Consciousness: here, there and everywhere?

A landscape of consciousness: Toward a taxonomy of explanations and implications

Diverse explanations or theories of consciousness are arrayed on a roughly physicalist-to-nonphysicalist landscape of essences and mechanisms. Categories: Materialism Theories (philosophical, neurobiological, electromagnetic field, computational and informational, homeostatic and affective, embodied and enactive, relational, representational, language, phylogenetic evolution); Non-Reductive Physicalism; Quantum Theories; Integrated Information Theory; Panpsychisms; Monisms; Dualisms; Idealisms; Anomalous and Altered States Theories; Challenge Theories. There are many subcategories, especially for Materialism Theories. Each explanation is self-described by its adherents, critique is minimal and only for clarification, and there is no attempt to adjudicate among theories. The implications of consciousness explanations or theories are assessed with respect to four questions: meaning/purpose/value (if any); AI consciousness; virtual immortality; and survival beyond death. A Landscape of Consciousness, I suggest, offers perspective.

Inferring Consciousness in Phylogenetically Distant Organisms

The neural dynamics of subjectivity (NDS) approach to the biological explanation of consciousness is outlined and applied to the problem of inferring consciousness in animals phylogenetically distant from ourselves. The NDS approach holds that consciousness or felt experience is characteristic of systems whose nervous systems have been shaped to realize subjectivity through a combination of network interactions and large-scale dynamic patterns. Features of the vertebrate brain architecture that figure in other accounts of the biology of consciousness are viewed as inessential. Deep phylogenetic branchings in the animal kingdom occurred before the evolution of complex behavior, cognition, and sensing. These capacities arose independently in brain architectures that differ widely across arthropods, vertebrates, and cephalopods, but with conservation of large-scale dynamic patterns of a kind that have an apparent link to felt experience in humans. An evolutionary perspective also motivates a strongly gradualist view of consciousness; a simple distinction between conscious and nonconscious animals will probably be replaced with a view that admits differences of degree, perhaps on many dimensions.

What does decoding from the PFC reveal about consciousness?

Disputes between rival theories of consciousness have often centered on whether perceptual contents can be decoded from the prefrontal cortex (PFC). Failures to decode from the PFC are taken to challenge 'cognitive' theories of consciousness such as the global workspace theory and higher-order monitoring theories, and decoding successes have been taken to confirm these theories. However, PFC decoding shows both too much and too little. Too much because cognitive theories of consciousness do not need PFC rerepresentation of perceptual contents since pointers to perceptual representations suffice. Too little because there is evidence that PFC decoding of perceptual content reflects postperceptual cognitive representation, such as thoughts that have those perceptual contents rather than conscious percepts.

Rethinking Mental Automatism: De Clérambault's Theory in the Age of Novel Psychoactive Drugs: Psychotropic Effects and Synthetic Psychosis

The widespread use of novel psychoactive substances (NPSs)-defined as new narcotic or psychotropic agents not classified under the Single Convention on Narcotic Drugs of 1961 or the Convention on Psychotropic Substances of 1971-poses a significant challenge to contemporary mental health paradigms due to their impact on psychiatric disorders. This study revisits and expands upon the theory of mental automatism as proposed by Gaëtan Gatian de Clérambault, aiming to elucidate the psychopathological mechanisms underlying substance-induced psychoses (SIP) and their distinction from non-induced psychoses (schizophrenia and related disorders). Through a phenomenological and clinical investigation, we explore the relevance of mental automatism in the development of toxic psychoses, drawing upon the historical and contemporary literature. This research highlights the psychopathological distinctions between induced and non-induced psychoses and the transition mechanisms from acute to chronic psychosis states. De Clérambault's theory, supplemented by Janet, Jackson, and Bonhoeffer's contributions, provides a foundational framework for understanding the genesis of SIP. Our findings suggest that NPS consumption, particularly among adolescents and psychiatric patients, significantly correlates with increased risks of SIP, marked by a transition to chronicity influenced by biological lesions triggered by substance use. Furthermore, we propose a comprehensive framework for SIP, integrating mental automatism, psychopathological distinctions, and transition mechanisms. This framework aims to refine diagnostic criteria and therapeutic approaches, addressing gaps in clinical practice and research. The study underscores the need for a nuanced understanding of SIP, advocating for a paradigm shift in psychiatric assessment and treatment approaches to better address the complexities of substance-induced mental health disorders.

A measure centrality index for systematic empirical comparison of consciousness theories

Consciousness science is marred by disparate constructs and methodologies, making it challenging to systematically compare theories. This foundational crisis casts doubts on the scientific character of the field itself. Addressing it, we propose a framework for systematically comparing consciousness theories by introducing a novel inter-theory classification interface, the Measure Centrality Index (MCI). Recognizing its gradient distribution, the MCI assesses the degree of importance a specific empirical measure has for a given consciousness theory. We apply the MCI to probe how the empirical measures of the Global Neuronal Workspace Theory (GNW), Integrated Information Theory (IIT), and Temporospatial Theory of Consciousness (TTC) would fare within the context of the other two. We demonstrate that direct comparison of IIT, GNW, and TTC is meaningful and valid for some measures like Lempel-Ziv Complexity (LZC), Autocorrelation Window (ACW), and possibly Mutual Information (MI). In contrast, it is problematic for others like the anatomical and physiological neural correlates of consciousness (NCC) due to their MCI-based differential weightings within the structure of the theories. In sum, we introduce and provide proof-of-principle of a novel systematic method for direct inter-theory empirical comparisons, thereby addressing isolated evolution of theories and confirmatory bias issues in the state-of-the-art neuroscience of consciousness.

