Modern Approaches to the Problem of Consciousness

Philosophical Framework

Modern consciousness research is rooted in the philosophical tradition that highlights the so-called "hard problem of consciousness"—explaining how subjective experience arises from neurophysiological processes. This problem was formulated by David Chalmers, who emphasized the gap between objective descriptions of the brain and the phenomenal content of consciousness. In response, theoretical approaches emerged aiming to link subjectivity with information integration and global data processing in the brain.

In particular, Giulio Tononi's Integrated Information Theory (IIT) proposes measuring the level of consciousness through a system's ability to integrate information, reflecting the unity and diversity of experience [Tononi, 2004]. Concurrently, Bernard Baars' Global Workspace Theory (GWT) views consciousness as the result of global information broadcasting across neural networks, providing access to various cognitive modules [Baars, 2006]. These concepts build a bridge between philosophical questions and empirical methods, enabling the formulation of testable hypotheses and conducting experiments.

Introduction

The problem of consciousness remains one of the most complex and controversial in psychology and cognitive sciences. Contemporary research focuses on identifying the neural correlates of consciousness (NCC), i.e., the minimal neural mechanisms necessary for the emergence of conscious experience. The use of neuroimaging methods such as functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) has allowed localization of activity associated with conscious states and the study of their emergence dynamics [Schartner et al., 2017].

Experiments with visual perception, such as binocular rivalry, reveal differences between conscious and unconscious perception, showing that consciousness is linked to the global broadcasting of information in the brain. The Global Workspace Theory explains how information becomes available for conscious perception through the activation of widespread neural networks, supported by experimental data [Baars, 2006]. Moreover, modern transcranial magnetic stimulation (TMS) methods allow not only observation but also modification of conscious states, revealing causal relationships between brain activity and consciousness [Casali et al., 2013].

In recent years, integrated information models have proposed quantitative indicators of consciousness level, such as the PCI index, successfully applied to assess consciousness in coma patients and various wakefulness states. Split-consciousness experiments demonstrate the multiplicity of perceptual processes and the complexity of information integration in the brain. An interdisciplinary approach combining psychophysiology, neuroscience, and philosophy becomes key to advancing understanding of consciousness, as no single discipline alone can fully reveal its nature. Modern methods and experiments create a rich empirical basis for addressing the hard problem of consciousness, but the question of how exactly subjective experience arises from neural processes remains open and requires further theoretical and experimental reflection.

Research Review

How to Measure and Objectify the Level and Content of Consciousness?

The paradox of measuring consciousness begins with the fact that consciousness is simultaneously a process, a phenomenon, and a subjective experience that is difficult to reduce to objective parameters. How can one quantitatively assess what is, by definition, experienced from within and not directly observable? In attempts to bridge this gap, scientists have turned to neurophysiological data, seeking quantitative indices capable of reflecting the level and content of consciousness.

One of the most influential approaches is Giulio Tononi's Integrated Information Theory (IIT), which proposes measuring consciousness through the parameter Φ (Phi)—the degree of integration and complexity of information in the brain. According to Tononi, consciousness arises where informational processes have a high degree of integration, i.e., when the system is not reducible to the sum of its parts but functions as a unified whole. This allows moving from abstract philosophical reasoning to concrete numerical estimates that can be compared with neurophysiological data [Tononi, 2004].

An important experimental confirmation of this idea came from Schartner et al. (2017), who used magnetoencephalography (MEG) to measure the diversity of neural signals in states induced by psychedelics (ketamine, LSD, psilocybin). They found that in such states, spontaneous signal diversity significantly increases compared to normal wakefulness. This indicates that consciousness in these states becomes "richer" and "more diverse," correlating with subjective reports of experience intensity. The authors emphasize that their measures of complexity and entropy of neural signals align well with Integrated Information Theory and entropy-based theories, providing a quantitative link between neurophysiology and phenomenology of consciousness [Schartner et al., 2017].

However, despite the appeal of these measures, Tanaka (2018) and Walter (2022) criticize the neurocentric approach, pointing out that none of the existing indices reflect the full spectrum of subjective conscious content (cC). They stress that attempts to reduce consciousness to neural correlates inevitably face limitations because consciousness includes not only activation level or complexity but also qualitative aspects of experience that are difficult to formalize. This creates an obstacle to precise and comprehensive measurement of consciousness [Tanaka et al., 2018].

