Giving a definition of consciousness with a coherent theoretical framework is a daunting task that would benefit from simple conceptual dissociations to improve interpretability. Identifying the neural correlates of consciousness has become crucial to allow progress in the science of consciousness. Following the Koch and Crick seminal definition, neural correlates of consciousness are the minimal neural processes that must occur in the brain for a particular conscious experience to occur (Crick and Koch 1990). However, this definition leaves the possibility of multiple types of neuronal markers of consciousness, two of which are those of conscious contents and those of states of consciousness.

Traditionally, research on consciousness has developed separately in these two pillars. While some researchers, mainly cognitive neuroscientists, primarily focused on the neuronal processes behind conscious access of specific content (e.g. the capacity to report stimuli as seen versus not seen or to discriminate stimuli). The second line of researchers focused on global states of consciousness (e.g. sleep, anesthesia, and disorders of consciousness) (Goupil and Bekinschtein 2012, Sanders et al. 2012, Boly et al. 2013, Bayne et al. 2016). This research has been rather developed by physicians with questions of diagnosis and prognosis often sanctioned by ethical and end-of-life questions.

Neuronal markers of content (NM-Cs) are a reflection of the neural processes that occur for a specific experience. On one hand, NM-Cs are studied by comparing conditions where specific conscious content (e.g. perception of sound or image) is present or absent while stimulus properties and the state of consciousness remain unchanged. The difference between the neural activities averaged by trials depending on the capacity to report (reported perceived, e.g. “seen”) compared to the lack of capacity to report (reported not perceived, e.g. “unseen”) is generally considered to be a marker of access content. Several different paradigms exist such as perceptual suppression, masking, or threshold paradigms in different sensory modalities (Kim and Blake 2005, Del Cul et al. 2007, Dehaene and Changeux 2011). On another hand, there are tasks that assess the capacity to attend and integrate perceptual and cognitive hierarchical regularities such as the auditory local–global (LG) paradigm (Bekinschtein et al. 2009). The two different types of paradigms and examples show a gradient of content—where one end is about the mentioned access consciousness (seen/unseen), and on the other hand is the processing of hierarchical regularities (the LG paradigm as an example). Various methods such as electroencephalography (EEG), magnetoencephalography, or functional magnetic resonance imaging (fMRI) allow for studying the neural correlates of these conscious perceptual experiences (Tsuchiya et al. 2015, Koch et al. 2016). From these studies, the NM-Cs differentiate the “seen” from the “unseen” range from the primary and secondary networks of early perceptual and cognitive integration to abstract cognitive implementation associative areas (Dehaene and Changeux 2011). Electrophysiological studies on monkeys and humans have revealed several signatures of auditory awareness like P3b event-related potentials and oscillations in α/β (9–30 Hz) and γ (>40 Hz) bands between the visual cortex and frontoparietal cortices (Dehaene and Changeux 2011).

Neuronal markers of state (NM-Ss) are used to differentiate states of consciousness. These include conditions as diverse as sleep, partial complex seizures, general anesthesia, and patients in an unresponsive wakefulness syndrome (UWS) or minimally consciousness state (Laureys et al. 2004). NM-Ss can signal the emergence of consciousness, with the brain having to be at an appropriate level of processing to “ensure adequate cortical excitability” for the emergence of consciousness (Koch et al. 2016). Consciousness disorders in patients with brain injury are a good model as they provide a spectrum of different conscious states. The current taxonomy to describe these patients is based on behavioral responsiveness [Coma Recovery Scale-Revised, CRS-R (Kalmar and Giacino 2005)]. This evaluation classifies these patients in different clinical conditions: UWS (Laureys et al. 2010)—previously called the vegetative state, characterized by a behavioral examination of preserved reflexive behavior, such as eye-opening and spontaneous breathing, without apparent awareness of self and the environment (Jennett and Plum 1972). The second clinical condition is the minimally conscious state (MCS) [more recently proposed to be renamed as cortically mediated state (Naccache 2018)], where patients show reproducible behavioral responses, suggesting environmental awareness, such as slow visual pursuit or response to simple commands; and finally, the emergence from MCS, where the patient is able to maintain some degree of basic communication (Giacino et al. 2002). These three clinical categories can be considered “ordered” in a gradient reflecting the richness of conscious experience (Bayne et al. 2016). Additionally, MCS can be subcategorized into MCS− and MCS+. MCS− refers to patients who demonstrate non-reflexive behaviors like visual pursuit and orientation to stimuli, whereas MCS+ denotes patients capable of more advanced behaviors such as command following and verbalization, signifying higher levels of awareness and communication ability within the MCS spectrum (Bruno et al. 2011, Edlow et al. 2021) (for a review, see Edlow et al. (2021) on further details of disorders of consciousness (DoC) and the patients’ emergence).

