Accelerated Aging after Traumatic Brain Injury: An ENIGMA Multi-Cohort Mega-Analysis.

OBJECTIVE: The long-term consequences of traumatic brain injury (TBI) on brain structure remain uncertain. Given evidence that a single significant brain injury event increases the risk of dementia, brain-age estimation could provide a novel and efficient indexing of the long-term consequences of TBI. Brain-age procedures use predictive modeling to calculate brain-age scores for an individual using structural magnetic resonance imaging (MRI) data. Complicated mild, moderate, and severe TBI (cmsTBI) is associated with a higher predicted age difference (PAD), but the progression of PAD over time remains unclear. We sought to examine whether PAD increases as a function of time since injury (TSI) and if injury severity and sex interacted to influence this progression. METHODS: Through the ENIGMA Adult Moderate and Severe (AMS)-TBI working group, we examine the largest TBI sample to date (n = 343), along with controls, for a total sample size of n = 540, to replicate and extend prior findings in the study of TBI brain age. Cross-sectional T1w-MRI data were aggregated across 7 cohorts, and brain age was established using a similar brain age algorithm to prior work in TBI. RESULTS: Findings show that PAD widens with longer TSI, and there was evidence for differences between sexes in PAD, with men showing more advanced brain age. We did not find strong evidence supporting a link between PAD and cognitive performance. INTERPRETATION: This work provides evidence that changes in brain structure after cmsTBI are dynamic, with an initial period of change, followed by relative stability in brain morphometry, eventually leading to further changes in the decades after a single cmsTBI. ANN NEUROL 2024;96:365-377.

Globus pallidus externus drives increase in network-wide alpha power with propofol-induced loss-of-consciousness in humans.

States of consciousness are likely mediated by multiple parallel yet interacting cortico-subcortical recurrent networks. Although the mesocircuit model has implicated the pallidocortical circuit as one such network, this circuit has not been extensively evaluated to identify network-level electrophysiological changes related to loss of consciousness (LOC). We characterize changes in the mesocircuit in awake versus propofol-induced LOC in humans by directly simultaneously recording from sensorimotor cortices (S1/M1) and globus pallidus interna and externa (GPi/GPe) in 12 patients with Parkinson disease undergoing deep brain stimulator implantation. Propofol-induced LOC is associated with increases in local power up to 20 Hz in GPi, 35 Hz in GPe, and 100 Hz in S1/M1. LOC is likewise marked by increased pallidocortical alpha synchrony across all nodes, with increased alpha/low beta Granger causal (GC) flow from GPe to all other nodes. In contrast, LOC is associated with decreased network-wide beta coupling and beta GC from M1 to the rest of the network. Results implicate an important and possibly central role of GPe in mediating LOC-related increases in alpha power, supporting a significant role of the GPe in modulating cortico-subcortical circuits for consciousness. Simultaneous LOC-related suppression of beta synchrony highlights that distinct oscillatory frequencies act independently, conveying unique network activity.

Consciousness is supported by near-critical slow cortical electrodynamics.

Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, we empirically identify a mathematically specific critical point near which waking cortical oscillatory dynamics operate, which is known as the edge-of-chaos critical point, or the boundary between stability and chaos. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magnetoencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of low-frequency cortical electric oscillations away from this critical point; conversely, we show that psychedelics may increase the information richness of cortical activity by tuning low-frequency cortical oscillations closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC) and show that assessing the proximity of slow cortical oscillatory electrodynamics to the edge-of-chaos critical point may be useful as an index of consciousness in the clinical setting.

Common Data Element for Disorders of Consciousness: Recommendations from the Working Group on Therapeutic Interventions.

BACKGROUND: Over the past 30 years, there have been significant advances in the understanding of the mechanisms associated with loss and recovery of consciousness following severe brain injury. This work has provided a strong grounding for the development of novel restorative therapeutic interventions. Although all interventions are aimed at modulating and thereby restoring brain function, the landscape of existing interventions encompasses a very wide scope of techniques and protocols. Despite vigorous research efforts, few approaches have been assessed with rigorous, high-quality randomized controlled trials. As a growing number of exploratory interventions emerge, it is paramount to develop standardized approaches to reporting results. The successful evaluation of novel interventions depends on implementation of shared nomenclature and infrastructure. To address this gap, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups and charged them with developing common data elements (CDEs). Here, we report the work of the Therapeutic Interventions Working Group. METHODS: The working group reviewed existing CDEs relevant to therapeutic interventions within the National Institutes of Health National Institute of Neurological Disorders and Stroke database and reviewed the literature for assessing key areas of research in the intervention space. CDEs were then proposed, iteratively discussed and reviewed, classified, and organized in a case report form (CRF). RESULTS: We developed a unified CRF, including CDEs and key design elements (i.e., methodological or protocol parameters), divided into five sections: (1) patient information, (2) general study information, (3) behavioral interventions, (4) pharmacological interventions, and (5) device interventions. CONCLUSIONS: The newly created CRF enhances systematization of future work by proposing a portfolio of measures that should be collected in the development and implementation of studies assessing novel interventions intended to increase the level of consciousness or rate of recovery of consciousness in patients with disorders of consciousness.

