Longitudinal assessments highlight long-term behavioural recovery in disorders of consciousness.

Accurate diagnosis and prognosis of disorders of consciousness is complicated by the variability amongst patients' trajectories. However, the majority of research and scientific knowledge in this field is based on cross-sectional studies. The translational gap in applying this knowledge to inform clinical management can only be bridged by research that systematically examines follow-up. In this study, we present findings from a novel longitudinal study of the long-term recovery trajectory of 39 patients, repeatedly assessed using the Coma Recovery Scale-Revised once every 3 months for 2 years, generating 185 assessments. Despite the expected inter-patient variability, there was a statistically significant improvement in behaviour over time. Further, improvements began approximately 22 months after injury. Individual variation in the trajectory of recovery was influenced by initial diagnosis. Patients with an initial diagnosis of unresponsive wakefulness state, who progressed to the minimally conscious state, did so at a median of 485 days following onset-later than 12-month period after which current guidelines propose permanence. Although current guidelines are based on the expectation that patients with traumatic brain injury show potential for recovery over longer periods than those with non-traumatic injury, we did not observe any differences between trajectories in these two subgroups. However, age was a significant predictor, with younger patients showing more promising recovery. Also, progressive increases in arousal contributed exponentially to improvements in behavioural awareness, especially in minimally conscious patients. These findings highlight the importance of indexing arousal when measuring awareness, and the potential for interventions to regulate arousal to aid long-term behavioural recovery in disorders of consciousness

Bedside EEG predicts longitudinal behavioural changes in disorders of consciousness.

Providing an accurate prognosis for prolonged disorder of consciousness (pDOC) patients remains a clinical challenge. Large cross-sectional studies have demonstrated the diagnostic and prognostic value of functional brain networks measured using high-density electroencephalography (hdEEG). Nonetheless, the prognostic value of these neural measures has yet to be assessed by longitudinal follow-up. We address this gap by assessing the utility of hdEEG to prognosticate long-term behavioural outcome, employing longitudinal data collected from a cohort of patients assessed systematically with resting hdEEG and the Coma Recovery Scale-Revised (CRS-R) at the bedside over a period of two years. We used canonical correlation analysis to relate clinical (including CRS-R scores combined with demographic variables) and hdEEG variables to each other. This analysis revealed that the patient's age, and the hdEEG theta band power and alpha band connectivity, contributed most significantly to the relationship between hdEEG and clinical variables. Further, we found that hdEEG measures recorded at the time of assessment augmented clinical measures in predicting CRS-R scores at the next assessment. Moreover, the rate of hdEEG change not only predicted later changes in CRS-R scores, but also outperformed clinical measures in terms of prognostic power. Together, these findings suggest that improvements in functional brain networks precede changes in behavioural awareness in pDOC. We demonstrate here that bedside hdEEG assessments conducted at specialist nursing homes are feasible, have clinical utility, and can complement clinical knowledge and systematic behavioural assessments to inform prognosis and care

Fractal dimension of cortical functional connectivity networks & severity of disorders of consciousness.

Recent evidence suggests that the quantity and quality of conscious experience may be a function of the complexity of activity in the brain and that consciousness emerges in a critical zone between low and high-entropy states. We propose fractal shapes as a measure of proximity to this critical point, as fractal dimension encodes information about complexity beyond simple entropy or randomness, and fractal structures are known to emerge in systems nearing a critical point. To validate this, we tested several measures of fractal dimension on the brain activity from healthy volunteers and patients with disorders of consciousness of varying severity. We used a Compact Box Burning algorithm to compute the fractal dimension of cortical functional connectivity networks as well as computing the fractal dimension of the associated adjacency matrices using a 2D box-counting algorithm. To test whether brain activity is fractal in time as well as space, we used the Higuchi temporal fractal dimension on BOLD time-series. We found significant decreases in the fractal dimension between healthy volunteers (n = 15), patients in a minimally conscious state (n = 10), and patients in a vegetative state (n = 8), regardless of the mechanism of injury. We also found significant decreases in adjacency matrix fractal dimension and Higuchi temporal fractal dimension, which correlated with decreasing level of consciousness. These results suggest that cortical functional connectivity networks display fractal character and that this is associated with level of consciousness in a clinically relevant population, with higher fractal dimensions (i.e. more complex) networks being associated with higher levels of consciousness. This supports the hypothesis that level of consciousness and system complexity are positively associated, and is consistent with previous EEG, MEG, and fMRI studies

Methylphenidate-mediated motor control network enhancement in patients with traumatic brain injury.

