An Unpredictable Brain Is a Conscious, Responsive Brain.

Severe traumatic brain injuries typically result in loss of consciousness or coma. In deeply comatose patients with traumatic brain injury, cortical dynamics become simple, repetitive, and predictable. We review evidence that this low-complexity, high-predictability state results from a passive cortical state, represented by a stable repetitive attractor, that hinders the flexible formation of neuronal ensembles necessary for conscious experience. Our data and those from other groups support the hypothesis that this cortical passive state is because of the loss of thalamocortical input. We identify the unpredictability and complexity of cortical dynamics captured by local field potential as a sign of recovery from this passive coma attractor. In this Perspective article, we discuss how these electrophysiological biomarkers of the recovery of consciousness could inform the design of closed-loop stimulation paradigms to treat disorders of consciousness.

Brain-Computer Interfaces for Communication in Patients with Disorders of Consciousness: A Gap Analysis and Scientific Roadmap.

BACKGROUND: We developed a gap analysis that examines the role of brain-computer interfaces (BCI) in patients with disorders of consciousness (DoC), focusing on their assessment, establishment of communication, and engagement with their environment. METHODS: The Curing Coma Campaign convened a Coma Science work group that included 16 clinicians and neuroscientists with expertise in DoC. The work group met online biweekly and performed a gap analysis of the primary question. RESULTS: We outline a roadmap for assessing BCI readiness in patients with DoC and for advancing the use of BCI devices in patients with DoC. Additionally, we discuss preliminary studies that inform development of BCI solutions for communication and assessment of readiness for use of BCIs in DoC study participants. Special emphasis is placed on the challenges posed by the complex pathophysiologies caused by heterogeneous brain injuries and their impact on neuronal signaling. The differences between one-way and two-way communication are specifically considered. Possible implanted and noninvasive BCI solutions for acute and chronic DoC in adult and pediatric populations are also addressed. CONCLUSIONS: We identify clinical and technical gaps hindering the use of BCI in patients with DoC in each of these contexts and provide a roadmap for research aimed at improving communication for adults and children with DoC, spanning the clinical spectrum from intensive care unit to chronic care.

Charting the road forward in psychiatric neurosurgery: proceedings of the 2016 American Society for Stereotactic and Functional Neurosurgery workshop on neuromodulation for psychiatric disorders.

OBJECTIVE: Refractory psychiatric disease is a major cause of morbidity and mortality worldwide, and there is a great need for new treatments. In the last decade, investigators piloted novel deep brain stimulation (DBS)-based therapies for depression and obsessive-compulsive disorder (OCD). Results from recent pivotal trials of these therapies, however, did not demonstrate the degree of efficacy expected from previous smaller trials. To discuss next steps, neurosurgeons, neurologists, psychiatrists and representatives from industry convened a workshop sponsored by the American Society for Stereotactic and Functional Neurosurgery in Chicago, Illinois, in June of 2016. DESIGN: Here we summarise the proceedings of the workshop. Participants discussed a number of issues of importance to the community. First, we discussed how to interpret results from the recent pivotal trials of DBS for OCD and depression. We then reviewed what can be learnt from lesions and closed-loop neurostimulation. Subsequently, representatives from the National Institutes of Health, the Food and Drug Administration and industry discussed their views on neuromodulation for psychiatric disorders. In particular, these third parties discussed their criteria for moving forward with new trials. Finally, we discussed the best way of confirming safety and efficacy of these therapies, including registries and clinical trial design. We close by discussing next steps in the journey to new neuromodulatory therapies for these devastating illnesses. CONCLUSION: Interest and motivation remain strong for deep brain stimulation for psychiatric disease. Progress will require coordinated efforts by all stakeholders.

Frequency-Dependent Representation of Reinforcement-Related Information in the Human Medial and Lateral Prefrontal Cortex.