Cognitive Motor Dissociation: Gap Analysis and Future Directions.

BACKGROUND: Patients with disorders of consciousness who are behaviorally unresponsive may demonstrate volitional brain responses to motor imagery or motor commands detectable on functional magnetic resonance imaging or electroencephalography. This state of cognitive motor dissociation (CMD) may have prognostic significance. METHODS: The Neurocritical Care Society's Curing Coma Campaign identified an international group of experts who convened in a series of monthly online meetings between September 2021 and April 2023 to examine the science of CMD and identify key knowledge gaps and unmet needs. RESULTS: The group identified major knowledge gaps in CMD research: (1) lack of information about patient experiences and caregiver accounts of CMD, (2) limited epidemiological data on CMD, (3) uncertainty about underlying mechanisms of CMD, (4) methodological variability that limits testing of CMD as a biomarker for prognostication and treatment trials, (5) educational gaps for health care personnel about the incidence and potential prognostic relevance of CMD, and (6) challenges related to identification of patients with CMD who may be able to communicate using brain-computer interfaces. CONCLUSIONS: To improve the management of patients with disorders of consciousness, research efforts should address these mechanistic, epidemiological, bioengineering, and educational gaps to enable large-scale implementation of CMD assessment in clinical practice.

Functional connectivity alterations in traumatic brain injury patients with late seizures.

PTE is a neurological disorder characterized by recurrent and spontaneous epileptic seizures. PTE is a major public health problem occurring in 2-50% of TBI patients. Identifying PTE biomarkers is crucial for the development of effective treatments. Functional neuroimaging studies in patients with epilepsy and in epileptic rodents have observed that abnormal functional brain activity plays a role in the development of epilepsy. Network representations of complex systems ease quantitative analysis of heterogeneous interactions within a unified mathematical framework. In this work, graph theory was used to study resting state functional magnetic resonance imaging (rs-fMRI) and reveal functional connectivity abnormalities that are associated with seizure development in traumatic brain injury (TBI) patients. We examined rs-fMRI of 75 TBI patients from Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) which aims to identify validated Post-traumatic epilepsy (PTE) biomarkers and antiepileptogenic therapies using multimodal and longitudinal data acquired from 14 international sites. The dataset includes 28 subjects who had at least one late seizure after TBI and 47 subjects who had no seizures within 2 years post-injury. Each subject's neural functional network was investigated by computing the correlation between the low frequency time series of 116 regions of interest (ROIs). Each subject's functional organization was represented as a network consisting of nodes, brain regions, and edges that show the relationship between the nodes. Then, several graph measures concerning the integration and the segregation of the functional brain networks were extracted in order to highlight changes in functional connectivity between the two TBI groups. Results showed that the late seizure-affected group had a compromised balance between integration and segregation and presents functional networks that are hyperconnected, hyperintegrated but at the same time hyposegregated compared with seizure-free patients. Moreover, TBI subjects who developed late seizures had more low betweenness hubs.

Evaluating denoising strategies in resting-state functional magnetic resonance in traumatic brain injury (EpiBioS4Rx).

