Challenges for theories of consciousness: seeing or knowing, the missing ingredient and how to deal with panpsychism

Association of Bidirectional Network Cores in the Brain with Perceptual Awareness and Cognition

The brain comprises a complex network of interacting regions. To understand the roles and mechanisms of this intricate network, it is crucial to elucidate its structural features related to cognitive functions. Recent empirical evidence suggests that both feedforward and feedback signals are necessary for conscious perception, emphasizing the importance of subnetworks with bidirectional interactions. However, the link between such subnetworks and conscious perception remains unclear due to the complexity of brain networks. In this study, we propose a framework for extracting subnetworks with strong bidirectional interactions-termed the "cores" of a network-from brain activity. We applied this framework to resting-state and task-based human fMRI data from participants of both sexes to identify regions forming strongly bidirectional cores. We then explored the association of these cores with conscious perception and cognitive functions. We found that the extracted central cores predominantly included cerebral cortical regions rather than subcortical regions. Additionally, regarding their relation to conscious perception, we demonstrated that the cores tend to include regions previously reported to be affected by electrical stimulation that altered conscious perception, although the results are not statistically robust due to the small sample size. Furthermore, in relation to cognitive functions, based on a meta-analysis and comparison of the core structure with a cortical functional connectivity gradient, we found that the central cores were related to unimodal sensorimotor functions. The proposed framework provides novel insights into the roles of network cores with strong bidirectional interactions in conscious perception and unimodal sensorimotor functions.

The evolution of human-type consciousness - a by-product of mammalian innovation mechanism - a preliminary hypothesis

Human consciousness is often viewed as one of the pinnacles of evolution, with most theories positioning it as an upgrade of pre-existing cognitive skills. However, conscious perception, memory, action, and in some situations even decision-making, are often inferior-less complex, slower, and less accurate-than their nonconscious (subliminal) counterparts. The interface hypothesis challenges this perspective, proposing that human-type consciousness is not an advanced version of earlier cognitive capacities but a novel function that entered the arena of cognitive and operational processes and fundamentally changed its rules. According to this hypothesis, the neocortex emerged as part of an advanced innovation mechanism, where its unpredictable, chaotic activity is used to generate alternative patterns. The process of cropping these alternatives from the chaotic neocortex and mediating them to the constrained, goal-oriented, linear control system requires a serially functioning interface. Consciousness, it is suggested, arose as a byproduct or a side effect of this interface, eventually expanding its influence to a wide range of cognitive and operational functions. This perspective has significant implications for our understanding of human cognition, creativity, and the distinctive capacities of human consciousness, potentially bridging the gap between neuroscientific findings and phenomenological experiences of consciousness.

Human high-order thalamic nuclei gate conscious perception through the thalamofrontal loop

Human high-order thalamic nuclei activity is known to closely correlate with conscious states. However, it is not clear how those thalamic nuclei and thalamocortical interactions directly contribute to the transient process of human conscious perception. We simultaneously recorded stereoelectroencephalography data from the thalamic nuclei and prefrontal cortex (PFC), while patients with implanted electrodes performed a visual consciousness task. Compared with the ventral nuclei and PFC, the intralaminar and medial nuclei presented earlier and stronger consciousness-related activity. Transient thalamofrontal neural synchrony and cross-frequency coupling were both driven by the θ phase of the intralaminar and medial nuclei during conscious perception. The intralaminar and medial thalamic nuclei thus play a gate role to drive the activity of the PFC during the emergence of conscious perception.

Context-Sensitive Conscious Interpretation and Layer-5 Pyramidal Neurons in Multistable Perception

INTRODUCTION

There appears to be a fundamental difference between the two ways of how an object becomes perceptually experienced. One occurs when preconscious object-specifying sensory data processing crosses a certain threshold so that sensory constituents of object depiction become consciously experienced. The other occurs when the already consciously experienced sensory features of the object become interpreted as belonging to a certain visual object category. Surprisingly, experimental facts about neural markers of conscious access gathered so far do not allow us to distinguish mechanisms responsible for these two varieties.

METHODS

A cortical multicompartment layer-5 pyramidal neuron-based generic processing model is presented in order to conceptualize a possible mechanistic solution for the explanatory cul-de-sac. To support the argument, a review of pertinent research is compiled as associated with data from studies where physically invariant perceptual stimuli have underwent alternative interpretation(s) by the brain.

RESULTS

Recent developments in the newly emerging field of cellular psycho(physio)logy are introduced, offering a hypothetical solution for distinguishing the mechanisms subserving sensory content experience and conscious interpretation.

