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

Abstract

1AbstractConsciousness 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.2Significance StatementComplexity has long been of interest in consciousness science and had a fundamental impact on many of today’s theories of consciousness. The perturbational complexity index (PCI) uses the complexity of the brain’s response to cortical perturbations to quantify the presence of consciousness. We propose criticality as a unifying framework underlying maximal complexity and sensitivity to perturbation in the conscious brain. We demonstrate that criticality measures derived from resting-state electroencephalography can distinguish conscious from unconscious states, using propofol, xenon and ketamine anesthesia, and from these measures we were able to predict the PCI with a mean error below 7%. Our results support the hypothesis that critical brain dynamics are implicated in the emergence of consciousness and may provide new directions for the assessment of consciousness.

Hemispherotomy: cortical islands of deep sleep in awake humans

“…Third, the spectral exponent has been previously tested as an index of consciousness in large samples of healthy controls and patients, including challenging conditions of sensorimotor disconnection and behavioral unresponsiveness. In good agreement with perturbational measures of brain complexity (the Perturbational Complexity Index 84 ), the spectral exponent robustly discriminated between conscious and unconscious states, across wakefulness, sleep, physiological or pharmacological dreams, anesthesia induced by different compounds, and severe brain injury 18,41,43,45 . Furthemore, unlike other clinical brainbased markers of consciousness, the spectral exponent has been validated across the sleep-wake cycle in a reference pediatric sample 46 , spanning the typical age range of patients undergoing cortical disconnection.…”

“…Further, to provide a comprehensive quanti cation of broad-band electrophysiological slowing, we estimated the spectral exponent, which re ects the 1/f-like decay of the Power Spectral Density (PSD) and thus the relative contribution of high and low frequencies. Notably, the spectral exponent has been proven as a reliable index of consciousness across various physiological 32,33,34,35,36,37,38,39,40 pharmacological 41,42,43,44,45 and pathological conditions 18,42,44 , including states of disconnected consciousness. Crucially in the present context, the spectral exponent has been extensively validated in large pediatric samples to distinguish between wakefulness 46,47,48,49 and various sleep stages, including deep NREM sleep 35,46 .…”

Psychedelics and disorders of consciousness: the current landscape and the path forward

“…2023 )]. Only recently new experimental investigations are pinpointing the relationship between criticality and other measures, such as PCI ( Maschke et al. 2023 ) or surrogates of integrated information ( Kim and Lee 2019 ).…”

The role of etiology in the identification of clinical markers of consciousness: comparing EEG alpha power, complexity, and spectral exponent

“…However, it remains unclear whether EEG complexity is an independent marker of level of consciousness, or epiphenomenal to changes in the spectral exponent. Although many studies have demonstrated a strong correlation between spectral exponent and spontaneous (Medel et al 2020;Alnes et al 2021;Maschke, Duclos, Owen, et al 2022) and evoked signal complexity (Colombo et al 2019;Maschke et al 2023), most studies of signal complexity do not concurrently analyze changes in the spectral exponent.…”