Lateral frontoparietal effective connectivity differentiates and predicts state of consciousness in a cohort of patients with traumatic disorders of consciousness.

Neuroimaging studies have suggested an important role for the default mode network (DMN) in disorders of consciousness (DoC). However, the extent to which DMN connectivity can discriminate DoC states-unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS)-is less evident. Particularly, it is unclear whether effective DMN connectivity, as measured indirectly with dynamic causal modelling (DCM) of resting EEG can disentangle UWS from healthy controls and from patients considered conscious (MCS+). Crucially, this extends to UWS patients with potentially "covert" awareness (minimally conscious star, MCS*) indexed by voluntary brain activity in conjunction with partially preserved frontoparietal metabolism as measured with positron emission tomography (PET+ diagnosis; in contrast to PET- diagnosis with complete frontoparietal hypometabolism). Here, we address this gap by using DCM of EEG data acquired from patients with traumatic brain injury in 11 UWS (6 PET- and 5 PET+) and in 12 MCS+ (11 PET+ and 1 PET-), alongside with 11 healthy controls. We provide evidence for a key difference in left frontoparietal connectivity when contrasting UWS PET- with MCS+ patients and healthy controls. Next, in a leave-one-subject-out cross-validation, we tested the classification performance of the DCM models demonstrating that connectivity between medial prefrontal and left parietal sources reliably discriminates UWS PET- from MCS+ patients and controls. Finally, we illustrate that these models generalize to an unseen dataset: models trained to discriminate UWS PET- from MCS+ and controls, classify MCS* patients as conscious subjects with high posterior probability (pp > .92). These results identify specific alterations in the DMN after severe brain injury and highlight the clinical utility of EEG-based effective connectivity for identifying patients with potential covert awareness.

Resting state networks in patients with acute disorders of consciousness after severe traumatic brain injury.

OBJECTIVES: This study aims to describe resting state networks (RSN) in patients with disorders of consciousness (DOC)s after acute severe traumatic brain injury (TBI). METHODS: Adult patients with TBI with a GCS score <8 who remained in a coma, minimally conscious state (MCS), or unresponsive wakefulness syndrome (UWS), between 2017 and 2020 were included. Blood-oxygen-level dependent imaging was performed to compare their RSN with 10 healthy volunteers. RESULTS: Of a total of 293 patients evaluated, only 13 patients were included according to inclusion criteria: 7 in coma (54%), 2 in MCS (15%), and 4 (31%) had an UWS. RSN analysis showed that the default mode network (DMN) was present and symmetric in 6 patients (46%), absent in 1 (8%), and asymmetric in 6 (46%). The executive control network (ECN) was present in all patients but was asymmetric in 3 (23%). The right ECN was absent in 2 patients (15%) and the left ECN in 1 (7%). The medial visual network was present in 11 (85%) patients. Finally, the cerebellar network was symmetric in 8 patients (62%), asymmetric in 1 (8%), and absent in 4 (30%). CONCLUSIONS: A substantial impairment in activation of RSN is demonstrated in patients with DOC after severe TBI in comparison with healthy subjects. Three patterns of activation were found: normal/complete activation, 2) asymmetric activation or partially absent, and 3) absent activation.

Whole-brain glucose metabolic pattern differentiates minimally conscious state from unresponsive wakefulness syndrome.

