Aperiodic brain activity and response to anesthesia vary in disorders of consciousness.

In the human electroencephalogram (EEG), oscillatory power co-exist with non-oscillatory, aperiodic activity. Although EEG analysis has traditionally focused exclusively on oscillatory power, recent investigations have shown that the aperiodic EEG component can distinguish conscious wakefulness from sleep and anesthetic-induced unconsciousness. This study investigates the aperiodic EEG component of individuals in a disorder of consciousness (DOC); how it changes in response to exposure to anesthesia; and how it relates to the brain's information richness and criticality. High-density EEG was recorded from 43 individuals in a DOC, with 16 of these individuals undergoing a protocol of propofol anesthesia. The aperiodic component was defined by the spectral slope of the power spectral density. Our results demonstrate that the EEG aperiodic component is more informative about the participants' level of consciousness than the oscillatory component, especially for patients that suffered from a stroke. Importantly, the pharmacologically induced change in the spectral slope from 30 to 45 Hz positively correlated with individual's pre-anesthetic level of consciousness. The pharmacologically induced loss of information-richness and criticality was associated with individual's pre-anesthetic aperiodic component. During exposure to anesthesia, the aperiodic component distinguished individuals with DOC, according to their 3-month recovery status. The aperiodic EEG component has been historically neglected; this research highlights the necessity of considering this measure for the assessment of individuals in DOC and future research that seeks to understand the neurophysiological underpinnings of consciousness.

The posterior dominant rhythm: an electroencephalographic biomarker for cognitive recovery after general anaesthesia.

BACKGROUND: The posterior dominant rhythm (PDR) was the first oscillatory pattern noted in the EEG. Evoked by wakeful eyelid closure, these oscillations dissipate over seconds during loss of arousal. The peak frequency of the PDR maintains stability over years, suggesting utility as a state biomarker in the surveillance of acute cognitive impairments. This EEG signature has not been systematically investigated for tracking cognitive dysfunction after anaesthetic-induced loss of consciousness. METHODS: This substudy of Reconstructing Consciousness and Cognition (NCT01911195) investigated the PDR and cognitive function in 60 adult volunteers randomised to either 3 h of isoflurane general anaesthesia or resting wakefulness. Serial measurements of EEG power and cognitive task performance were assessed relative to pre-intervention baseline. Mixed-effects models allowed quantification of PDR and neurocognitive trajectories after return of responsiveness (ROR). RESULTS: Individuals in the control group showed stability in the PDR peak frequency over several hours (median difference/inter-quartile range [IQR] of 0.02/0.20 Hz, P=0.39). After isoflurane general anaesthesia, the PDR peak frequency was initially reduced at ROR (median difference/IQR of 0.88/0.65 Hz, P<0.001). PDR peak frequency recovered at a rate of 0.20 Hz h-1. After ROR, the PDR peak frequency correlated with reaction time and accuracy on multiple cognitive tasks (P<0.001). CONCLUSION: The temporal trajectory of the PDR peak frequency could be a useful perioperative marker for tracking cognitive dysfunction on the order of hours after surgery, particularly for cognitive domains of working memory, visuomotor speed, and executive function. CLINICAL TRIAL REGISTRATION: NCT01911195.

Brain Responses to Propofol in Advance of Recovery from Coma and Disorders of Consciousness: A Preliminary Study.

Rationale: Predicting recovery of consciousness in unresponsive, brain-injured individuals has crucial implications for clinical decision-making. Propofol induces distinctive brain network reconfiguration in the healthy brain as it loses consciousness. In patients with disorders of consciousness, the brain network's reconfiguration to propofol may reveal the patient's underlying capacity for consciousness. Objectives: To design and test a new metric for the prognostication of consciousness recovery in disorders of consciousness. Methods: Using a within-subject design, we conducted an anesthetic protocol with concomitant high-density EEG in 12 patients with a disorder of consciousness after a brain injury. We quantified the reconfiguration of EEG network hubs and directed functional connectivity before, during, and after propofol exposure and obtained an index of propofol-induced network reconfiguration: the adaptive reconfiguration index. We compared the index of patients who recovered consciousness 3 months after EEG (n = 3) to that of patients who did not recover or remained in a chronic disorder of consciousness (n = 7) and conducted a logistic regression to assess prognostic accuracy. Measurements and Main Results: The adaptive reconfiguration index was significantly higher in patients who later recovered full consciousness (U value = 21, P = 0.008) and able to discriminate with 100% accuracy whether the patient recovered consciousness. Conclusions: The adaptive reconfiguration index of patients who recovered from a disorder of consciousness at 3-month follow-up was linearly separable from that of patients who did not recover or remained in a chronic disorder of consciousness on the single-subject level. EEG and propofol can be administered at the bedside with few contraindications, affording the adaptive reconfiguration index tremendous translational potential as a prognostic measure of consciousness recovery in acute clinical settings.