Resting-state functional MRI is increasingly used in the clinical setting and is now included in some diagnostic guidelines for severe brain injury patients. However, to ensure high-quality data, one should mitigate fMRI-related noise typical of this population. Therefore, we aimed to evaluate the ability of different preprocessing strategies to mitigate noise-related signal (i.e., in-scanner movement and physiological noise) in functional connectivity (FC) of traumatic brain injury (TBI) patients. We applied nine commonly used denoising strategies, combined into 17 pipelines, to 88 TBI patients from the Epilepsy Bioinformatics Study for Anti-epileptogenic Therapy clinical trial. Pipelines were evaluated by three quality control (QC) metrics across three exclusion regimes based on the participant's head movement profile. While no pipeline eliminated noise effects on FC, some pipelines exhibited relatively high effectiveness depending on the exclusion regime. Once high-motion participants were excluded, the choice of denoising pipeline becomes secondary - although this strategy leads to substantial data loss. Pipelines combining spike regression with physiological regressors were the best performers, whereas pipelines that used automated data-driven methods performed comparatively worse. In this study, we report the first large-scale evaluation of denoising pipelines aimed at reducing noise-related FC in a clinical population known to be highly susceptible to in-scanner motion and significant anatomical abnormalities. If resting-state functional magnetic resonance is to be a successful clinical technique, it is crucial that procedures mitigating the effect of noise be systematically evaluated in the most challenging populations, such as TBI datasets.

Neural oscillations track recovery of consciousness in acute traumatic brain injury patients.

Electroencephalography (EEG), easily deployed at the bedside, is an attractive modality for deriving quantitative biomarkers of prognosis and differential diagnosis in severe brain injury and disorders of consciousness (DOC). Prior work by Schiff has identified four dynamic regimes of progressive recovery of consciousness defined by the presence or absence of thalamically-driven EEG oscillations. These four predefined categories (ABCD model) relate, on a theoretical level, to thalamocortical integrity and, on an empirical level, to behavioral outcome in patients with cardiac arrest coma etiologies. However, whether this theory-based stratification of patients might be useful as a diagnostic biomarker in DOC and measurably linked to thalamocortical dysfunction remains unknown. In this work, we relate the reemergence of thalamically-driven EEG oscillations to behavioral recovery from traumatic brain injury (TBI) in a cohort of N = 38 acute patients with moderate-to-severe TBI and an average of 1 week of EEG recorded per patient. We analyzed an average of 3.4 hr of EEG per patient, sampled to coincide with 30-min periods of maximal behavioral arousal. Our work tests and supports the ABCD model, showing that it outperforms a data-driven clustering approach and may perform equally well compared to a more parsimonious categorization. Additionally, in a subset of patients (N = 11), we correlated EEG findings with functional magnetic resonance imaging (fMRI) connectivity between nodes in the mesocircuit-which has been theoretically implicated by Schiff in DOC-and report a trend-level relationship that warrants further investigation in larger studies.

EEG Power spectra and subcortical pathology in chronic disorders of consciousness.

BACKGROUND: Despite a growing understanding of disorders of consciousness following severe brain injury, the association between long-term impairment of consciousness, spontaneous brain oscillations, and underlying subcortical damage, and the ability of such information to aid patient diagnosis, remains incomplete. METHODS: Cross-sectional observational sample of 116 patients with a disorder of consciousness secondary to brain injury, collected prospectively at a tertiary center between 2011 and 2013. Multimodal analyses relating clinical measures of impairment, electroencephalographic measures of spontaneous brain activity, and magnetic resonance imaging data of subcortical atrophy were conducted in 2018. RESULTS: In the final analyzed sample of 61 patients, systematic associations were found between electroencephalographic power spectra and subcortical damage. Specifically, the ratio of beta-to-delta relative power was negatively associated with greater atrophy in regions of the bilateral thalamus and globus pallidus (both left > right) previously shown to be preferentially atrophied in chronic disorders of consciousness. Power spectrum total density was also negatively associated with widespread atrophy in regions of the left globus pallidus, right caudate, and in the brainstem. Furthermore, we showed that the combination of demographics, encephalographic, and imaging data in an analytic framework can be employed to aid behavioral diagnosis. CONCLUSIONS: These results ground, for the first time, electroencephalographic presentation detected with routine clinical techniques in the underlying brain pathology of disorders of consciousness and demonstrate how multimodal combination of clinical, electroencephalographic, and imaging data can be employed in potentially mitigating the high rates of misdiagnosis typical of this patient cohort.

Noninvasive Brain Stimulation Therapies to Promote Recovery of Consciousness: Where We Are and Where We Should Go.