AIMS: The patient being minimally conscious state (MCS) may benefit from wake-up interventions aimed at improving quality of life and have a higher probability of recovering higher level of consciousness compared to patients with the unresponsive wakefulness syndrome (UWS). However, differentiation of the MCS and UWS poses challenge in clinical practice. This study aimed to explore glucose metabolic pattern (GMP) obtained from 18F-labeled-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) in distinguishing between UWS and MCS. METHODS: Fifty-seven patients with disorders of consciousness (21 cases of UWS and 36 cases of MCS) who had undergone repeated standardized Coma Recovery Scale-Revised (CRS-R) evaluations were enrolled in this prospective study. 18F-FDG-PET was carried out in all patients and healthy controls (HCs). Voxel-based scaled subprofile model/principal component analysis (SSM/PCA) was used to generate GMPs. The expression score of whole-brain GMP was obtained, and its diagnostic accuracy was compared with the standardized uptake value ratio (SUVR). The diagnostic efficiency was validated by one-year later clinical outcomes. RESULTS: UWS-MCS GMP exhibited hypometabolism in the frontal-parietal cortex, along with hypermetabolism in the unilateral lentiform nucleus, putamen, and anterior cingulate gyrus. The UWS-MCS-GMP expression score was significantly higher in UWS compared to MCS patients (0.90 ± 0.85 vs. 0 ± 0.93, p < 0.001). UWS-MCS-GMP expression score achieved an area under the curve (AUC) of 0.77 to distinguish MCS from UWS, surpassing that of SUVR based on the frontoparietal cortex (AUC = 0.623). UWS-MCS-GMP expression score was significantly correlated with the CRS-R score (r = -0.45, p = 0.004) and accurately predicted the one-year outcome in 73.7% of patients. CONCLUSION: UWS and MCS exhibit specific glucose metabolism patterns, the UWS-MCS-GMP expression score significantly distinguishes MCS from UWS, making SSM/PCA a potential diagnostic methods in clinical practice for individual patients.

Low-density EEG-based Functional Connectivity Discriminates Minimally Conscious State plus from minus.

OBJECTIVE: Within the continuum of consciousness, patients in a Minimally Conscious State (MCS) may exhibit high-level behavioral responses (MCS+) or may not (MCS-). The evaluation of residual consciousness and related classification is crucial to propose tailored rehabilitation and pharmacological treatments, considering the inherent differences among groups in diagnosis and prognosis. Currently, differential diagnosis relies on behavioral assessments posing a relevant risk of misdiagnosis. In this context, EEG offers a non-invasive approach to model the brain as a complex network. The search for discriminating features could reveal whether behavioral responses in post-comatose patients have a defined physiological background. Additionally, it is essential to determine whether the standard behavioral assessment for quantifying responsiveness holds physiological significance. METHODS: In this prospective observational study, we investigated whether low-density EEG-based graph metrics could discriminate MCS+/- patients by enrolling 57 MCS patients (MCS-: 30; males: 28). At admission to intensive rehabilitation, 30 min resting-state closed-eyes EEG recordings were performed together with consciousness diagnosis following international guidelines. After EEG preprocessing, graphs' metrics were estimated using different connectivity measures, at multiple connection densities and frequency bands (α,θ,δ). Metrics were also provided to cross-validated Machine Learning (ML) models with outcome MCS+/-. RESULTS: A lower level of brain activity integration was found in the MCS- group in the α band. Instead, in the δ band MCS- group presented an higher level of clustering (weighted clustering coefficient) respect to MCS+. The best-performing solution in discriminating MCS+/- through the use of ML was an Elastic-Net regularized logistic regression with a cross-validation accuracy of 79% (sensitivity and specificity of 74% and 85% respectively). CONCLUSION: Despite tackling the MCS+/- differential diagnosis is highly challenging, a daily-routine low-density EEG might allow to differentiate across these differently responsive brain networks. SIGNIFICANCE: Graph-theoretical features are shown to discriminate between these two neurophysiologically similar conditions, and may thus support the clinical diagnosis.

Toward an interventional science of recovery after coma.