The feedback-related negativity (FRN) is a commonly observed potential in scalp electroencephalography (EEG) studies related to the valence of feedback about a subject's performance. This potential classically manifests as a negative deflection in medial frontocentral EEG contacts following negative feedback. Recent work has shown prominence of theta power in the spectral composition of the FRN, placing it within the larger class of "frontal midline theta" cognitive control signals. Although the dorsal anterior cingulate cortex (dACC) is thought to be the cortical generator of the FRN, conclusive data regarding its origin and propagation are lacking. Here we examine intracranial electrophysiology from the human medial and lateral prefrontal cortex (PFC) to better understand the anatomical localization and communication patterns of the FRN. We show that the FRN is evident in both low- and high-frequency local field potentials (LFPs) recorded on electrocorticography. The FRN is larger in medial compared with lateral PFC, and coupling between theta band phase and high-frequency LFP power is also greater in medial PFC. Using Granger causality and conditional mutual information analyses, we provide evidence that feedback-related information propagates from medial to lateral PFC, and that this information transfer oscillates with theta-range periodicity. These results provide evidence for the dACC as the cortical source of the FRN, provide insight into the local computation of frontal midline theta, and have implications for reinforcement learning models of cognitive control.

Frontal networks associated with command following after hemorrhagic stroke.

BACKGROUND AND PURPOSE: Level of consciousness is frequently assessed by command-following ability in the clinical setting. However, it is unclear what brain circuits are needed to follow commands. We sought to determine what networks differentiate command following from noncommand following patients after hemorrhagic stroke. METHODS: Structural MRI, resting-state functional MRI, and electroencephalography were performed on 25 awake and unresponsive patients with acute intracerebral and subarachnoid hemorrhage. Structural injury was assessed via volumetric T1-weighted MRI analysis. Functional connectivity differences were analyzed against a template of standard resting-state networks. The default mode network (DMN) and the task-positive network were investigated using seed-based functional connectivity. Networks were interrogated by pairwise coherence of electroencephalograph leads in regions of interest defined by functional MRI. RESULTS: Functional imaging of unresponsive patients identified significant differences in 6 of 16 standard resting-state networks. Significant voxels were found in premotor cortex, dorsal anterior cingulate gyrus, and supplementary motor area. Direct interrogation of the DMN and task-positive network revealed loss of connectivity between the DMN and the orbitofrontal cortex and new connections between the task-positive network and DMN. Coherence between electrodes corresponding to right executive network and visual networks was also decreased in unresponsive patients. CONCLUSIONS: Resting-state functional MRI and electroencephalography coherence data support a model in which multiple, chiefly frontal networks are required for command following. Loss of DMN anticorrelation with task-positive network may reflect a loss of inhibitory control of the DMN by motor-executive regions. Frontal networks should thus be a target for future investigations into the mechanism of responsiveness in the intensive care unit environment.

Direct, intraoperative observation of ~0.1 Hz hemodynamic oscillations in awake human cortex: implications for fMRI.

An almost sinusoidal, large amplitude ~0.1 Hz oscillation in cortical hemodynamics has been repeatedly observed in species ranging from mice to humans. However, the occurrence of 'slow sinusoidal hemodynamic oscillations' (SSHOs) in human functional magnetic resonance imaging (fMRI) studies is rarely noted or considered. As a result, little investigation into the cause of SSHOs has been undertaken, and their potential to confound fMRI analysis, as well as their possible value as a functional biomarker has been largely overlooked. Here, we report direct observation of large-amplitude, sinusoidal ~0.1 Hz hemodynamic oscillations in the cortex of an awake human undergoing surgical resection of a brain tumor. Intraoperative multispectral optical intrinsic signal imaging (MS-OISI) revealed that SSHOs were spatially localized to distinct regions of the cortex, exhibited wave-like propagation, and involved oscillations in the diameter of specific pial arterioles, indicating that the effect was not the result of systemic blood pressure oscillations. fMRI data collected from the same subject 4 days prior to surgery demonstrates that ~0.1 Hz oscillations in the BOLD signal can be detected around the same region. Intraoperative optical imaging data from a patient undergoing epilepsy surgery, in whom sinusoidal oscillations were not observed, is shown for comparison. This direct observation of the '0.1 Hz wave' in the awake human brain, using both intraoperative imaging and pre-operative fMRI, confirms that SSHOs occur in the human brain, and can be detected by fMRI. We discuss the possible physiological basis of this oscillation and its potential link to brain pathologies, highlighting its relevance to resting-state fMRI and its potential as a novel target for functional diagnosis and delineation of neurological disease.

Primate thalamic nuclei select abstract rules and shape prefrontal dynamics.