Seeking more comprehensive models, Olesen (2023) proposed integrating the Free Energy Principle with IIT. He showed that surprisal measures in the brain fluctuate synchronously with consciousness measures based on integrated information, indicating a close relationship between the brain's information-theoretic properties and conscious states. This expands the understanding of consciousness as a process that not only integrates information but also minimizes uncertainty, consistent with predictive coding and free energy ideas [Olesen et al., 2023].

Another aspect of measuring consciousness relates to neural network dynamics. Koch and colleagues (2016) identify neural correlates of consciousness (NCC) as the minimal set of neural processes necessary and sufficient for conscious perception. They emphasize that NCC can be localized using neuroimaging methods such as fMRI and MEG, allowing objective recording of transitions between conscious and unconscious perception. Experiments with binocular rivalry, where two different images are presented to each eye, demonstrate that consciousness switches between these images, and cortical neural activities correspond to the current conscious content.

Dehaene (2014) develops the Global Workspace Theory, explaining information broadcasting in the brain as a key mechanism of consciousness. According to this theory, consciousness arises when information becomes available to a wide range of cognitive processes through a global neural network. This explains why some stimuli remain unconscious—they do not reach the global workspace. Experimental data confirm that activity in frontoparietal brain areas is associated with conscious perception, while unconscious processes are limited to local sensory zones.

An important tool for studying causal relationships in consciousness has been transcranial magnetic stimulation (TMS). It allows temporary modulation of activity in specific brain areas and observation of changes in conscious states. For example, Sarasso et al. (2015) showed that anesthesia with propofol and ketamine reduces the complexity and diversity of EEG signals, correlating with loss of consciousness. This confirms that dynamic complexity of neural processes is an objective marker of consciousness.

Nevertheless, Seth and colleagues (2008) emphasize that measuring consciousness requires combining behavioral and neurophysiological approaches. They propose an extended framework considering both objective brain activity indicators and subjective reports, allowing a fuller capture of the consciousness phenomenon. This is especially important in clinical cases, such as diagnosing vegetative states, where behavioral responses are limited, and neurophysiological data can provide key insights into consciousness level.

Philosophically, Singer (2025) draws attention to the epistemological gap between material brain processes and subjective experience. He suggests that perception is formed not only by neural activity but also by prior cognitive settings (priors) influencing sensory data interpretation. This complicates the task of measuring consciousness because subjective experience depends on context and individual perceptual characteristics, which are not always reflected in neurophysiological data. Modern research demonstrates that measuring consciousness is not simply searching for a universal index but a complex task requiring integration of quantitative measures of complexity and diversity of neural signals, localization of neural correlates, and consideration of subjective and contextual factors. In this sense, Integrated Information Theory and Global Workspace Theory provide powerful tools but do not exhaust the problem.

The next step is to understand why consciousness evolved and what functions it performs, linking measurements with biological meaning and adaptive value of conscious states. This leads to the question of whether consciousness is an evolutionary adaptive mechanism and what its functions are.

Is Consciousness an Evolutionary Adaptive Mechanism, and What Are Its Functions?

Continuing the topic of objectifying consciousness, the inevitable question arises: why did consciousness appear in evolution, and what function does it serve? Answers to this question are no less complex than the problem of measuring consciousness itself, since consciousness is not just a set of neurophysiological processes but a phenomenon with subjective experience and adaptive significance. In recent years, several key positions have formed in science attempting to explain the evolutionary role of consciousness and its functional features.

One influential view is the hypothesis that consciousness arose as an evolutionary advantage for social interaction and coordination within groups. Fitch and co-authors argue that the ability to predict others' behavior and coordinate actions with the group was the original adaptive function of consciousness. This idea resonates with earlier views, such as those of Andrews and Miller, who emphasize the social roots of consciousness, linking it to the development of social reward and pain mechanisms. In this context, consciousness is not merely internal experience but a tool for survival in complex social structures where successful coordination and prediction of others' intentions are critical.

However, not all researchers agree that consciousness has a direct adaptive function. Dennett and Block [Block, 1995] consider consciousness more as an epiphenomenon—a byproduct of evolution without independent function. Dennett, for example, insists that consciousness is a "mixture" of various processes, many of which lack direct functional significance. He emphasizes that consciousness cannot be reduced to a single entity but should be viewed as a collection of different "consciousnesses" that may serve different roles. This position questions the idea that consciousness arose solely for adaptive purposes.