Differential classification of states of consciousness using envelope- and phase-based functional connectivity.

The development of sophisticated computational tools to quantify changes in the brain's oscillatory dynamics across states of consciousness have included both envelope- and phase-based measures of functional connectivity (FC), but there are very few direct comparisons of these techniques using the same dataset. The goal of this study was to compare an envelope-based (i.e. Amplitude Envelope Correlation, AEC) and a phase-based (i.e. weighted Phase Lag Index, wPLI) measure of FC in their classification of states of consciousness. Nine healthy participants underwent a three-hour experimental anesthetic protocol with propofol induction and isoflurane maintenance, in which five minutes of 128-channel electroencephalography were recorded before, during, and after anesthetic-induced unconsciousness, at the following time points: Baseline; light sedation with propofol (Light Sedation); deep unconsciousness following three hours of surgical levels of anesthesia with isoflurane (Unconscious); five minutes prior to the recovery of consciousness (Pre-ROC); and three hours following the recovery of consciousness (Recovery). Support vector machine classification was applied to the source-localized EEG in the alpha (8-13 Hz) frequency band in order to investigate the ability of AEC and wPLI (separately and together) to discriminate i) the four states from Baseline; ii) Unconscious ("deep" unconsciousness) vs. Pre-ROC ("light" unconsciousness); and iii) responsiveness (Baseline, Light Sedation, Recovery) vs. unresponsiveness (Unconscious, Pre-ROC). AEC and wPLI yielded different patterns of global connectivity across states of consciousness, with AEC showing the strongest network connectivity during the Unconscious epoch, and wPLI showing the strongest connectivity during full consciousness (i.e., Baseline and Recovery). Both measures also demonstrated differential predictive contributions across participants and used different brain regions for classification. AEC showed higher classification accuracy overall, particularly for distinguishing anesthetic-induced unconsciousness from Baseline (83.7 ± 0.8%). AEC also showed stronger classification accuracy than wPLI when distinguishing Unconscious from Pre-ROC (i.e., "deep" from "light" unconsciousness) (AEC: 66.3 ± 1.2%; wPLI: 56.2 ± 1.3%), and when distinguishing between responsiveness and unresponsiveness (AEC: 76.0 ± 1.3%; wPLI: 63.6 ± 1.8%). Classification accuracy was not improved compared to AEC when both AEC and wPLI were combined. This analysis of source-localized EEG data demonstrates that envelope- and phase-based FC provide different information about states of consciousness but that, on a group level, AEC is better able to detect relative alterations in brain FC across levels of anesthetic-induced unconsciousness compared to wPLI.

"You're Part of Us and We're Happy to Have You Here": Practices of Social Inclusion for Persons with Dementia.

Objectives: Practices of social inclusion are important for maintaining the relationships of persons with dementia and are associated with positive clinical outcomes. The objective of this study was to explore the in-action practices of social inclusion in the activity center of a community-based organization.Methods: This study applies an ethnographic approach - including participant observation, informal and semi-structured interviews - with persons with dementia (n = 31) and organization staff members (n = 9) to explore the in-action practices of social inclusion.Results: Seven in-action practices of inclusion were identified: ensuring time for individual relationships, building schedules centered around flexibility, empowering decision-making, normalizing dementia-related behaviors, involving family members, soliciting and integrating persons with dementia's feedback, and supporting persons with dementia to practice social inclusion.Conclusions: Care providers of individuals with dementia can effectively facilitate active connections with them by continually soliciting and incorporating their feedback, and by supporting persons with dementia to practice inclusion and care for others.Clinical Implications: Community-based organizations can be effective at supporting the active connection of individuals with dementia with others and should be promoted for individuals with mild to moderate dementia.

Long-range temporal correlations in the brain distinguish conscious wakefulness from induced unconsciousness.