Flexible behavior depends on abstract rules to generalize beyond specific instances, and outcome monitoring to adjust actions. Cortical circuits are posited to read out rules from high-dimensional representations of task-relevant variables in prefrontal cortex (PFC). We instead hypothesized that converging inputs from PFC, directly or via basal ganglia (BG), enable primate-specific thalamus to select rules. To test this, we simultaneously measured spiking activity across PFC and two connected thalamic nuclei of monkeys applying rules. Abstract rule information first appeared in the ventroanterior thalamus (VA) - the main thalamic hub between BG and PFC. The mediodorsal thalamus (MD) also represented rule information before PFC, which persisted after rule cues were removed, to help maintain activation of relevant posterior PFC cell ensembles. MD, a major recipient of midbrain dopamine input, was first to represent information about behavioral outcomes. This persisted after the trial (also in PFC). A PFC-BG-thalamus model reproduced key findings, and thalamic-lesion modeling disrupted PFC rule representations. These results suggest a revised view of the neural basis of flexible behavior in primates, featuring a central role for thalamus in selecting high-level cognitive information from PFC and implementing post-error behavioral adjustments, and of the functional organization of PFC along its anterior-posterior dimension.

Motor deficits correlate with resting state motor network connectivity in patients with brain tumours.

While a tumour in or abutting primary motor cortex leads to motor weakness, how tumours elsewhere in the frontal or parietal lobes affect functional connectivity in a weak patient is less clear. We hypothesized that diminished functional connectivity in a distributed network of motor centres would correlate with motor weakness in subjects with brain masses. Furthermore, we hypothesized that interhemispheric connections would be most vulnerable to subtle disruptions in functional connectivity. We used task-free functional magnetic resonance imaging connectivity to probe motor networks in control subjects and patients with brain tumours (n = 22). Using a control dataset, we developed a method for automated detection of key nodes in the motor network, including the primary motor cortex, supplementary motor area, premotor area and superior parietal lobule, based on the anatomic location of the hand-motor knob in the primary motor cortex. We then calculated functional connectivity between motor network nodes in control subjects, as well as patients with and without brain masses. We used this information to construct weighted, undirected graphs, which were then compared to variables of interest, including performance on a motor task, the grooved pegboard. Strong connectivity was observed within the identified motor networks between all nodes bilaterally, and especially between the primary motor cortex and supplementary motor area. Reduced connectivity was observed in subjects with motor weakness versus subjects with normal strength (P < 0.001). This difference was driven mostly by decreases in interhemispheric connectivity between the primary motor cortices (P < 0.05) and between the left primary motor cortex and the right premotor area (P < 0.05), as well as other premotor area connections. In the subjects without motor weakness, however, performance on the grooved pegboard did not relate to interhemispheric connectivity, but rather was inversely correlated with connectivity between the left premotor area and left supplementary motor area, for both the left and the right hands (P < 0.01). Finally, two subjects who experienced severe weakness following surgery for their brain tumours were followed longitudinally, and the subject who recovered showed reconstitution of her motor network at follow-up. The subject who was persistently weak did not reconstitute his motor network. Motor weakness in subjects with brain tumours that do not involve primary motor structures is associated with decreased connectivity within motor functional networks, particularly interhemispheric connections. Motor networks become weaker as the subjects become weaker, and may become strong again during motor recovery.

Deep brain stimulation: a mechanistic and clinical update.

Deep brain stimulation (DBS), the practice of placing electrodes deep into the brain to stimulate subcortical structures with electrical current, has been increasing as a neurosurgical procedure over the past 15 years. Originally a treatment for essential tremor, DBS is now used and under investigation across a wide spectrum of neurological and psychiatric disorders. In addition to applying electrical stimulation for clinical symptomatic relief, the electrodes implanted can also be used to record local electrical activity in the brain, making DBS a useful research tool. Human single-neuron recordings and local field potentials are now often recorded intraoperatively as electrodes are implanted. Thus, the increasing scope of DBS clinical applications is being matched by an increase in investigational use, leading to a rapidly evolving understanding of cortical and subcortical neurocircuitry. In this review, the authors discuss recent innovations in the clinical use of DBS, both in approved indications as well as in indications under investigation. Deep brain stimulation as an investigational tool is also reviewed, paying special attention to evolving models of basal ganglia and cortical function in health and disease. Finally, the authors look to the future across several indications, highlighting gaps in knowledge and possible future directions of DBS treatment.