CONCLUSION

The multicompartment single cell-based mechanistic approach to brain process correlates of conscious perception appears to have an added value beyond the traditional inter-areal connectivity-based theoretical stances.

Unpacking the complexities of consciousness: Theories and reflections

As the field of consciousness science matures, the research agenda has expanded from an initial focus on the neural correlates of consciousness, to developing and testing theories of consciousness. Several theories have been put forward, each aiming to elucidate the relationship between consciousness and brain function. However, there is an ongoing, intense debate regarding whether these theories examine the same phenomenon. And, despite ongoing research efforts, it seems like the field has so far failed to converge around any single theory, and instead exhibits significant polarization. To advance this discussion, proponents of five prominent theories of consciousness-Global Neuronal Workspace Theory (GNWT), Higher-Order Theories (HOT), Integrated Information Theory (IIT), Recurrent Processing Theory (RPT), and Predictive Processing (PP)-engaged in a public debate in 2022, as part of the annual meeting of the Association for the Scientific Study of Consciousness (ASSC). They were invited to clarify the explananda of their theories, articulate the core mechanisms underpinning the corresponding explanations, and outline their foundational premises. This was followed by an open discussion that delved into the testability of these theories, potential evidence that could refute them, and areas of consensus and disagreement. Most importantly, the debate demonstrated that at this stage, there is more controversy than agreement between the theories, pertaining to the most basic questions of what consciousness is, how to identify conscious states, and what is required from any theory of consciousness. Addressing these core questions is crucial for advancing the field towards a deeper understanding and comparison of competing theories.

Why Uncertainty Is Essential for Consciousness: Local Prospect Theory vs. Predictive Processing

We present and develop local prospect theory (LPT), a novel framework for understanding consciousness, and, in particular, subjective experience and free will. While predictive processing (PP) theories model the brain as trying to optimize the accuracy of predictions, LPT sees uncertainty as an essential feature of conscious decision-making. This is achieved by creating a "local prospect"-a range of potential developments colored by subjective experience from which an agent can freely choose how to react. Drawing on global workspace theory, LPT conceptualizes consciousness as a self-maintaining process of circulating neural activation, creating a temporary working memory where thoughts and feelings coming from different brain modules enter into an asynchronous, non-linear interaction. This contrasts with unconscious processes, which operate automatically and deterministically. LPT proposes entropy-based measures, including the determination of actions by conditions and the breadth of prospect, to quantify the range of potential developments considered. This framework allows us to understand Buddhist practices and concepts, such as mindfulness, liberation from attachments, and meditation, which broaden consciousness and de-automatize reactions by reducing the influence of conditioning. The proposed prospect measure may be operationalized by indicators such as the variety of action, breadth of perception, and unpredictability of behavior, thus allowing for the empirical testing of the theory.

Association of bidirectional network cores in the brain with perceptual awareness and cognition

The brain comprises a complex network of interacting regions. To understand the roles and mechanisms of this intricate network, it is crucial to elucidate its structural features related to cognitive functions. Recent empirical evidence suggests that both feedforward and feedback signals are necessary for conscious perception, emphasizing the importance of subnetworks with bidirectional interactions. However, the link between such subnetworks and conscious perception remains unclear due to the complexity of brain networks. In this study, we propose a framework for extracting subnetworks with strong bidirectional interactions-termed the "cores" of a network-from brain activity. We applied this framework to resting-state and task-based human fMRI data from participants of both sexes to identify regions forming strongly bidirectional cores. We then explored the association of these cores with conscious perception and cognitive functions. We found that the extracted central cores predominantly included cerebral cortical regions rather than subcortical regions. Additionally, regarding their relation to conscious perception, we demonstrated that the cores tend to include regions previously reported to be affected by electrical stimulation that altered conscious perception, although the results are not statistically robust due to the small sample size. Furthermore, in relation to cognitive functions, based on a meta-analysis and comparison of the core structure with a cortical functional connectivity gradient, we found that the central cores were related to unimodal sensorimotor functions. The proposed framework provides novel insights into the roles of network cores with strong bidirectional interactions in conscious perception and unimodal sensorimotor functions.

