Global Neuronal Workspace Theory Research Articles

Interaction between top-down decision-driven congruency effect and bottom-up input-driven congruency effect is correlated with conscious awareness.

In a conventional (Stroop) priming paradigm, it was well documented that objective prime-target incongruency delays response time (RT) to target compared to prime-target congruent condition. Recent evidence suggests that incongruency between the target and subjectively reported prime identity also delays RT over and above the classic congruency effect. When the prime is rendered invisible, the former effect is fundamentally a bottom-up (BU) stimulus-driven congruency effect and the latter a top-down (TD) guess-driven congruency effect. An influential theory of consciousness, global neuronal workspace theory, postulates that the long-lasting simultaneous and reciprocal interaction between TD decision network and BU input network is preserved during conscious processing and disabled during unconscious processing. Current study is focused on testing this theoretical postulation using two behavioral experiments. Our results showed that indeed TD-congruency and BU-congruency produced additive RT effects on prime-invisible trials, which implies that TD and BU prime representations are activated in independent neuronal populations. Meanwhile, an underadditive interaction effect was observed as prime visibility rose, which is a signature that TD and BU prime representations recruited overlapping neuronal populations during conscious perception. In addition, we suggest that current behavioral paradigm might be a financially friendly alternative to detect the presence of representational overlap in the brain between a wide range of mental representations, such as expectation, prediction, conscious/unconscious perception, and conscious/unconscious working memory. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Teorija dendritičke integracije kao stanični most za dominantne suvremene teorije svijesti

Consciousness is often described as the final frontier in science, tackled from multiple disciplines including philosophy, neuroscience, and computer science. Consciousness is most commonly defined as what exists from a first-person perspective, as the feeling of what it is like to be something, as well as through neuronal mechanisms that generate and support this phenomenology. Countless theories on consciousness have emerged to try to elucidate this complicated phenomenon. In our review, we aim to examine the three dominant theories of consciousness - Global Neuronal Workspace Theory (GNWT), Recurrent Processing Theory (RPT), Higher-order Theory (HOT) - and the Dendritic Integration Theory (DIT) as a newer, less prominent, theory that focuses on the cellular basis of consciousness. We propose that DIT may complement the postulations of the other three theories through its cellular approach that bridges state and content consciousness. Finally, we discuss the future of consciousness research more generally.

Unveiling the Mind’s Mystery: Exploring the Neurological Basis of Consciousness and its Impact on Human Health

Viewed as one of the biggest mysteries in science, consciousness was once overlooked as a research topic and is now an expanding field in neuroscience. Currently, there is no set definition for consciousness, and its biological underpinnings are not fully understood. Disorders of consciousness, where appropriate levels of consciousness are not achieved for a given period, can have a significant impact on quality of life. To recognize the implications of consciousness, it is important to understand the neurological basis of consciousness disorders. Today, research is limited to patients that suffer from long-term states of unconsciousness. However, scientists have been able to form a framework for the biological circuits involved in consciousness. It has been determined that consciousness is regulated through the integration of neural circuits between several parts of the brain. Many theories associated with the neural circuits that allow the human body to sustain consciousness exist: the Global Neuronal Workspace Theory, Information Integration Theory, and Temporospatial Theory of Consciousness. External factors can also lead to disorders of consciousness. While researchers have developed a clearer picture of the biological underpinnings of consciousness, treatments and recovery from disorders of consciousness remains challenging. As such, further work is needed to improve patient outcomes in disorders of consciousness. Here, we will define the areas of the brain related to consciousness, discuss the biological systems involved in conscious systems, and discuss disorders of consciousness and their current treatments. Finally, we will discuss new approaches to treatments and how they can improve patient outcomes.

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 evolutionary origins ofthe Global Neuronal Workspace invertebrates.

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.

About the compatibility between the perturbational complexity index andthe global neuronal workspace theory ofconsciousness.

