The ConTraSt database for analysing and comparing empirical studies of consciousness theories

Bridging flexible goal-directed cognition and consciousness: The Goal-Aligning Representation Internal Manipulation theory

Goal-directed manipulation of internal representations is a key element of human flexible behaviour, while consciousness is commonly associated with higher-order cognition and human flexibility. Current perspectives have only partially linked these processes, thus preventing a clear understanding of how they jointly generate flexible cognition and behaviour. Moreover, these limitations prevent an effective exploitation of this knowledge for technological scopes. We propose a new theoretical perspective that extends our 'three-component theory of flexible cognition' toward higher-order cognition and consciousness, based on the systematic integration of key concepts from Cognitive Neuroscience and AI/Robotics. The theory proposes that the function of conscious processes is to support the alignment of representations with multi-level goals. This higher alignment leads to more flexible and effective behaviours. We analyse here our previous model of goal-directed flexible cognition (validated with more than 20 human populations) as a starting GARIM-inspired model. By bridging the main theories of consciousness and goal-directed behaviour, the theory has relevant implications for scientific and technological fields. In particular, it contributes to developing new experimental tasks and interpreting clinical evidence. Finally, it indicates directions for improving machine learning and robotics systems and for informing real-world applications (e.g., in digital-twin healthcare and roboethics).

Unifying biophysical consciousness theories with MaxCon: maximizing configurations of brain connectivity

There is such a vast proliferation of scientific theories of consciousness that it is worrying some scholars. There are even competitions to test different theories, and the results are inconclusive. Consciousness research, far from converging toward a unifying framework, is becoming more discordant than ever, especially with respect to theoretical elements that do not have a clear neurobiological basis. Rather than dueling theories, an integration across theories is needed to facilitate a comprehensive view on consciousness and on how normal nervous system dynamics can develop into pathological states. In dealing with what is considered an extremely complex matter, we try to adopt a perspective from which the subject appears in relative simplicity. Grounded in experimental and theoretical observations, we advance an encompassing biophysical theory, MaxCon, which incorporates aspects of several of the main existing neuroscientific consciousness theories, finding convergence points in an attempt to simplify and to understand how cellular collective activity is organized to fulfill the dynamic requirements of the diverse theories our proposal comprises. Moreover, a computable index indicating consciousness level is presented. Derived from the level of description of the interactions among cell networks, our proposal highlights the association of consciousness with maximization of the number of configurations of neural network connections -constrained by neuroanatomy, biophysics and the environment- that is common to all consciousness theories.

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.

Early Electrophysiological Correlates of Perceptual Consciousness Are Affected by Both Exogenous and Endogenous Attention

It has been proposed that visual awareness negativity (VAN), which is an early ERP component, constitutes a neural correlate of visual consciousness that is independent of perceptual and cognitive mechanisms. In the present study, we investigated whether VAN is indeed a specific marker of phenomenal awareness or rather reflects the involvement of attention. To this end, we reanalyzed data collected in a previously published EEG experiment in which awareness of visual stimuli and two aspects that define attentional involvement, namely, the inherent saliency and task relevance of a stimulus, were manipulated orthogonally. During the experimental procedure, participants (n = 41) were presented with images of faces that were backward-masked or unmasked, fearful or neutral, and defined as task-relevant targets or task-irrelevant distractors. Single-trial ERP analysis revealed that VAN was highly dependent on attentional manipulations in the early time window (140-200 msec), up to the point that the effect of awareness was not observed for attentionally irrelevant stimuli (i.e., neutral faces presented as distractors). In the late time window (200-350 msec), VAN was present in all attentional conditions, but its amplitude was significantly higher in response to fearful faces and task-relevant face images than in response to neutral ones and task-irrelevant ones, respectively. In conclusion, we demonstrate that the amplitude of VAN is highly dependent on both exogenous (stimulus saliency) and endogenous attention (task requirements). Our results challenge the view that VAN constitutes an attention-independent correlate of phenomenal awareness.