Toward a universal theory of consciousness

While falsifiability has been broadly discussed as a desirable property of a theory of consciousness, in this paper, we introduce the meta-theoretic concept of "Universality" as an additional desirable property for a theory of consciousness. The concept of universality, often assumed in physics, posits that the fundamental laws of nature are consistent and apply equally everywhere in the universe and remain constant over time. This assumption is crucial in science, acting as a guiding principle for developing and testing theories. When applied to theories of consciousness, universality can be defined as the ability of a theory to determine whether any fully described dynamical system is conscious or non-conscious. Importantly, for a theory to be universal, the determinant of consciousness needs to be defined as an intrinsic property of a system as opposed to replying on the interpretation of the external observer. The importance of universality originates from the consideration that given that consciousness is a natural phenomenon, it could in principle manifest in any physical system that satisfies a certain set of conditions whether it is biological or non-biological. To date, apart from a few exceptions, most existing theories do not possess this property. Instead, they tend to make predictions as to the neural correlates of consciousness based on the interpretations of brain functions, which makes those theories only applicable to brain-centric systems. While current functionalist theories of consciousness tend to be heavily reliant on our interpretations of brain functions, we argue that functionalist theories could be converted to a universal theory by specifying mathematical formulations of the constituent concepts. While neurobiological and functionalist theories retain their utility in practice, we will eventually need a universal theory to fully explain why certain types of systems possess consciousness.

Thalamic contributions to the state and contents of consciousness

Consciousness can be conceptualized as varying along at least two dimensions: the global state of consciousness and the content of conscious experience. Here, we highlight the cellular and systems-level contributions of the thalamus to conscious state and then argue for thalamic contributions to conscious content, including the integrated, segregated, and continuous nature of our experience. We underscore vital, yet distinct roles for core- and matrix-type thalamic neurons. Through reciprocal interactions with deep-layer cortical neurons, matrix neurons support wakefulness and determine perceptual thresholds, whereas the cortical interactions of core neurons maintain content and enable perceptual constancy. We further propose that conscious integration, segregation, and continuity depend on the convergent nature of corticothalamic projections enabling dimensionality reduction, a thalamic reticular nucleus-mediated divisive normalization-like process, and sustained coherent activity in thalamocortical loops, respectively. Overall, we conclude that the thalamus plays a central topological role in brain structures controlling conscious experience.

An integrative, multiscale view on neural theories of consciousness

How is conscious experience related to material brain processes? A variety of theories aiming to answer this age-old question have emerged from the recent surge in consciousness research, and some are now hotly debated. Although most researchers have so far focused on the development and validation of their preferred theory in relative isolation, this article, written by a group of scientists representing different theories, takes an alternative approach. Noting that various theories often try to explain different aspects or mechanistic levels of consciousness, we argue that the theories do not necessarily contradict each other. Instead, several of them may converge on fundamental neuronal mechanisms and be partly compatible and complementary, so that multiple theories can simultaneously contribute to our understanding. Here, we consider unifying, integration-oriented approaches that have so far been largely neglected, seeking to combine valuable elements from various theories.

The Loss of Spatiality and Temporality in Twilight Consciousness: The Emergence of Exogenous Psychosis Induced by Novel Psychoactive Substances

BACKGROUND

The state of twilight consciousness is marked by a focused narrowing of awareness, maintaining vigilance and attention while simultaneously experiencing perceptual shifts in the surrounding environment. It is crucial to recognize that this twilight state represents not just a contraction but also an expansion of conscious experience.

SUMMARY

Substances of abuse, particularly new psychoactive substances, play a significant role in inducing this twilight state. They achieve this by deconstructing essential components of consciousness, such as the perception of time and space.

KEY MESSAGE

This paper aimed to explore the phenomenon of the twilight state of consciousness and shed light on how new psychoactive substances can alter the perception of time and space during this twilight phase, potentially triggering exogenous psychosis. This comprehensive inquiry employs a phenomenological approach to the study of consciousness, recognizing it as the primary tool for ascribing significance to this intricate yet often overlooked aspect of psychopathology.

Behavioral indicators of heterogeneous subjective experience in animals across the phylogenetic spectrum: Implications for comparative animal phenomenology

This behavioral study was undertaken to provide empirical evidence in favor of or opposed to the notion that animals across a wide breadth of the animal kingdom have subjective (personal) experience that varies with their lifestyles, ecological constraints, or phylogeny. Twelve species representing two invertebrate phyla and six vertebrate classes were observed unobtrusively in 15-min episodes, during which three modes of behavior (volitional, interactive, and egocentric) were quantified according to the frequency, variety, and dynamism of each mode. Volitional behavior was the most prevalent and dynamic mode for nearly all species, largely without regard to phylogenetic position. Interactive behavior likewise varied inconsistently across the entire evolutionary spectrum. Egocentric behavior was concentrated among the avian and mammalian species, but evidence of it were observed in the invertebrate species as well. Diagrams of the matrix constructed from the three qualitative modes and three quantitative attributes for each mode provide a metaphorical representation of the unique experiential profile of each species. To the extent that these behavioral measures correlate with the nature of the animal's subjective experience, they support the growing view that phenomenology is heterogeneous, multimodal, and non-linear in extent across the animal kingdom.

The hidden structure of consciousness

According to Loorits, if we want consciousness to be explained in terms of natural sciences, we should be able to analyze its seemingly non-structural aspects, like qualia, in structural terms. However, the studies conducted over the last three decades do not seem to be able to bridge the explanatory gap between physical phenomena and phenomenal experience. One possible way to bridge the explanatory gap is to seek the structure of consciousness within consciousness itself, through a phenomenal analysis of the qualitative aspects of experience. First, this analysis leads us to identify the explanandum concerning the simplest forms of experience not in qualia but in the unitary set of qualities found in early vision. Second, it leads us to hypothesize that consciousness is also made up of non-apparent parts, and that there exists a hidden structure of consciousness. This structure, corresponding to a simple early visual experience, is constituted by a Hierarchy of Spatial Belongings nested within each other. Each individual Spatial Belonging is formed by a primary content and a primary space. The primary content can be traced in the perceptibility of the contents we can distinguish in the phenomenal field. The primary space is responsible for the perceptibility of the content and is not perceptible in itself. However, the phenomenon I refer to as subtraction of visibility allows us to characterize it as phenomenally negative. The hierarchical relationships between Spatial Belongings can ensure the qualitative nature of components of perceptual organization, such as object, background, and detail. The hidden structure of consciousness presents aspects that are decidedly counterintuitive compared to our idea of phenomenal experience. However, on the one hand, the Hierarchy of Spatial Belongings can explain the qualities of early vision and their appearance as a unitary whole, while on the other hand, it might be more easily explicable in terms of brain organization. In other words, the hidden structure of consciousness can be considered a bridge structure which, placing itself at an intermediate level between experience and physical properties, can contribute to bridging the explanatory gap.

