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

EEG Response to Sedation Interruption Complements Behavioral Assessment After Severe Brain Injury

OBJECTIVE

Accurate assessment of the level of consciousness and potential to recover in patients with severe brain injury underpins crucial decisions in the intensive care unit but remains a major challenge for the clinical team. The neurological wake-up test is a widely used assessment tool. However, many patients' behavioral responses during a short interruption of sedation are ambiguous or absent, yielding little prognostic value. This study assesses the brain's electroencephalogram response during an interruption of propofol sedation to complement behavioral assessment during the neurological wake-up test to predict survival, recovery of consciousness, and long-term functional outcomes in patients with acute severe brain injury.

METHODS

We recorded 128-channel EEG from 41 severely brain-injured patients during a clinically indicated neurological wake-up test. Behavioral assessment was performed before and after interruption of propofol sedation, using the Glasgow Coma Scale. Brain response to sedation interruption was quantified using EEG power, spatial ratios, and the spectral exponent.

RESULTS

Recovery of responsiveness during the neurological wake-up test is reflected in participants' brain response to sedation interruption. Electrophysiological patterns can be decoupled from participant behavioral response, with some individuals demonstrating neurophysiological signs of waking up despite an absent behavioral response. Using the brain response to complement behavioral assessment improved prognostic value, distinguished patients according to survival and outperformed outcome predictions of the patients' attending physician.

INTERPRETATION

EEG can complement behavioral assessment during the neurological wake-up test to improve prognostication, inform clinicians, family members, and caregivers, and to set realistic goals for treatment and therapy.

Pharmacological therapies for early and long-term recovery in disorders of consciousness: current knowledge and promising avenues

INTRODUCTION

Disorders of consciousness (DoC) are characterized by impaired arousal and/or awareness, ranging from coma to unresponsive wakefulness syndrome, minimally conscious state, and cognitive motor dissociation. Pharmacological treatment options remain limited, complicated by the heterogeneity of etiologies, such as traumatic brain injury, stroke, and infections. The lack of rigorous clinical trials has led to off-label use of treatments, often without clear mechanistic understanding, posing challenges for effective patient care.

AREAS COVERED

In this perspective, the authors report on key studies concerning the effectiveness of pharmacological interventions, including dopaminergic and GABAergic agents, antidepressants, statins, and anticonvulsants, in promoting recovery of consciousness in DoC.

EXPERT OPINION

Robust longitudinal clinical trials are needed, with priority given to early subacute phase intervention. Outcomes should be better defined, considering immediate responses to medication while also increasing the emphasis on long-term quality of life. Unified functional and mechanistic frameworks are needed to guide research and foster collaboration. Furthermore, a shift toward personalized medicine would benefit this heterogeneous population. Moving forward, assessing the efficacy of more unconventional or 'paradoxical' pharmacological options in treatment plans will be essential. The authors also expect an increased use of AI tools to identify factors that best predict treatment responses.

Capturing the emergent dynamical structure in biophysical neural models

Complex neural systems can display structured emergent dynamics. Capturing this structure remains a significant scientific challenge. Using information theory, we apply Dynamical Independence (DI) to uncover the emergent dynamical structure in a minimal 5-node biophysical neural model, shaped by the interplay of two key aspects of brain organisation: integration and segregation. In our study, functional integration within the biophysical neural model is modulated by a global coupling parameter, while functional segregation is influenced by adding dynamical noise, which counteracts global coupling. Leveraging transfer entropy, DI defines a dimensionally-reduced macroscopic variable (e.g., a coarse-graining) as emergent to the extent that it behaves as an independent dynamical process, distinct from the micro-level dynamics. Dynamical dependence (a departure from dynamical independence) is measured by minimising the transfer entropy from microlevel variables to macroscopic variables across spatial scales. Our results indicate that the degree of emergence of macroscopic variables is relatively minimised at balanced points of integration and segregation and maximised at the extremes. Additionally, our method identifies to which degree the macroscopic dynamics are localised across microlevel nodes, thereby elucidating the emergent dynamical structure through the relationship between microscopic and macroscopic processes. We find that deviation from a balanced point between integration and segregation results in a less localised, more distributed emergent dynamical structure as identified by DI. This finding suggests that a balance of functional integration and segregation is associated with lower levels of emergence (higher dynamical dependence), which may be crucial for sustaining coherent, localised emergent macroscopic dynamical structures. This work also provides a complete computational implementation for the identification of emergent neural dynamics that could be applied both in silico and in vivo.