Taking consciousness for real: Increasing the ecological validity of the study of conscious vs. unconscious processes

The study of consciousness has developed well-controlled, rigorous methods for manipulating and measuring consciousness. Yet, in the process, experimental paradigms grew farther away from everyday conscious and unconscious processes, which raises the concern of ecological validity. In this review, we suggest that the field can benefit from adopting a more ecological approach, akin to other fields of cognitive science. There, this approach challenged some existing hypotheses, yielded stronger effects, and enabled new research questions. We argue that such a move is critical for studying consciousness, where experimental paradigms tend to be artificial and small effect sizes are relatively prevalent. We identify three paths for doing so-changing the stimuli and experimental settings, changing the measures, and changing the research questions themselves-and review works that have already started implementing such approaches. While acknowledging the inherent challenges, we call for increasing ecological validity in consciousness studies.

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.

Tests for consciousness in humans and beyond

Which systems/organisms are conscious? New tests for consciousness ('C-tests') are urgently needed. There is persisting uncertainty about when consciousness arises in human development, when it is lost due to neurological disorders and brain injury, and how it is distributed in nonhuman species. This need is amplified by recent and rapid developments in artificial intelligence (AI), neural organoids, and xenobot technology. Although a number of C-tests have been proposed in recent years, most are of limited use, and currently we have no C-tests for many of the populations for which they are most critical. Here, we identify challenges facing any attempt to develop C-tests, propose a multidimensional classification of such tests, and identify strategies that might be used to validate them.

(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.

Quantifying empirical support for theories of consciousness: a tentative methodological framework

Understanding consciousness is central to understanding human nature. We have competing theories of consciousness. In interdisciplinary consciousness studies most believe that consciousness can be naturalized (i.e., consciousness depends in some substantial way on processes in - or states of - the brain). For roughly two decades, proponents of almost every theory have focused on collecting empirical support for their preferred theory, on the tacit assumption that empirical evidence will resolve the debates. Yet, it remains unclear how empirical evidence can do this in practice. Here I address this issue by offering (a sketch of) a methodology to quantify the divergent sets of empirical support proposed in favor of extant theories of consciousness. This in turn forms the foundation for a process of inference to the best explanation inspired by Bayesian confirmation theory. In interdisciplinary consciousness studies we are blessed with an abundance of theories, but we have reached a point where, going forward, it would be beneficial to focus on the most promising ones. Methods for assessment and comparison are necessary to identify which those are. While future refinement is likely, the methodology for assessment and comparison proposed here is a first step toward a novel way of approaching this through a quantification of empirical support for theories of consciousness.

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.

A construct-first approach to consciousness science

We propose a new approach to consciousness science that instead of comparing complex theoretical positions deconstructs existing theories, takes their central assumptions while disregarding their auxiliary hypotheses, and focuses its investigations on the main constructs that these central assumptions rely on (like global workspace, recurrent processing, metarepresentation). Studying how these main constructs are anchored in lower-level constructs characterizing underlying neural processing will not just offer an alternative to theory comparisons but will also take us one step closer to empirical resolutions. Moreover, exploring the compatibility and possible combinations of the lower-level constructs will allow for new theoretical syntheses. This construct-first approach will improve our ability to understand the commitments of existing theories and pave the way for moving beyond them.

Consciousness in the cradle: on the emergence of infant experience

Although each of us was once a baby, infant consciousness remains mysterious and there is no received view about when, and in what form, consciousness first emerges. Some theorists defend a 'late-onset' view, suggesting that consciousness requires cognitive capacities which are unlikely to be in place before the child's first birthday at the very earliest. Other theorists defend an 'early-onset' account, suggesting that consciousness is likely to be in place at birth (or shortly after) and may even arise during the third trimester. Progress in this field has been difficult, not just because of the challenges associated with procuring the relevant behavioral and neural data, but also because of uncertainty about how best to study consciousness in the absence of the capacity for verbal report or intentional behavior. This review examines both the empirical and methodological progress in this field, arguing that recent research points in favor of early-onset accounts of the emergence of consciousness.