Extrapolating animal consciousness

I argue that the question of animal consciousness is an extrapolation problem and, as such, is best tackled by deploying currently accepted methodology for validating experimental models of a phenomenon of interest. This methodology relies on an assessment of similarities and dissimilarities between experimental models, the partial replication of findings across complementary models, and evidence from the successes and failures of explanations, technologies and medical applications developed by extrapolating and aggregating findings from multiple models. Crucially important, this methodology does not require a commitment to any particular theory or construct of consciousness, thus avoiding theory-biased reinterpretations of empirical findings rampant in the literature.

Collective intelligence: A unifying concept for integrating biology across scales and substrates

A defining feature of biology is the use of a multiscale architecture, ranging from molecular networks to cells, tissues, organs, whole bodies, and swarms. Crucially however, biology is not only nested structurally, but also functionally: each level is able to solve problems in distinct problem spaces, such as physiological, morphological, and behavioral state space. Percolating adaptive functionality from one level of competent subunits to a higher functional level of organization requires collective dynamics: multiple components must work together to achieve specific outcomes. Here we overview a number of biological examples at different scales which highlight the ability of cellular material to make decisions that implement cooperation toward specific homeodynamic endpoints, and implement collective intelligence by solving problems at the cell, tissue, and whole-organism levels. We explore the hypothesis that collective intelligence is not only the province of groups of animals, and that an important symmetry exists between the behavioral science of swarms and the competencies of cells and other biological systems at different scales. We then briefly outline the implications of this approach, and the possible impact of tools from the field of diverse intelligence for regenerative medicine and synthetic bioengineering.

Hierarchical consciousness: the Nested Observer Windows model

Foremost in our experience is the intuition that we possess a unified conscious experience. However, many observations run counter to this intuition: we experience paralyzing indecision when faced with two appealing behavioral choices, we simultaneously hold contradictory beliefs, and the content of our thought is often characterized by an internal debate. Here, we propose the Nested Observer Windows (NOW) Model, a framework for hierarchical consciousness wherein information processed across many spatiotemporal scales of the brain feeds into subjective experience. The model likens the mind to a hierarchy of nested mosaic tiles-where an image is composed of mosaic tiles, and each of these tiles is itself an image composed of mosaic tiles. Unitary consciousness exists at the apex of this nested hierarchy where perceptual constructs become fully integrated and complex behaviors are initiated via abstract commands. We define an observer window as a spatially and temporally constrained system within which information is integrated, e.g. in functional brain regions and neurons. Three principles from the signal analysis of electrical activity describe the nested hierarchy and generate testable predictions. First, nested observer windows disseminate information across spatiotemporal scales with cross-frequency coupling. Second, observer windows are characterized by a high degree of internal synchrony (with zero phase lag). Third, observer windows at the same spatiotemporal level share information with each other through coherence (with non-zero phase lag). The theoretical framework of the NOW Model accounts for a wide range of subjective experiences and a novel approach for integrating prominent theories of consciousness.

Approaching the nature of consciousness through a phenomenal analysis of early vision. What is the explanandum?

Loorits (2014) identifies the solution to the hard problem of consciousness in the possibility of fully analyzing seemingly non-structural aspects of consciousness in structural terms. However, research on consciousness conducted in recent decades has failed to bridge the explanatory gap between the brain and conscious mind. One reason why the explanatory gap cannot be filled, and consequently the problem remains hard, is that experience and neural structure are too different or "distant" to be directly compatible. Conversely, structural aspects of consciousness can be found in phenomenal experience. One possible alternative, therefore, is to seek the structure of seemingly non-structural aspects of consciousness not in the neural substrate, but within consciousness itself, through a phenomenal analysis of the qualitative aspects of experience, starting from its simplest forms. An essential premise is to reformulate the explanandum of consciousness, which is usually attributed to qualia and what it is like to be in a certain state. However, these properties do not allow us to identify the fundamental aspects of phenomenal experience. Sensations such as the redness of red or the painfulness of pain are inseparable from the context of the experience to which they belong, making qualia appear as phenomenal artifacts. Furthermore, the simplest qualitative aspects can be found in early vision. They are involved in perceptual organization and necessarily have relational significance. The unitary set of qualities found in early vision-such as those related to being an object, background or detail-constitutes the explanandum of the simplest forms of consciousness and seems to imply a justifying structure. Although early vision is characterized by interdependent qualitative components that form a unitary whole, we cannot find in it the structure of seemingly non-structural aspects of consciousness. Phenomenal appearance alone does not seem sufficient to identify a unitary structure of consciousness. However, the closeness of these characteristics to a unitary structure prompts us to delve into less explored territory, using the components of experience also as possible explanans.

(Dis)confirming theories of consciousness and their predictions: towards a Lakatosian consciousness science

The neuroscience of consciousness is undergoing a significant empirical acceleration thanks to several adversarial collaborations that intend to test different predictions of rival theories of consciousness. In this context, it is important to pair consciousness science with confirmation theory, the philosophical discipline that explores the interaction between evidence and hypotheses, in order to understand how exactly, and to what extent, specific experiments are challenging or validating theories of consciousness. In this paper, I examine this intricate relationship by adopting a Lakatosian lens. I propose that Lakatos' philosophy of science can aid consciousness scientists to better interpret adversarial collaborations in consciousness science and, more generally, to develop a confirmation-theoretic model of theory-appraisal in this field. I do so by suggesting that such a model be built upon three Lakatos-inspired criteria for assessing the relationship between empirical evidence and theoretical predictions: (i) the model should represent the 'distinction between prediction and accommodation'; (ii) the model should represent the 'structural relevance' of predictions; (iii) the model should represent the 'boldness' of the predictions. I argue that a Lakatosian model of theory-appraisal has both normative and descriptive virtues, and can move the debate forward by acknowledging that theory-appraisal needs to consider the diachronic development of theories, their logical structure, and their relationship with background beliefs and knowledge.

