Cognitive Motor Dissociation Research Articles

A Survey of Surrogates and Health Care Professionals Indicates Support of Cognitive Motor Dissociation-Assisted Prognostication.

Prognostication of patients with acute disorders of consciousness is imprecise but more accurate technology-supported predictions, such as cognitive motor dissociation (CMD), are emerging. CMD refers to the detection of willful brain activation following motor commands using functional magnetic resonance imaging or machine learning-supported analysis of the electroencephalogram in clinically unresponsive patients. CMD is associated with long-term recovery, but acceptance by surrogates and health care professionals is uncertain. The objective of this study was to determine receptiveness for CMD to inform goals of care (GoC) decisions and research participation among health care professionals and surrogates of behaviorally unresponsive patients. This was a two-center study of surrogates of and health care professionals caring for unconscious patients with severe neurological injury who were enrolled in two prospective US-based studies. Participants completed a 13-item survey to assess demographics, religiosity, minimal acceptable level of recovery, enthusiasm for research participation, and receptiveness for CMD to support GoC decisions. Completed surveys were obtained from 196 participants (133 health care professionals and 63 surrogates). Across all respondents, 93% indicated that they would want their loved one or the patient they cared for to participate in a research study that supports recovery of consciousness if CMD were detected, compared to 58% if CMD were not detected. Health care professionals were more likely than surrogates to change GoC with a positive (78% vs. 59%, p = 0.005) or negative (83% vs. 59%, p = 0.0002) CMD result. Participants who reported religion was the most important part of their life were least likely to change GoC with or without CMD. Participants who identified as Black (odds ratio [OR] 0.12, 95% confidence interval [CI] 0.04-0.36) or Hispanic/Latino (OR 0.39, 95% CI 0.2-0.75) and those for whom religion was the most important part of their life (OR 0.18, 95% CI 0.05-0.64) were more likely to accept a lower minimum level of recovery. Technology-supported prognostication and enthusiasm for clinical trial participation was supported across a diverse spectrum of health care professionals and surrogate decision-makers. Education for surrogates and health care professionals should accompany integration of technology-supported prognostication.

Covert Consciousness in the ICU.

For critically ill patients with acute severe brain injuries, consciousness may reemerge before behavioral responsiveness. The phenomenon of covert consciousness (i.e., cognitive motor dissociation) may be detected by advanced neurotechnologies such as task-based functional MRI (fMRI) and electroencephalography (EEG) in patients who appear unresponsive on the bedside behavioral examination. In this narrative review, we summarize the state-of-the-science in ICU detection of covert consciousness. Further, we consider the prognostic and therapeutic implications of diagnosing covert consciousness in the ICU, as well as its potential to inform discussions about continuation of life-sustaining therapy for patients with severe brain injuries. We reviewed salient medical literature regarding covert consciousness. We included clinical studies investigating the diagnostic performance characteristics and prognostic utility of advanced neurotechnologies such as task-based fMRI and EEG. We focus on clinical guidelines, professional society scientific statements, and neuroethical analyses pertaining to the implementation of advanced neurotechnologies in the ICU to detect covert consciousness. We extracted study results, guideline recommendations, and society scientific statement recommendations regarding the diagnostic, prognostic, and therapeutic relevance of covert consciousness to the clinical care of ICU patients with severe brain injuries. Emerging evidence indicates that covert consciousness is present in approximately 15-20% of ICU patients who appear unresponsive on behavioral examination. Covert consciousness may be detected in patients with traumatic and nontraumatic brain injuries, including patients whose behavioral examination suggests a comatose state. The presence of covert consciousness in the ICU may predict the pace and extent of long-term functional recovery. Professional society guidelines now recommend assessment of covert consciousness using task-based fMRI and EEG. However, the clinical criteria for patient selection for such investigations are uncertain and global access to advanced neurotechnologies is limited.