The theoretical and behavioral findings are also verified—and in many cases enriched (Naccache 2018)—by NM-Ss. For example, different electrophysiological markers derived from EEG recording in a resting state (Chennu et al. 2014, Sitt et al. 2014) are able to discriminate UWS patients from MCS patients. In the same way, fMRI during a resting state period (Demertzi et al. 2014, 2015, 2019, Di Perri et al. 2016), positron emission tomography with metabolic markers (Stender et al. 2014, Hermann et al. 2021b) or the calculation of an index reflecting the EEG reaction after stimulation by transcranial magnetic stimulation (Casarotto et al. 2016), is capable of discriminating between UWS and MCS patients. This contrast makes it possible to study the UWS as a state of wakefulness without awareness, and the MCS as a state with minimal behaviors consistent with awareness of the environment or the self. Sleep provides an additional valuable model of altered and reversible states of consciousness, with the advantage of the possibility of recording NM-Ss in healthy participants. Indeed, there are clear EEG markers (Comsa et al. 2019, Imperatori et al. 2021, Manasova and Stankovski 2023) and fMRI activity patterns characterizing brain activity in wakefulness and during different sleep stages (Dang-Vu et al. 2010, Peigneux 2014, Song and Tagliazucchi 2020). Additional models of interest include anesthesia (Lewis et al. 2012, Barttfeld et al. 2015, Chennu et al. 2016, Zelmann et al. 2023) or complex seizures (Guo et al. 2016, Blumenfeld 2021).

Hence, there is rich literature studying particular brain activity features as putative NM-Ss or NM-Cs. However, not much is known when it comes to comparing those given features on both dimensions simultaneously. While several studies have attempted to study content and state separately, a theoretical development proposes a 3D axis with an x-axis corresponding to subjective conscious content (as reported by the participant), the y-axis to the objective state of consciousness (defined by behavior and body signals), and the z-axis to a subjective state of consciousness (as reported by the participant) (Bachmann 2012). In the examples presented here, we used markers of objective state of consciousness in the y-axis. However, the proposed framework is also compatible when subjective state markers are considered. Bayne and colleagues, on the other hand, propose a multidimensional graph like a radar chart with different axes (Bayne et al. 2016): content-related (e.g. content gating and content range) and functional dimensions (e.g. relating to attentional control, memory consolidation, verbal report, reasoning, and action selection). The problem with this representation is that it is difficult to standardize and, hence, less applicable. Interestingly, Sergent et al. (2017) created a unique EEG protocol allowing the exploration of eight axes (own name recognition, temporal attention, spatial attention, detection of spatial incongruence motor planning, and modulations of these effects by the global context) but the construction of such a paradigm is complex. For Chalmers, studying content and conscious state at the same time is difficult in experimental conditions (Chalmers 1997), with most studies contrasting variable content in a given state of consciousness or studying brain differences in different states.

A pertinent perspective to note is that the categorization of state and content is nuanced. Recent work shows that these categories are part of a spectrum that often overlaps (Andrillon 2023, Andrillon and Oudiette 2023). On one hand, we have sensory processing during different levels of arousal (Andrillon and Kouider 2020); content during states of low arousal (Solms 2000, Leslie et al. 2007); responsiveness to the environment during lucid dreams and other sleep stages (Türker et al. 2023); and phenomena such as mind-wandering and mind-blanking during active wakefulness, which are hypothesized to originate from local sleep occurrences (Andrillon et al. 2021). However, in all of these cases, the content and state dimensions are present and can be disentangled using subjective and objective measures (albeit without an existing unit of measurement and based on assumptions, which should always be well reported).

