MRI-based structural and functional connectome metrics and neuropsychological scores in 26 mild traumatic brain injury subjects (29.4 ± 8.0 years, 20 males) at 1 and 6 months postinjury. We quantified the relationship between functional and structural connectomes using network diffusion (ND) model propagation time, a measure that can be interpreted as how much of the structural connectome is being utilized for the spread of functional activation, as captured via the functional connectome. Overall cognition showed significant improvement from 1 to 6 months (t25 = -2.15, p = .04). None of the structural or functional global connectome metrics was significantly different between 1 and 6 months, or when compared to 34 age- and gender-matched controls (28.6 ± 8.8 years, 25 males). We predicted longitudinal changes in overall cognition from changes in global connectome measures using a partial least squares regression model (cross-validated R2 = .27). We observe that increased ND model propagation time, increased structural connectome segregation, and increased functional connectome integration were related to better cognitive recovery. We interpret these findings as suggesting two connectome-based postinjury recovery mechanisms: one of neuroplasticity that increases functional connectome integration and one of remote white matter degeneration that increases structural connectome segregation. We hypothesize that our inherently multimodal measure of ND model propagation time captures the interplay between these two mechanisms.

Feasibility of Non-Gaussian Diffusion Metrics in Chronic Disorders of Consciousness

Diagnostic accuracy of different chronic disorders of consciousness (DOC) can be affected by the false negative errors in up to 40% cases. In the present study, we aimed to investigate the feasibility of a non-Gaussian diffusion approach in chronic DOC and to estimate a sensitivity of diffusion kurtosis imaging (DKI) metrics for the differentiation of vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state (MCS) from a healthy brain state. We acquired diffusion MRI data from 18 patients in chronic DOC (11 VS/UWS, 7 MCS) and 14 healthy controls. A quantitative comparison of the diffusion metrics for grey (GM) and white (WM) matter between the controls and patient group showed a significant (p < 0.05) difference in supratentorial WM and GM for all evaluated diffusion metrics, as well as for brainstem, corpus callosum, and thalamus. An intra-subject VS/UWS and MCS group comparison showed only kurtosis metrics and fractional anisotropy differences using tract-based spatial statistics, owing mainly to macrostructural differences on most severely lesioned hemispheres. As a result, we demonstrated an ability of DKI metrics to localise and detect changes in both WM and GM and showed their capability in order to distinguish patients with a different level of consciousness.