The changes in neural complexity and connectivity in thalamocortical and cortico-cortical systems after propofol-induced unconsciousness in different temporal scales

Existing studies have indicated neural activity across diverse temporal and spatial scales. However, the alterations in complexity, functional connectivity, and directional connectivity within the thalamocortical and corticocortical systems across various scales during propofol-induced unconsciousness remain uncertain. We analyzed the stereo-electroencephalography (SEEG) from wakefulness to unconsciousness among the brain regions of the prefrontal cortex, temporal lobe, and anterior nucleus of the thalamus. The complexity (examined by permutation entropy (PE)), functional connectivity (permutation mutual information (PMI)), and directional connectivity (symbolic conditional mutual information (SCMI) and directionality index (DI)) were calculated across various scales. In the lower-band frequency (0.1-45 Hz) SEEG, after the loss of consciousness, PE significantly decreased (p < 0.001) in all regions and scales, except for the thalamus, which remained relatively unchanged at large scales (τ=32 ms). Following the loss of consciousness, inter-regional PMI either significantly increased or remained stable across different scales (τ=4 ms to 32 ms). During the unconscious state, SCMI between brain regions exhibited inconsistent changes across scales. In the late unconscious stage, the inter-regional DI across all scales indicated a shift from a balanced state of information flow between brain regions to a pattern where the prefrontal cortex and thalamus drive the temporal lobe. Our findings demonstrate that propofol-induced unconsciousness is associated with reduced cortical complexity, diverse functional connectivity, and a disrupted balance of information integration among thalamocortical and cortico-cortical systems. This study enhances the theoretical understanding of anesthetic-induced loss of consciousness by elucidating the scale- and region-specific effects of propofol on thalamocortical and cortico-cortical systems.

Spatiospectral dynamics of electroencephalography patterns during propofol-induced alterations of consciousness states

Altered consciousness induced by anesthetics is characterized by distinct spatial and spectral neural dynamics that are readily apparent in the human electroencephalogram. Despite considerable study, we remain uncertain which brain regions and neural oscillations are involved, as well as how they are impacted when consciousness is disrupted. The experimental data was obtained from the open-access dataset, which contains pre-processed EEG data recorded from 20 healthy participants during propofol sedation. Using unsupervised machine learning methods (i.e., non-negative matrix factorization, NMF), we investigated the spatiospectral dynamic evolution of brain activity from awake to sedation and back induced by propofol in healthy research volunteers. Our methods yielded six dynamical patterns that continuously reflect the neural activity changes in specific brain regions and frequency bands under propofol sedation. Temporal dynamic analyses showed that differences in alpha oscillation patterns were less pronounced in response group than drowsy group, with hemispheric asymmetry in posterior occipital lobe over the course of the sedation procedure. We designed an index 'hemispheric lateralization modulation of alpha [HLM(α)]' to measure asymmetry during awake state and predicting individual variability in propofol-induced alterations of consciousness states, obtaining prediction AUC of 0.8462. We present an alpha modulation index which characterizes how these patterns track the transition from awake to sedation as a function of increasing dosage. Our study reveals dynamics indices that track the evolution of neurophysiological of propofol on brain circuits. Analyzing the spatiospectral dynamics influenced by propofol provides valuable understanding of the mechanisms of these agents and strategies for monitoring and precisely controlling the level of consciousness in patients under sedation and general anesthesia.

Prediction of Alpha Power Using Multiple Subjective Measures and Autonomic Responses

Alpha oscillations are associated with various cognitive functions. However, the determinants of alpha power variation remain ambiguous, primarily due to its inconsistent associations with autonomic responses and subjective states under different experimental conditions. To thoroughly examine the correlations between alpha power variation and these factors, we implemented a range of experimental conditions, encompassing attentional and emotional tasks, as well as a resting-state. In addition to the electroencephalogram data, we gathered a suite of autonomic response measurements and subjective ratings. We employed multiple linear regression analysis, utilizing autonomic responses and subjective reports as predictors of alpha power. We also subtracted the aperiodic components for better estimation of the power of periodic alpha oscillations. Our results from two separately conducted experiments robustly demonstrated that the combined use of autonomic response measurements and subjective ratings effectively predicted the parietal-occipital periodic alpha power variation across a range of conditions. These predictions were supported by leave-one-participant-out cross-validation and cross-experiment validation, confirming that multiple linear relationships can be generalized to new participants. This study demonstrates the links of alpha power variations with autonomic responses and subjective states, suggesting that during investigations of the cognitive functions of alpha oscillations, it is important to consider the potential influences of autonomic responses and subjective states on alpha oscillations.