Therapeutic options for patients with disorders of consciousness (DoC) are still underexplored. Noninvasive brain stimulation (NIBS) techniques modulate neural activity of targeted brain areas and hold promise for the treatment of patients with DoC. In this review, we provide a summary of published research using NIBS as therapeutic intervention for DoC patients, with a focus on (but not limited to) randomized controlled trials (RCT). We aim to identify current challenges and knowledge gaps specific to NIBS research in DoC. Furthermore, we propose possible solutions and perspectives for this field. Thus far, the most studied technique remains transcranial electrical stimulation; however, its effect remains moderate. The identified key points that NIBS researchers should focus on in future studies are (1) the lack of large-scale RCTs; (2) the importance of identifying the endotypes of responders; and (3) the optimization of stimulation parameters to maximize the benefits of NIBS.

Consciousness among delta waves: a paradox?

A common observation in EEG research is that consciousness vanishes with the appearance of delta (1-4 Hz) waves, particularly when those waves are high amplitude. High amplitude delta oscillations are frequently observed in states of diminished consciousness, including slow wave sleep, anaesthesia, generalized epileptic seizures, and disorders of consciousness, such as coma and the vegetative state. This strong correlation between loss of consciousness and high amplitude delta oscillations is thought to stem from the widespread cortical deactivation that occurs during the 'down states' or troughs of these slow oscillations. Recently, however, many studies have reported the presence of prominent delta activity during conscious states, which casts doubt on the hypothesis that high amplitude delta oscillations are an indicator of unconsciousness. These studies include work in Angelman syndrome, epilepsy, behavioural responsiveness during propofol anaesthesia, postoperative delirium, and states of dissociation from the environment such as dreaming and powerful psychedelic states. The foregoing studies complement an older, yet largely unacknowledged, body of literature that has documented awake, conscious patients with high amplitude delta oscillations in clinical reports from Rett syndrome, Lennox-Gastaut syndrome, schizophrenia, mitochondrial diseases, hepatic encephalopathy, and non-convulsive status epilepticus. At the same time, a largely parallel body of recent work has reported convincing evidence that the complexity or entropy of EEG and magnetoencephalographic signals strongly relates to an individual's level of consciousness. Having reviewed this literature, we discuss plausible mechanisms that would resolve the seeming contradiction between high amplitude delta oscillations and consciousness. We also consider implications concerning theories of consciousness, such as integrated information theory and the entropic brain hypothesis. Finally, we conclude that false inferences of unconscious states can be best avoided by examining measures of electrophysiological complexity in addition to spectral power.

Relational Integration in the Human Brain: A Review and Synthesis.

Relational integration is required when multiple explicit representations of relations between entities must be jointly considered to make inferences. We provide an overview of the neural substrate of relational integration in humans and the processes that support it, focusing on work on analogical and deductive reasoning. In addition to neural evidence, we consider behavioral and computational work that has informed neural investigations of the representations of individual relations and of relational integration. In very general terms, evidence from neuroimaging, neuropsychological, and neuromodulatory studies points to a small set of regions (generally left lateralized) that appear to constitute key substrates for component processes of relational integration. These include posterior parietal cortex, implicated in the representation of first-order relations (e.g., A:B); rostrolateral pFC, apparently central in integrating first-order relations so as to generate and/or evaluate higher-order relations (e.g., A:B::C:D); dorsolateral pFC, involved in maintaining relations in working memory; and ventrolateral pFC, implicated in interference control (e.g., inhibiting salient information that competes with relevant relations). Recent work has begun to link computational models of relational representation and reasoning with patterns of neural activity within these brain areas.

Distributed Code for Semantic Relations Predicts Neural Similarity during Analogical Reasoning.

The ability to generate and process semantic relations is central to many aspects of human cognition. Theorists have long debated whether such relations are coarsely coded as links in a semantic network or finely coded as distributed patterns over some core set of abstract relations. The form and content of the conceptual and neural representations of semantic relations are yet to be empirically established. Using sequential presentation of verbal analogies, we compared neural activities in making analogy judgments with predictions derived from alternative computational models of relational dissimilarity to adjudicate among rival accounts of how semantic relations are coded and compared in the brain. We found that a frontoparietal network encodes the three relation types included in the design. A computational model based on semantic relations coded as distributed representations over a pool of abstract relations predicted neural activities for individual relations within the left superior parietal cortex and for second-order comparisons of relations within a broader left-lateralized network.

Longitudinal changes in blood-based biomarkers in chronic moderate to severe traumatic brain injury: preliminary findings.