Cognitive Motor Dissociation in Disorders of Consciousness

BackgroundPatients with brain injury who are unresponsive to commands may perform cognitive tasks that are detected on functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). This phenomenon, known as cognitive motor dissociation, has not been systematically studied in a large cohort of persons with disorders of consciousness.MethodsIn this prospective cohort study conducted at six international centers, we collected clinical, behavioral, and task-based fMRI and EEG data from a convenience sample of 353 adults with disorders of consciousness. We assessed the response to commands on task-based fMRI or EEG in participants without an observable response to verbal commands (i.e., those with a behavioral diagnosis of coma, vegetative state, or minimally conscious state–minus) and in participants with an observable response to verbal commands. The presence or absence of an observable response to commands was assessed with the use of the Coma Recovery Scale–Revised (CRS-R).ResultsData from fMRI only or EEG only were available for 65% of the participants, and data from both fMRI and EEG were available for 35%. The median age of the participants was 37.9 years, the median time between brain injury and assessment with the CRS-R was 7.9 months (25% of the participants were assessed with the CRS-R within 28 days after injury), and brain trauma was an etiologic factor in 50%. We detected cognitive motor dissociation in 60 of the 241 participants (25%) without an observable response to commands, of whom 11 had been assessed with the use of fMRI only, 13 with the use of EEG only, and 36 with the use of both techniques. Cognitive motor dissociation was associated with younger age, longer time since injury, and brain trauma as an etiologic factor. In contrast, responses on task-based fMRI or EEG occurred in 43 of 112 participants (38%) with an observable response to verbal commands.ConclusionsApproximately one in four participants without an observable response to commands performed a cognitive task on fMRI or EEG as compared with one in three participants with an observable response to commands. (Funded by the James S. McDonnell Foundation and others.)

Impact of Aphasia on Brain Activation to Motor Commands in Patients with Acute Intracerebral Hemorrhage.

Brain activation to motor commands is seen in 15% of clinically unresponsive patients with acute brain injury. This state called cognitive motor dissociation (CMD) is detectable by electroencephalogram (EEG) or functional magnetic resonance imaging, predicts long-term recovery, and is recommended by recent guidelines to support prognostication. However, false negative CMD results are a particular concern, and occult aphasia in clinically unresponsive patients may be a major factor. This study aimed to quantify the impact of aphasia on CMD testing. We prospectively studied 61 intensive care unit patients admitted with acute primary intracerebral hemorrhage (ICH) who had behavioral evidence of command following or were able to mimic motor commands. All patients underwent an EEG-based motor command paradigm used to detect CMD and comprehensive aphasia assessments. Logistic regression was used to identify predictors of brain activation, including aphasia types and associations with recovery of independence (Glasgow Outcome Scale-Extended score ≥ 4). Of 61 patients, 50 completed aphasia and the EEG-based motor command paradigm. A total of 72% (n = 36) were diagnosed with aphasia. Patients with impaired comprehension (i.e., receptive or global aphasia) were less likely to show brain activation than those with intact comprehension (odds ratio [OR] 0.23 [95% confidence interval 0.05-0.89], p = 0.04). Brain activation was independently associated with Glasgow Outcome Scale-Extended ≥ 4 by 12months (OR 2.4 [95% confidence interval 1.2-5.0], p = 0.01) accounting for the Functional Outcome in Patients with Primary ICH score (OR1.3 [95% confidence interval 1.0-1.8], p = 0.01). Brain activation to motor commands is four times less likely for patients with primary ICH with impaired comprehension. False negative results due to occult receptive aphasia need to be considered when interpreting CMD testing. Early detection of brain activation may help predict long-term recovery in conscious patients with ICH.

Neuroethics, Covert Consciousness, and Disability Rights: What Happens When Artificial Intelligence Meets Cognitive Motor Dissociation?