Neural signatures of visual awareness independent of postperceptual processing

What are the neural processes associated with perceptual awareness that are distinct from preconscious sensory encoding and postperceptual processes such as reporting an experience? Using electroencephalography and a no-report visual masking paradigm, we manipulated stimulus visibility by varying the time between stimuli and masks in linear steps (17, 33, 50, 67, and 83 ms). Awareness increased nonlinearly, with stimuli never seen at the two shortest intervals, always seen at the two longest, and 50% seen at the intermediate interval. Separate report and no-report conditions were used to isolate awareness from task performance. Our results revealed a neural signal closely linked to perceptual awareness, independent of the task: a fronto-central event-related potential that we refer to as the N2 (~250 to 300 ms). Earlier event-related potential signals reflected the linear manipulation of stimulus strength, while later signals like P3b and temporal generalization of decoding were tied to task performance, appearing only in the report condition. Taken together, these findings inform current debates regarding theories of consciousness and offer new avenues for exploring the neural mechanisms supporting conscious processing.

Panpsychism and dualism in the science of consciousness

A resurgence of panpsychism and dualism is a matter of ongoing debate in modern neuroscience. Although metaphysically hostile, panpsychism and dualism both persist in the science of consciousness because the former is proposed as a straightforward answer to the problem of integrating consciousness into the fabric of physical reality, whereas the latter proposes a simple solution to the problem of free will by endowing consciousness with causal power as a prerequisite for moral responsibility. I take the Integrated Information Theory (IIT) as a paradigmatic exemplar of a theory of consciousness (ToC) that makes its commitments to panpsychism and dualism within a unified framework. These features are not, however, unique for IIT. Many ToCs are implicitly prone to some degree of panpsychism whenever they strive to propose a universal definition of consciousness, associated with one or another known phenomenon. Yet, those ToCs that can be characterized as strongly emergent are at risk of being dualist. A remedy against both covert dualism and uncomfortable corollaries of panpsychism can be found in the evolutionary theory of life, called here "bioprotopsychism" and generalized in terms of autopoiesis and the free energy principle. Bioprotopsychism provides a biologically inspired basis for a minimalist approach to consciousness via the triad "chemotaxis-efference copy mechanism-counterfactual active inference" by associating the stream of weakly emergent conscious states with an amount of information (best guesses) of the brain, engaged in unconscious predictive processing.

Two Levels of Integrated Information Theory: From Autonomous Systems to Conscious Life

Integrated Information Theory (IIT) is one of the most prominent candidates for a theory of consciousness, although it has received much criticism for trying to live up to expectations. Based on the relevance of three issues generalized from the developments of IITs, we have summarized the main ideas of IIT into two levels. At the second level, IIT claims to be strictly anchoring consciousness, but the first level on which it is based is more about autonomous systems or systems that have reached some other critical complexity. In this paper, we argue that the clear gap between the two levels of explanation of IIT has led to these criticisms and that its panpsychist tendency plays a crucial role in this. We suggest that the problems of IIT are far from being "pseudoscience", and by adding more necessary elements, when the first level is combined with the second level, IIT can genuinely move toward an appropriate theory of consciousness that can provide necessary and sufficient interpretations.

Familiarity Alters the Bandwidth of Perceptual Awareness

Results from paradigms like change blindness and inattentional blindness indicate that observers are unaware of numerous aspects of the visual world. However, intuition suggests that perceptual experience is richer than these results indicate. Why does it feel like we see so much when the data suggests we see so little? One possibility stems from the fact that experimental studies always present observers with stimuli that they have never seen before. Meanwhile, when forming intuitions about perceptual experience, observers reflect on their experiences with scenes with which they are highly familiar (e.g., their office). Does prior experience with a scene change the bandwidth of perceptual awareness? Here, we asked if observers were better at noticing alterations to the periphery in familiar scenes compared with unfamiliar scenes. We found that observers noticed changes to the periphery more frequently with familiar stimuli. Signal detection theoretic analyses revealed that when observers are unfamiliar with a stimulus, they are less sensitive at noticing (d') and are more conservative in their response criterion (c). Taken together, these results suggest that prior knowledge expands the bandwidth of perceptual awareness. It should be stressed that these results challenge the widely held idea that prior knowledge fills in perception. Overall, these findings highlight how prior knowledge plays an important role in determining the limits of perceptual experience and is an important factor to consider when attempting to reconcile the tension between empirical observation and personal introspection.