Recovery of consciousness after coma remains one of the most challenging areas for accurate diagnosis and effective therapeutic engagement in the clinical neurosciences. Recovery depends on preservation of neuronal integrity and evolving changes in network function that re-establish environmental responsiveness. It typically occurs in defined steps: it begins with eye opening and unresponsiveness in a vegetative state, then limited recovery of responsiveness characterizes the minimally conscious state, and this is followed by recovery of reliable communication. This review considers several points for novel interventions, for example, in persons with cognitive motor dissociation in whom a hidden cognitive reserve is revealed. Circuit mechanisms underlying restoration of behavioral responsiveness and communication are discussed. An emerging theme is the possibility to rescue latent capacities in partially damaged human networks across time. These opportunities should be exploited for therapeutic engagement to achieve individualized solutions for restoration of communication and environmental interaction across varying levels of recovery.

Urban people's preferences for life-sustaining treatment or artificial nutrition and hydration in advance decisions.

BACKGROUND: The Patient Right to Autonomy Act (PRAA), implemented in Taiwan in 2019, enables the creation of advance decisions (AD) through advance care planning (ACP). This legal framework allows for the withholding and withdrawal of life-sustaining treatment (LST) or artificial nutrition and hydration (ANH) in situations like irreversible coma, vegetative state, severe dementia, or unbearable pain. This study aims to investigate preferences for LST or ANH across various clinical conditions, variations in participant preferences, and factors influencing these preferences among urban residents. METHODS: Employing a survey of legally structured AD documents and convenience sampling for data collection, individuals were enlisted from Taipei City Hospital, serving as the primary trial and demonstration facility for ACP in Taiwan since the commencement of the PRAA in its inaugural year. The study examined ADs and ACP consultation records, documenting gender, age, welfare entitlement, disease conditions, family caregiving experience, location of ACP consultation, participation of second-degree relatives, and the intention to participate in ACP. RESULTS: Data from 2337 participants were extracted from electronic records. There was high consistency in the willingness to refuse LST and ANH, with significant differences noted between terminal diseases and extremely severe dementia. Additionally, ANH was widely accepted as a time-limited treatment, and there was a prevalent trend of authorizing a health care agent (HCA) to make decisions on behalf of participants. Gender differences were observed, with females more inclined to decline LST and ANH, while males tended towards accepting full or time-limited treatment. Age also played a role, with younger participants more open to treatment and authorizing HCA, and older participants more prone to refusal. CONCLUSION: Diverse preferences in LST and ANH were shaped by the public's current understanding of different clinical states, gender, age, and cultural factors. Our study reveals nuanced end-of-life preferences, evolving ADs, and socio-demographic influences. Further research could explore evolving preferences over time and healthcare professionals' perspectives on LST and ANH decisions for neurological patients..

Predicting outcome in disorders of consciousness: A mega-analysis.

OBJECTIVE: Assessing recovery potential in patients with disorders of consciousness (DoC) is pivotal for guiding clinical and ethical decisions. We conducted a mega-analysis of individual patient data to understand (1) if a time threshold exists, beyond which regaining consciousness is almost impossible, and (2) how recovery varies based on factors such as diagnosis, etiology, age, sex, and neuropsychological status. METHODS: A systematic literature search revealed a total of 3290 patients. In this sample, we performed a Cox proportional hazards analysis for interval censored data. RESULTS: We observed a late saturation of probability to regain consciousness in Kaplan-Meier curves, and the annual rate of recovery was remarkably stable, in that approximately 35% of patients regained consciousness per year. Patients in minimally conscious state (MCS) recovered more frequently than patients in unresponsive wakefulness syndrome (UWS). No significant difference was observed between the recovery dynamics of MCS subgroups: MCS+ and MCS-. Patients with hypoxic brain lesions showed worse recovery rate than patients with traumatic brain injury and patients with vascular brain lesions, while the latter two categories did not differ from each other. Male patients had moderately better chance to regain consciousness. While younger UWS patients recovered more frequently than older patients, it was not the case in MCS. INTERPRETATION: Our findings highlight the necessity for neurologists to exercise caution when making negative predictions in individual cases, challenge traditional beliefs regarding recovery timelines, and underscore the importance of conducting detailed and prolonged assessments to better understand recovery prospects in DoC.