In this article, we consider the intersection of cognitive motor dissociation (CMD) and artificial intelligence (AI), hence when CMD meets AI. In covert consciousness, there is a discordance between the observed behavior, the traditional bedside mode of assessment, and the response to volitional commands as depicted by neuroimaging or EEG studies. This alphabet soup of acronyms represents both the promise and peril of nascent technology in covert consciousness. On the diagnostic side, there is the complexity and uncertainty of identifying the discordance between cognitive activity and overt behavior. On the therapeutic side, when AI is used to generate speech, there is the possibility of misrepresenting the thoughts and intentions of those who are otherwise voiceless. This concordance of factors makes the application of AI to CMD worthy of deeper consideration. We offer this analysis in the spirit of anticipatory governance, a prudential process by which one plans to prevent or mitigate unintended consequences of novel technology. We first consider the normative challenges posed by CMD for clinical practice, neuroethics, and the law. We then explore the history of covert consciousness and the relationship of severe brain injury to the right-to-die movement, before introducing three biographies of brain injury that highlight the potential impact of disability bias or ableism in clinical practice, assistive technology, and translational research. Subsequently, we explore how AI might give voice to conscious individuals who are unable to communicate and the ethical challenges that this technology must overcome to promote human flourishing drawing upon what Nussbaum and Sen have described as a "capabilities approach" to promote normative reasoning.

Exploring the Significance of Cognitive Motor Dissociation on Patient Outcome in Acute Disorders of Consciousness.

Cognitive motor dissociation (CMD) is characterized by a dissociation between volitional brain responses and motor control, detectable only through techniques such as electroencephalography (EEG) and functional magnetic resonance imaging. Hence, it has recently emerged as a major challenge in the assessment of patients with disorders of consciousness. Specifically, this review focuses on the prognostic implications of CMD detection during the acute stage of brain injury. CMD patients were identified in each diagnostic category (coma, unresponsive wakefulness syndrome/vegetative state, minimally conscious state minus) with a relatively similar prevalence of around 20%. Current knowledge tends to indicate that the diagnosis of CMD in the acute phase often predicts a more favorable clinical outcome compared with other unresponsive non-CMD patients. Nevertheless, the review underscores the limited research in this domain, probably at least partially explained by its nascent nature and the lack of uniformity in the nomenclature for CMD-related disorders, hindering the impact of the literature in the field.

Precise detection of awareness in disorders of consciousness using deep learning framework

Diagnosis of disorders of consciousness (DOC) remains a formidable challenge. Deep learning methods have been widely applied in general neurological and psychiatry disorders, while limited in DOC domain. Considering the successful use of resting-state functional MRI (rs-fMRI) for evaluating patients with DOC, this study seeks to explore the conjunction of deep learning techniques and rs-fMRI in precisely detecting awareness in DOC. We initiated our research with a benchmark dataset comprising 140 participants, including 76 unresponsive wakefulness syndrome (UWS), 25 minimally conscious state (MCS), and 39 Controls, from three independent sites. We developed a cascade 3D EfficientNet-B3-based deep learning framework tailored for discriminating MCS from UWS patients, referred to as “DeepDOC”, and compared its performance against five state-of-the-art machine learning models. We also included an independent dataset consists of 11 DOC patients to test whether our model could identify patients with cognitive motor dissociation (CMD), in which DOC patients were behaviorally diagnosed unconscious but could be detected conscious by brain computer interface (BCI) method. Our results demonstrate that DeepDOC outperforms the five machine learning models, achieving an area under curve (AUC) value of 0.927 and accuracy of 0.861 for distinguishing MCS from UWS patients. More importantly, DeepDOC excels in CMD identification, achieving an AUC of 1 and accuracy of 0.909. Using gradient-weighted class activation mapping algorithm, we found that the posterior cortex, encompassing the visual cortex, posterior middle temporal gyrus, posterior cingulate cortex, precuneus, and cerebellum, as making a more substantial contribution to classification compared to other brain regions. This research offers a convenient and accurate method for detecting covert awareness in patients with MCS and CMD using rs-fMRI data.

Covert cortical processing: a diagnosis in search of a definition.