Assessing the commensurability of theories of consciousness: On the usefulness of common denominators in differentiating, integrating and testing hypotheses

How deep is the current diversity in the panoply of theories to define consciousness, and to what extent do these theories share common denominators? Here we first examine to what extent different theories are commensurable (or comparable) along particular dimensions. We posit logical (and, when applicable, empirical) commensurability as a necessary condition for identifying common denominators among different theories. By consequence, dimensions for inclusion in a set of logically and empirically commensurable theories of consciousness can be proposed. Next, we compare a limited subset of neuroscience-based theories in terms of commensurability. This analysis does not yield a denominator that might serve to define a minimally unifying model of consciousness. Theories that seem to be akin by one denominator can be remote by another. We suggest a methodology of comparing different theories via multiple probing questions, allowing to discern overall (dis)similarities between theories. Despite very different background definitions of consciousness, we conclude that, if attention is paid to the search for a common methological approach to brain-consciousness relationships, it should be possible in principle to overcome the current Babylonian confusion of tongues and eventually integrate and merge different theories.

Temporal integration by multi-level regularities fosters the emergence of dynamic conscious experience

The relationship between integration and awareness is central to contemporary theories and research on consciousness. Here, we investigated whether and how information integration over time, by incorporating the underlying regularities, contributes to our awareness of the dynamic world. Using binocular rivalry, we demonstrated that structured visual streams, constituted by shape, motion, or idiom sequences containing perceptual- or semantic-level regularities, predominated over their nonstructured but otherwise matched counterparts in the competition for visual awareness. Despite the apparent resemblance, a substantial dissociation of the observed rivalry advantages emerged between perceptual- and semantic-level regularities. These effects stem from nonconscious and conscious temporal integration processes, respectively, with the former but not the latter being vulnerable to perturbations in the spatiotemporal integration window. These findings corroborate the essential role of structure-guided information integration in visual awareness and highlight a multi-level mechanism where temporal integration by perceptually and semantically defined regularities fosters the emergence of continuous conscious experience.

Emergence and Causality in Complex Systems: A Survey of Causal Emergence and Related Quantitative Studies

Emergence and causality are two fundamental concepts for understanding complex systems. They are interconnected. On one hand, emergence refers to the phenomenon where macroscopic properties cannot be solely attributed to the cause of individual properties. On the other hand, causality can exhibit emergence, meaning that new causal laws may arise as we increase the level of abstraction. Causal emergence (CE) theory aims to bridge these two concepts and even employs measures of causality to quantify emergence. This paper provides a comprehensive review of recent advancements in quantitative theories and applications of CE. It focuses on two primary challenges: quantifying CE and identifying it from data. The latter task requires the integration of machine learning and neural network techniques, establishing a significant link between causal emergence and machine learning. We highlight two problem categories: CE with machine learning and CE for machine learning, both of which emphasize the crucial role of effective information (EI) as a measure of causal emergence. The final section of this review explores potential applications and provides insights into future perspectives.

Brain organoids and organoid intelligence from ethical, legal, and social points of view

Human brain organoids, aka cerebral organoids or earlier "mini-brains", are 3D cellular models that recapitulate aspects of the developing human brain. They show tremendous promise for advancing our understanding of neurodevelopment and neurological disorders. However, the unprecedented ability to model human brain development and function in vitro also raises complex ethical, legal, and social challenges. Organoid Intelligence (OI) describes the ongoing movement to combine such organoids with Artificial Intelligence to establish basic forms of memory and learning. This article discusses key issues regarding the scientific status and prospects of brain organoids and OI, conceptualizations of consciousness and the mind-brain relationship, ethical and legal dimensions, including moral status, human-animal chimeras, informed consent, and governance matters, such as oversight and regulation. A balanced framework is needed to allow vital research while addressing public perceptions and ethical concerns. Interdisciplinary perspectives and proactive engagement among scientists, ethicists, policymakers, and the public can enable responsible translational pathways for organoid technology. A thoughtful, proactive governance framework might be needed to ensure ethically responsible progress in this promising field.

Carving Nature at Its Joints: A Comparison of CEMI Field Theory with Integrated Information Theory and Global Workspace Theory

The quest to comprehend the nature of consciousness has spurred the development of many theories that seek to explain its underlying mechanisms and account for its neural correlates. In this paper, I compare my own conscious electromagnetic information field (cemi field) theory with integrated information theory (IIT) and global workspace theory (GWT) for their ability to 'carve nature at its joints' in the sense of predicting the entities, structures, states and dynamics that are conventionally recognized as being conscious or nonconscious. I go on to argue that, though the cemi field theory shares features of both integrated information theory and global workspace theory, it is more successful at carving nature at its conventionally accepted joints between conscious and nonconscious systems, and is thereby a more successful theory of consciousness.

The feasibility of artificial consciousness through the lens of neuroscience

Interactions with large language models (LLMs) have led to the suggestion that these models may soon be conscious. From the perspective of neuroscience, this position is difficult to defend. For one, the inputs to LLMs lack the embodied, embedded information content characteristic of our sensory contact with the world around us. Secondly, the architectures of present-day artificial intelligence algorithms are missing key features of the thalamocortical system that have been linked to conscious awareness in mammals. Finally, the evolutionary and developmental trajectories that led to the emergence of living conscious organisms arguably have no parallels in artificial systems as envisioned today. The existence of living organisms depends on their actions and their survival is intricately linked to multi-level cellular, inter-cellular, and organismal processes culminating in agency and consciousness.