A pilot human study using ketamine to treat disorders of consciousness

Post-comatose disorders of consciousness (DoC) represent persistent neurological conditions with limited therapeutic options and a poor prognosis. Recent works advocate for exploring the effects of psychedelics to enhance brain complexity in DoC and ameliorate their consciousness. We investigated sub-anesthetic concentration of the atypical psychedelic ketamine for treating post-comatose prolonged DoC through a double-blind, placebo-controlled, cross-over trial involving three adult patients. Incremental concentrations of intravenous ketamine and saline were administered, alongside continuous electroencephalogram (EEG) recording and assessments of conscious behaviors and spastic paresis. Brain complexity, measured by Lempel-Ziv complexity (LZC) and explainable consciousness indicator (ECI), revealed increased LZC during ketamine infusion but no change in ECI. Patients exhibited reduced spastic paresis and increased arousal as time spent with eyes open but no positive change in diagnosis. No adverse effects were noted. This study contributes to understanding the relationship between consciousness and brain complexity and suggests a potential therapeutic role for ketamine in DoC.

Electrophysiological Signatures of Alpha Coma

PURPOSE

Recent research on quantitative EEG in coma has proposed several metrics correlating with consciousness level. However, the heterogeneous nature of coma can challenge the generalizability of these measures. This study investigates alpha-coma, an electroclinical pattern characterized by a widespread, nonreactive alpha rhythm often linked to poor outcomes. The aim was to quantify the electrophysiological features of alpha-coma and compare them to the alpha rhythm in awake controls, seeking clearer insights into quantitative EEG analysis in comatose states.

METHODS

Fourteen alpha-coma patients were retrospectively selected from University Hospitals of Geneva and age-matched with 14 healthy control subjects from an open-source dataset. EEG data were preprocessed and analyzed to extract power spectra, spectral decay (aperiodic activity), sample entropy, and functional connectivity.

RESULTS

Alpha-coma patients did not differ in alpha power but exhibited significantly higher levels of spectral decay ( p < 0.001), suggesting a convergence toward an inhibitory state. Sample entropy was significantly higher in alpha-coma patients ( p = 0.01), indicating an increase in the cortical complexity in alpha-coma compared with healthy subjects.

CONCLUSIONS

Alpha-coma shows increased aperiodic activity and EEG complexity, despite similar alpha power and clustering coefficient. The increased aperiodic activity aligns with findings in other comatose patients, including those sedated or with subcortical dysfunction. However, the increased entropy contradicts existing literature, suggesting that alpha-coma may represent a state of widespread cortical dysfunction likely resulting from nonhierarchical, turbulent brain activity. This indicates that the loss of consciousness does not guarantee consistent cortical measures across the whole spectrum of EEG patterns.

The Lifespan Evolution of Individualized Neurophysiological Traits

How do neurophysiological traits that characterize individuals evolve across the lifespan? To address this question, we analyzed brief, task-free magnetoencephalographic recordings from over 1,000 individuals aged 4-89. We found that neurophysiological activity is significantly more similar between individuals in childhood than in adulthood, though periodic patterns of brain activity remain reliable markers of individuality across all ages. The cortical regions most critical for determining individuality shift across neurodevelopment and aging, with sensorimotor cortices becoming increasingly prominent in adulthood. These developmental changes in neurophysiology align closely with the expression of cortical genetic systems related to ion transport and neurotransmission, suggesting a growing influence of genetic factors on neurophysiological traits across the lifespan. Notably, this alignment peaks in late adolescence, a critical period when genetic factors significantly shape brain individuality. Overall, our findings highlight the role of sensorimotor regions in defining individual brain traits and reveal how genetic influences on these traits intensify with age. This study advances our understanding of the evolving biological foundations of inter-individual differences.

Lay summary

This study examines how brain activity reflects the development of individuality across a person's life. Using magnetoencephalography to capture brief recordings of spontaneous brain activity, the researchers distinguished between over 1,000 individuals, spanning ages 4 to 89. They found that the brain regions most associated with individuality change with age: sensory and motor regions become increasingly distinctive in early adulthood, highlighting their role in shaping a person's unique characteristics of brain activity. The study also revealed that changes in brain activity across different ages correspond to specific patterns of gene expression, shedding light on how genetics influence brain individuality. These findings deepen our understanding of the biological foundations of inter-individual differences and how it evolves over the lifespan.

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.