Historically, clinical evaluation of unresponsive patients following brain injury has relied principally on serial behavioral examination to search for emerging signs of consciousness and track recovery. Advances in neuroimaging and electrophysiologic techniques now enable clinicians to peer into residual brain functions even in the absence of overt behavioral signs. These advances have expanded clinicians' ability to sub-stratify behaviorally unresponsive and seemingly unaware patients following brain injury by querying and classifying covert brain activity made evident through active or passive neuroimaging or electrophysiologic techniques, including functional MRI, electroencephalography (EEG), transcranial magnetic stimulation-EEG, and positron emission tomography. Clinical research has thus reciprocally influenced clinical practice, giving rise to new diagnostic categories including cognitive-motor dissociation (i.e. 'covert consciousness') and covert cortical processing (CCP). While covert consciousness has received extensive attention and study, CCP is relatively less understood. We describe that CCP is an emerging and clinically relevant state of consciousness marked by the presence of intact association cortex responses to environmental stimuli in the absence of behavioral evidence of stimulus processing. CCP is not a monotonic state but rather encapsulates a spectrum of possible association cortex responses from rudimentary to complex and to a range of possible stimuli. In constructing a roadmap for this evolving field, we emphasize that efforts to inform clinicians, philosophers, and researchers of this condition are crucial. Along with strategies to sensitize diagnostic criteria and disorders of consciousness nosology to these vital discoveries, democratizing access to the resources necessary for clinical identification of CCP is an emerging clinical and ethical imperative.

Advancing Our Knowledge of Cognition in Disorders of Consciousness: A Critical Revisit

This narrative review aims to elucidate an emerging state of consciousness termed “cognitive-motor dissociation (CMD),” characterized by brain activity patterns closely resembling those observed in healthy individuals. This distinctive phenomenon is notably evident in patients diagnosed with comatose states, unresponsive wakefulness states, or minimally conscious states. Employing functional magnetic resonance imaging or electroencephalography holds promise for identifying CMD. The emergence of CMD not only introduces a fresh conceptual framework but also provides valuable predictive insights into outcomes and prognoses for individuals with disorders of consciousness. However, the recognition of CMD raises ethical considerations, particularly in evaluating the decision-making capacity regarding life-or-death choices for individuals in this state. Therefore, it is crucial to advocate for further scientific and comprehensive research to enhance our understanding of CMD and navigate its nuanced complexities.

How to diagnose cognitive-motor dissociation in patients with chronic disorders of consciousness? Development of a novel set of fMRI paradigms for the Russian patient population

How to diagnose cognitive-motor dissociation in patients with chronic disorders of consciousness? Development of a novel set of fMRI paradigms for the Russian patient population

Medical AI, inductive risk and the communication of uncertainty: the case of disorders of consciousness

Some patients, following brain injury, do not outwardly respond to spoken commands, yet show patterns of brain activity that indicate responsiveness. This is ‘cognitive-motor dissociation’ (CMD). Recent research has used...

Diagnosis and Prognosis in Disorders of Consciousness: An Active Paradigm fMRI Study

Diagnoses in patients with disorders of consciousness are prone to misdiagnosis; thus, research has sought approaches to increase reliability, for instance, with functional MRI. By applying a motor imagery task, patients showing covert command following despite the absence of behavioural signs of awareness can be identified as being in a cognitive motor dissociation. This study seeks to determine the proportion of patients, with unresponsive wakefulness syndrome and minimally conscious state, who display covert command following. Moreover, the prognostic value of the improved diagnosis and different methodical approaches to analyse the functional MRI data were evaluated. 73 disorder of consciousness patients (35 unresponsive, 35 minimally conscious, and three already recovered) underwent weekly standardized behavioural assessments with the coma-recovery scale—revised and one functional MRI examination comparing their brain activations in the supplementary motor area between phases of imaging playing tennis and rest. 27 healthy controls served as a control group. The data was evaluated using different region-of-interest analyses (one- and two-tailed small-volume correction and region-of-interest exploration approaches) and a whole-brain analysis. Based on the one-tailed small volume correction data, seven patients, all of nontraumatic aetiology, showed covert command following. The one-tailed region-of-interest exploration identified three additional responders. 10 patients showed significantly more activation during rest than during the imagery paradigm (negative responders). 40% of patients (minimally conscious patients being three times more likely) showed significant activations in the whole brain analysis. Besides, no significant further associations were found between covert command following and clinical parameters. The analyses showed that the tennis paradigm could identify patients with cognitive motor dissociation with a nontraumatic aetiology, but our data failed to show any short-term prognostic validity. The relevance of negative responders and activated regions outside of the region of interest should be further investigated.