Optimized trans-cranial direct current stimulation for prolonged consciousness disorder in a patient with titanium mesh cranioplasty.

BACKGROUND: Transcranial direct current stimulation (tDCS) has been used for the restoration of awareness in patients with a minimal consciousness state (MCS). Most brains of patients in MCS may structurally and electrophysiologically differ from un-damaged brains. Moreover, tDCS is currently contraindicated for patients with craniotomy or skull with metallic implants. CASE PRESENTATION: We present a case with prolonged MCS over 1 year, who had severe brain damage, ventriculoperitoneal shunt, and cranioplasty with a titanium mesh, which was treated with tDCS which optimized with the simulation of the electric field based on the patient's brain MRI. The patient was resulting in emergence from MCS. Six months later, she ate meals orally and started walking with assistance. DISCUSSION AND PERSPECTIVE: This personalized simulation based on MRI would make the treatment available even to patients with severe brain structural changes and metallic instrumentation.

Breakdown of effective information flow in disorders of consciousness: Insights from TMS-EEG.

BACKGROUND: The complexity of the neurophysiological mechanisms underlying human consciousness is widely acknowledged, with information processing and flow originating in cortex conceived as a core mechanism of consciousness emergence. Combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is considered as a promising technique to understand the effective information flow associated with consciousness. OBJECTIVES: To investigate information flow with TMS-EEG and its relationship to different consciousness states. METHODS: We applied an effective information flow analysis by combining time-varying multivariate adaptive autoregressive model and adaptive directed transfer function on TMS-EEG data of frontal, motor and parietal cortex in patients with disorder of consciousness (DOC), including 14 vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients, 21 minimally conscious state (MCS) patients, and 22 healthy subjects. RESULTS: TMS in DOC patients, particularly VS/UWS, induced a significantly weaker effective information flow compared to healthy subjects. The bidirectional directed information flow was lost in DOC patients with TMS of frontal, motor and parietal cortex. The interactive ROI rate of the information flow network induced by TMS of frontal and parietal cortex was significantly lower in VS/UWS than in MCS. The interactive ROI rate correlated with DOC clinical scales. CONCLUSIONS: TMS-EEG revealed a physiologically relevant correlation between TMS-induced information flow and levels of consciousness. This suggests that breakdown of effective cortical information flow serves as a viable marker of human consciousness. SIGNIFICANCE: Findings offer a unique perspective on the relevance of information flow in DOC, thus providing a novel way of understanding the physiological basis of human consciousness.

Single session of intermittent theta burst stimulation alters brain activity of patients in vegetative state.

BACKGROUND: Non-invasive brain stimulation is considered as a promising technology for treating patients with disorders of consciousness (DOC). Various approaches and protocols have been proposed; however, few of them have shown potential effects on patients with vegetative state (VS). This study aimed to explore the neuro-modulation effects of intermittent theta burst stimulation (iTBS) on the brains of patients with VS and to provide a pilot investigation into its possible role in treating such patients. METHODS: We conducted a sham-controlled crossover study, a real and a sham session of iTBS were delivered over the left dorsolateral prefrontal cortex of such patients. A measurement of an electroencephalography (EEG) and a behavioral assessment of the Coma Recovery Scale-Revised (CRS-R) were applied to evaluate the modulation effects of iTBS before and after stimulation. RESULTS: No meaningful changes of CRS-R were found. The iTBS altered the spectrum, complexity and functional connectivity of the patients. The real stimulation induced a trend of decreasing of delta power at T1 and T2 in the frontal region, significant increasing of permutation entropy at the T2 in the left frontal region. In addition, brain functional connectivity, particularly inter-hemispheric connectivity, was strengthened between the electrodes of the frontal region. The sham stimulation, however, did not induce any significant changes of the brain activity. CONCLUSIONS: One session of iTBS significantly altered the oscillation power, complexity and functional connectivity of brain activity of VS patients. It may be a valuable tool on modulating the brain activities of patients with VS.