Infants' top-down perceptual modulation is specific to own-race faces

Recent studies have revealed the influence of higher-level cognitive systems in modulating perceptual processing (top-down perceptual modulation) in infancy. However, more research is needed to understand how top-down processes in infant perception contribute to early perceptual development. To this end, this study examined infants' top-down perception of own- and other-race faces to reveal whether top-down modulation is linked to the emergence of perceptual specialization. Infants first learned an association between a sound and faces, with the race of the faces manipulated between groups (own race vs. other race). We then tested infants' face perception across various levels of perceptual difficulty (manipulated by presentation duration) and indexed top-down perception by the change in perception when infants heard the sound previously associated with the face (predictive sound) versus an irrelevant sound. Infants exhibited top-down face perception for own-race faces (Experiment 1). However, we present new evidence that infants did not show evidence of top-down modulation for other-race faces (Experiment 2), suggesting an experience-based specificity of this capacity with more effective top-down modulation in familiar perceptual contexts. In addition, we ruled out the possibility that this face race effect was due to differences in infants' associative learning of the sound and faces between the two groups. This work has important implications for understanding the mechanisms supporting perceptual development and how they relate to top-down perception in infancy.

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.

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.

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.

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.

The involvement of the human prefrontal cortex in the emergence of visual awareness

Exploring the neural mechanisms of awareness is a fundamental task of cognitive neuroscience. There is an ongoing dispute regarding the role of the prefrontal cortex (PFC) in the emergence of awareness, which is partially raised by the confound between report- and awareness-related activity. To address this problem, we designed a visual awareness task that can minimize report-related motor confounding. Our results show that saccadic latency is significantly shorter in the aware trials than in the unaware trials. Local field potential (LFP) data from six patients consistently show early (200-300ms) awareness-related activity in the PFC, including event-related potential and high-gamma activity. Moreover, the awareness state can be reliably decoded by the neural activity in the PFC since the early stage, and the neural pattern is dynamically changed rather than being stable during the representation of awareness. Furthermore, the enhancement of dynamic functional connectivity, through the phase modulation at low frequency, between the PFC and other brain regions in the early stage of the awareness trials may explain the mechanism of conscious access. These results indicate that the PFC is critically involved in the emergence of awareness.

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.

Neural electrophysiological correlates of detection and identification awareness

Humans have conscious experiences of the events in their environment. Previous research from electroencephalography (EEG) has shown visual awareness negativity (VAN) at about 200 ms to be a neural correlate of consciousness (NCC). However, when considering VAN as an NCC, it is important to explore which particular experiences are associated with VAN. Recent research proposes that VAN is an NCC of lower-level experiences (detection) rather than higher-level experiences (identification). However, previous results are mixed and have several limitations. In the present study, the stimulus was a ring with a Gabor patch tilting either left or right. On each trial, subjects rated their awareness on a three-level perceptual awareness scale that captured both detection (something vs. nothing) and identification (identification vs. something). Separate staircases were used to adjust stimulus opacity to the detection threshold and the identification threshold. Bayesian linear mixed models provided extreme evidence (BF10 = 131) that VAN was stronger at the detection threshold than at the identification threshold. Mean VAN decreased from [Formula: see text]2.12 microV [[Formula: see text]2.86, [Formula: see text]1.42] at detection to [Formula: see text]0.46 microV [[Formula: see text]0.79, [Formula: see text]0.11] at identification. These results strongly support the claim that VAN is an NCC of lower-level experiences of seeing something rather than of higher-level experiences of specific properties of the stimuli. Thus, results are consistent with recurrent processing theory in that phenomenal visual consciousness is reflected by VAN. Further, results emphasize that it is important to consider the level of experience when searching for NCC.

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.

Visual Perception Is Highly Flexible and Context Dependent in Young Infants: A Case of Top-Down-Modulated Motion Perception

Top-down modulation is an essential cognitive component in human perception. Despite mounting evidence of top-down perceptual modulation in adults, it is largely unknown whether infants can engage in this cognitive function. Here, we examined top-down modulation of motion perception in 6- to 8-month-old infants (recruited in North America) via their smooth-pursuit eye movements. In four experiments, we demonstrated that infants' perception of motion direction can be flexibly shaped by briefly learned predictive cues when no coherent motion is available. The current findings present a novel insight into infant perception and its development: Infant perceptual systems respond to predictive signals engendered from higher-level learning systems, leading to a flexible and context-dependent modulation of perception. This work also suggests that the infant brain is sophisticated, interconnected, and active when placed in a context in which it can learn and predict.