An important clarification is made by Block, who distinguishes functional and phenomenal aspects of consciousness [Block, 1995]. He introduces the concepts of "access consciousness" and "phenomenal consciousness." Access consciousness relates to the ability to use information for reasoning, speech, and action, whereas phenomenal consciousness is the subjective experience, the "what it is like." According to Block, these two aspects are often confused, leading to misunderstandings about consciousness functions. For example, functional processes can be implemented without phenomenal experience, calling into question the direct adaptive role of subjective consciousness.

LeDoux [LeDoux et al., 2017] also emphasizes the distinction between functional availability of information and subjective experience, noting that consciousness functions depend on what we understand by consciousness. He proposes viewing consciousness as a mechanism ensuring information integration for decision-making and adaptive behavior but not necessarily linked to phenomenal experience. This aligns with Global Workspace ideas, where consciousness is the process of information broadcasting across neural networks, providing access to various cognitive systems [Baars, 2006].

Integrated Information Theories, particularly Tononi's work [Tononi, 2004], offer a quantitative assessment of consciousness level through the parameter Φ (Phi), reflecting the degree of integration and differentiation of information in a system. According to this theory, consciousness is not merely a function but a fundamental property of systems with a high degree of information integration. This allows considering consciousness as an evolutionarily advantageous state because information integration enhances organism adaptability, improving processing of complex stimuli and coordination of actions.

Experimental data confirm the link between consciousness level and neural process complexity. Schartner and colleagues [Schartner et al., 2017] showed that psychedelic states induced by ketamine, LSD, and psilocybin are accompanied by increased diversity of neural signals, correlating with changes in subjective experience. These data support theories linking consciousness with neural complexity and diversity, which may be an adaptive mechanism for expanding perception and behavior range.

Contrary to social and integrative theories, Humphrey and Crystal focus on evolutionary functions of consciousness related to memory and learning. Crystal, for example, views consciousness as a mechanism providing episodic memory, enabling animals to better navigate changing environments and predict consequences of their actions. This broadens understanding of consciousness functions beyond social coordination, including cognitive abilities necessary for survival.

Interestingly, Nagel [Nagel], famous for the question "What is it like to be a bat?", emphasizes the uniqueness of subjective experience, which cannot be reduced to functional processes. His position questions the possibility of fully explaining consciousness through evolutionary functions, as subjectivity remains the "hard problem" of consciousness.

Finally, Andrews and Miller propose empirical tests of the social origins hypothesis of consciousness, such as the "social stimulus significance test" and the "agency reattribution test." These approaches aim to identify specific adaptations of consciousness related to social interaction, which may help distinguish functional aspects of consciousness from epiphenomenal ones. The question of whether consciousness is an evolutionary adaptive mechanism remains open and multifaceted. On one hand, there are compelling arguments that consciousness provides social coordination, information integration, and cognitive advantages. On the other hand, critics point to the complexity of phenomenal experience and the possibility of its epiphenomenal nature. This contradiction leads to the next important question: can consciousness be reduced to physical brain processes, or does it require a special explanation? This question becomes central in the subsequent discussion of consciousness reduction.

Is It Possible to Reduce Consciousness to Physical Brain Processes?

The transition from discussing consciousness functions to the question of its reduction to physical brain processes is a step from "why" to "how." If consciousness indeed performs adaptive functions, a natural question arises: can it be fully explained through neurophysiology and brain physics? In this context, the key is to find mechanisms linking subjective experience with objective processes.

Giulio Tononi's Integrated Information Theory (IIT) proposes formalizing consciousness as a system's capacity to integrate information. According to Tononi, consciousness corresponds to the amount of integrated information measured by the parameter Φ (Phi), reflecting how indivisible the system is in its informational structure [Tononi, 2004]. This allows moving from abstract reasoning to quantitative assessments of consciousness level. However, despite mathematical rigor, IIT faces the problem of explaining why information integration produces subjective experience rather than just functional processing.

An important empirical confirmation of IIT ideas is provided by M. Schartner and colleagues, who showed that under psychedelics (ketamine, LSD, psilocybin), there is an increase in neural signal diversity measured by Lempel-Ziv complexity in magnetoencephalographic data [Schartner et al., 2017]. This indicates increased integrative informational brain activity in altered consciousness states. Interestingly, these changes localize in occipito-parietal areas, highlighting the importance of spatial integration in forming conscious experiences.

