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Despite the absence of responsiveness during anesthesia, conscious experience may persist. However, reliable, easily acquirable and interpretable neurophysiological markers of the presence of consciousness in unresponsive states are still missing. A promising marker is based on the decay-rate of the power spectral density (PSD) of the resting EEG. We acquired resting electroencephalogram (EEG) in three groups of healthy participants (n = 5 each), before and during anesthesia induced by either xenon, propofol or ketamine. Dosage of each anesthetic agent was tailored to yield unresponsiveness (Ramsay score = 6). Delayed subjective reports assessed whether conscious experience was present (‘Conscious report’) or absent/inaccessible to recall (‘No Report’). We estimated the decay of the PSD of the resting EEG—after removing oscillatory peaks—via the spectral exponent β, for a broad band (1–40 Hz) and narrower sub-bands (1–20 Hz, 20–40 Hz). Within-subject anesthetic changes in β were assessed. Furthermore, based on β, ‘Conscious report’ states were discriminated against ‘no report’ states. Finally, we evaluated the correlation of the resting spectral exponent with a recently proposed index of consciousness, the Perturbational Complexity Index (PCI), derived from a previous TMS-EEG study. The spectral exponent of the resting EEG discriminated states in which consciousness was present (wakefulness, ketamine) from states where consciousness was reduced or abolished (xenon, propofol). Loss of consciousness substantially decreased the (negative) broad-band spectral exponent in each subject undergoing xenon or propofol anesthesia—indexing an overall steeper PSD decay. Conversely, ketamine displayed an overall PSD decay similar to that of wakefulness—consistent with the preservation of consciousness—yet it showed a flattening of the decay in the high-frequencies (20–40 Hz)—consistent with its specific mechanism of action. The spectral exponent was highly correlated to PCI, corroborating its interpretation as a marker of the presence of consciousness. A steeper PSD of the resting EEG reliably indexed unconsciousness in anesthesia, beyond sheer unresponsiveness. •Unconsciousness does not imply unresponsiveness.•Consciousness is abolished during xenon and propofol, yet preserved during ketamine.•EEG Spectral exponent indexes the 1/f-like decay of non-oscillatory PSD background.•Xenon and propofol steepen broad-band decay; ketamine flattens high-frequency decay.•Spectral exponent separates un/consciousness in anesthesia-induced unresponsiveness.

By connecting old and recent notions, different spatial scales, and research domains, we introduce a novel framework on the consequences of brain injury focusing on a key role of slow waves. We argue that the long-standing finding of EEG slow waves after brain injury reflects the intrusion of sleep-like cortical dynamics during wakefulness; we illustrate how these dynamics are generated and how they can lead to functional network disruption and behavioral impairment. Finally, we outline a scenario whereby post-injury slow waves can be modulated to reawaken parts of the brain that have fallen asleep to optimize rehabilitation strategies and promote recovery. In this Perspective, the authors propose that brain injury can result in sleep-like slowing of cortical EEG waves during wakefulness. The generation of these dynamics and their effects on brain networks and behavior are discussed, as well as future directions for neuromodulation.

Consciousness can be defined by two components: arousal (wakefulness) and awareness (subjective experience). However, neurophysiological consciousness metrics able to disentangle between these components have not been reported. Here, we propose an explainable consciousness indicator (ECI) using deep learning to disentangle the components of consciousness. We employ electroencephalographic (EEG) responses to transcranial magnetic stimulation under various conditions, including sleep ( n  = 6), general anesthesia ( n  = 16), and severe brain injury ( n  = 34). We also test our framework using resting-state EEG under general anesthesia ( n  = 15) and severe brain injury ( n  = 34). ECI simultaneously quantifies arousal and awareness under physiological, pharmacological, and pathological conditions. Particularly, ketamine-induced anesthesia and rapid eye movement sleep with low arousal and high awareness are clearly distinguished from other states. In addition, parietal regions appear most relevant for quantifying arousal and awareness. This indicator provides insights into the neural correlates of altered states of consciousness. The authors propose an explainable consciousness indicator using deep learning to quantify arousal and awareness under sleep, anesthesia, and in patients with disorders of consciousness.

Over the last years, a surge of empirical studies converged on complexity-related measures as reliable markers of consciousness across many different conditions, such as sleep, anesthesia, hallucinatory states, coma, and related disorders. Most of these measures were independently proposed by researchers endorsing disparate frameworks and employing different methods and techniques. Since this body of evidence has not been systematically reviewed and coherently organized so far, this positive trend has remained somewhat below the radar. The aim of this paper is to make this consilience of evidence in the science of consciousness explicit. We start with a systematic assessment of the growing literature on complexity-related measures and identify their common denominator, tracing it back to core theoretical principles and predictions put forward more than 20 years ago. In doing this, we highlight a consistent trajectory spanning two decades of consciousness research and provide a provisional taxonomy of the present literature. Finally, we consider all of the above as a positive ground to approach new questions and devise future experiments that may help consolidate and further develop a promising field where empirical research on consciousness appears to have, so far, naturally converged.