Rhythmic neuronal synchronization across large-scale networks is thought to play a key role in the regulation of conscious states. Changes in neuronal oscillation amplitude across states of consciousness have been widely reported, but little is known about possible changes in the temporal dynamics of these oscillations. The temporal structure of brain oscillations may provide novel insights into the neural mechanisms underlying consciousness. To address this question, we examined long-range temporal correlations (LRTC) of EEG oscillation amplitudes recorded during both wakefulness and anesthetic-induced unconsciousness. Importantly, the time-varying EEG oscillation envelopes were assessed over the course of a sevoflurane sedation protocol during which the participants alternated between states of consciousness and unconsciousness. Both spectral power and LRTC in oscillation amplitude were computed across multiple frequency bands. State-dependent differences in these features were assessed using non-parametric tests and supervised machine learning. We found that periods of unconsciousness were associated with increases in LRTC in beta (15-30Hz) amplitude over frontocentral channels and with a suppression of alpha (8-13Hz) amplitude over occipitoparietal electrodes. Moreover, classifiers trained to predict states of consciousness on single epochs demonstrated that the combination of beta LRTC with alpha amplitude provided the highest classification accuracy (above 80%). These results suggest that loss of consciousness is accompanied by an augmentation of temporal persistence in neuronal oscillation amplitude, which may reflect an increase in regularity and a decrease in network repertoire compared to the brain's activity during resting-state consciousness.

General relationship of global topology, local dynamics, and directionality in large-scale brain networks.

The balance of global integration and functional specialization is a critical feature of efficient brain networks, but the relationship of global topology, local node dynamics and information flow across networks has yet to be identified. One critical step in elucidating this relationship is the identification of governing principles underlying the directionality of interactions between nodes. Here, we demonstrate such principles through analytical solutions based on the phase lead/lag relationships of general oscillator models in networks. We confirm analytical results with computational simulations using general model networks and anatomical brain networks, as well as high-density electroencephalography collected from humans in the conscious and anesthetized states. Analytical, computational, and empirical results demonstrate that network nodes with more connections (i.e., higher degrees) have larger amplitudes and are directional targets (phase lag) rather than sources (phase lead). The relationship of node degree and directionality therefore appears to be a fundamental property of networks, with direct applicability to brain function. These results provide a foundation for a principled understanding of information transfer across networks and also demonstrate that changes in directionality patterns across states of human consciousness are driven by alterations of brain network topology.

Neurophysiological correlates of sevoflurane-induced unconsciousness.

BACKGROUND: Recent studies of anesthetic-induced unconsciousness in humans have focused predominantly on the intravenous drug propofol and have identified anterior dominance of alpha rhythms and frontal phase-amplitude coupling patterns as neurophysiological markers. However, it is unclear whether the correlates of propofol-induced unconsciousness are generalizable to inhaled anesthetics, which have distinct molecular targets and which are used more commonly in clinical practice. METHODS: The authors recorded 64-channel electroencephalograms in healthy human participants during consciousness, sevoflurane-induced unconsciousness, and recovery (n = 10; n = 7 suitable for analysis). Spectrograms and scalp distributions of low-frequency (1 Hz) and alpha (10 Hz) power were analyzed, and phase-amplitude modulation between these two frequencies was calculated in frontal and parietal regions. Phase lag index was used to assess phase relationships across the cortex. RESULTS: At concentrations sufficient for unconsciousness, sevoflurane did not result in a consistent anteriorization of alpha power; the relationship between low-frequency phase and alpha amplitude in the frontal cortex did not undergo characteristic transitions. By contrast, there was significant cross-frequency coupling in the parietal region during consciousness that was not observed after loss of consciousness. Furthermore, a reversible disruption of anterior-posterior phase relationships in the alpha bandwidth was identified as a correlate of sevoflurane-induced unconsciousness. CONCLUSION: In humans, sevoflurane-induced unconsciousness is not correlated with anteriorization of alpha and related cross-frequency patterns, but rather by a disruption of phase-amplitude coupling in the parietal region and phase-phase relationships across the cortex.

Assessing levels of consciousness with symbolic analysis.

'Covert consciousness' is a state in which consciousness is present without the capacity for behavioural response, and it can occur in patients with intraoperative awareness or unresponsive wakefulness syndrome. To detect and prevent this undesirable state, it is critical to develop a reliable neurobiological assessment of an individual's level of consciousness that is independent of behaviour. One such approach that shows potential is measuring surrogates of cortical communication in the brain using electroencephalography (EEG). EEG is practicable in clinical application, but involves many fundamental signal processing problems, including signal-to-noise ratio and high dimensional complexity. Symbolic analysis of EEG can mitigate these problems, improving the measurement of brain connectivity and the ability to successfully assess levels of consciousness. In this article, we review the problem of covert consciousness, basic neurobiological principles of consciousness, current methods of measuring brain connectivity and the advantages of symbolic processing, with a focus on symbolic transfer entropy (STE). Finally, we discuss recent advances and clinical applications of STE and other symbolic analyses to assess levels of consciousness.