Injury patterns associated with cognitive motor dissociation.

In unconscious appearing patients with acute brain injury, wilful brain activation to motor commands without behavioural signs of command following, known as cognitive motor dissociation (CMD), is associated with functional recovery. CMD can be detected by applying machine learning to EEG recorded during motor command presentation in behaviourally unresponsive patients. Identifying patients with CMD carries clinical implications for patient interactions, communication with families, and guidance of therapeutic decisions but underlying mechanisms of CMD remain unknown. By analysing structural lesion patterns and network level dysfunction we tested the hypothesis that, in cases with preserved arousal and command comprehension, a failure to integrate comprehended motor commands with motor outputs underlies CMD. Manual segmentation of T2-fluid attenuated inversion recovery and diffusion weighted imaging sequences quantifying structural injury was performed in consecutive unresponsive patients with acute brain injury (n = 107) who underwent EEG-based CMD assessments and MRI. Lesion pattern analysis was applied to identify lesion patterns common among patients with (n = 21) and without CMD (n = 86). Thalamocortical and cortico-cortical network connectivity were assessed applying ABCD classification of power spectral density plots and weighted pairwise phase consistency (WPPC) to resting EEG, respectively. Two distinct structural lesion patterns were identified on MRI for CMD and three for non-CMD patients. In non-CMD patients, injury to brainstem arousal pathways including the midbrain were seen, while no CMD patients had midbrain lesions. A group of non-CMD patients was identified with injury to the left thalamus, implicating possible language comprehension difficulties. Shared lesion patterns of globus pallidus and putamen were seen for a group of CMD patients, which have been implicated as part of the anterior forebrain mesocircuit in patients with reversible disorders of consciousness. Thalamocortical network dysfunction was less common in CMD patients [ABCD-index 2.3 (interquartile range, IQR 2.1-3.0) versus 1.4 (IQR 1.0-2.0), P < 0.0001; presence of D 36% versus 3%, P = 0.0006], but WPPC was not different. Bilateral cortical lesions were seen in patients with and without CMD. Thalamocortical disruption did not differ for those with CMD, but long-range WPPC was decreased in 1-4 Hz [odds ratio (OR) 0.8; 95% confidence interval (CI) 0.7-0.9] and increased in 14-30 Hz frequency ranges (OR 1.2; 95% CI 1.0-1.5). These structural and functional data implicate a failure of motor command integration at the anterior forebrain mesocircuit level with preserved thalamocortical network function for CMD patients with subcortical lesions. Amongst patients with bilateral cortical lesions preserved cortico-cortical network function is associated with CMD detection. These data may allow screening for CMD based on widely available structural MRI and resting EEG.

Cognitive Motor Dissociation: Gap Analysis and Future Directions.

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. 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. 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. 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.

Prognosis of consciousness disorders in the intensive care unit

Assessments of consciousness are a critical part of prognostic algorithms for critically ill patients suffering from severe brain injuries. There have been significant advances in the field of coma science over the past two decades, providing clinicians with more advanced and precise tools for diagnosing and prognosticating disorders of consciousness (DoC). Advanced neuroimaging and electrophysiological techniques have vastly expanded our understanding of the biological mechanisms underlying consciousness, and have helped identify new states of consciousness. One of these, termed cognitive motor dissociation, can predict functional recovery at 1 year post brain injury, and is present in up to 15–20% of patients with DoC. In this chapter, we review several tools that are used to predict DoC, describing their strengths and limitations, from the neurological examination to advanced imaging and electrophysiologic techniques. We also describe multimodal assessment paradigms that can be used to identify covert consciousness and thus help recognize patients with the potential for future recovery and improve our prognostication practices.