Objectives: This longitudinal study aims at 1) providing preliminary evidence of changes in blood-based biomarkers across time in chronic TBI and 2) relating these changes to outcome measures and cerebral structure and activity.Methods: Eight patients with moderate-to-severe TBI (7 males, 35 ± 7.6 years old, 5 severe TBI, 17.52 ± 3.84 months post-injury) were evaluated at monthly intervals across 6 time-points using: a) Blood-based biomarkers (GFAP, NSE, S100A12, SDBP145, UCH-L1, T-tau, P-tau, P-tau/T-tau ratio); b) Magnetic Resonance Imaging to evaluate changes in brain structure; c) Resting-state electroencephalograms to evaluate changes in brain function; and d) Outcome measures to assess cognition, emotion, and functional recovery (MOCA, RBANS, BDI-II, and DRS).Results: Changes in P-tau levels were found across time [p = .007]. P-tau was positively related to functional [p < .001] and cognitive [p = .006] outcomes, and negatively related to the severity of depression, 6 months later [R = -0.901; p =.006]. P-tau and P-tau/T-tau ratio were also positively correlated to shape change in subcortical areas such as brainstem [T(7) = 4.71, p = .008] and putamen [T(7) = 3.25, p = .012].Conclusions: Our study provides preliminary findings that suggest a positive relationship between P-tau and the recovery of patients with chronic TBI.

Mechanisms Underlying Disorders of Consciousness: Bridging Gaps to Move Toward an Integrated Translational Science.

AIM: In order to successfully detect, classify, prognosticate, and develop targeted therapies for patients with disorders of consciousness (DOC), it is crucial to improve our mechanistic understanding of how severe brain injuries result in these disorders. METHODS: To address this need, the Curing Coma Campaign convened a Mechanisms Sub-Group of the Coma Science Work Group (CSWG), aiming to identify the most pressing knowledge gaps and the most promising approaches to bridge them. RESULTS: We identified a key conceptual gap in the need to differentiate the neural mechanisms of consciousness per se, from those underpinning connectedness to the environment and behavioral responsiveness. Further, we characterised three fundamental gaps in DOC research: (1) a lack of mechanistic integration between structural brain damage and abnormal brain function in DOC; (2) a lack of translational bridges between micro- and macro-scale neural phenomena; and (3) an incomplete exploration of possible synergies between data-driven and theory-driven approaches. CONCLUSION: In this white paper, we discuss research priorities that would enable us to begin to close these knowledge gaps. We propose that a fundamental step towards this goal will be to combine translational, multi-scale, and multimodal data, with new biomarkers, theory-driven approaches, and computational models, to produce an integrated account of neural mechanisms in DOC. Importantly, we envision that reciprocal interaction between domains will establish a "virtuous cycle," leading towards a critical vantage point of integrated knowledge that will enable the advancement of the scientific understanding of DOC and consequently, an improvement of clinical practice.

Proceedings of the First Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness.

Coma and disorders of consciousness (DoC) are highly prevalent and constitute a burden for patients, families, and society worldwide. As part of the Curing Coma Campaign, the Neurocritical Care Society partnered with the National Institutes of Health to organize a symposium bringing together experts from all over the world to develop research targets for DoC. The conference was structured along six domains: (1) defining endotype/phenotypes, (2) biomarkers, (3) proof-of-concept clinical trials, (4) neuroprognostication, (5) long-term recovery, and (6) large datasets. This proceedings paper presents actionable research targets based on the presentations and discussions that occurred at the conference. We summarize the background, main research gaps, overall goals, the panel discussion of the approach, limitations and challenges, and deliverables that were identified.

Early brain biomarkers of post-traumatic seizures: initial report of the multicentre epilepsy bioinformatics study for antiepileptogenic therapy (EpiBioS4Rx) prospective study.

BACKGROUND: Traumatic brain injury (TBI) causes early seizures and is the leading cause of post-traumatic epilepsy. We prospectively assessed structural imaging biomarkers differentiating patients who develop seizures secondary to TBI from patients who do not. DESIGN: Multicentre prospective cohort study starting in 2018. Imaging data are acquired around day 14 post-injury, detection of seizure events occurred early (within 1 week) and late (up to 90 days post-TBI). RESULTS: From a sample of 96 patients surviving moderate-to-severe TBI, we performed shape analysis of local volume deficits in subcortical areas (analysable sample: 57 patients; 35 no seizure, 14 early, 8 late) and cortical ribbon thinning (analysable sample: 46 patients; 29 no seizure, 10 early, 7 late). Right hippocampal volume deficit and inferior temporal cortex thinning demonstrated a significant effect across groups. Additionally, the degree of left frontal and temporal pole thinning, and clinical score at the time of the MRI, could differentiate patients experiencing early seizures from patients not experiencing them with 89% accuracy. CONCLUSIONS AND RELEVANCE: Although this is an initial report, these data show that specific areas of localised volume deficit, as visible on routine imaging data, are associated with the emergence of seizures after TBI.