Nevertheless, Integrated Information Theory is not the only attempt to reduce consciousness to physical processes. Quantum theories of consciousness, for example, proposed by Hartmut Neven and colleagues, suggest that consciousness arises during moments of quantum superposition and entanglement, and the structure of this superposition determines qualitative characteristics of experience—qualia [Neven et al., 2024]. This approach attempts to solve the "binding problem" of consciousness by explaining perceptual unity through quantum nonlocality. However, quantum theories remain controversial due to lack of direct experimental evidence and difficulty integrating with classical neurophysiology.

In contrast to reductionist approaches, holistic and dualist theories, such as those of Max Velmans, argue that consciousness cannot be reduced to physical processes because subjective experience has objective causal efficacy and requires special description [Velmans, 1995]. Velmans proposes viewing consciousness as an aspect of information that complements physical reality rather than reducing to it. This avoids the reductionist trap but generates complexity in integration with neuroscience.

Crick and Koch, in their works from the 1990s and 2000s, promoted the idea that consciousness results from information integration in neural networks, especially in the cerebral cortex. They focused on neural correlates of consciousness (NCC), which can be localized and measured using modern neuroimaging methods. However, even with successful NCC identification, the question remains how exactly these correlates generate subjective experience.

Daniel Dennett, a well-known critic of reductionism, opposes the idea of "magical" subjective experience, considering consciousness as the result of multiple functional brain processes explainable without invoking special qualia. His multiple drafts theory emphasizes that consciousness is not a single object but a stream of parallel processes, questioning the possibility of simple reduction.

An important addition to these theories comes from modern experiments with transcranial magnetic stimulation (TMS), which allow not only observing consciousness correlates but also intervening in them, revealing causal links between brain activity and conscious states. Such studies show that consciousness depends on dynamic integration of activity in widespread neural networks, consistent with Global Workspace Theory. This theory describes consciousness as a process of information broadcasting in the brain when certain representations become accessible to various cognitive systems.

On the other hand, split-consciousness studies in patients with split brains demonstrate multiplicity of perception and consciousness processes, complicating the idea of consciousness as a unified physical process. This suggests that reducing consciousness to local physical processes may be insufficient, and more complex models considering distributed and multiple conscious states are needed.

Overall, modern approaches to reducing consciousness to physical brain processes balance between rigorous quantitative theories like IIT and more philosophically oriented holistic views. Experimental data, including neuroimaging and TMS, confirm that consciousness is closely linked to information integration in the brain, but the question of how physical processes generate subjective experience remains open.

The transition to the next stage—the correlation of subjective experience (qualia) and objective scientific data—requires accounting for these complexities. How can one objectively measure and describe what is inherently subjective? This question becomes central in attempts to unify empirical methods and philosophical concepts of consciousness.

How to Correlate Subjective Experience (Qualia) and Objective Scientific Data?

Moving from the question of consciousness reduction to physical brain processes, we face a fundamental problem: how to link subjective experience, or qualia, with objective measurements and scientific models? This is the classic "hard problem of consciousness," formulated by David Chalmers, which questions the possibility of fully explaining phenomenal experience through neurophysiology. Chalmers emphasizes that consciousness is not just information processing but the presence of "what it is like" to be a subject, which cannot be reduced to functional descriptions.

In cognitive science and neuroscience, there is an attempt to circumvent this problem through theories focusing on information access and integration. The Global Workspace Theory (GWT), proposed by Bernard Baars, considers consciousness as a mechanism of global information access, allowing different brain modules to exchange data for decision-making and behavior control. Baars writes: "In cognitive theory, consciousness is represented as a function of global access, providing an infinite variety of focal contents for executive control and decision-making" [Baars, 2006]. This theory emphasizes the functional aspect of consciousness but leaves open the question of the nature of subjective experience.

In contrast, Ned Block introduces a distinction between phenomenal consciousness and access consciousness. He points out that phenomenal consciousness is precisely subjective experience, while access consciousness is the ability to use information for reasoning and action. Block criticizes reductionist approaches that attribute consciousness functions to phenomenal experience, citing the example of "blindsight," where patients can respond to stimuli without awareness of perception. He states: "The function of phenomenal consciousness is not reducible to providing access to information for action control" [Block, 1995]. This distinction helps understand why objective brain activity data do not always correlate with subjective experience.