Accelerating scientific progress through Bayesian adversarial collaboration

Adversarial collaboration has been championed as the gold standard for resolving scientific disputes but has gained relatively limited traction in neuroscience and allied fields. In this perspective, we argue that adversarial collaborative research has been stymied by an overly restrictive concern with the falsification of scientific theories. We advocate instead for a more expansive view that frames adversarial collaboration in terms of Bayesian belief updating, model comparison, and evidence accumulation. This framework broadens the scope of adversarial collaboration to accommodate a wide range of informative (but not necessarily definitive) studies while affording the requisite formal tools to guide experimental design and data analysis in the adversarial setting. We provide worked examples that demonstrate how these tools can be deployed to score theoretical models in terms of a common metric of evidence, thereby furnishing a means of tracking the amount of empirical support garnered by competing theories over time.

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.

Consciousness: a neurosurgical perspective

Neurosurgeons are in a unique position to shed light on the neural basis for consciousness, not only by their clinical care of patients with compromised states of consciousness, but also by employing neurostimulation and neuronal recordings through intracranial electrodes in awake surgical patients, as well as during stages of sleep and anethesia. In this review, we discuss several aspects of consciousness, i.e., perception, memory, and willed actions, studied by electrical stimulation and single neuron recordings in the human brain. We demonstrate how specific neuronal activity underlie the emergence of concepts, memories, and intentions in human consciousness. We discuss the representation of specific conscious content by temporal lobe neurons and present the discovery of "concept cells" and the encoding and retrieval of memories by neurons in the medial temporal lobe. We review prefrontal and parietal neuronal activation that precedes conscious intentions to act. Taken together with other studies in the field, these findings suggest that specific conscious experience may arise from stochastic fluctuations of neuronal activity, reaching a dynamic threshold. Advances in brain recording and stimulation technology coupled with the rapid rise in artificial intelligence are likely to increase the amount and analysis capabilities of data obtained from the human brain, thereby improving the decoding of conscious and preconscious states and open new horizons for modulation of human cognitive functions such as memory and volition.

The evolutionary origins of the Global Neuronal Workspace in vertebrates

The Global Neuronal Workspace theory of consciousness offers an explicit functional architecture that relates consciousness to cognitive abilities such as perception, attention, memory, and evaluation. We show that the functional architecture of the Global Neuronal Workspace, which is based mainly on human studies, corresponds to the cognitive-affective architecture proposed by the Unlimited Associative Learning theory that describes minimal consciousness. However, we suggest that when applied to basal vertebrates, both models require important modifications to accommodate what has been learned about the evolution of the vertebrate brain. Most importantly, comparative studies suggest that in basal vertebrates, the Global Neuronal Workspace is instantiated by the event memory system found in the hippocampal homolog. This proposal has testable predictions and implications for understanding hippocampal and cortical functions, the evolutionary relations between memory and consciousness, and the evolution of unified perception.

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.

Hierarchical fluctuation shapes a dynamic flow linked to states of consciousness

Consciousness arises from the spatiotemporal neural dynamics, however, its relationship with neural flexibility and regional specialization remains elusive. We identified a consciousness-related signature marked by shifting spontaneous fluctuations along a unimodal-transmodal cortical axis. This simple signature is sensitive to altered states of consciousness in single individuals, exhibiting abnormal elevation under psychedelics and in psychosis. The hierarchical dynamic reflects brain state changes in global integration and connectome diversity under task-free conditions. Quasi-periodic pattern detection revealed that hierarchical heterogeneity as spatiotemporally propagating waves linking to arousal. A similar pattern can be observed in macaque electrocorticography. Furthermore, the spatial distribution of principal cortical gradient preferentially recapitulated the genetic transcription levels of the histaminergic system and that of the functional connectome mapping of the tuberomammillary nucleus, which promotes wakefulness. Combining behavioral, neuroimaging, electrophysiological, and transcriptomic evidence, we propose that global consciousness is supported by efficient hierarchical processing constrained along a low-dimensional macroscale gradient.