The role of advanced neuroimaging in intracerebral hemorrhage.

In this report, the authors sought to summarize existing literature to provide an overview of the currently available techniques and to critically assess the evidence for or against their application in intracerebral hemorrhage (ICH) for management, prognostication, and research. Functional imaging in ICH represents a potential major step forward in the ability of physicians to assess patients suffering from this devastating illness due to the advantages over standing imaging modalities focused on general tissue structure alone, but its use is highly controversial due to the relative paucity of literature and the lack of consolidation of the predominantly small data sets that are currently in existence. Current data support that diffusion tensor imaging and tractography, diffusion-perfusion weighted MRI techniques, and functional MRI all possess major potential in the areas of highlighting motor deficits, motor recovery, and network reorganization. Novel clinical studies designed to objectively assess the value of each of these modalities on a wider scale in conjunction with other methods of investigation and management will allow for their rapid incorporation into standard practice.

Microscale multicircuit brain stimulation: Achieving real-time brain state control for novel applications.

Neurological and psychiatric disorders typically result from dysfunction across multiple neural circuits. Most of these disorders lack a satisfactory neuromodulation treatment. However, deep brain stimulation (DBS) has been successful in a limited number of disorders; DBS typically targets one or two brain areas with single contacts on relatively large electrodes, allowing for only coarse modulation of circuit function. Because of the dysfunction in distributed neural circuits - each requiring fine, tailored modulation - that characterizes most neuropsychiatric disorders, this approach holds limited promise. To develop the next generation of neuromodulation therapies, we will have to achieve fine-grained, closed-loop control over multiple neural circuits. Recent work has demonstrated spatial and frequency selectivity using microstimulation with many small, closely-spaced contacts, mimicking endogenous neural dynamics. Using custom electrode design and stimulation parameters, it should be possible to achieve bidirectional control over behavioral outcomes, such as increasing or decreasing arousal during central thalamic stimulation. Here, we discuss one possible approach, which we term microscale multicircuit brain stimulation (MMBS). We discuss how machine learning leverages behavioral and neural data to find optimal stimulation parameters across multiple contacts, to drive the brain towards desired states associated with behavioral goals. We expound a mathematical framework for MMBS, where behavioral and neural responses adjust the model in real-time, allowing us to adjust stimulation in real-time. These technologies will be critical to the development of the next generation of neurostimulation therapies, which will allow us to treat problems like disorders of consciousness and cognition.

Real-time emotion detection by quantitative facial motion analysis.

BACKGROUND: Research into mood and emotion has often depended on slow and subjective self-report, highlighting a need for rapid, accurate, and objective assessment tools. METHODS: To address this gap, we developed a method using digital image speckle correlation (DISC), which tracks subtle changes in facial expressions invisible to the naked eye, to assess emotions in real-time. We presented ten participants with visual stimuli triggering neutral, happy, and sad emotions and quantified their associated facial responses via detailed DISC analysis. RESULTS: We identified key alterations in facial expression (facial maps) that reliably signal changes in mood state across all individuals based on these data. Furthermore, principal component analysis of these facial maps identified regions associated with happy and sad emotions. Compared with commercial deep learning solutions that use individual images to detect facial expressions and classify emotions, such as Amazon Rekognition, our DISC-based classifiers utilize frame-to-frame changes. Our data show that DISC-based classifiers deliver substantially better predictions, and they are inherently free of racial or gender bias. LIMITATIONS: Our sample size was limited, and participants were aware their faces were recorded on video. Despite this, our results remained consistent across individuals. CONCLUSIONS: We demonstrate that DISC-based facial analysis can be used to reliably identify an individual's emotion and may provide a robust and economic modality for real-time, noninvasive clinical monitoring in the future.

In-Hospital Amantadine Does Not Improve Outcomes After Severe Traumatic Brain Injury: An 11-Year Propensity-Matched Retrospective Analysis.