The technology, opportunities, and challenges of Synthetic Biological Intelligence

Integrating neural cultures developed through synthetic biology methods with digital computing has enabled the early development of Synthetic Biological Intelligence (SBI). Recently, key studies have emphasized the advantages of biological neural systems in some information processing tasks. However, neither the technology behind this early development, nor the potential ethical opportunities or challenges, have been explored in detail yet. Here, we review the key aspects that facilitate the development of SBI and explore potential applications. Considering these foreseeable use cases, various ethical implications are proposed. Ultimately, this work aims to provide a robust framework to structure ethical considerations to ensure that SBI technology can be both researched and applied responsibly.

Theoretical Neurobiology of Consciousness Applied to Human Cerebral Organoids

Organoids and specifically human cerebral organoids (HCOs) are one of the most relevant novelties in the field of biomedical research. Grown either from embryonic or induced pluripotent stem cells, HCOs can be used as in vitro three-dimensional models, mimicking the developmental process and organization of the developing human brain. Based on that, and despite their current limitations, it cannot be assumed that they will never at any stage of development manifest some rudimentary form of consciousness. In the absence of behavioral indicators of consciousness, the theoretical neurobiology of consciousness being applied to unresponsive brain-injured patients can be considered with respect to HCOs. In clinical neurology, it is difficult to discern a capacity for consciousness in unresponsive brain-injured patients who provide no behavioral indicators of consciousness. In such scenarios, a validated neurobiological theory of consciousness, which tells us what the neural mechanisms of consciousness are, could be used to identify a capacity for consciousness. Like the unresponsive patients that provide a diagnostic difficulty for neurologists, HCOs provide no behavioral indicators of consciousness. Therefore, this article discusses how three prominent neurobiological theories of consciousness apply to human cerebral organoids. From the perspective of the Temporal Circuit Hypothesis, the Global Neuronal Workspace Theory, and the Integrated Information Theory, we discuss what neuronal structures and functions might indicate that cerebral organoids have a neurobiological capacity to be conscious.

The Fundamental Tension in Integrated Information Theory 4.0's Realist Idealism

Integrated Information Theory (IIT) is currently one of the most influential scientific theories of consciousness. Here, we focus specifically on a metaphysical aspect of the theory's most recent version (IIT 4.0), what we may call its idealistic ontology, and its tension with a kind of realism about the external world that IIT also endorses. IIT 4.0 openly rejects the mainstream view that consciousness is generated by the brain, positing instead that consciousness is ontologically primary while the physical domain is just "operational". However, this philosophical position is presently underdeveloped and is not rigorously formulated in IIT, potentially leading to many misinterpretations and undermining its overall explanatory power. In the present paper we aim to address this issue. We argue that IIT's idealistic ontology should be understood as a specific combination of phenomenal primitivism, reductionism regarding Φ-structures and complexes, and eliminativism about non-conscious physical entities. Having clarified this, we then focus on the problematic tension between IIT's idealistic ontology and its simultaneous endorsement of realism, according to which there is some kind of external reality independent of our minds. After refuting three potential solutions to this theoretical tension, we propose the most plausible alternative: understanding IIT's realism as an assertion of the existence of other experiences beyond one's own, what we call a non-solipsistic idealist realism. We end with concluding remarks and future research avenues.

The exclusionary approach to consciousness

The standard approach in the field of consciousness research involves identifying the neural correlates of consciousness (NCCs) by comparing neural activity between conscious and unconscious trials. However, this method has been met with criticism due to the lack of consensus on how to operationalize and measure consciousness. In this paper, I propose an alternative approach: the exclusionary approach. Rather than utilizing near-threshold conditions to contrast conscious and unconscious trials, this approach leverages the widely accepted notion that subjective reports are reliable under normal conditions. I propose that this can be done by assessing whether consciousness remains stable across trials while manipulating other factors such as reports, tasks, stimulation, or attention. We can use the resulting contrast to exclude certain kinds of neural activity as candidate NCCs. This method produces results that are less contentious, allowing for the establishment of hard criteria for theories of consciousness. Additionally, this approach does not require the development of new research paradigms, but can incorporate existing studies, particularly those aimed at identifying confounding factors in the standard approach. It is important to note, however, that the proposed exclusionary approach does not negate the value of the identification approach. Rather, they should be considered as complementary methods.

Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical terms

This paper presents Integrated Information Theory (IIT) 4.0. IIT aims to account for the properties of experience in physical (operational) terms. It identifies the essential properties of experience (axioms), infers the necessary and sufficient properties that its substrate must satisfy (postulates), and expresses them in mathematical terms. In principle, the postulates can be applied to any system of units in a state to determine whether it is conscious, to what degree, and in what way. IIT offers a parsimonious explanation of empirical evidence, makes testable predictions concerning both the presence and the quality of experience, and permits inferences and extrapolations. IIT 4.0 incorporates several developments of the past ten years, including a more accurate formulation of the axioms as postulates and mathematical expressions, the introduction of a unique measure of intrinsic information that is consistent with the postulates, and an explicit assessment of causal relations. By fully unfolding a system's irreducible cause-effect power, the distinctions and relations specified by a substrate can account for the quality of experience.

Simultaneity of consciousness with physical reality: the key that unlocks the mind-matter problem

The problem of explaining the relationship between subjective experience and physical reality remains difficult and unresolved. In most explanations, consciousness is epiphenomenal, without causal power. The most notable exception is Integrated Information Theory (IIT), which provides a causal explanation for consciousness. However, IIT relies on an identity between subjectivity and a particular type of physical structure, namely with an information structure that has intrinsic causal power greater than the sum of its parts. Any theory that relies on a psycho-phyiscal identity must eventually appeal to panpsychism, which undermines that theory's claim to be fundamental. IIT has recently pivoted towards a strong version of causal emergence, but macroscopic structures cannot be stronger causally than their microphysical parts without some new physical law or governing principle. The approach taken here is designed to uncover such a principle. The decisive argument is entirely deductive from initial premises that are phenomenologically certain. If correct, the arguments prove that conscious experience is sufficient to create additional degrees of causal freedom independently of the content of experience, and in a manner that is unpredictable and unobservable by any temporally sequential means. This provides a fundamental principle about consciousness, and a conceptual bridge between it and the physics describing what is experienced. The principle makes testable predictions about brain function, with notable differences from IIT, some of which are also empirically testable.