Terson Syndrome: Not to Be Missed in Patients with Disorders of Consciousness

The diagnosis of clinical cognitive motor dissociation (cCMD) can be hindered by pitfalls during standardized clinical evaluation based on gold-standard neurobehavioral rating scales. We introduce here a new pitfall, by reporting two cases of Terson syndrome (TS) after subarachnoid haemorrhage (SAH) caused by the rupture of an anterior communicant artery aneurysm, hospitalized in the Acute Neurorehabilitation Unit (ANR) of CHUV. TS is reported to occur in 8–19.3% of patients suffering from SAH. It can lead to significant visual impairment and if unrecognized, may impair the patient’s capacity to interact appropriately with the environment; it thus presents an important pitfall in recognizing clinical cognitive–motor dissociation (cCMD) in patients with altered states of consciousness. An early ophthalmological exam should be considered in all patients with SAH and disorders of consciousness or visual complaints.

Functional Neuroimaging in Patients With Disorders of Consciousness: Caution Advised.

Functional Neuroimaging in Patients With Disorders of Consciousness: Caution Advised.

Ethical implications of detecting cognitive motor dissociation early after brain injury (P4-7.005)

<h3>Objective:</h3> To determine the impact of cognitive motor disassociation (CMD) in goals of care (GOC) decisions for surrogate decision makers and healthcare professionals (HCPs) of unconscious patients and assess support for clinical research participation. <h3>Background:</h3> Predictions of recovery from acute disorders of consciousness are imprecise but novel diagnostic tools are emerging. CMD refers to the detection of willful brain activation following motor commands in the absence of behavioral command following as detected by machine learning-supported EEG or MRI analysis. This phenomenon has been identified as a predictor of long-term recovery but acceptance of technology-supported prognostication by surrogates and HCPs remains uncertain. <h3>Design/Methods:</h3> We recruited surrogates and HCPs caring for unconscious patients with intracerebral hemorrhage. All participants completed a thirteen-item survey that captured data on demographics, education, religiosity, support for research participation, and receptiveness to technology-assisted prognostication in decision-making. <h3>Results:</h3> A total of 134 participants completed the survey, including 85 HCPs (40 physicians/PAs, 45 RNs) and 49 surrogates. There were no differences in sex between the two groups (67% of HCPs and 61% of surrogates were female). Surrogates reported stronger religious affiliation with 73% indicating religion was “very important” or “the most important part” of their life vs. 29% of HCPs. Both surrogates (73%) and HCPs (93%) indicated a diagnosis of CMD would help in decision-making. There was broad support for clinical trial participation in surrogates (86%) and HCPs (89%). HCPs were more likely than surrogates to change their goals if CMD could not be detected (OR 5.5, 95%-CI 2.4–12.7, p=0.00005). There was only a trend for a higher chance of HCPs to change their goals if CMD could be detected when compared to surrogates (OR 1.9, 95%-CI 0.9–3.8, p=0.08). <h3>Conclusions:</h3> These results demonstrate acceptance of technology-supported prognostication amongst HCPs and surrogate decision-makers. Targeted education to interpret detection and failure of detection of CMD is needed. <b>Disclosure:</b> Mr. Heinonen has nothing to disclose. Miss Carmona has nothing to disclose. Kevin Doyle has nothing to disclose. Ms. Grobois has nothing to disclose. Miss Kruger has nothing to disclose. Dr. Velazquez has nothing to disclose. Ms. Vrosgou has nothing to disclose. Dr. Shen has nothing to disclose. Mrs. Cespedes has nothing to disclose. Ms. Yazdi has nothing to disclose. Dr. Ghoshal has nothing to disclose. Dr. Roh has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Portola Pharmaceuticals. Dr. Agarwal has nothing to disclose. Dr. Park has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Neurocritical Care. The institution of Dr. Park has received research support from National Institutes of Health. The institution of Dr. Dugdale has received research support from McDonald Agape Foundation. Dr. Dugdale has received publishing royalties from a publication relating to health care. Dr. Dugdale has received publishing royalties from a publication relating to health care. Dr. Dugdale has received personal compensation in the range of $500-$4,999 for serving as a Speaking honoraria for various lectures with Multiple organizations. Dr. Claassen has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Marinus. Dr. Claassen has stock in iCE Neurosystems. The institution of Dr. Claassen has received research support from NINDS. The institution of Dr. Claassen has received research support from McDonnel Foundation. Dr. Claassen has received publishing royalties from a publication relating to health care. Dr. Claassen has received publishing royalties from a publication relating to health care.