Critical dynamics in spontaneous EEG predict anesthetic-induced loss of consciousness and perturbational complexity.

Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigate dynamical properties of the resting-state electroencephalogram (EEG) of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. Importantly, all participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams), enabling an experimental dissociation between unresponsiveness and unconsciousness. For each condition, we measure (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related metrics, revealing that states of unconsciousness are characterized by a distancing from both avalanche criticality and the edge of chaos. We then ask whether these same dynamical properties are predictive of the perturbational complexity index (PCI), a TMS-based measure that has shown remarkably high sensitivity in detecting consciousness independently of behavior. We successfully predict individual subjects' PCI values with considerably high accuracy from resting-state EEG dynamical properties alone. Our results establish a firm link between perturbational complexity and criticality, and provide further evidence that criticality is a necessary condition for the emergence of consciousness.

Modulation of brain activity in brain-injured patients with a disorder of consciousness in intensive care with repeated 10-Hz transcranial alternating current stimulation (tACS): a randomised controlled trial protocol.

INTRODUCTION: Therapeutic interventions for disorders of consciousness lack consistency; evidence supports non-invasive brain stimulation, but few studies assess neuromodulation in acute-to-subacute brain-injured patients. This study aims to validate the feasibility and assess the effect of a multi-session transcranial alternating current stimulation (tACS) intervention in subacute brain-injured patients on recovery of consciousness, related brain oscillations and brain network dynamics. METHODS AND ANALYSES: The study is comprised of two phases: a validation phase (n=12) and a randomised controlled trial (n=138). Both phases will be conducted in medically stable brain-injured adult patients (traumatic brain injury and hypoxic-ischaemic encephalopathy), with a Glasgow Coma Scale score ≤12 after continuous sedation withdrawal. Recruitment will occur at the intensive care unit of a Level 1 Trauma Centre in Montreal, Quebec, Canada. The intervention includes a 20 min 10 Hz tACS at 1 mA intensity or a sham session over parieto-occipital cortical sites, repeated over five consecutive days. The current's frequency targets alpha brain oscillations (8-13 Hz), known to be associated with consciousness. Resting-state electroencephalogram (EEG) will be recorded four times daily for five consecutive days: pre and post-intervention, at 60 and 120 min post-tACS. Two additional recordings will be included: 24 hours and 1-week post-protocol. Multimodal measures (blood samples, pupillometry, behavioural consciousness assessments (Coma Recovery Scale-revised), actigraphy measures) will be acquired from baseline up to 1 week after the stimulation. EEG signal analysis will focus on the alpha bandwidth (8-13 Hz) using spectral and functional network analyses. Phone assessments at 3, 6 and 12 months post-tACS, will measure long-term functional recovery, quality of life and caregivers' burden. ETHICS AND DISSEMINATION: Ethical approval for this study has been granted by the Research Ethics Board of the CIUSSS du Nord-de-l'Île-de-Montréal (Project ID 2021-2279). The findings of this two-phase study will be submitted for publication in a peer-reviewed academic journal and submitted for presentation at conferences. The trial's results will be published on a public trial registry database (ClinicalTrials.gov). TRIAL REGISTRATION NUMBER: NCT05833568.

Performance assessment in brain-computer interface-based augmentative and alternative communication.

A large number of incommensurable metrics are currently used to report the performance of brain-computer interfaces (BCI) used for augmentative and alterative communication (AAC). The lack of standard metrics precludes the comparison of different BCI-based AAC systems, hindering rapid growth and development of this technology. This paper presents a review of the metrics that have been used to report performance of BCIs used for AAC from January 2005 to January 2012. We distinguish between Level 1 metrics used to report performance at the output of the BCI Control Module, which translates brain signals into logical control output, and Level 2 metrics at the Selection Enhancement Module, which translates logical control to semantic control. We recommend that: (1) the commensurate metrics Mutual Information or Information Transfer Rate (ITR) be used to report Level 1 BCI performance, as these metrics represent information throughput, which is of interest in BCIs for AAC; 2) the BCI-Utility metric be used to report Level 2 BCI performance, as it is capable of handling all current methods of improving BCI performance; (3) these metrics should be supplemented by information specific to each unique BCI configuration; and (4) studies involving Selection Enhancement Modules should report performance at both Level 1 and Level 2 in the BCI system. Following these recommendations will enable efficient comparison between both BCI Control and Selection Enhancement Modules, accelerating research and development of BCI-based AAC systems.