This paper investigates the compatibility between the theoretical framework of the global neuronal workspace theory (GNWT) of conscious processing and the perturbational complexity index (PCI). Even if it has been introduced within the framework of a concurrent theory (i.e.Integrated Information Theory), PCI appears, in principle, compatible with the main tenet of GNWT, which is a conscious process that depends on a long-range connection between different cortical regions, more specifically on the amplification, global propagation, and integration of brain signals. Notwithstanding this basic compatibility, a number of limited compatibilities and apparent differences emerge. This paper starts from the description of brain complexity, a notion that is crucial for PCI, to then summary of the main features of PCI and the main tenets of GNWT. Against this background, the text explores the compatibility between PCI and GNWT. It concludes that GNWT and PCI are fundamentally compatible, even though there are some partial disagreements and some points to further examine.

Continuous Theta Burst Stimulation to the left anterior medial prefrontal cortex influences metacognitive efficiency

The contribution of the prefrontal areas to visual awareness is critical for the Global Neuronal Workspace Theory and higher-order theories of consciousness. The goal of the present study was to test the potential engagement of the anterior medial prefrontal cortex (aMPFC) in visual awareness judgements. We aimed to temporarily influence the neuronal dynamics of the left aMPFC via neuroplasticity-like mechanisms. We used different Theta Burst Stimulation (TBS) protocols in combination with a visual identification task and visual awareness ratings. Either continuous TBS (cTBS), intermittent TBS (iTBS), or sham TBS was applied prior to the experimental paradigm in a within-participant design. Compared with sham TBS, we observed an increase in participants’ ability to judge their perception adequately (metacognitive efficiency) following cTBS but not iTBS. The effect was accompanied by lower visual awareness ratings in incorrect responses. No significant differences in the identification task performance were observed. We interpret these results as evidence of the involvement of PFC in the brain network that underlies metacognition. Further, we discuss whether the results of TMS studies on perceptual metacognition can be taken as evidence for PFC involvement in awareness itself.

On Integrated Information Theory (IIT) and Adversarial Collaboration: A Conversation with Christof Koch, PhD

The following interview explores neuroscientist Christof Koch's participation in the adversarial collaboration, testing the integrated information theory (IIT) of consciousness against the global neuronal workspace theory (GNW). The interview offers a current update on the adversarial project and then pivots to Koch's responses to three standing critiques of IIT, which include the inexactness of IIT's measures of the neural correlates of consciousness, the charge that IIT implies an unwieldy panpsychism, and the claim that IIT conflates its measures with consciousness.

Integrated world modeling theory expanded: Implications for the future of consciousness.

Integrated world modeling theory (IWMT) is a synthetic theory of consciousness that uses the free energy principle and active inference (FEP-AI) framework to combine insights from integrated information theory (IIT) and global neuronal workspace theory (GNWT). Here, I first review philosophical principles and neural systems contributing to IWMT's integrative perspective. I then go on to describe predictive processing models of brains and their connections to machine learning architectures, with particular emphasis on autoencoders (perceptual and active inference), turbo-codes (establishment of shared latent spaces for multi-modal integration and inferential synergy), and graph neural networks (spatial and somatic modeling and control). Future directions for IIT and GNWT are considered by exploring ways in which modules and workspaces may be evaluated as both complexes of integrated information and arenas for iterated Bayesian model selection. Based on these considerations, I suggest novel ways in which integrated information might be estimated using concepts from probabilistic graphical models, flow networks, and game theory. Mechanistic and computational principles are also considered with respect to the ongoing debate between IIT and GNWT regarding the physical substrates of different kinds of conscious and unconscious phenomena. I further explore how these ideas might relate to the "Bayesian blur problem," or how it is that a seemingly discrete experience can be generated from probabilistic modeling, with some consideration of analogies from quantum mechanics as potentially revealing different varieties of inferential dynamics. I go on to describe potential means of addressing critiques of causal structure theories based on network unfolding, and the seeming absurdity of conscious expander graphs (without cybernetic symbol grounding). Finally, I discuss future directions for work centered on attentional selection and the evolutionary origins of consciousness as facilitated "unlimited associative learning." While not quite solving the Hard problem, this article expands on IWMT as a unifying model of consciousness and the potential future evolution of minds.

Spontaneous neuronal avalanches as a correlate of access consciousness.