Neurobehavioral Progress and Signs of Transition in Children With Prolonged Disorders of Consciousness: A Retrospective Longitudinal Study With the Coma Recovery Scale-Revised.

BACKGROUND: Research on disorders of consciousness in children is scarce and includes disparate and barely comparable participants and assessment instruments and therefore provides inconclusive information on the clinical progress and recovery in this population. This study retrospectively investigated the neurobehavioral progress and the signs of transition between states of consciousness in a group of children admitted to a rehabilitation program either with an unresponsive wakefulness syndrome (UWS) or in a minimally conscious state (MCS). METHODS: Systematic weekly assessments were conducted with the Coma Recovery Scale-Revised (CRS-R) until emergence from MCS, discharge, or death. RESULTS: Twenty-one children, nine admitted with a UWS and 12 admitted in an MCS, were included in the study. Four children with a UWS transitioned to an MCS with a CRS-R of 10 (9.2 to 12.2) by showing visual pursuit, visual fixation, or localization to noxious stimulation. Twelve children emerged from the MCS with a CRS-R of 20.5 (19 to 21.7). Children who emerged from the MCS had had a shorter time postinjury and higher CRS-R at admission, compared with those who did not emerge. CONCLUSIONS: Almost half of the children who were admitted with a UWS transitioned to an MCS, and almost all who were admitted in an MCS emerged from this state. Children who emerged had shorter times since injury and higher scores on the CRS-R at admission, compared with those who did not emerge.

Stationary stable cross-correlation pattern and task specific deviations in unresponsive wakefulness syndrome as well as clinically healthy subjects.

Brain dynamics is highly non-stationary, permanently subject to ever-changing external conditions and continuously monitoring and adjusting internal control mechanisms. Finding stationary structures in this system, as has been done recently, is therefore of great importance for understanding fundamental dynamic trade relationships. Here we analyse electroencephalographic recordings (EEG) of 13 subjects with unresponsive wakefulness syndrome (UWS) during rest and while being influenced by different acoustic stimuli. We compare the results with a control group under the same experimental conditions and with clinically healthy subjects during overnight sleep. The main objective of this study is to investigate whether a stationary correlation pattern is also present in the UWS group, and if so, to what extent this structure resembles the one found in healthy subjects. Furthermore, we extract transient dynamical features via specific deviations from the stationary interrelation pattern. We find that (i) the UWS group is more heterogeneous than the two groups of healthy subjects, (ii) also the EEGs of the UWS group contain a stationary cross-correlation pattern, although it is less pronounced and shows less similarity to that found for healthy subjects and (iii) deviations from the stationary pattern are notably larger for the UWS than for the two groups of healthy subjects. The results suggest that the nervous system of subjects with UWS receive external stimuli but show an overreaching reaction to them, which may disturb opportune information processing.

Dissociations between spontaneous electroencephalographic features and the perturbational complexity index in the minimally conscious state.

The analysis of spontaneous electroencephalogram (EEG) is a cornerstone in the assessment of patients with disorders of consciousness (DoC). Although preserved EEG patterns are highly suggestive of consciousness even in unresponsive patients, moderately or severely abnormal patterns are difficult to interpret. Indeed, growing evidence shows that consciousness can be present despite either large delta or reduced alpha activity in spontaneous EEG. Quantifying the complexity of EEG responses to direct cortical perturbations (perturbational complexity index [PCI]) may complement the observational approach and provide a reliable assessment of consciousness even when spontaneous EEG features are inconclusive. To seek empirical evidence of this hypothesis, we compared PCI with EEG spectral measures in the same population of minimally conscious state (MCS) patients (n = 40) hospitalized in rehabilitation facilities. We found a remarkable variability in spontaneous EEG features across MCS patients as compared with healthy controls: in particular, a pattern of predominant delta and highly reduced alpha power-more often observed in vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients-was found in a non-negligible number of MCS patients. Conversely, PCI values invariably fell above an externally validated empirical cutoff for consciousness in all MCS patients, consistent with the presence of clearly discernible, albeit fleeting, behavioural signs of awareness. These results confirm that, in some MCS patients, spontaneous EEG rhythms may be inconclusive about the actual capacity for consciousness and suggest that a perturbational approach can effectively compensate for this pitfall with practical implications for the individual patient's stratification and tailored rehabilitation.