Biomusic: a novel technology for revealing the personhood of people with profound multiple disabilities.

It is often difficult for family members and caregivers to interact with persons with profound multiple disabilities (PMD) because of the severely compromised communicative repertoire of this population. The resulting communication challenges may limit the ability of others to perceive personhood in individuals with PMD. This preliminary study investigated the effects of music generated in real time from physiological signals (biomusic) on caregiver perceptions of their interactions with persons with PMD. Caregivers (n = 10; parents and clinical staff) engaged in four, 10-min interactions with a person with PMD (n = 3; diagnoses = traumatic brain injury, pervasive developmental disorder, hypoxic brain injury), whose biomusic was projected throughout. Caregivers participated in two open-ended, semi-structured interviews to explore the effect of biomusic on these interactions. Most caregiver responses to biomusic were very positive, and many reported that biomusic caused an improvement in their interaction with and perceptions of the person with PMD. By providing audible evidence of the changing physiological state of persons with PMD, biomusic may enhance the perceived personhood of these individuals and enrich interactions with their family members and caregivers.

"I made you a small room in my heart": how therapeutic clowns meet the needs of older adults in nursing homes.

Therapeutic clowns are increasingly common in nursing homes, where residents often encounter factors that can undermine their quality of life and dignity. We aimed to understand the strategies of successful therapeutic clowning with a diverse older adult population, and the unique contributions of elder-clowning to the nursing home experience. Using an interpretivist descriptive methodology, twenty-three (n=23) experienced therapeutic clowns from eight countries were interviewed to understand the needs of nursing home residents met by elder-clowns, and strategies and techniques the clowns use to address them. Participants identified five major needs: to escape routine; for reassurance of worth; for meaningful, personalized social interaction unrestricted by communication barriers; to have culturally meaningful opportunities for reminiscence; and to have a space where residents could be unapologetically themselves. The artistic and emotional strategies used by the therapeutic clowns to address these needs illustrate how creativity, imagination and relational presence can provide nursing home residents with a sense of being known and belonging. Elder-clowns also positively affect the nursing home staff and enrich the interpersonal interactions in the residence. Through their focus on the social and emotional needs of residents, elder-clowns can play an important and distinct role in creating an optimal nursing home experience.

Assessing Cognitive Outcomes in Coma Survivors: A Literature Review.

(1) Background: Although cognitive impairments in coma survivors are common, methods of measuring long-term cognitive outcomes in this population are inconsistent, precluding the development of a strong evidence-base to support clinical decision making. In this literature review, we identify and characterize the measures used to track cognitive recovery in coma survivors to data. (2) Methods: We extracted the instrument used for cognitive assessment, the cognitive domains assessed, methods administration and scoring, and timing of assessment from 134 of 996 screened records. (3) Results: A total of 133 unique cognitive tests and cognitive testing batteries were identified, with 97 cognitive instruments used in less than three articles. The instruments assessed 20 different cognitive domains, with 73 articles also using tests that assess general "cognitive ability". Cognitive instruments ranged from subjective assessments to comprehensive cognitive batteries. There were inconsistent points of reference for the timing of assessment across studies, with few studies repeating assessments at more than one time point, and arbitrary time intervals between tests. (4) Conclusions: Overall, this review illustrates the enormous disparity between studies that track cognitive outcome in coma survivors, and the need for a systematic, patient-accessible method of assessing cognitive functioning in future studies with this population.

"We are still doing some magic": Exploring the effectiveness of online therapeutic clowning.

BACKGROUND: Therapeutic clowns use embodied practices to engage with clients, their families and healthcare staff to empower patients and create therapeutic relationships. This study explored the effectiveness of a virtual therapeutic clown initiative. METHODS: Thirteen therapeutic clowns participated in a semi-structured interview to discuss their experiences with online clowning; additionally, four dyads consisting of a clown duo and a client explored multiple perspectives of a shared online clowning experience. Data were analyzed according to the six core competencies of therapeutic clowning. RESULTS: Although all therapeutic clowns and caregivers reported challenges and limitations with the medium, virtual therapeutic clowning was effective for empowering clients and forming therapeutic relationships. Clowns successfully used many strategies to maintain their core clowning competencies in the virtual environment. CONCLUSIONS: Virtual clowning may be more beneficial for some clients than in-person clowning and has the potential to extend therapeutic clowning beyond its traditional domains of practice.

Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia.

Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigated dynamical properties of the resting-state electroencephalogram of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. We then studied the relation of these dynamic properties with the perturbational complexity index (PCI), which has shown remarkably high sensitivity in detecting consciousness independent of behavior. All participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams)., enabling an experimental dissociation between unresponsiveness and unconsciousness. We estimated (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related measures, and found that states of unconsciousness were characterized by a distancing from both the edge of activity propagation and the edge of chaos. We were then able to predict individual subjects' PCI (i.e., PCImax) with a mean absolute error below 7%. Our results establish a firm link between the PCI and criticality and provide further evidence for the role of criticality in the emergence of consciousness.

Barriers to and mediators of brain-computer interface user acceptance: focus group findings.

Brain-computer interfaces (BCI) are designed to enable individuals with severe motor impairments such as amyotrophic lateral sclerosis (ALS) to communicate and control their environment. A focus group was conducted with individuals with ALS (n=8) and their caregivers (n=9) to determine the barriers to and mediators of BCI acceptance in this population. Two key categories emerged: personal factors and relational factors. Personal factors, which included physical, physiological and psychological concerns, were less important to participants than relational factors, which included corporeal, technological and social relations with the BCI. The importance of these relational factors was analysed with respect to published literature on actor-network theory (ANT) and disability, and concepts of voicelessness and personhood. Future directions for BCI research are recommended based on the emergent focus group themes. PRACTITIONER SUMMARY: This manuscript explores human factor issues involved in designing and evaluating brain-computer interface (BCI) systems for users with severe motor disabilities. Using participatory research paradigms and qualitative methods, this work draws attention to personal and relational factors that act as barriers to, or mediators of, user acceptance of this technology.

Challenges of developing communicative interaction in individuals with congenital profound intellectual and multiple disabilities.

BACKGROUND: Physiological responses have been used in individuals with acquired disability to enable communicative interaction without motor movement. This study explored four autonomic nervous system (ANS) signals-electrodermal activity, skin temperature, cardiac patterns and respiratory patterns-to enable interaction with individuals born with profound intellectual and multiple disabilities (PIMD). METHOD: A series of case studies were conducted to teach a 15-year-old individual with PIMD to voluntarily control his ANS signals for the purposes of communicative interaction. Training was carried out according to an alternating treatment single-subject research design. RESULTS: Training was unsuccessful; however, ANS signal patterns revealed issues unique to people with PIMD: profound intrasubject variability, discrepancy between physiological responses and caregiver perspectives, and the participant's lack of contingency awareness. CONCLUSIONS: These three priority areas unique to people with congenital PIMD must be addressed before ANS signals can be used to enable communicative interaction with this population.

Paradoxical markers of conscious levels: Effects of propofol on patients in disorders of consciousness.

Human consciousness is widely understood to be underpinned by rich and diverse functional networks, whose breakdown results in unconsciousness. Candidate neural correlates of anesthetic-induced unconsciousness include: (1) disrupted frontoparietal functional connectivity; (2) disrupted brain network hubs; and (3) reduced spatiotemporal complexity. However, emerging counterexamples have revealed that these markers may appear outside of the state they are associated with, challenging both their inclusion as markers of conscious level, and the theories of consciousness that rely on their evidence. In this study, we present a case series of three individuals in disorders of consciousness (DOC) who exhibit paradoxical brain responses to exposure to anesthesia. High-density electroencephalographic data were recorded from three patients with unresponsive wakefulness syndrome (UWS) while they underwent a protocol of propofol anesthesia with a targeted effect site concentration of 2 µg/ml. Network hubs and directionality of functional connectivity in the alpha frequency band (8-13 Hz), were estimated using the weighted phase lag index (wPLI) and directed phase lag index (dPLI). The spatiotemporal signal complexity was estimated using three types of Lempel-Ziv complexity (LZC). Our results illustrate that exposure to propofol anesthesia can paradoxically result in: (1) increased frontoparietal feedback-dominant connectivity; (2) posterior network hubs; and (3) increased spatiotemporal complexity. The case examples presented in this paper challenge the role of functional connectivity and spatiotemporal complexity in theories of consciousness and for the clinical evaluation of levels of human consciousness.