BACKGROUND: Disruption of dopamine neurotransmission is associated with functional impairment after severe traumatic brain injury (sTBI). This has prompted the study of dopamine agonists, such as amantadine, to assist recovery of consciousness. Randomized trials have mostly addressed the posthospital setting, with inconsistent findings. Therefore, we evaluated the efficacy of early amantadine administration on recovery of consciousness after sTBI. METHODS: We searched the medical records of all patients with sTBI admitted to our hospital between 2010 and 2021 who survived 10 days postinjury. We identified all patients receiving amantadine and compared them with all patients not receiving amantadine and a propensity score-matched nonamantadine group. Primary outcome measures included discharge Glasgow Coma Scale, Glasgow Outcome Scale-Extended score, length of stay, mortality, recovery of command-following (CF), and days to CF. RESULTS: In our study population, 60 patients received amantadine and 344 did not. Compared with the propensity score-matched nonamantadine group, the amantadine group had no difference in mortality (86.67% vs. 88.33%, P = 0.783), rates of CF (73.33% vs. 76.67%, P = 0.673), or percentage of patients with severe (3-8) discharge Glasgow Coma Scale scores (11.11% vs. 12.28%, P = 0.434). In addition, the amantadine group was less likely to have a favorable recovery (discharge Glasgow Outcome Scale-Extended score 5-8) (14.53% vs. 16.67%, P < 0.001), had a longer length of stay (40.5 vs. 21.0 days, P < 0.001), and had a longer time to CF (11.5 vs. 6.0 days, P = 0.011). No difference in adverse events existed between groups. CONCLUSIONS: Our findings do not support the early administration of amantadine for sTBI. Larger inpatient randomized trials are necessary to further investigate amantadine treatment for sTBI.

Predicting traumatic brain injury outcomes using a posterior dominant rhythm.

OBJECTIVE: Predicting severe traumatic brain injury (sTBI) outcomes is challenging, and existing models have limited applicability to individual patients. This study aimed to identify metrics that could predict recovery following sTBI. The researchers strived to demonstrate that a posterior dominant rhythm on electroencephalography is strongly associated with positive outcomes and to develop a novel machine learning-based model that accurately forecasts the return of consciousness. METHODS: In this retrospective study, the authors assessed all intubated adults admitted with sTBI (Glasgow Coma Scale [GCS] score ≤ 8) from 2010 to 2021, who underwent EEG recording < 30 days from sTBI (n = 195). Seventy-three clinical, radiographic, and EEG variables were collected. Based on the presence of a PDR within 30 days of injury, two cohorts were created-those with a PDR (PDR[+] cohort, n = 51) and those without (PDR[-] cohort, n = 144)-to assess differences in presentation and four outcomes: in-hospital survival, recovery of command following, Glasgow Outcome Scale-Extended (GOS-E) score at discharge, and GOS-E score at 6 months post discharge. AutoScore, a machine learning-based clinical score generator that selects and assigns weights to important predictive variables, was used to create a prognostic model that predicts in-hospital survival and recovery of command following. Lastly, the MRC-CRASH and IMPACT traumatic brain injury predictive models were used to compare expected patient outcomes with true outcomes. RESULTS: At presentation, the PDR(-) cohort had a lower mean GCS motor subscore (1.97 vs 2.45, p = 0.048). Despite no difference in predicted outcomes (via MRC-CRASH and IMPACT), the PDR(+) cohort had superior rates of in-hospital survival (84.3% vs 63.9%, p = 0.007), recovery of command following (76.5% vs 53.5%, p = 0.004), and mean discharge GOS-E score (3.00 vs 2.39, p = 0.006). There was no difference in the 6-month GOS-E score. AutoScore was then used to identify the 7 following variables that were highly predictive of in-hospital survival and recovery of command: age, body mass index, systolic blood pressure, pupil reactivity, blood glucose, and hemoglobin (all at presentation), and a PDR on EEG. This model had excellent discrimination for predicting in-hospital survival (area under the curve [AUC] 0.815) and recovery of command following (AUC 0.700). CONCLUSIONS: A PDR on EEG in sTBI patients predicts favorable outcomes. The authors' prognostic model has strong accuracy in predicting these outcomes, and performed better than previously reported models. The authors' model can be valuable in clinical decision-making as well as counseling families following these types of injuries.

Brain Circuitry of Consciousness: A Review of Current Models and a Novel Synergistic Model With Clinical Application.