An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory

The relationship between conscious experience and brain activity has intrigued scientists and philosophers for centuries. In the last decades, several theories have suggested different accounts for these relationships. These theories have developed in parallel, with little to no cross-talk among them. To advance research on consciousness, we established an adversarial collaboration between proponents of two of the major theories in the field, Global Neuronal Workspace and Integrated Information Theory. Together, we devised and preregistered two experiments that test contrasting predictions of these theories concerning the location and timing of correlates of visual consciousness, which have been endorsed by the theories' proponents. Predicted outcomes should either support, refute, or challenge these theories. Six theory-impartial laboratories will follow the study protocol specified here, using three complementary methods: Functional Magnetic Resonance Imaging (fMRI), Magneto-Electroencephalography (M-EEG), and intracranial electroencephalography (iEEG). The study protocol will include built-in replications, both between labs and within datasets. Through this ambitious undertaking, we hope to provide decisive evidence in favor or against the two theories and clarify the footprints of conscious visual perception in the human brain, while also providing an innovative model of large-scale, collaborative, and open science practice.

Consciousness as a Memory System

We suggest that there is confusion between why consciousness developed and what additional functions, through continued evolution, it has co-opted. Consider episodic memory. If we believe that episodic memory evolved solely to accurately represent past events, it seems like a terrible system-prone to forgetting and false memories. However, if we believe that episodic memory developed to flexibly and creatively combine and rearrange memories of prior events in order to plan for the future, then it is quite a good system. We argue that consciousness originally developed as part of the episodic memory system-quite likely the part needed to accomplish that flexible recombining of information. We posit further that consciousness was subsequently co-opted to produce other functions that are not directly relevant to memory per se, such as problem-solving, abstract thinking, and language. We suggest that this theory is compatible with many phenomena, such as the slow speed and the after-the-fact order of consciousness, that cannot be explained well by other theories. We believe that our theory may have profound implications for understanding intentional action and consciousness in general. Moreover, we suggest that episodic memory and its associated memory systems of sensory, working, and semantic memory as a whole ought to be considered together as the conscious memory system in that they, together, give rise to the phenomenon of consciousness. Lastly, we suggest that the cerebral cortex is the part of the brain that makes consciousness possible, and that every cortical region contributes to this conscious memory system.

How much consciousness is there in complexity?

The notion of complexity currently receives significant attention in neuroscience, mainly through the popularity of the Integrated Information Theory (IIT). It has proven successful in research centred on discriminating states of consciousness, while little theoretical and experimental effort was directed toward studying the content. In this paper, we argue that exploring the relationship between complexity and conscious content is necessary to understand the importance of information-theoretic measures for consciousness research properly. We outline how content could be experimentally operationalised and how rudimental testable hypotheses can be formulated without requiring IIT formalisms. This approach would not only allow for a better understanding of aspects of consciousness captured by complexity but could also facilitate comparison efforts for theories of consciousness.

Theories of consciousness

Recent years have seen a blossoming of theories about the biological and physical basis of consciousness. Good theories guide empirical research, allowing us to interpret data, develop new experimental techniques and expand our capacity to manipulate the phenomenon of interest. Indeed, it is only when couched in terms of a theory that empirical discoveries can ultimately deliver a satisfying understanding of a phenomenon. However, in the case of consciousness, it is unclear how current theories relate to each other, or whether they can be empirically distinguished. To clarify this complicated landscape, we review four prominent theoretical approaches to consciousness: higher-order theories, global workspace theories, re-entry and predictive processing theories and integrated information theory. We describe the key characteristics of each approach by identifying which aspects of consciousness they propose to explain, what their neurobiological commitments are and what empirical data are adduced in their support. We consider how some prominent empirical debates might distinguish among these theories, and we outline three ways in which theories need to be developed to deliver a mature regimen of theory-testing in the neuroscience of consciousness. There are good reasons to think that the iterative development, testing and comparison of theories of consciousness will lead to a deeper understanding of this most profound of mysteries.