PRIMARY OBJECTIVE: To investigate functional improvement late (>6 months) after traumatic brain injury (TBI). To this end, we conducted a double-blind, placebo-controlled experimental medicine study to test the hypothesis that a widely used cognitive enhancer would benefit patients with TBI. RESEARCH DESIGN: We focused on motor control function using a sequential finger opposition fMRI paradigm in both patients and age-matched controls. METHODS AND PROCEDURES: Patients' fMRI and DTI scans were obtained after randomised administration of methylphenidate or placebo. Controls were scanned without intervention. To assess differences in motor speed, we compared reaction times from the baseline condition of a sustained attention task. MAIN OUTCOMES AND RESULTS: Patients' reaction times correlated with wide-spread motor-related white matter abnormalities. Administration of methylphenidate resulted in faster reaction times in patients, which were not significantly different from those achieved by controls. This was also reflected in the fMRI findings in that patients on methylphenidate activated the left inferior frontal gyrus significantly more than when on placebo. Furthermore, stronger functional connections between pre-/post-central cortices and cerebellum were noted for patients on methylphenidate. CONCLUSIONS: Our findings suggest that residual functionality in patients with TBI may be enhanced by a single dose of methylphenidate.The study was funded by the Evelyn Trust- grant number 06/20. C.D. was funded by the Clinical Academic Research Awards organized by the East of England Multi Professional Deanery. B.J.S. consults for Cambridge Cognition, Otsuka, Servier and Lundbeck. She holds a grant from Janssen/J&J and has share options in Cambridge Cognition. D.K.M. is supported by the Neuroscience Theme of the NIHR Cambridge Biomedical Research Centre and NIHR Senior Investigator awards, and by Framework Program 7 funding from the European Commission (TBIcare). He has received lecture and consultancy fees and support for research from Glaxo SmithKline, Solvay and Linde. E.A.S. is funded by the Stephen Erskine Fellowship, Queens' College, Cambridge, UK

A hierarchy of event-related potential markers of auditory processing in disorders of consciousness.

Functional neuroimaging of covert perceptual and cognitive processes can inform the diagnoses and prognoses of patients with disorders of consciousness, such as the vegetative and minimally conscious states (VS;MCS). Here we report an event-related potential (ERP) paradigm for detecting a hierarchy of auditory processes in a group of healthy individuals and patients with disorders of consciousness. Simple cortical responses to sounds were observed in all 16 patients; 7/16 (44%) patients exhibited markers of the differential processing of speech and noise; and 1 patient produced evidence of the semantic processing of speech (i.e. the N400 effect). In several patients, the level of auditory processing that was evident from ERPs was higher than the abilities that were evident from behavioural assessment, indicating a greater sensitivity of ERPs in some cases. However, there were no differences in auditory processing between VS and MCS patient groups, indicating a lack of diagnostic specificity for this paradigm. Reliably detecting semantic processing by means of the N400 effect in passively listening single-subjects is a challenge. Multiple assessment methods are needed in order to fully characterise the abilities of patients with disorders of consciousness

Consciousness-specific dynamic interactions of brain integration and functional diversity

Abstract: Prominent theories of consciousness emphasise different aspects of neurobiology, such as the integration and diversity of information processing within the brain. Here, we combine graph theory and dynamic functional connectivity to compare resting-state functional MRI data from awake volunteers, propofol-anaesthetised volunteers, and patients with disorders of consciousness, in order to identify consciousness-specific patterns of brain function. We demonstrate that cortical networks are especially affected by loss of consciousness during temporal states of high integration, exhibiting reduced functional diversity and compromised informational capacity, whereas thalamo-cortical functional disconnections emerge during states of higher segregation. Spatially, posterior regions of the brain’s default mode network exhibit reductions in both functional diversity and integration with the rest of the brain during unconsciousness. These results show that human consciousness relies on spatio-temporal interactions between brain integration and functional diversity, whose breakdown may represent a generalisable biomarker of loss of consciousness, with potential relevance for clinical practice

A synergistic workspace for human consciousness revealed by Integrated Information Decomposition.