Identifying patients with cognitive motor dissociation using resting-state temporal stability

Using task-dependent neuroimaging techniques, recent studies discovered a fraction of patients with disorders of consciousness (DOC) who had no command-following behaviors but showed a clear sign of awareness as healthy controls, which was defined as cognitive motor dissociation (CMD). However, existing task-dependent approaches might fail when CMD patients have cognitive function (e.g., attention, memory) impairments, in which patients with covert awareness cannot perform a specific task accurately and are thus wrongly considered unconscious, which leads to false-negative findings. Recent studies have suggested that sustaining a stable functional organization over time, i.e., high temporal stability, is crucial for supporting consciousness. Thus, temporal stability could be a powerful tool to detect the patient's cognitive functions (e.g., consciousness), while its alteration in the DOC and its capacity for identifying CMD were unclear. The resting-state fMRI (rs-fMRI) study included 119 participants from three independent research sites. A sliding-window approach was used to investigate global and regional temporal stability, which measured how stable the brain's functional architecture was across time. The temporal stability was compared in the first dataset (36/16 DOC/controls), and then a Support Vector Machine (SVM) classifier was built to discriminate DOC from controls. Furthermore, the generalizability of the SVM classifier was tested in the second independent dataset (35/21 DOC/controls). Finally, the SVM classifier was applied to the third independent dataset, where patients underwent rs-fMRI and brain-computer interface assessment (4/7 CMD/potential non-CMD), to test its performance in identifying CMD. Our results showed that global and regional temporal stability was impaired in DOC patients, especially in regions of the cingulo-opercular task control network, default-mode network, fronto-parietal task control network, and salience network. Using temporal stability as the feature, the SVM model not only showed good performance in the first dataset (accuracy = 90%), but also good generalizability in the second dataset (accuracy = 84%). Most importantly, the SVM model generalized well in identifying CMD in the third dataset (accuracy = 91%). Our preliminary findings suggested that temporal stability could be a potential tool to assist in diagnosing CMD. Furthermore, the temporal stability investigated in this study also contributed to a deeper understanding of the neural mechanism of consciousness.

Neuroprognostication after cardiac arrest: what the cardiologist should know.

Two aspects are a key to mastering prognostication of comatose cardiac arrest survivors: a detailed knowledge about the clinical trajectories of consciousness recovery (or lack thereof) and the ability to correctly interpret the results of multimodal investigations, which include clinical examination, electroencephalography, neuroimaging, evoked potentials, and blood biomarkers. While the very good and the very poor ends of the clinical spectrum typically do not pose diagnostic challenges, the intermediate 'grey zone' of post-cardiac arrest encephalopathy requires cautious interpretation of the available information and sufficiently long clinical observation. Late recovery of coma patients with initially ambiguous diagnostic results is increasingly reported, as are unresponsive patients with various forms of residual consciousness, including so-called cognitive motor dissociation, rendering prognostication of post-anoxic coma highly complex. The aim of this paper is to provide busy clinicians with a high-yield, concise overview of neuroprognostication after cardiac arrest, emphasizing notable developments in the field since 2020.