How consciousness arises in the brain has important implications for clinical decision-making. We summarize recent findings in consciousness studies to provide a toolkit for clinicians to assess deficits in consciousness and predict outcomes after brain injury. Commonly encountered disorders of consciousness are highlighted, followed by the clinical scales currently used to diagnose them. We review recent evidence describing the roles of the thalamocortical system and brainstem arousal nuclei in supporting awareness and arousal and discuss the utility of various neuroimaging studies in evaluating disorders of consciousness. We explore recent theoretical progress in mechanistic models of consciousness, focusing on 2 major models, the global neuronal workspace and integrated information theory, and review areas of controversy. Finally, we consider the potential implications of recent research for the day-to-day decision-making of clinical neurosurgeons and propose a simple "three-strikes" model to infer the integrity of the thalamocortical system, which can guide prognosticating return to consciousness.

The mTOR pathway is activated in glial cells in mesial temporal sclerosis.

Mammalian target of rapamycin (mTOR) is a key protein kinase that regulates basic cellular processes, including development and growth. Mutations in mTOR cause tuberous sclerosis complex (TSC), a condition that is characterized by developmental brain malformations (cortical tubers) and epilepsy. Although considerable insight has been gained recently into the pathologic dysfunction of mTOR in tubers in TSC-related epilepsy, data on the mTOR cascade in mesial temporal lobe epilepsy (MTLE) are lacking. Immunohistochemical investigation with confocal microscopy was performed to evaluate mTOR cascade and to correlate its activity with cellular alterations observed in surgically resected samples of human neocortex and hippocampus in MTLE. We compared results in human tissue to findings in the rat pilocarpine model of sclerotic MTLE. In nonsclerotic and control hippocampus, many neurons in the CA1 subfield expressed high levels of phospho-S6 (p-S6), a reliable marker of mTOR activation. In nonsclerotic and control hippocampus, as well as in magnetic resonance imaging (MRI) normal human neocortex, protoplasmic astrocytes did not express p-S6. In contrast, in sclerotic hippocampus, prominent p-S6 immunostaining was observed mainly in astrocytes and microglia located in the areas of neuronal loss and astrogliosis, whereas neurons in preserved areas of CA1 expressed significantly lower levels of p-S6 immunopositivity than neurons in nonsclerotic or control CA1 subfields. In surgically resected neocortex with chronic astroglial scar tissue, only microglia revealed moderate p-S6 immunoreactivity. Different from human sclerotic epileptic hippocampus, astrogliosis in the chronic rat pilocarpine model of epilepsy was not characterized by glial cells with mTOR activation. The mTOR cascade is activated in astroglial cells in sclerotic MTLE, but not in astrocytes in chronic neocortical scarring or in the pilocarpine model of MTLE. These findings suggest that the astroglial "scar" in sclerotic MTLE has active, ongoing cellular changes. Targeting mTOR in MTLE may provide new pathways for the medical therapy of epilepsy.

Cortical recordings reveal hidden early signs of recovery following traumatic brain injury: A case report.

Prognosticating recovery of consciousness after severe traumatic brain injury (TBI) is a difficult task. Understanding the mechanism of recovery of consciousness in these patients will undoubtedly help clarify this issue. Recent research has underscored the importance of electrophysiological data in characterizing the state of the brain during this period of unconsciousness. Here, we investigated cortical electrophysiological recordings from a single TBI patient and discovered that high-frequency activity associated with the return of consciousness reappeared in a spatiotemporal fashion. We observed a shift toward higher frequencies first in the anterior cingulate cortex, and then later in the dorsolateral prefrontal cortex. This finding suggests that recovery may originate in more internal cortices and progress to superficial ones. Although this observation occurred in a single patient, it points to a potential mechanism for recovery of normal cortical activity in the return of consciousness following TBI.

Low-molecular-weight heparin compared with unfractionated heparin in critically ill COVID-19 patients.