Detecting awareness after acute brain injury

Advances over the past two decades in functional neuroimaging have provided new diagnostic and prognostic tools for patients with severe brain injury. Some of the most pertinent developments in this area involve the assessment of residual brain function in patients in the intensive care unit during the acute phase of severe injury, when they are at their most vulnerable and prognosis is uncertain. Advanced neuroimaging techniques, such as functional MRI and EEG, have now been used to identify preserved cognitive processing, including covert conscious awareness, and to relate them to outcome in patients who are behaviourally unresponsive. Yet, technical and logistical challenges to clinical integration of these advanced neuroimaging techniques remain, such as the need for specialised expertise to acquire, analyse, and interpret data and to determine the appropriate timing for such assessments. Once these barriers are overcome, advanced functional neuroimaging technologies could improve diagnosis and prognosis for millions of patients worldwide.

Adolescent-to-adult gains in cognitive flexibility are adaptively supported by reward sensitivity, exploration, and neural variability

Cognitive flexibility exhibits dynamic changes throughout development, with different forms of flexibility showing dissociable developmental trajectories. In this review, we propose that an adolescent-specific mode of flexibility in the face of changing environmental contingencies supports the emergence of adolescent-to-adult gains in cognitive shifting efficiency. We first describe how cognitive shifting abilities monotonically improve from childhood to adulthood, accompanied by increases in brain state flexibility, neural variability, and excitatory/inhibitory balance. We next summarize evidence supporting the existence of a dopamine-driven, adolescent peak in flexible behavior that results in reward seeking, undirected exploration, and environmental sampling. We propose a neurodevelopmental framework that relates these adolescent behaviors to the refinement of neural phenotypes relevant to mature cognitive flexibility, and thus highlight the importance of the adolescent period in fostering healthy neurocognitive trajectories.

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.

Electroencephalographic signatures of consciousness: uncovering the fake news

Amongst electroencephalographic markers of anaesthetic-induced unresponsiveness, those that estimate loss of frontoparietal functional connectivity detect loss of sensory perceptual connection with the outside world, rather than full phenomenological unconsciousness. This transition to unconsciousness is manifest as further incremental changes in indices of electroencephalographic complexity.

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.

The biological role of local and global fMRI BOLD signal variability in human brain organization

Variability drives the organization and behavior of complex systems, including the human brain. Understanding the variability of brain signals is thus necessary to broaden our window into brain function and behavior. Few empirical investigations of macroscale brain signal variability have yet been undertaken, given the difficulty in separating biological sources of variance from artefactual noise. Here, we characterize the temporal variability of the most predominant macroscale brain signal, the fMRI BOLD signal, and systematically investigate its statistical, topographical and neurobiological properties. We contrast fMRI acquisition protocols, and integrate across histology, microstructure, transcriptomics, neurotransmitter receptor and metabolic data, fMRI static connectivity, and empirical and simulated magnetoencephalography data. We show that BOLD signal variability represents a spatially heterogeneous, central property of multi-scale multi-modal brain organization, distinct from noise. Our work establishes the biological relevance of BOLD signal variability and provides a lens on brain stochasticity across spatial and temporal scales.

Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach

Background

Stroke is a debilitating disease affecting millions of people worldwide. Despite the survival rate has significantly increased over the years, many stroke survivors are left with severe impairments impacting their quality of life. Rehabilitation programs have proved to be successful in improving the recovery process. However, a reliable model of sensorimotor recovery and a clear identification of predictive markers of rehabilitation-induced recovery are still needed. This article introduces the cross-modality protocols designed to investigate the rehabilitation treatment's effect in a group of stroke survivors.

Methods/design

A total of 75 stroke patients, admitted at the IRCCS San Camillo rehabilitation Hospital in Venice (Italy), will be included in this study. Here, we describe the rehabilitation programs, clinical, neuropsychological, and physiological/imaging [including electroencephalography (EEG), transcranial magnetic stimulation (TMS), and magnetic resonance imaging (MRI) techniques] protocols set up for this study. Blood collection for the characterization of predictive biological biomarkers will also be taken. Measures derived from data acquired will be used as candidate predictors of motor recovery.

Discussion/summary

The integration of cutting-edge physiological and imaging techniques, with clinical and cognitive assessment, dose of rehabilitation and biological variables will provide a unique opportunity to define a predictive model of recovery in stroke patients. Taken together, the data acquired in this project will help to define a model of rehabilitation induced sensorimotor recovery, with the final aim of developing personalized treatments promoting the greatest chance of recovery of the compromised functions.