The simultaneous study of state and content neural correlates implies the following research question: what is the relationship of different neuronal markers in a 2D space of level and content of consciousness axes? Importantly, the same neuronal marker (e.g. delta power) can either reflect the same or different neuronal process across levels and contents of consciousness. To address this question, we introduce a simple framework comprising a 2D space to examine brain features across both dimensions concurrently. This approach facilitates the characterization of various types of markers based on their positioning within the 2D space. We explore this space using two experimental examples: a comparison of states of consciousness (normal sleep or disorders of consciousness) and types of conscious content (auditory or visual). In this 2D space, we put the directionality of different EEG markers when contrasting two conditions (e.g., perceived versus not-perceived or different levels of cognitive processing in the case of the content exploration; and a global state of consciousness versus a global state of unconsciousness in the case of the state exploration). The capacity of the markers to distinguish the contrasted conditions is measured using an Area Under the receiver operating characteristic (ROC) Curve (AUC). The framework’s capability to assess simply the behavior of neuronal markers on the state and content conditions demonstrates its relevance to the consciousness research community.

In this study, we included three separate cohorts of healthy controls and one patient population with disorders of consciousness. Each of the separate groups of healthy controls came in for one of the following EEG experiments: the visual masking paradigm (Del Cul et al. 2007), a session consisting of a period of resting wakefulness followed by a nap, and an experiment using the LG paradigm (Bekinschtein et al. 2009). Whereas the patient population underwent EEG recordings during the LG paradigm (Bekinschtein et al. 2009).

In this work, we propose a framework that permits the direct comparison of EEG markers of state and conscious content in the same space. With two implementation examples, we show that neural correlates depict different properties in discriminating these dimensions of consciousness.

The challenge in a 2D representation of neuronal markers of consciousness is to find a minimal relevant contrast. In these two examples, we contrast both conscious state and conscious content, but independently. The state was studied by contrasting healthy participants in non-REM Stage 2 sleep and in the awake state. We also studied the state condition by contrasting MCS patients and UWS patients, diagnosed in the clinic, since the MCS state is considered an altered state of consciousness, and the UWS state as a state of wakefulness without awareness. However, we have to note here that the UWS versus MCS contrast is less dichotomous than it seems due to the possibility that some UWS patients are in a covert conscious condition (as called cognitive motor dissociation) (Owen et al. 2006, Schiff 2015) as well as the heterogeneity within the two clinical categories (Naccache 2018, Hermann et al. 2021a). The conscious content was studied in two modalities: visual and auditory. There is a high distance in the contrast of the conscious content between the sensory modalities, but also due to the type of perceptual processing (masking, threshold vision, and detection of novelty), the challenge is to find a sufficiently salient contrast between the two conditions to capture, unambiguously, the perceptual or cognitive differences to obtain a robust neural characterization.

The first example, wake-sleep, and visual conscious access use the proposed representation with a task such as a visual perception protocol as well as other states of consciousness such as NREM sleep (Fig. 3). The second example, the auditory LG paradigm is particularly powerful because it allows for a dual analysis, first, the study of the early, automatic response to novelty (Fig. 3b; Supplementary Fig. S1), and, second, the late and conscious response (Fig. 3). The analysis of this early response is, therefore, a kind of control, since previous studies demonstrated that the brain processing of this rule does not require conscious awareness (Bekinschtein et al. 2009). In this example, we confirm with the LD/LS contrast that the putative EEG markers are less able to discriminate between the two conditions compared to the GD/GS contrast.

The comparison between the two examples highlights and challenges the fact that the different EEG markers evolve in the same direction according to the level of consciousness and the conscious content. One might intuitively hypothesize that most markers would be located in the light purple quadrants (top-right and bottom-left) of the graphical representation (Fig. 1), i.e. markers that increase with the state of consciousness and that also increase with the conscious content. In fact, most of the markers lie in the quadrants of the inverse relationship between state and content suggesting that they might play different roles in the state and content contrast. This result stresses the relevance of the proposed 2D framework to characterize simultaneously the behavior of markers in both the state and content dimensions.