BACKGROUND: Thrombosis in COVID-19 worsens mortality. In our study, we sought to investigate how the dose and type of anticoagulation (AC) can influence patient outcomes. METHODS: This is a single-center retrospective analysis of critically ill intubated patients with COVID-19, comparing low-molecular-weight heparin (LMWH) and unfractionated heparin (UFH) at therapeutic and prophylactic doses. Of 218 patients, 135 received LMWH (70 prophylactic, 65 therapeutic) and 83 UFH (11 prophylactic, 72 therapeutic). The primary outcome was mortality. Secondary outcomes were thromboembolic complications confirmed on imaging and major bleeding complications. Cox proportional-hazards regression models were used to determine whether the type and dose of AC were independent predictors of survival. We performed Kaplan-Meier survival analysis to compare the cumulative survivals. RESULTS: Overall, therapeutic AC, with either LMWH (65% vs 79%, P = .09) or UFH (32% vs 46%, P = .73), conveyed no survival benefit over prophylactic AC. UFH was associated with a higher mortality rate than LMWH (66% vs 28%, P = .001), which was also evident in the multivariable analysis (LMWH vs UFH mortality, hazard ratio: 0.47, P = .001) and in the Kaplan-Meier survival analysis. Thrombotic and bleeding complications did not depend on the AC type (prophylactic LMWH vs UFH: thrombosis P = .49, bleeding P = .075; therapeutic LMWH vs UFH: thrombosis P = .5, bleeding P = .17). When comparing prophylactic with therapeutic AC, the rate of both thrombotic and bleeding complications was higher with the use of LMWH compared with UFH. In addition, transfusion requirements were significantly higher with both therapeutic LMWH and UFH. CONCLUSIONS: Among intubated critically ill COVID-19 intensive care unit patients, therapeutic AC, with either LMWH or UFH, conveyed no survival benefit over prophylactic AC. AC with LMWH was associated with higher cumulative survival compared with AC with UFH.

Injury to thalamocortical projections following traumatic brain injury results in attractor dynamics for cortical networks.

Major theories of consciousness predict that complex electroencephalographic (EEG) activity is required for consciousness, yet it is not clear how such activity arises in the corticothalamic system. The thalamus is well-known to control cortical excitability via interlaminar projections, but whether thalamic input is needed for complexity is not known. We hypothesized that the thalamus facilitates complex activity by adjusting synaptic connectivity, thereby increasing the availability of different configurations of cortical neurons (cortical "states"), as well as the probability of state transitions. To test this hypothesis, we characterized EEG activity from prefrontal cortex (PFC) in traumatic brain injury (TBI) patients with and without injuries to thalamocortical projections, measured with diffusion tensor imaging (DTI). We found that injury to thalamic projections (especially from the mediodorsal thalamus) was strongly associated with unconsciousness and delta-band EEG activity. Using advanced signal processing techniques, we found that lack of thalamic input led to 1.) attractor dynamics for cortical networks with a tendency to visit the same states, 2.) a reduced repertoire of possible states, and 3.) high predictability of transitions between states. These results imply that complex PFC activity associated with consciousness depends on thalamic input. Our model implies that restoration of cortical connectivity is a critical function of the thalamus after brain injury. We draw a critical connection between thalamic input and complex cortical activity associated with consciousness.

Alpha and broadband high-frequency activity track task dynamics and predict performance in controlled decision-making.

Intracranial recordings in human subjects provide a unique, fine-grained temporal and spatial resolution inaccessible to conventional non-invasive methods. A prominent signal in these recordings is broadband high-frequency activity (approx. 70-150 Hz), generally considered to reflect neuronal excitation. Here we explored the use of this broadband signal to track, on a single-trial basis, the temporal and spatial distribution of task-engaged areas involved in decision-making. We additionally focused on the alpha rhythm (8-14 Hz), thought to regulate the (dis)engagement of neuronal populations based on task demands. Using these signals, we characterized activity across cortex using intracranial recordings in patients with intractable epilepsy performing the Multi-Source Interference Task, a Stroop-like decision-making paradigm. We analyzed recordings both from grid electrodes placed over cortical areas including frontotemporal and parietal cortex, and depth electrodes in prefrontal regions, including cingulate cortex. We found a widespread negative relationship between alpha power and broadband activity, substantiating the gating role of alpha in regions beyond sensory/motor cortex. Combined, these signals reflect the spatio-temporal pattern of task-engagement, with alpha decrease signifying task-involved regions and broadband increase temporally locking to specific task aspects, distributed over cortical sites. We report sites that only respond to stimulus presentation or to the decision report and, interestingly, sites that reflect the time-on-task. The latter predict the subject's reaction times on a trial-by-trial basis. A smaller subset of sites showed modulation with task condition. Taken together, alpha and broadband signals allow tracking of neuronal population dynamics across cortex on a fine temporal and spatial scale.