Brain responses to transcranial magnetic stimulation (TMS) as measured with electroencephalography (EEG) have so far been assessed either by TMS-evoked EEG potentials (TEPs), mostly reflecting phase-locked neuronal activity, or time-frequency-representations (TFRs), reflecting oscillatory power arising from a mixture of both evoked (i.e., phase-locked) and induced (i.e., non-phase-locked) responses. Single-pulse TMS of the human primary motor cortex induces a specific pattern of oscillatory changes, characterized by an early (30–200 ms after TMS) synchronization in the α- and β-bands over the stimulated sensorimotor cortex and adjacent lateral frontal cortex, followed by a late (200–400 ms) α- and β-desynchronization over the stimulated and contralateral sensorimotor cortex. As GABAergic inhibition plays an important role in shaping oscillatory brain activity, we sought here to understand if GABAergic inhibition contributes to these TMS-induced oscillations. We tested single oral doses of alprazolam, diazepam, zolpidem (positive modulators of the GABAA receptor), and baclofen (specific GABAB receptor agonist). Diazepam and zolpidem enhanced, and alprazolam tended to enhance while baclofen decreased the early α-synchronization. Alprazolam and baclofen enhanced the early β-synchronization. Baclofen enhanced the late α-desynchronization, and alprazolam, diazepam and baclofen enhanced the late β-desynchronization. The observed GABAergic drug effects on TMS-induced α- and β-band oscillations were not explained by drug-induced changes on corticospinal excitability, muscle response size, or resting-state EEG power. Our results provide first insights into the pharmacological profile of TMS-induced oscillatory responses of motor cortex. •The response to TMS of M1 is composed of evoked and induced oscillatory activity.•TMS induced early α-/β-synchronization and late α-/β-desynchronization in M1.•GABAAergic vs. GABABergic drugs had opposite effects on early α-synchronization.•GABAAergic and GABABergic drugs enhanced the late β-desynchronization.

Transcranial magnetic stimulation (TMS) of the primary motor cortex (M1) can excite both cortico-cortical and cortico-spinal axons resulting in TMS-evoked potentials (TEPs) and motor-evoked potentials (MEPs), respectively. Despite this remarkable difference with other cortical areas, the influence of motor output and its amplitude on TEPs is largely unknown. Here we studied TEPs resulting from M1 stimulation and assessed whether their waveform and spectral features depend on the MEP amplitude. To this aim, we performed two separate experiments. In experiment 1, single-pulse TMS was applied at the same supra-threshold intensity on primary motor, prefrontal, premotor and parietal cortices and the corresponding TEPs were compared by means of local mean field power and time-frequency spectral analysis. In experiment 2 we stimulated M1 at resting motor threshold in order to elicit MEPs characterized by a wide range of amplitudes. TEPs computed from high-MEP and low-MEP trials were then compared using the same methods applied in experiment 1. In line with previous studies, TMS of M1 produced larger TEPs compared to other cortical stimulations. Notably, we found that only TEPs produced by M1 stimulation were accompanied by a late event-related desynchronization (ERD-peaking at ~300 ms after TMS), whose magnitude was strongly dependent on the amplitude of MEPs. Overall, these results suggest that M1 produces peculiar responses to TMS possibly reflecting specific anatomo-functional properties, such as the re-entry of proprioceptive feedback associated with target muscle activation.

During non-rapid eye movement (NREM) sleep (stage N3), when consciousness fades, cortico-cortical interactions are impaired while neurons are still active and reactive. Why is this? We compared cortico-cortical evoked-potentials recorded during wakefulness and NREM by means of time–frequency analysis and phase-locking measures in 8 epileptic patients undergoing intra-cerebral stimulations/recordings for clinical evaluation. We observed that, while during wakefulness electrical stimulation triggers a chain of deterministic phase-locked activations in its cortical targets, during NREM the same input induces a slow wave associated with an OFF-period (suppression of power>20Hz), possibly reflecting a neuronal down-state. Crucially, after the OFF-period, cortical activity resumes to wakefulness-like levels, but the deterministic effects of the initial input are lost, as indicated by a sharp drop of phase-locked activity. These findings suggest that the intrinsic tendency of cortical neurons to fall into a down-state after a transient activation (i.e. bistability) prevents the emergence of stable patterns of causal interactions among cortical areas during NREM. Besides sleep, the same basic neurophysiological dynamics may play a role in pathological conditions in which thalamo-cortical information integration and consciousness are impaired in spite of preserved neuronal activity. •Human intracranial cortico-cortical evoked potentials change upon falling asleep.•Stimulation during NREM sleep triggers a slow wave-like response.•Slow waves are characterized by brief activations followed by cortical OFF-periods.•This bistable dynamics obliterates the causal effect of the stimulation.•Bistability disrupts causal interactions within the sleeping brain.