Although the analyses of the exact location of each marker lie beyond the original objectives of this work, we will briefly interpret them. The NM-S analysis in the first example (Fig. 2) is mostly consistent with well-established knowledge of the relative spectral characteristics of wakefulness versus various sleep stages (Imperatori et al. 2021, Manasova and Stankovski 2023). In N2 sleep, we observe an increase in the relative delta and theta powers, as well as a decrease in alpha, beta, and gamma bands, which is aligned with previous reports (Imperatori et al. 2021) where all band comparisons are reported to be significant except for theta. Furthermore, we observe an increase in wSMI for the theta band in N2 sleep, which is present, but not strong enough (Imperatori et al. 2021). The NM-Ss in the second example (UWS/MCS contrast, Fig. 3) have an intuitive interpretation that is aligned with existing literature: while delta decreases with higher states of consciousness theta and alpha both increase and higher frequencies are less informative (Sitt et al. 2014).

In terms of conscious content in the first example (Fig. 2), we found that delta and theta were higher in seen conditions, and in the second example (Fig. 3) this is the case only for delta, which is higher in GD compared to the GS condition, that may reflect the slow late potentials associated with conscious access, a process uniquely underlying awareness. In the first example (Fig. 2), contrary to some results in the literature we also found a reduction of gamma power, this is likely due to the more careful computation we used (20–40 Hz, the average across all electrodes, and normalized to the full spectrum power), as supported by Dwarakanath et al. (2023), who investigate the changes in conscious content in the prefrontal cortex using a binocular rivalry paradigm and show that there is a suppression of 20–40 Hz activity concurrent with 1–9 Hz transients, both of which follow the exogenous stimulus changes of physical stimulus alternations. Importantly, these high-frequency suppressions and 1–9 Hz transients precede the endogenous binocular rivalry perceptual transitions. The same is true for markers of complexity and functional connectivity that decrease in the post-perceptual period with conscious content (Example 1, Fig. 2). This could be explained by a “gating” mechanism, where the conscious perceptual input would close, creating a refractory period, which is reflected in a decrease of these markers in post-perceptual time. The reduction in complexity with conscious content is also compatible with the proposal of higher stability of neuronal activity during conscious access (Schurger et al. 2015).

Further reflecting on Figs 2 and 3 and the inverse relationship of the markers of content with those of the state, we can therefore think that there is a temporal constraint on the functional cognitive architecture theorized under the name of a cognitive cycle (Madl et al. 2011). According to its authors, awareness would consist of cascading cycles of recurrent cerebral events. Each cognitive cycle would then detect the current situation and interpret it according to a given context. According to Franklin et al. (2005), “conscious events occur as a sequence of discrete, coherent episodes separated by quite short periods of no conscious content” similar to the frames of a movie, and these frames of consciousness would be discrete but the conscious experience would seem continuous. A complementary framework is proposed by Herzog et al. (2016), where the authors argue for a rendering of the unconscious content in discrete conscious moments. They propose a two-stage model that is different from “snapshot” theories. Visual information is processed unconsciously with a high temporal resolution followed by a discrete conscious percept (the outputs of unconscious processing) at a slower rate than the visual sampling (Herzog et al. 2016). This rate of conscious percepts is not fixed but depends on the unconscious processing reaching an attractor state (Herzog et al. 2016).

Our study introduces a novel 2D state–content space that effectively represents EEG markers related to the state and content of consciousness. This innovative framework reveals significant relationships between these markers across both dimensions. In our examples, we observed an anticorrelation between the state and content dimensions in certain EEG markers, indicating that as one dimension’s value increases, the other’s decreases. This finding highlights the nuanced interplay between state and content markers and provides deeper insights into their behavior. The proposed 2D space has broad applicability across different perceptual modalities and various contrasts, offering a unified framework for examining consciousness. The value of this representation is both theoretical and experimental because it allows to disentangle content and state of consciousness signatures by studying multiple contrasts in the same framework, constituting an important tool to better interpret the true neuronal mechanisms underlying consciousness and cognition in different states and for different contents.