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.

A Patient With Minimally Conscious Syndrome Due to Cerebrovascular Accident Whose Symptoms Resolved With Zolpidem.

OBJECTIVE: In this report, we discuss the case of a patient with minimally conscious state (MCS) whose clinical condition significantly improved after Zolpidem therapy. We aim to provide supportive evidence for inclusion of zolpidem trials in patients with MCS. METHODS: Our team used electronic medical records, direct patient care experiences, and literature review to obtain information for this case report. RESULTS: Twice daily zolpidem therapy led to significant clinical improvement in our patient with MCS. In addition, this improvement was maintained throughout an increasingly arduous medical course. CONCLUSIONS: Minimally conscious state is a disorder with limited proven therapeutic options. Zolpidem administration has demonstrated immense benefit in a select population of patients, including ours. Given the potential for great improvement with limited downside, zolpidem trial presents an intriguing treatment option. Further clarification of prognostic features to stratify responders and nonresponders to therapy is needed.

How well do neural signatures of resting-state EEG detect consciousness? A large-scale clinical study.

The assessment of consciousness states, especially distinguishing minimally conscious states (MCS) from unresponsive wakefulness states (UWS), constitutes a pivotal role in clinical therapies. Despite that numerous neural signatures of consciousness have been proposed, the effectiveness and reliability of such signatures for clinical consciousness assessment still remains an intense debate. Through a comprehensive review of the literature, inconsistent findings are observed about the effectiveness of diverse neural signatures. Notably, the majority of existing studies have evaluated neural signatures on a limited number of subjects (usually below 30), which may result in uncertain conclusions due to small data bias. This study presents a systematic evaluation of neural signatures with large-scale clinical resting-state electroencephalography (EEG) signals containing 99 UWS, 129 MCS, 36 emergence from the minimally conscious state, and 32 healthy subjects (296 total) collected over 3 years. A total of 380 EEG-based metrics for consciousness detection, including spectrum features, nonlinear measures, functional connectivity, and graph-based measures, are summarized and evaluated. To further mitigate the effect of data bias, the evaluation is performed with bootstrap sampling so that reliable measures can be obtained. The results of this study suggest that relative power in alpha and delta serve as dependable indicators of consciousness. With the MCS group, there is a notable increase in the phase lag index-related connectivity measures and enhanced functional connectivity between brain regions in comparison to the UWS group. A combination of features enables the development of an automatic detector of conscious states.

Diagnostic value of PET imaging in clinically unresponsive patients.

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

Effects of different frequencies music on cortical responses and functional connectivity in patients with minimal conscious state.

The objective of this study was to investigate brain activation and functional network patterns during musical interventions in different frequency bands using functional near-infrared spectroscopy, and to provide a basis for more effective music therapy strategy selection for patients in minimally conscious state (MCS). Twenty six MCS patients and 20 healthy people were given music intervention with low frequency (31-180 Hz), medium frequency (180-4k Hz), and high frequency (4k-22k Hz) audio. In MCS patients, low frequency music intervention induced activation of left prefrontal cortex and left primary sensory cortex (S1), also a left-hemisphere lateralization effect of dorsolateral prefrontal cortex (DLPFC). And the functional connectivity of right DLPFC-right S1 was significantly improved by high frequency music intervention. The low frequency and high frequency music may contribute more than medium frequency music to the recovery of consciousness. This study also validated the effectiveness of fNIRS in studies of brain function in MCS patients.