Decades of research have advanced our understanding of the biophysical mechanisms underlying consciousness. However, an overarching framework bridging between models of consciousness and the large-scale organization of spontaneous brain activity is still missing. Based on the observation that spontaneous brain activity dynamically switches between epochs of segregation and large-scale integration of information, we hypothesize a brain-state dependence of conscious access, whereby the presence of either segregated or integrated states marks distinct modes of information processing. We first review influential works on the neuronal correlates of consciousness, spontaneous resting-state brain activity and dynamical system theory. Then, we propose a test experiment to validate our hypothesis that conscious access occurs in aperiodic cycles, alternating windows where new incoming information is collected but not experienced, to punctuated short-lived integration events, where conscious access to previously collected content occurs. In particular, we suggest that the integration events correspond to neuronal avalanches, which are collective bursts of neuronal activity ubiquitously observed in electrophysiological recordings. If confirmed, the proposed framework would link the physics of spontaneous cortical dynamics, to the concept of ignition within the global neuronal workspace theory, whereby conscious access manifest itself as a burst of neuronal activity.

Multilevel development of cognitive abilities in an artificial neural network

Several neuronal mechanisms have been proposed to account for the formation of cognitive abilities through postnatal interactions with the physical and sociocultural environment. Here, we introduce a three-level computational model of information processing and acquisition of cognitive abilities. We propose minimal architectural requirements to build these levels, and how the parameters affect their performance and relationships. The first sensorimotor level handles local nonconscious processing, here during a visual classification task. The second level or cognitive level globally integrates the information from multiple local processors via long-ranged connections and synthesizes it in a global, but still nonconscious, manner. The third and cognitively highest level handles the information globally and consciously. It is based on the global neuronal workspace (GNW) theory and is referred to as the conscious level. We use the trace and delay conditioning tasks to, respectively, challenge the second and third levels. Results first highlight the necessity of epigenesis through the selection and stabilization of synapses at both local and global scales to allow the network to solve the first two tasks. At the global scale, dopamine appears necessary to properly provide credit assignment despite the temporal delay between perception and reward. At the third level, the presence of interneurons becomes necessary to maintain a self-sustained representation within the GNW in the absence of sensory input. Finally, while balanced spontaneous intrinsic activity facilitates epigenesis at both local and global scales, the balanced excitatory/inhibitory ratio increases performance. We discuss the plausibility of the model in both neurodevelopmental and artificial intelligence terms.

Decoding rapidly presented visual stimuli from prefrontal ensembles without report nor post-perceptual processing.

The role of the primate prefrontal cortex (PFC) in conscious perception is debated. The global neuronal workspace theory of consciousness predicts that PFC neurons should contain a detailed code of the current conscious contents. Previous research showed that PFC is indeed activated in paradigms of conscious visual perception, including no-report paradigms where no voluntary behavioral report of the percept is given, thus avoiding a conflation of signals related to visual consciousness with signals related to the report. Still, it has been argued that prefrontal modulation could reflect post-perceptual processes that may be present even in the absence of report, such as thinking about the perceived stimulus, therefore reflecting a consequence rather than a direct correlate of conscious experience. Here, we investigate these issues by recording neuronal ensemble activity from the macaque ventrolateral PFC during briefly presented visual stimuli, either in isolated trials in which stimuli were clearly perceived or in sequences of rapid serial visual presentation (RSVP) in which perception and post-perceptual processing were challenged. We report that the identity of each stimulus could be decoded from PFC population activity even in the RSVP condition. The first visual signals could be detected at 60 ms after stimulus onset and information was maximal at 150 ms. However, in the RSVP condition, 200 ms after the onset of a stimulus, the decoding accuracy quickly dropped to chance level and the next stimulus started to be decodable. Interestingly, decoding in the ventrolateral PFC was stronger compared to posterior parietal cortex for both isolated and RSVP stimuli. These results indicate that neuronal populations in the macaque PFC reliably encode visual stimuli even under conditions that have been shown to challenge conscious perception and/or substantially reduce the probability of post-perceptual processing in humans. We discuss whether the observed activation reflects conscious access, phenomenal consciousness, or merely a preconscious bottom-up wave.