Consciousness beyond the human case

There is growing interest in the relationship been AI and consciousness. Joseph LeDoux and Jonathan Birch thought it would be a good moment to put some of the big questions in this area to some leading experts. The challenge of addressing the questions they raised was taken up by Kristin Andrews, Nicky Clayton, Nathaniel Daw, Chris Frith, Hakwan Lau, Megan Peters, Susan Schneider, Anil Seth, Thomas Suddendorf, and Marie Vanderkerckhoeve.

Brain organoids, consciousness, ethics and moral status

Advances in the field of human stem cells are often a source of public and ethical controversy. Researchers must frequently balance diverse societal perspectives on questions of morality with the pursuit of medical therapeutics and innovation. Recent developments in brain organoids make this challenge even more acute. Brain organoids are a new class of brain surrogate generated from human pluripotent stem cells (hPSCs). They have gained traction as a model for studying the intricacies of the human brain by using advancements in stem cell biology to recapitulate aspects of the developing human brain in vitro. However, recent observation of neural oscillations spontaneously emerging from these organoids raises the question of whether brain organoids are or could become conscious. At the same time, brain organoids offer a potentially unique opportunity to scientifically understand consciousness. To address these issues, experimental biologists, philosophers, and ethicists united to discuss the possibility of consciousness in human brain organoids and the consequent ethical and moral implications.

An implementation of integrated information theory in resting-state fMRI

Integrated Information Theory was developed to explain and quantify consciousness, arguing that conscious systems consist of elements that are integrated through their causal properties. This study presents an implementation of Integrated Information Theory 3.0, the latest version of this framework, to functional MRI data. Data were acquired from 17 healthy subjects who underwent sedation with propofol, a short-acting anaesthetic. Using the PyPhi software package, we systematically analyze how Φ^max, a measure of integrated information, is modulated by the sedative in different resting-state networks. We compare Φ^max to other proposed measures of conscious level, including the previous version of integrated information, Granger causality, and correlation-based functional connectivity. Our results indicate that Φ^max presents a variety of sedative-induced behaviours for different networks. Notably, changes to Φ^max closely reflect changes to subjects' conscious level in the frontoparietal and dorsal attention networks, which are responsible for higher-order cognitive functions. In conclusion, our findings present important insight into different measures of conscious level that will be useful in future implementations to functional MRI and other forms of neuroimaging.

Towards modern post-coma care based on neuroscientific evidence

Background

Understanding the mechanisms underlying human consciousness is pivotal to improve the prognostication and treatment of severely brain-injured patients. Consciousness remains an elusive concept and the identification of its neural correlates is an active subject of research, however recent neuroscientific advances have allowed scientists to better characterize disorders of consciousness. These breakthroughs question the historical nomenclature and our current management of post-comatose patients.

Method

This review examines the contribution of consciousness neurosciences to the current clinical management of severe brain injury. It investigates the major impact of consciousness disorders on healthcare systems, the scientific frameworks employed to identify their neural correlates and how evidence-based data from neuroimaging research have reshaped the landscape of post-coma care in recent years.

Results

Our increased ability to detect behavioral and neurophysiological signatures of consciousness has led to significant changes in taxonomy and clinical practice. We advocate for a multimodal framework for the management of severely brain-injured patients based on precision medicine and evidence-based decisions, integrating epidemiology, health economics and neuroethics.

Conclusions

Major progress in brain imaging and clinical assessment have opened the door to a new era of post-coma care based on standardized neuroscientific evidence. We highlight its implications in clinical applications and call for improved collaborations between researchers and clinicians to better translate findings to the bedside.

A systematic approach to brain dynamics: cognitive evolution theory of consciousness

The brain integrates volition, cognition, and consciousness seamlessly over three hierarchical (scale-dependent) levels of neural activity for their emergence: a causal or 'hard' level, a computational (unconscious) or 'soft' level, and a phenomenal (conscious) or 'psyche' level respectively. The cognitive evolution theory (CET) is based on three general prerequisites: physicalism, dynamism, and emergentism, which entail five consequences about the nature of consciousness: discreteness, passivity, uniqueness, integrity, and graduation. CET starts from the assumption that brains should have primarily evolved as volitional subsystems of organisms, not as prediction machines. This emphasizes the dynamical nature of consciousness in terms of critical dynamics to account for metastability, avalanches, and self-organized criticality of brain processes, then coupling it with volition and cognition in a framework unified over the levels. Consciousness emerges near critical points, and unfolds as a discrete stream of momentary states, each volitionally driven from oldest subcortical arousal systems. The stream is the brain's way of making a difference via predictive (Bayesian) processing. Its objective observables could be complexity measures reflecting levels of consciousness and its dynamical coherency to reveal how much knowledge (information gain) the brain acquires over the stream. CET also proposes a quantitative classification of both disorders of consciousness and mental disorders within that unified framework.