Giulio Tononi develops Integrated Information Theory (IIT), which attempts to quantitatively assess consciousness level through the parameter Φ (Phi), reflecting the degree of integration and differentiation of information in a system. Tononi argues that consciousness is a system's capacity to integrate information such that its state cannot be decomposed into independent parts. This explains the unity of subjective experience and its richness simultaneously [Tononi, 2004]. The theory offers a bridge between subjectivity and objectivity since Φ can be measured via neurophysiological data, but the question remains how well this measure truly reflects phenomenal consciousness.

An important experimental direction involves attempts at direct access to consciousness content. For example, Tanaka and colleagues proposed the CHANCE method, enabling researchers to "experience" and "know" the full spectrum of a subject's conscious content in scientific experiments [Tanaka et al., 2018]. This radical approach aims to overcome the barrier between subjective and objective but remains in theoretical and methodological development stages.

Neurophysiological studies confirm that consciousness is associated with specific brain activity patterns. For instance, functional magnetic resonance imaging (fMRI) studies identify neural correlates of consciousness (NCC), showing that conscious perception is linked to activation of global brain networks, including frontal and parietal areas [Owen et al., 2006]. However, these correlates do not explain why these processes are accompanied by subjective experience.

Visual perception experiments, such as binocular rivalry, demonstrate that the same stimuli can be perceived consciously or unconsciously, reflected in differences in brain activity. This indicates that consciousness is not merely the presence of information but its special status in the cognitive system. Attention and working memory play roles in "bringing" information into consciousness, consistent with Global Workspace Theory.

Modern neuroimaging methods, such as magnetoencephalography (MEG), allow measuring diversity and complexity of brain signals. Schartner et al.'s study showed that psychedelic states are accompanied by increased spontaneous diversity of MEG signals, correlating with changes in conscious experience [Schartner et al., 2017]. This indicates that subjective changes in consciousness are reflected in objective brain activity parameters, bringing us closer to quantitative consciousness assessment.

Transcranial magnetic stimulation (TMS) is used to study causal relationships between brain activity and consciousness. The method allows temporary modulation of activity in specific brain areas and observation of changes in conscious states. For example, the Perturbational Complexity Index (PCI), developed by Casali and colleagues, measures the complexity of brain responses to TMS and serves as an objective indicator of consciousness level, independent of behavior and sensory processing [Casali et al., 2013]. This opens the way for clinical applications and more precise understanding of consciousness.

Philosophers and neuroscientists such as Jack Singer and Antonio Damasio emphasize the role of "feelings" and interoception—internal perception of bodily states—as the basis of subjectivity and "ownership" of experience. They propose that these ancient neural mechanisms create a "feeling mind," complemented but not replaced by the neocortex forming the modern mind. This highlights that subjective experience cannot be reduced to digital information processing but requires consideration of analog, emotional aspects.

Overall, attempts to correlate qualia with objective data face a fundamental paradox: subjective experience is inherently inaccessible to direct external observation, but its manifestations can be indirectly measured through neural correlates and behavioral responses. Global Workspace and Integrated Information theories offer functional and quantitative models that advance understanding of consciousness but do not resolve the question of subjectivity's nature.

The transition to experimental methods that allow not only describing but also manipulating conscious states opens new horizons. Modern neuroimaging technologies, TMS, and psychedelic research provide tools for deeper study of brain-consciousness relationships. This leads to the need to integrate philosophical concepts with empirical data to build a holistic picture of consciousness.

The question of how exactly subjective experience arises from objective processes remains open, but today we have methods enabling measurement and modeling of consciousness with unprecedented precision. The next step is expanding experimental approaches that allow not only recording consciousness correlates but also revealing the dynamics of its emergence and change in real time. This leads to consideration of modern experimental methods expanding our understanding of consciousness.

How Do Modern Experimental Methods Expand the Understanding of Consciousness?

The transition from discussing subjective experience to objective data requires tools capable of recording and analyzing brain activity with high precision. Modern neurophysiological methods such as magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and transcranial magnetic stimulation (TMS) open new horizons in consciousness study. They allow not only localization of consciousness correlates but also investigation of the dynamics of its manifestations in real time.