Memory in repeat sports-related concussive injury and single-impact traumatic brain injury.

Background: Repeat sports-related concussive/subconcussive injury (RC/SCI) is related to memory impairment. Objective & Methods: We sought to determine memory differences between persons with RC/SCI, moderate-to-severe single-impact traumatic brain injury (SI-TBI), and healthy controls. MRI scans from a subsample of participants with SI-TBI were used to identify the neuroanatomical correlates of observed memory process differences between the brain injury groups. Results: Both brain injury groups evidenced worse learning and recall in contrast to controls, although SI-TBI group had poorer memory than the RC/SCI group. Regarding memory process differences, in contrast to controls, the SI-TBI group evidenced difficulties with encoding, consolidation, and retrieval, while the RC/SCI group showed deficits in consolidation and retrieval. Delayed recall was predicted by encoding, with consolidation as a secondary predictor in the SI-TBI group. In the RC/SCI group, delayed recall was only predicted by consolidation. MRI data showed that the consolidation index we used mapped onto hippocampal atrophy. Conclusions: RC/SCI is primarily associated with consolidation deficits, which differs from SI-TBI. Given the role of the hippocampus in memory consolidation and the fact that hyperphosphorylated tau tends to accumulate in the medial temporal lobe in RC/SCI, consolidation deficits may be a cognitive marker of chronic traumatic encephalopathy in athletes.

The Curing Coma Campaign: Framing Initial Scientific Challenges-Proceedings of the First Curing Coma Campaign Scientific Advisory Council Meeting.

Coma and disordered consciousness are common manifestations of acute neurological conditions and are among the most pervasive and challenging aspects of treatment in neurocritical care. Gaps exist in patient assessment, outcome prognostication, and treatment directed specifically at improving consciousness and cognitive recovery. In 2019, the Neurocritical Care Society (NCS) launched the Curing Coma Campaign in order to address the "grand challenge" of improving the management of patients with coma and decreased consciousness. One of the first steps was to bring together a Scientific Advisory Council including coma scientists, neurointensivists, neurorehabilitationists, and implementation experts in order to address the current scientific landscape and begin to develop a framework on how to move forward. This manuscript describes the proceedings of the first Curing Coma Campaign Scientific Advisory Council meeting which occurred in conjunction with the NCS Annual Meeting in October 2019 in Vancouver. Specifically, three major pillars were identified which should be considered: endotyping of coma and disorders of consciousness, biomarkers, and proof-of-concept clinical trials. Each is summarized with regard to current approach, benefits to the patient, family, and clinicians, and next steps. Integration of these three pillars will be essential to the success of the Curing Coma Campaign as will expanding the "curing coma community" to ensure broad participation of clinicians, scientists, and patient advocates with the goal of identifying and implementing treatments to fundamentally improve the outcome of patients.

Imaging biomarkers of posttraumatic epileptogenesis.

Traumatic brain injury (TBI) affects 2.5 million people annually within the United States alone, with over 300 000 severe injuries resulting in emergency room visits and hospital admissions. Severe TBI can result in long-term disability. Posttraumatic epilepsy (PTE) is one of the most debilitating consequences of TBI, with an estimated incidence that ranges from 2% to 50% based on severity of injury. Conducting studies of PTE poses many challenges, because many subjects with TBI never develop epilepsy, and it can be more than 10 years after TBI before seizures begin. One of the unmet needs in the study of PTE is an accurate biomarker of epileptogenesis, or a panel of biomarkers, which could provide early insights into which TBI patients are most susceptible to PTE, providing an opportunity for prophylactic anticonvulsant therapy and enabling more efficient large-scale PTE studies. Several recent reviews have provided a comprehensive overview of this subject (Neurobiol Dis, 123, 2019, 3; Neurotherapeutics, 11, 2014, 231). In this review, we describe acute and chronic imaging methods that detect biomarkers for PTE and potential mechanisms of epileptogenesis. We also describe shortcomings in current acquisition methods, analysis, and interpretation that limit ongoing investigations that may be mitigated with advancements in imaging techniques and analysis.