Three levels of information processing in the brain

Information, the measure of order in a complex system, is the opposite of entropy, the measure of chaos and disorder. We can distinguish several levels at which information is processed in the brain. The first one is the level of serial molecular genetic processes, similar in some aspects to digital computations (DC). At the same time, higher cognitive activity is probably based on parallel neural network computations (NNC). The advantage of neural networks is their intrinsic ability to learn, adapting their parameters to specific tasks and to external data. However, there seems to be a third level of information processing as well, which involves subjective consciousness and its units, so called qualia. They are difficult to study experimentally, and the very fact of their existence is hard to explain within the framework of modern physical theory. Here I propose a way to consider consciousness as the extension of basic physical laws - namely, total entropy dissipation leading to a system simplification. At the level of subjective consciousness, the brain seems to convert information embodied by neural activity to a more simple and compact form, internally observed as qualia. Whereas physical implementations of both DC and NNC are essentially approximate and probabilistic, qualia-associated computations (QAC) make the brain capable of recognizing general laws and relationships. While elaborating a behavioral program, the conscious brain does not act blindly or gropingly but according to the very meaning of such general laws, which gives it an advantage compared to any artificial intelligence system.

Cerebral Organoid Research Ethics and Pinning the Tail on the Donkey

The risk of creating cerebral organoids/assembloids conscious enough to suffer is a recurrent concern in organoid research ethics. On one hand, we should, apparently, avoid discovering how to distinguish between organoids that it would be permissible (non-conscious) and impermissible (conscious) to use in research, since if successful we would create organoids that suffer. On the other, if we do not, the risk persists that research might inadvertently continue to cause organoids to suffer. Moreover, since modeling some brain disorders may require inducing stress in organoids, it is unclear how to eliminate the risk, if we want to develop effective therapies. We are committed to harm avoidance but hamstrung by a presumption that we should avoid research that might tell us clearly when suffering occurs. How can we negotiate this challenge and maximize the therapeutic benefits of cerebral organoid research? The author interrogates the challenge, suggesting a tentative way forward.

Perceptual and semantic same-different processing under subliminal conditions

Although other types of subliminal integrative processing are widely refuted by recent studies, subliminal same-different processing (SSDP) remains unchallenged to this day. Using shapes, categorical images, and Chinese characters as stimuli, the current study assessed whether SSDP can occur on a perceptual and semantic basis. Although some significant results were found, the effects are much weaker than previous studies, with Bayes factors suggesting that these effects are not reliable. It is therefore concluded that substantiating claims of SSDP requires more reliable evidence than currently available.

Peripheral control of psychiatric disorders: Focus on OCD. Are we there yet?

"We are all in this together" - we often hear this phrase when we want to flag up a problem that is not for a single individual but concerns us all. A similar reflection has been recently made in the field of mental disorders where brain-centric scientists have started to zoom out their brain-focused graphical representations of the mechanisms regulating psychiatric diseases to include other organs or mediators that did not belong historically to the world of neuroscience. The brain itself - that has long been seen as a master in command secluded in its fortress (the blood brain barrier), has now become a collection of Airbnb(s) where all sorts of cells come in and out and sometimes even rearrange the furniture! Under this new framework of reference, mental disorders have become multisystem pathologies where different biological systems - not just the CNS -contribute 'all together' to the development and severity of the disease. In this narrative review article, we will focus on one of the most popular biological systems that has been shown to influence the functioning of the CNS: the immune system. We will specifically highlight the two main features of the immune system and the CNS that we think are important in the context of mental disorders: plasticity and memory.

Consciousness in a Rotor? Science and Ethics of Potentially Conscious Human Cerebral Organoids

Human cerebral organoids are three-dimensional biological cultures grown in the laboratory to mimic as closely as possible the cellular composition, structure, and function of the corresponding organ, the brain. For now, cerebral organoids lack blood vessels and other characteristics of the human brain, but are also capable of having coordinated electrical activity. They have been usefully employed for the study of several diseases and the development of the nervous system in unprecedented ways. Research on human cerebral organoids is proceeding at a very fast pace and their complexity is bound to improve. This raises the question of whether cerebral organoids will also be able to develop the unique feature of the human brain, consciousness. If this is the case, some ethical issues would arise. In this article, we discuss the necessary neural correlates and constraints for the emergence of consciousness according to some of the most debated neuroscientific theories. Based on this, we consider what the moral status of a potentially conscious brain organoid might be, in light of ethical and ontological arguments. We conclude by proposing a precautionary principle and some leads for further investigation. In particular, we consider the outcomes of some very recent experiments as entities of a potential new kind.

Functional Neurologic Disorders, disorders to be managed by neurologists, or are neurologists wandering in a dangerous field with inadequate resources?

In recent years, some neurologists reconsidered their approach to Medically Unexplained Symptoms and proposed Functional Neurologic Disorders (FND) as a new entity, claiming that neurology could offer alternative treatment options to the psychotherapies provided in psychiatry settings. FNDs, for this purpose, should include only the disorders listed as Conversion from the Somatic Symptom and Related Disorders (SSRD) group. The present review analyzes the rationale of this position and challenges the arguments provided for its support. The review also discusses the systematization of these disorders as provided by public health systems. It outlines risks stemming from economic support and public funding uncertainty, given their negligible epidemiological dimensions resulting from the parcellation of SSRD. The review underlines the unresolved issue of Factitious Disorders, which are in the same SSRD category of the international classification but are, nonetheless, overlooked by the theoretical proponents of the FND entity. Comorbidity with other psychiatric disorders is also analyzed. We propose a model that supports the continuum between different SSRD conditions, including Factitious Disorders. The model is based on the emergence of feigned death reflex and deception from frontal lobe dysfunction. Finally, the paper summarizes the wealth of historical psychiatric and psychodynamic approaches and critical reviews. The study also puts in context the categorization and interpretation efforts provided by the most eminent researchers of the past century.

Sensory modality defines the relation between EEG Lempel-Ziv diversity and meaningfulness of a stimulus

Diversity of brain activity is a robust neural correlate of global states of consciousness. It has been proposed that diversity measures specifically reflect the temporal variability of conscious experience. Previous studies supported this hypothesis by showing that perception of meaningful visual stimuli causes richer, more-variable experiences than perception of meaningless stimuli, and this is reflected in greater brain signal diversity. To investigate whether this relation is consistent across sensory modalities, to participants we presented three versions of naturalistic visual and auditory stimuli (videos and audiobooks) that varied in the amount of meaning (original, scrambled, and noise), while recording electroencephalographic signals. We report three main findings. First, greater meaningfulness of visual stimuli was related to higher Lempel-Ziv diversity of EEG signals, but the opposite effect was found in the auditory modality. Second, visual perception was related to generally higher EEG diversity than auditory perception. Third, perception of meaningful visual stimuli and auditory stimuli respectively resulted in higher and lower EEG diversity in comparison to the resting state. In conclusion, the signal diversity of continuous brain signals depends on the stimulated sensory modality, therefore it is not a generic index of the variability of conscious experience.