An important example is the work of Schartner et al., where MEG was used to measure brain signal diversity under the influence of psychedelics—ketamine, LSD, and psilocybin. The authors found that in states accompanied by subjective experience of expanded consciousness, there is a significant increase in spontaneous diversity of brain signals. This indicates that consciousness is not merely linked to activity in specific brain areas but reflects complex integrative dynamics manifested in diversity and complexity of neural patterns. "I feared losing control of my mind"—participants described their sensations, emphasizing the depth of consciousness change in these states. This experiment demonstrates that neurophysiological methods can capture not only "where" and "when" but also "how" consciousness changes at the brain activity level.

Psychedelic states become a unique model for consciousness study because they induce qualitatively new phenomenological experiences. Gallimore notes that stable manifestation of psychedelic phenomenology can be considered as a heightened level of consciousness. This expands traditional views of consciousness beyond ordinary wakefulness and sleep states. Such data allow not only describing subjective experiences but also linking them with objective neurophysiological markers.

Neuroimaging, especially fMRI, has played a key role in identifying neural correlates of consciousness. A classic example is Owen et al.'s study, where fMRI demonstrated preserved awareness in a patient in a vegetative state. This discovery overturned views on consciousness in patients with severe consciousness disorders and showed that consciousness can exist without external manifestations. This approach allows not only diagnosing consciousness state but also assessing its level and quality.

Transcranial magnetic stimulation (TMS) complements the picture by providing a tool for causal analysis. Casali et al. used TMS combined with electroencephalography (EEG) to assess consciousness level in patients with various disorders. They developed an integrated information index quantitatively reflecting the brain's capacity for information integration and differentiation—key consciousness characteristics. This index, based on Tononi's Integrated Information Theory, allows objective consciousness level assessment beyond simple brain activity observation.

Interestingly, modern consciousness theories such as Dehaene's Global Neuronal Workspace Theory (GNWT) and Tononi's Integrated Information Theory find experimental confirmation precisely through such methods. GNWT describes consciousness as a process of global information broadcasting across neural networks, confirmed by observations of brain activity dynamics during cognitive tasks. For example, visual perception and binocular rivalry experiments show how conscious perception is linked to global information integration rather than mere local sensory area activation.

Integrated Information models, measured via the Φ (Phi) index, provide quantitative assessment of consciousness level, especially important when comparing different states—from wakefulness to sleep and anesthesia. Casali et al. showed that this index decreases with loss of consciousness and recovers upon awakening, confirming its validity as a consciousness marker.

Split-consciousness experiments, for example in split-brain patients, reveal multiplicity of perception and awareness processes, challenging the classical idea of a unified, indivisible consciousness. These data emphasize the complexity and multilayered nature of conscious processes, requiring an interdisciplinary approach combining neurophysiology, cognitive psychology, and philosophy of consciousness.

Clark and Gallese propose viewing the brain as a prediction machine, where consciousness arises from constant matching of sensory data with internal expectations. This approach integrates empirical data with theoretical models, expanding understanding of consciousness as a dynamic process rather than a static state.

Servajean emphasizes the importance of interdisciplinary methods combining psychophysiology, neuroscience, and philosophy for comprehensive consciousness study. Such synthesis allows not only recording neural correlates but also interpreting them in the context of subjective experience and cognitive functions.

Cognitive experiments with attention and working memory reveal mechanisms through which information becomes accessible to consciousness. For example, Dehaene's studies demonstrate that attention and working memory act as filters and buffers, ensuring global information broadcasting, consistent with Global Workspace Theory. Modern experimental methods not only record brain activity but also allow investigation of dynamic processes of information integration and differentiation underlying consciousness. They open the way to quantitative assessments of consciousness level and understanding its neurophysiological foundations.

The remaining open question is how fully these methods can capture the subjective side of consciousness, the hard problem of qualia. This leads to the need for critical analysis and evaluation of existing approaches' limitations, which will be the topic of the next section.

