Our lived world is what we consciously perceive it to be. Therefore, according to one of the most established sleep neuroscientists, without consciousness there is nothing (Tononi, 2004). At least, there is nothing for the person who lacks conscious perception of the external world and this is evident in brain damaged patients such as split-brain, blindsight and amnestic individuals. The study of such conditions early in the 1960s and 1970s paved the way for the scientific examination of visual consciousness, although consciousness as related to brain activity had attracted scientific interest long before that (LeDoux et al., 2020).

The most frequently used method to investigate how consciousness is reflected on a neural level is the electroencephalogram (EEG). This line of research suggests that oscillatory activity is one of the major prerequisites of consciousness (Ruhnau et al., 2014). Among the EEG oscillations, the alpha band is often regarded as the one of major importance, especially at the pre-stimulus window. However, a local view of the neural correlates of consciousness (NCC) is not regarded as an adequate one. Consciousness is hypothesised to emerge from the integration of neural activity from different brain regions which receive stimuli-related information (John, 2002). The study of functional connectivity interactions among resting-state brain networks (e.g., somatosensory and the default mode network or the integration of information flow among fronto-parietal regions) increased our understanding of the conscious perception of upcoming stimuli. Specifically, functional connectivity analysis of whole-brain networks during deep sleep and especially Rapid Eye Movement (REM) are widely studied as experimental paradigms of conscious awareness (Tagliazucchi and van Someren, 2017). Moreover, Valencia and Froese (2020) describe how the synchronisation of EEG oscillations is what brings about the informational integration and therefore sense of flow that characterise conscious experience. After all, the idea that synchronisation of neural activity is basic to the phenomenon of consciousness has long been supported by Crick and Koch (1990).

The integration of neural information, attributed to the cortical and thalamocortical circuits, is considered to constitute the top-down content of consciousness, whereas the neural circuits that control the arousal states, such as the diencephalon and the brainstem, are considered to modulate consciousness’ bottom-up mechanism; the crucial role of both these systems has been well established by studies on the effects of anaesthetic-induced unconsciousness and a synthesis of bottom-up and top-down neural pathways has been recently suggested to better explain the seemingly diverse effects of anaesthesia on conscious states (Mashour and Hudetz, 2017).

Numerous consciousness theories have been developed. In the field of neuroscience currently, the Information Integration Theory (IIT; Tononi, 2004) and the Global Neuronal Workspace Hypothesis (GNWH; Dehaene et al., 1998, 2003; Dehaene and Changeux, 2005) are the most prominent ones (for a review see Del Pin et al., 2021; Melloni et al., 2023). The prevalence of the IIT and the GNWH mainly lies in their effectiveness in producing testable hypotheses in the search of the NCC (Del Pin et al., 2021).

A core difference between these theories is that the GNWH views consciousness from an objective, third-person perspective, while the IIT also tries to operationalize a first-person subjective perspective (for a review see Seth and Bayne, 2022), therefore approximating the Aristotelian view of conscious experience, given the reflexivity that characterises his investigations of cognition and the mind (Caston, 2002; Smit and Hacker, 2020). As valuable to the investigation of consciousness as these theoretical formulations may be, still they involve limitations in empirically evaluating both the objective (access or representational) and the subjective (i.e., phenomenal) aspects of conscious operations. They also neglect the third quality of consciousness, long described by Aristotle and discussed by Stoneham (2008) in his Purely Relational account of perception: the relationship between the observer and the perceived object. In this paper, we will summarise these theories. We will then argue on the added value of investigating the brain’s aperiodic activity and we will suggest a hybrid approach to thoroughly investigate consciousness.

The signals that are transmitted when functional connectivity occurs are distinguished in two types of electrophysiological activity, periodic and aperiodic. While periodic activity consists of fruitful waves of signals regarding the information that is passed from a neural hub to another, scale-free asynchronous or aperiodic activity (AA) is traditionally considered as noise between those waves. Therefore, for many years researchers have been applying filters and elegant methodological protocols in order to isolate AA from the recorded EEG signal, considering it as simple noise that carries no useful information (for a review see He, 2014). Nevertheless, we have reached a technological level that allows us to have a much sharper perspective of AA. Nowadays, we can safely support that AA is not just noise, but consists of many different frequencies used by the brain to functionally communicate, echoing simultaneously (He et al., 2010).