Is One Spring Enough for a Conscious Stream? Comments on Mark Solms' The Hidden Spring

In this commentary, I discuss my main points of convergence and divergence with Mark Solms' conception of consciousness presented in his very stimulating opus, The Hidden Spring, and then frame two proposals to integrate some of his key concepts into the global neuronal workspace theory (GNWT) of consciousness.

What Might Interoceptive Inference Reveal about Consciousness?

The mainstream science of consciousness offers a few predominate views of how the brain gives rise to awareness. Chief among these are the Higher-Order Thought Theory, Global Neuronal Workspace Theory, Integrated Information Theory, and hybrids thereof. In parallel, rapid development in predictive processing approaches have begun to outline concrete mechanisms by which interoceptive inference shapes selfhood, affect, and exteroceptive perception. Here, we consider these new approaches in terms of what they might offer our empirical, phenomenological, and philosophical understanding of consciousness and its neurobiological roots.

How Energy Supports Our Brain to Yield Consciousness: Insights From Neuroimaging Based on the Neuroenergetics Hypothesis.

Consciousness is considered a result of specific neuronal processes and mechanisms in the brain. Various suggested neuronal mechanisms, including the information integration theory (IIT), global neuronal workspace theory (GNWS), and neuronal construction of time and space as in the context of the temporospatial theory of consciousness (TTC), have been laid forth. However, despite their focus on different neuronal mechanisms, these theories neglect the energetic-metabolic basis of the neuronal mechanisms that are supposed to yield consciousness. Based on the findings of physiology-induced (sleep), pharmacology-induced (general anesthesia), and pathology-induced [vegetative state/unresponsive wakeful syndrome (VS/UWS)] loss of consciousness in both human subjects and animals, we, in this study, suggest that the energetic-metabolic processes focusing on ATP, glucose, and γ-aminobutyrate/glutamate are indispensable for functional connectivity (FC) of normal brain networks that renders consciousness possible. Therefore, we describe the energetic-metabolic predispositions of consciousness (EPC) that complement the current theories focused on the neural correlates of consciousness (NCC).

Disruption of Conscious Access in Psychosis Is Associated with Altered Structural Brain Connectivity.

According to global neuronal workspace (GNW) theory, conscious access relies on long-distance cerebral connectivity to allow a global neuronal ignition coding for conscious content. In patients with schizophrenia and bipolar disorder, both alterations in cerebral connectivity and an increased threshold for conscious perception have been reported. The implications of abnormal structural connectivity for disrupted conscious access and the relationship between these two deficits and psychopathology remain unclear. The aim of this study was to determine the extent to which structural connectivity is correlated with consciousness threshold, particularly in psychosis. We used a visual masking paradigm to measure consciousness threshold, and diffusion MRI tractography to assess structural connectivity in 97 humans of either sex with varying degrees of psychosis: healthy control subjects (n = 46), schizophrenia patients (n = 25), and bipolar disorder patients with (n = 17) and without (n = 9) a history of psychosis. Patients with psychosis (schizophrenia and bipolar disorder with psychotic features) had an elevated masking threshold compared with control subjects and bipolar disorder patients without psychotic features. Masking threshold correlated negatively with the mean general fractional anisotropy of white matter tracts exclusively within the GNW network (inferior frontal-occipital fasciculus, cingulum, and corpus callosum). Mediation analysis demonstrated that alterations in long-distance connectivity were associated with an increased masking threshold, which in turn was linked to psychotic symptoms. Our findings support the hypothesis that long-distance structural connectivity within the GNW plays a crucial role in conscious access, and that conscious access may mediate the association between impaired structural connectivity and psychosis.

An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation.