Criticism and Limitations

One key limitation of modern approaches to consciousness study is the problem of precise measurement and objectification of subjective experience. Despite successes of Integrated Information Theory (IIT) and use of indices such as Φ (Phi) and PCI, these measures remain indirect and do not cover the fullness of conscious content. For example, Schartner et al. (2017) demonstrate increased neural signal diversity in psychedelic states correlating with subjective experience intensity, but this does not imply that such measures can fully reflect qualitative aspects of consciousness. Moreover, Tanaka (2018) and Walter (2022) point out that existing methods do not allow researchers direct access to the full spectrum of a subject's conscious content, limiting empirical study of the phenomenal side of consciousness. Despite quantitative successes, the question remains how well neurophysiological indices truly reflect subjectivity rather than only functional or informational processes.

A second significant problem relates to reductionism and attempts to reduce consciousness to physical brain processes. Theories based on information integration and global workspace offer convincing models of neural correlates of consciousness but do not solve the fundamental "hard problem"—explaining how subjective experience arises from objective processes. Quantum and electromagnetic theories of consciousness, proposed by Neven (2024), Maciver (2022), and Magro de Queiroz (2025), attempt to bridge this gap by introducing new physical mechanisms but face criticism due to lack of direct experimental evidence and difficulty integrating with classical neuroscience. Holistic approaches, such as those by Chen (2025) and Velmans (1995), propose viewing consciousness as inseparably linked to cognitive perspective but complicate theory formalization and empirical testing. Ultimately, reduction of consciousness to physical processes remains controversial and incomplete, limiting interpretation of neurophysiological research results.

A third limitation concerns the complexity and multiplicity of conscious processes. Split-consciousness experiments and studies of perceptual multiplicity show that consciousness is not a single homogeneous phenomenon but a collection of parallel and partially independent processes. This challenges classical models assuming a unified integrated consciousness system and requires development of more complex modular or constitutive models, as proposed by Lacalli (2025). Such multiplicity complicates both theoretical description and empirical study of consciousness since different aspects may manifest in various neural and cognitive processes.

Finally, the interdisciplinary nature of modern consciousness research, combining psychophysiology, neuroscience, and philosophy, generates methodological and conceptual difficulties. Differences in terminology, approaches, and explanatory criteria lead to challenges in data integration and forming a unified theoretical base. For example, the distinction between phenomenal and access consciousness emphasized by Block (1995) is often ignored in empirical studies, potentially causing concept confusion and erroneous conclusions. Moreover, philosophical problems related to subjectivity and experience quality remain unresolved despite progress in neurophysiology. Modern methods and theories of consciousness, while significantly advancing identification of correlates and mechanisms, face fundamental limitations related to measuring subjectivity, reducing phenomenal experience, multiplicity of conscious processes, and interdisciplinary integration. These limitations pose challenges for further research development and require new approaches capable of uniting empirical data with philosophical understanding of consciousness.

Conclusions

• Consciousness is presented as an integrative information processing system, where key aspects are unity and differentiation of neural signals, supported by Integrated Information Theory and experiments measuring brain activity complexity [Tononi, 2004].

• The hard problem of consciousness—explaining subjective experience—remains unresolved, as existing neurophysiological methods record consciousness correlates but do not provide direct access to the phenomenal side of experience.

• Neurophysiological methods, including fMRI and MEG, allow localization and dynamic tracking of neural correlates of consciousness, revealing activity in global neural networks, especially frontoparietal areas associated with conscious perception.

• Visual perception experiments, such as binocular rivalry, demonstrate differences between conscious and unconscious perception, confirming the role of the global workspace in broadcasting information accessible to consciousness [Baars, 2006].

• Transcranial magnetic stimulation (TMS) serves as a tool for identifying causal links between brain activity and conscious states, enabling modification of consciousness level and measurement via brain response complexity indices [Casali et al., 2013].

• Integrated Information models based on the parameter Φ (Phi) provide quantitative assessments of consciousness level, supported by experimental data showing Φ decreases with loss of consciousness and recovers upon awakening [Tononi, 2004].

• Split-consciousness studies in split-brain patients reveal multiplicity of perception processes, challenging the classical idea of unified consciousness and requiring more complex information integration models.

• Modern consciousness research combines interdisciplinary methods—psychophysiology, neuroscience, and philosophy—allowing integration of empirical data with theoretical models and expanding understanding of consciousness phenomena [Clark, 2013].

• Cognitive experiments with attention and working memory reveal mechanisms through which information becomes accessible to consciousness, confirming the role of the global workspace and dynamic neural integration.

• The main unresolved question is how integration and complexity of neural processes generate subjective phenomenal experience and whether it can be fully explained within physical and functional brain models.