•Sleep and development cause the EEG-PSD to rotate over opposite directions.•Wake and light-sleep PSD rotates over age, displaying flatter slope and lower offset.•Deep-sleep PSD decreases its offset over age, while retaining similar slope over age.•The hot-spot with slowest PSD migrates following a postero-anterior gradient over age.•Wake and light-sleep EEG aperiodic activity diverge from deep sleep activity over age. During development, the brain undergoes radical structural and functional changes following a posterior-to-anterior gradient, associated with profound changes of cortical electrical activity during both wakefulness and sleep. However, a systematic assessment of the developmental effects on aperiodic EEG activity maturation across vigilance states is lacking, particularly regarding its topographical aspects. Here, in a population of 160 healthy infants, children and teenagers (from 2 to 17 years, 10 subjects for each year), we investigated the development of aperiodic EEG activity in wakefulness and sleep. Specifically, we parameterized the shape of the aperiodic background of the EEG Power Spectral Density (PSD) by means of the spectral exponent and offset; the exponent reflects the rate of exponential decay of power over increasing frequencies and the offset reflects an estimate of the y-intercept of the PSD. We found that sleep and development caused the EEG-PSD to rotate over opposite directions: during wakefulness the PSD showed a flatter decay and reduced offset over development, while during sleep it showed a steeper decay and a higher offset as sleep becomes deeper. During deep sleep (N2, N3) only the spectral offset decreased over age, indexing a broad-band voltage reduction. As a result, the difference between values in deep sleep and those in both light sleep (N1) and wakefulness increased with age, suggesting a progressive differentiation of wakefulness from sleep EEG activity, most prominent over the frontal regions, the latest to complete maturation. Notably, the broad-band spectral exponent values during deep sleep stages were entirely separated from wakefulness values, consistently across developmental ages and in line with previous findings in adults. Concerning topographical development, the location showing the steepest PSD decay and largest offset shifted from posterior to anterior regions with age. This shift, particularly evident during deep sleep, paralleled the migration of sleep slow wave activity and was consistent with neuroanatomical and cognitive development. Overall, aperiodic EEG activity distinguishes wakefulness from sleep regardless of age; while, during development, it reveals a postero-anterior topographical maturation and a progressive differentiation of wakefulness from sleep. Our study could help to interpret changes due to pathological conditions and may elucidate the neurophysiological processes underlying the development of wakefulness and sleep.

Prolonged wakefulness alters cortical excitability, which is essential for proper brain function and cognition. However, besides prior wakefulness, brain function and cognition are also affected by circadian rhythmicity. Whether the regulation of cognition involves a circadian impact on cortical excitability is unknown. Here, we assessed cortical excitability from scalp electroencephalography (EEG) responses to transcranial magnetic stimulation in 22 participants during 29 h of wakefulness under constant conditions. Data reveal robust circadian dynamics of cortical excitability that are strongest in those individuals with highest endocrine markers of circadian amplitude. In addition, the time course of cortical excitability correlates with changes in EEG synchronization and cognitive performance. These results demonstrate that the crucial factor for cortical excitability, and basic brain function in general, is the balance between circadian rhythmicity and sleep need, rather than sleep homoeostasis alone. These findings have implications for clinical applications such as non-invasive brain stimulation in neurorehabilitation. Cognitive performance is impaired after prolonged wakefulness, yet the contribution of circadian rhythms for proper brain function remains unclear. Here the authors show that cortical excitability measured using TMS exhibits robust circadian dynamics which is correlated with cognitive performance.

The proportion of patients with metastatic colorectal cancer (mCRC) receiving second or further lines of treatment has not been widely studied. To shed light on this issue, we retrospectively analysed the treatments administered for metastatic disease, and investigated prognostic factors after a diagnosis of metastases, in a consecutive cohort of mCRC patients. Three hundred forty-six mCRC patients were enrolled: 173 were stage II or III (metachronous group), and 173 stage IV (synchronous group) at diagnosis. Survival was calculated between the date of metastatic disease and the date of death or last follow-up. Patients with synchronous lesions more frequently had multiple disease sites, peritoneal carcinomatosis and massive liver deposits, whereas significantly more patients with metachronous lesions developed lung metastases as the sole disease site. 97.4% patients received at least one, 62.4% two, 41.9% three and 23.7% four treatment lines. Patients with metachronous metastases more frequently underwent surgery of metastases in first-line treatment (48.5 versus 24.8%), and more of them were progression-free at the time of the analysis (44 versus 34.9%). At univariate analysis, age > 70 years, multiple disease sites and peritoneal carcinomatosis were associated with significantly decreased survival, whereas surgery of metastases and isolated lung metastases predicted better survival. At multivariate analysis, only peritoneal carcinomatosis and surgery of metastases independently affected survival. The percentage of patients who received an active treatment decreased going from first- to fourth-line treatment. However, the proportion of patients who received efficacious treatment in advanced line remained high. Surgery of metastases was the most important prognostic factors.