Entropy and Cross-Level Orderliness in Light of the Interconnection between the Neural System and Consciousness

Despite recent advances, the origin and utility of consciousness remains under debate. Using an evolutionary perspective on the origin of consciousness, this review elaborates on the promising theoretical background suggested in the temporospatial theory of consciousness, which outlines world-brain alignment as a critical predisposition for controlling behavior and adaptation. Such a system can be evolutionarily effective only if it can provide instant cohesion between the subsystems, which is possible only if it performs an intrinsic activity modified in light of the incoming stimulation. One can assume that the world-brain interaction results in a particular interference pattern predetermined by connectome complexity. This is what organisms experience as their exclusive subjective state, allowing the anticipation of regularities in the environment. Thus, an anticipative system can emerge only in a regular environment, which guides natural selection by reinforcing corresponding reactions and decreasing the system entropy. Subsequent evolution requires complicated, layered structures and can be traced from simple organisms to human consciousness and society. This allows us to consider the mode of entropy as a subject of natural evolution rather than an individual entity.

Profiles of animal consciousness: A species-sensitive, two-tier account to quality and distribution

The science of animal consciousness investigates (i) which animal species are conscious (the distribution question) and (ii) how conscious experience differs in detail between species (the quality question). We propose a framework which clearly distinguishes both questions and tackles both of them. This two-tier account distinguishes consciousness along ten dimensions and suggests cognitive capacities which serve as distinct operationalizations for each dimension. The two-tier account achieves three valuable aims: First, it separates strong and weak indicators of the presence of consciousness. Second, these indicators include not only different specific contents but also differences in the way particular contents are processed (by processes of learning, reasoning or abstraction). Third, evidence of consciousness from each dimension can be combined to derive the distinctive multi-dimensional consciousness profile of various species. Thus, the two-tier account shows how the kind of conscious experience of different species can be systematically compared.

System Integrated Information

Integrated information theory (IIT) starts from consciousness itself and identifies a set of properties (axioms) that are true of every conceivable experience. The axioms are translated into a set of postulates about the substrate of consciousness (called a complex), which are then used to formulate a mathematical framework for assessing both the quality and quantity of experience. The explanatory identity proposed by IIT is that an experience is identical to the cause-effect structure unfolded from a maximally irreducible substrate (a Φ-structure). In this work we introduce a definition for the integrated information of a system (φs) that is based on the existence, intrinsicality, information, and integration postulates of IIT. We explore how notions of determinism, degeneracy, and fault lines in the connectivity impact system-integrated information. We then demonstrate how the proposed measure identifies complexes as systems, the φs of which is greater than the φs of any overlapping candidate systems.

Unconscious integration: Current evidence for integrative processing under subliminal conditions

Integrative processing is traditionally believed to be dependent on consciousness. While earlier studies within the last decade reported many types of integration under subliminal conditions (i.e. without perceptual awareness), these findings are widely challenged recently. This review evaluates the current evidence for 10 types of subliminal integration that are widely studied: arithmetic processing, object-context integration, multi-word processing, same-different processing, multisensory integration and 5 different types of associative learning. Potential methodological issues concerning awareness measures are also taken into account. It is concluded that while there is currently no reliable evidence for subliminal integration, this does not necessarily refute 'unconscious' integration defined through non-subliminal (e.g. implicit) approaches.

Consciousness: Matter or EMF?

Conventional theories of consciousness (ToCs) that assume that the substrate of consciousness is the brain's neuronal matter fail to account for fundamental features of consciousness, such as the binding problem. Field ToC's propose that the substrate of consciousness is the brain's best accounted by some kind of field in the brain. Electromagnetic (EM) ToCs propose that the conscious field is the brain's well-known EM field. EM-ToCs were first proposed only around 20 years ago primarily to account for the experimental discovery that synchronous neuronal firing was the strongest neural correlate of consciousness (NCC). Although EM-ToCs are gaining increasing support, they remain controversial and are often ignored by neurobiologists and philosophers and passed over in most published reviews of consciousness. In this review I examine EM-ToCs against established criteria for distinguishing between ToCs and demonstrate that they outperform all conventional ToCs and provide novel insights into the nature of consciousness as well as a feasible route toward building artificial consciousnesses.

Quantum spin models for numerosity perception

Humans share with animals, both vertebrates and invertebrates, the capacity to sense the number of items in their environment already at birth. The pervasiveness of this skill across the animal kingdom suggests that it should emerge in very simple populations of neurons. Current modelling literature, however, has struggled to provide a simple architecture carrying out this task, with most proposals suggesting the emergence of number sense in multi-layered complex neural networks, and typically requiring supervised learning; while simple accumulator models fail to predict Weber's Law, a common trait of human and animal numerosity processing. We present a simple quantum spin model with all-to-all connectivity, where numerosity is encoded in the spectrum after stimulation with a number of transient signals occurring in a random or orderly temporal sequence. We use a paradigmatic simulational approach borrowed from the theory and methods of open quantum systems out of equilibrium, as a possible way to describe information processing in neural systems. Our method is able to capture many of the perceptual characteristics of numerosity in such systems. The frequency components of the magnetization spectra at harmonics of the system's tunneling frequency increase with the number of stimuli presented. The amplitude decoding of each spectrum, performed with an ideal-observer model, reveals that the system follows Weber's law. This contrasts with the well-known failure to reproduce Weber's law with linear system or accumulators models.