How is the information-processing architecture of the human brain organised, and how does its organisation support consciousness? Here, we combine network science and a rigorous information-theoretic notion of synergy to delineate a synergistic global workspace, comprising gateway regions that gather synergistic information from specialised modules across the human brain. This information is then integrated within the workspace and widely distributed via broadcaster regions. Through functional MRI analysis, we show that gateway regions of the synergistic workspace correspond to the human brains default mode network, whereas broadcasters coincide with the executive control network. We find that loss of consciousness due to general anaesthesia or disorders of consciousness corresponds to diminished ability of the synergistic workspace to integrate information, which is restored upon recovery. Thus, loss of consciousness coincides with a breakdown of information integration within the synergistic workspace of the human brain. This work contributes to conceptual and empirical reconciliation between two prominent scientific theories of consciousness, the Global Neuronal Workspace and Integrated Information Theory, while also advancing our understanding of how the human brain supports consciousness through the synergistic integration of information

Spectral signatures of reorganised brain networks in disorders of consciousness.

Theoretical advances in the science of consciousness have proposed that it is concomitant with balanced cortical integration and differentiation, enabled by efficient networks of information transfer across multiple scales. Here, we apply graph theory to compare key signatures of such networks in high-density electroencephalographic data from 32 patients with chronic disorders of consciousness, against normative data from healthy controls. Based on connectivity within canonical frequency bands, we found that patient networks had reduced local and global efficiency, and fewer hubs in the alpha band. We devised a novel topographical metric, termed modular span, which showed that the alpha network modules in patients were also spatially circumscribed, lacking the structured long-distance interactions commonly observed in the healthy controls. Importantly however, these differences between graph-theoretic metrics were partially reversed in delta and theta band networks, which were also significantly more similar to each other in patients than controls. Going further, we found that metrics of alpha network efficiency also correlated with the degree of behavioural awareness. Intriguingly, some patients in behaviourally unresponsive vegetative states who demonstrated evidence of covert awareness with functional neuroimaging stood out from this trend: they had alpha networks that were remarkably well preserved and similar to those observed in the controls. Taken together, our findings inform current understanding of disorders of consciousness by highlighting the distinctive brain networks that characterise them. In the significant minority of vegetative patients who follow commands in neuroimaging tests, they point to putative network mechanisms that could support cognitive function and consciousness despite profound behavioural impairment.This work was supported by grants from the Wellcome Trust [WT093811MA to T.B.]; the James S. McDonnell Foundation [to A.M.O. and J.D.P.]; the UK Medical Research Council [U.1055.01.002.00001.01 to A.M.O. and J.D.P.]; the Canada Excellence Research Chairs program [to A.M.O.]; the National Institute for Health Research Cambridge Biomedical Research Centre [to J.D.P.]; and the National Institute for Health Research Senior Investigator and Healthcare Technology Cooperative awards [to J.D.P.].This is the final version of the article. It first appeared from PLOS via http://dx.doi.org

Refinement of a 400-kb Critical Region Allows Genotypic Differentiation between Isolated Lissencephaly, Miller-Dieker Syndrome, and Other Phenotypes Secondary to Deletions of 17p13.3

Deletions of 17p13.3, including the LIS1 gene, result in the brain malformation lissencephaly, which is characterized by reduced gyration and cortical thickening; however, the phenotype can vary from isolated lissencephaly sequence (ILS) to Miller-Dieker syndrome (MDS). At the clinical level, these two phenotypes can be differentiated by the presence of significant dysmorphic facial features and a more severe grade of lissencephaly in MDS. Previous work has suggested that children with MDS have a larger deletion than those with ILS, but the precise boundaries of the MDS critical region and causative genes other than LIS1 have never been fully determined. We have completed a physical and transcriptional map of the 17p13.3 region from LIS1 to the telomere. Using fluorescence in situ hybridization, we have mapped the deletion size in 19 children with ILS, 11 children with MDS, and 4 children with 17p13.3 deletions not involving LIS1. We show that the critical region that differentiates ILS from MDS at the molecular level can be reduced to 400 kb. Using somatic cell hybrids from selected patients, we have identified eight genes that are consistently deleted in patients classified as having MDS. In addition, deletion of the genes CRK and 14-3-3ɛ delineates patients with the most severe lissencephaly grade. On the basis of recent functional data and the creation of a mouse model suggesting a role for 14-3-3ɛ in cortical development, we suggest that deletion of one or both of these genes in combination with deletion of LIS1 may contribute to the more severe form of lissencephaly seen only in patients with MDS