The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental exchanges and prevent entropic accumulation. In FEP-AI, minds and brains are predictive controllers for autonomous systems, where action-driven perception is realized as probabilistic inference. Integrated Information Theory (IIT) begins with considering the preconditions for a system to intrinsically exist, as well as axioms regarding the nature of consciousness. IIT has produced controversy because of its surprising entailments: quasi-panpsychism; subjectivity without referents or dynamics; and the possibility of fully-intelligent-yet-unconscious brain simulations. Here, I describe how these controversies might be resolved by integrating IIT with FEP-AI, where integrated information only entails consciousness for systems with perspectival reference frames capable of generating models with spatial, temporal, and causal coherence for self and world. Without that connection with external reality, systems could have arbitrarily high amounts of integrated information, but nonetheless would not entail subjective experience. I further describe how an integration of these frameworks may contribute to their evolution as unified systems theories and models of emergent causation. Then, inspired by both Global Neuronal Workspace Theory (GNWT) and the Harmonic Brain Modes framework, I describe how streams of consciousness may emerge as an evolving generation of sensorimotor predictions, with the precise composition of experiences depending on the integration abilities of synchronous complexes as self-organizing harmonic modes (SOHMs). These integrating dynamics may be particularly likely to occur via richly connected subnetworks affording body-centric sources of phenomenal binding and executive control. Along these connectivity backbones, SOHMs are proposed to implement turbo coding via loopy message-passing over predictive (autoencoding) networks, thus generating maximum a posteriori estimates as coherent vectors governing neural evolution, with alpha frequencies generating basic awareness, and cross-frequency phase-coupling within theta frequencies for access consciousness and volitional control. These dynamic cores of integrated information also function as global workspaces, centered on posterior cortices, but capable of being entrained with frontal cortices and interoceptive hierarchies, thus affording agentic causation. Integrated World Modeling Theory (IWMT) represents a synthetic approach to understanding minds that reveals compatibility between leading theories of consciousness, thus enabling inferential synergy.

Artificial intelligence and its natural limits

An argument with roots in ancient Greek philosophy claims that only humans are capable of a certain class of thought termed conceptual, as opposed to perceptual thought, which is common to humans, the higher animals, and some machines. We outline the most detailed modern version of this argument due to Mortimer Adler, who in the 1960s argued for the uniqueness of the human power of conceptual thought. He also admitted that if conceptual thought were ever manifested by machines, such an achievement would contradict his conclusion. We revisit Adler’s criterion in the light of the past five decades of artificial-intelligence (AI) research, and refine it in view of the classical definitions of perceptual and conceptual thought. We then examine two well-publicized examples of creative works (prose and art) produced by AI systems and show that evidence for conceptual thought appears to be lacking in them. Although clearer evidence for conceptual thought on the part of AI systems may arise in the near future, especially if the global neuronal workspace theory of consciousness prevails over its rival, integrated information theory, the question of whether AI systems can engage in conceptual thought appears to be still open.

Visual Functions Generating Conscious Seeing.

Visual functions are reviewed that coincide with conscious as opposed to unconscious vision. Four stages of vision are identified, going from the fully invisible, to subjectively invisible, unattended, and clearly visible. It is proposed that feature extraction, categorization, and some aspects of visual inference occur during full and subjective invisibility. Functions related to perceptual organization, such as grouping and figure-ground segregation, occur during inattention as well as full visibility. It is argued that perceptual organization is the function that is central to understanding the transition from unconscious to conscious seeing. It is discussed what this implies for theories of consciousness such as Recurrent Processing Theory, Higher Order Thought Theory, Integrated Information Theory, and Global Neuronal Workspace Theory.

Emotion in Chinese Words Could Not Be Extracted in Continuous Flash Suppression.

Previous studies have demonstrated the automatic vigilance effect for faces and pictures and have attributed it to the brain’s prioritized unconscious evaluation of early evolutionary stimuli that are critical to survival. Whether this effect exists for evolutionarily more recent stimuli, such as written words, has become the center of much debate. Apparently contradicting results have been reported in different languages, such as Hebrew, English, and Traditional Chinese (TC), with regard to the unconscious processing of emotional words in breaking continuous flash suppression (b-CFS). Our current study used two experiments (with two-character words or single-character words) to verify whether the emotional valence or the length of Simplified Chinese (SC) words would modulate conscious access in b-CFS. We failed to replicate the findings reported in Yang and Yeh (2011) using TC, but found that complex high-level emotional information could not be extracted from interocularly suppressed words regardless of their length. Our findings comply with the distinction between subliminal and preconscious states in Global Neuronal Workspace Theory and support the current notion that preconsciousness or partial awareness may be indispensable for high-level cognitive tasks such as reading comprehension.