The main characteristic that delineates AA from simple noise is the dynamic nature of this non-linear activity, that is characterised by an 1/f-like slope regarding the frequency domain. Often named as “scale-free” activity, such temporal dynamics are seen in several natural phenomena such as earthquakes (Baiesi and Paczuski, 2004), forest fires (Nicoletti et al., 2023), biological networks (Almaas and Barabási, 2006) and many more. Such dynamics are believed to carry useful information regardless of the underlying power law principles (He et al., 2010; He, 2014), although the fact that periodic and aperiodic activity overlap makes it difficult to distinguish them (Donoghue and Watrous, 2022). The narrow-band oscillations that are responsible for the synergy of different brain areas are limited in transmitting long range signals. However, distant neuronal hubs firing simultaneously could dynamically produce AA (He et al., 2010), which enables the assessment of distant network cooperation such as the one described by the GNWH.

Considering that structural connectivity shapes, in part, functional connectivity (Honey et al., 2010; Babaeeghazvini et al., 2021), structural differences could also induce changes in the aperiodic components of one’s functional connectivity, hence in the subjective experience of consciousness. Regarding the structural advantage that AA has in terms of connectivity, wide-spread aperiodic perturbations, termed neuronal avalanches, have been recently suggested to convey individualised information that is highly specific to the person experiencing them, hence the alternative term “brain fingerprint” (Sorrentino et al., 2022). We therefore believe that the subjectivity inherent in consciously experiencing the world could be reflected physically in this AA.

So far, we have presented arguments supporting the use of AA analysis to aid in thoroughly revealing the NCC, as periodic activity does not seem to explain it sufficiently. More specifically, we would like to shift the attention from traditional sleep research to the AA observed during the transition from slow wave activity to REM sleep and/or from drowsiness to the N1 sleep stage. Contemporary mathematical tools such as the Orthogonal Discrete Wavelet Transform (ODWT) offers a parameter free, excellent spatio-temporal analysis framework, which can identify the contribution of each EEG rhythm in very short time windows with high accuracy. When combined with functional connectivity analysis, it will also identify the dynamic interplay between different electrode sites (sensor level) or cortical regions (cortical level) (see Figure 2B). Further employing graph theory and network neuroscience may quantify the information flow and regions of high processing capacity, which will provide a hierarchical insight into the organisation of brain networks (modularity analysis and identification of important nodes / hubs) (see Figures 2C,D). This would be benefitted from employing high density electroencephalography (hD-EEG) ideally combined with either a neuroimaging modality (e.g., functional magnetic resonance imaging / fMRI) or a brain stimulation technique (e.g., navigated Transcranial Magnetic Stimulation; see Figure 2A), thus offering the opportunity to test consciousness theories through connectivity analysis.

Notably Aristotle, as a genuine mind biologist, believed that everything we experience must be reflected physically in the body (Smit and Hacker, 2020). This could suggest that multi-organ (e.g., brain-heart-muscle) interactions with brain activity (see Figure 2A), potentially further combined with sleep-related biomarkers’ analysis, could provide an even more integrative view of human consciousness. This is in line with the emerging scientific field of Network Physiology, aiming at understanding the interactions between different physiologic systems and how such synergies influence behaviour (e.g., Bartsch et al., 2015).

Yet, crucial to inferring consciousness from its mere biological, in this case neural, correlates, is firstly understanding it. Explaining conscious experience from a first-person perspective by observing it from a third-person perspective can only be achieved with the use of logic. Because no matter how rigorous the scientific method we use, the phenomenal character integral to the nature of (un)conscious experiences can best be described from a philosophical perspective. This is why we believe that if we are to thoroughly investigate consciousness, we need an interdisciplinary approach combining neuroscientific methods with philosophical endeavours. In such a way, not only will we provide empirical data that comprehensively reflect (un)conscious experiences, but we will also be able to ascribe meaning to those data, therefore understanding both the physical and the phenomenal properties of consciousness.

Publicly available datasets were analyzed in this study. This data can be found here: the original contributions presented in this perspective article are included in the references, further information can be directed to the corresponding author.

AL, TG, TS, and CF contributed to the conception of the work. AL, TG, and CF contributed to the outline of the manuscript. AL wrote the first draft, led the literature review and the writing of the manuscript. TG contributed to the literature review and wrote sections of the manuscript. TS and CF contributed substantially in revising it critically for important intellectual content. All authors contributed to the article and approved the submitted version.