Family caregivers improve the diagnostic accuracy of disorders of consciousness: from remote to near-bed auditory stimulation.

BACKGROUND: Family caregivers (FC) contribute to reducing the misdiagnosis rate in patients with disorders of consciousness (DOC). Unfortunately, the recent pandemic of COVID-19 imposed drastic restrictions that limited the access of FC to the sensory/cognitive stimulation protocols. Telemedicine approaches have been implemented to avoid discontinuity in care pathways and to ensure caregivers involvement in rehabilitation programs. AIM: The aim was to investigate whether the presence of FC remotely connected might help clinicians in eliciting higher cortically mediated behavioral responses in patients with DOC. DESIGN: Cross-sectional study. SETTING: Post-acute Unit of Neurorehabilitation. POPULATION: DOC due to severe brain injury. METHODS: Consecutive patients with DOC were assessed by means of the Coma Recovery Scale-Revised (CRS-R) by two expert examiners. Each patient underwent to five assessments in two weeks in three different conditions: 1) by the examiner only (standard); 2) with the verbal stimulation given by the FC remotely connected by PC tablet (caregiver in remote); and 3) with the verbal stimulation given by the FC physically present (caregiver in presence). RESULTS: Thirty patients with DOC (VS/UWS=10; MCS=20; mean age: 51, range: 21-79; vascular: 16; anoxic: 6; TBI=8) and their FC were enrolled. Higher total scores of CRS-R were recorded both in "caregiver in remote" and in "caregiver in presence" than in standard condition (standard vs. remote, Z=2.942, P=0.003; standard vs. presence, Z=3.736, P<0.001). Furthermore, the administration of the CRS-R with a FC, elicited higher levels of behavioral responses in MCS patients, than CRS-R performed in standard condition. In particular, 2 patients out of 30 (6.66%) showed higher scores and better diagnosis when the CRS-R was administered with FC in remote. Similarly, 5 out of 30 patients (16.66%) showed better diagnoses when the CRS-R was administered with FC in presence. Five patients changed diagnosis between standard and presence conditions (3 MCS- were diagnosed as MCS+; 2 MCS+ were diagnosed as conscious). CONCLUSIONS: Our findings add new evidence regarding the beneficial role of family members in the diagnosis of DOC, even mediated by telemedicine approach. CLINICAL REHABILITATION IMPACT: In future guidelines, FC should have an active and supporting role in the diagnostic and rehabilitative process of DOC.

Minimally conscious state plus versus minus: Likelihood of emergence and long-term functional independence.

OBJECTIVE: Severe brain injuries can result in disorders of consciousness, such as the Minimally Conscious State (MCS), where individuals display intermittent yet discernible signs of conscious awareness. The varied levels of responsiveness and awareness observed in this state have spurred the progressive delineation of two subgroups within MCS, termed "plus" (MCS+) and "minus" (MCS-). However, the clinical validity of these classifications remains uncertain. This study aimed to investigate and compare the likelihood of emergence from MCS, as well as the functional independence after emergence, in individuals categorized as in MCS+ and MCS-. METHODS: Demographic and behavioral data of 80 participants, admitted as either in MCS+ (n = 30) or MCS- (n = 50) to a long-term neurorehabilitation unit, were retrospectively analyzed. The neurobehavioral condition of each participant was evaluated weekly until discharge, demise, or emergence from MCS. The functional independence of those participants who emerged from MCS was assessed 6 months after emergence. RESULTS: While only about half of the individuals classified as in MCS- (n = 24) emerged from the MCS, all those admitted as in MCS+ did, and in a shorter postinjury period. Despite these differences, all individuals who emerged from the MCS demonstrated similar high disability and low functional independence 6 months after emergence, regardless of their state at admission. INTERPRETATION: Individuals classified as MCS+ exhibited a higher likelihood of emergence and a shorter time to emergence compared to those in MCS-. However, the level of functional independence 6 months after emergence was found to be unrelated to the initial state at admission.