Fronto-parietal networks shape human conscious report through attention gain and reorienting

How do attention and consciousness interact in the human brain? Rival theories of consciousness disagree on the role of fronto-parietal attentional networks in conscious perception. We recorded neural activity from 727 intracerebral contacts in 13 epileptic patients, while they detected near-threshold targets preceded by attentional cues. Clustering revealed three neural patterns: first, attention-enhanced conscious report accompanied sustained right-hemisphere fronto-temporal activity in networks connected by the superior longitudinal fasciculus (SLF) II-III, and late accumulation of activity (>300 ms post-target) in bilateral dorso-prefrontal and right-hemisphere orbitofrontal cortex (SLF I-III). Second, attentional reorienting affected conscious report through early, sustained activity in a right-hemisphere network (SLF III). Third, conscious report accompanied left-hemisphere dorsolateral-prefrontal activity. Task modeling with recurrent neural networks revealed multiple clusters matching the identified brain clusters, elucidating the causal relationship between clusters in conscious perception of near-threshold targets. Thus, distinct, hemisphere-asymmetric fronto-parietal networks support attentional gain and reorienting in shaping human conscious experience.

Not with a “zap” but with a “beep”: measuring the origins of perinatal experience

When does the mind begin? Infant psychology is mysterious in part because we cannot remember our first months of life, nor can we directly communicate with infants. Even more speculative is the possibility of mental life prior to birth. The question of when consciousness, or subjective experience, begins in human development thus remains incompletely answered, though boundaries can be set using current knowledge from developmental neurobiology and recent investigations of the perinatal brain. Here, we offer our perspective on how the development of a sensory perturbational complexity index (sPCI) based on auditory ("beep-and-zip"), visual ("flash-and-zip"), or even olfactory ("sniff-and-zip") cortical perturbations in place of electromagnetic perturbations ("zap-and-zip") might be used to address this question. First, we discuss recent studies of perinatal cognition and consciousness using techniques such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and, in particular, magnetoencephalography (MEG). While newborn infants are the archetypal subjects for studying early human development, researchers may also benefit from fetal studies, as the womb is, in many respects, a more controlled environment than the cradle. The earliest possible timepoint when subjective experience might begin is likely the establishment of thalamocortical connectivity at 26 weeks gestation, as the thalamocortical system is necessary for consciousness according to most theoretical frameworks. To infer at what age and in which behavioral states consciousness might emerge following the initiation of thalamocortical pathways, we advocate for the development of the sPCI and similar techniques, based on EEG, MEG, and fMRI, to estimate the perinatal brain's state of consciousness.

Consciousness, Memory, and the Human Self: Commentary on "Consciousness as a Memory System" by Budson et al (2022)

Philosophical theories have attempted to shed light on the intricate relationships between consciousness and memory since long before this became a major theme in psychology and neuroscience. In the December 2022 issue of Cognitive and Behavioral Neurology , Budson, Richman, and Kensinger (2022) introduced a comprehensive theoretical framework pertaining to the origins of consciousness in relation to the memory system, its implications on our real-time perception of the world, and the neuroanatomical correlates underlying these phenomena. Throughout their paper, Budson et al (2022) focus on their theory's explanatory value regarding several clinical syndromes and experimental findings. In this commentary, we first summarize the theory presented by Budson and colleagues (2022). Then, we suggest a complementary approach of studying the relationships between consciousness and memory through the concept of the human self and its protracted representation through time (so-called mental time travel). Finally, we elaborate on Budson and colleagues' (2022) neuroanatomical explanation to their theory and suggest that adding the concepts of brain networks and cortical gradients may contribute to their theory's interpretability.

Blurred Lines: Memory, Perceptions, and Consciousness: Commentary on "Consciousness as a Memory System" by Budson et al (2022)

In the previous issue, Budson, Richman, and Kensinger (2022) put forth the intriguing proposal that consciousness may have evolved from the episodic memory system. In addition to providing a possible evolutionary trajectory for consciousness, I believe that viewing consciousness as an extension of memory in this way is particularly useful for understanding some of the puzzling temporal complexities that are inherent to consciousness. For example, due to neural transmission delays, our conscious experience must necessarily lag the outside world, which creates a paradox for both conscious perception (Do we see the past, rather than the present?) and action (How can we make rapid decisions if it takes so long to become conscious of something?). These paradoxes can be elegantly solved by treating consciousness as a memory system. Finally, the proposal put forth by Budson and colleagues (2022) aligns with the emerging perspective that consciousness, like memory, represents a narrative time line of events rather than any single instant. However, I believe that this conceptualization can be further extended to include not only the past, but also the future. In this way, consciousness can be provocatively viewed as the remembered past, present, and future.

Assessing awareness in severe Alzheimer's disease

There is an urgent need to understand the nature of awareness in people with severe Alzheimer's disease (AD) to ensure effective person-centered care. Objective biomarkers of awareness validated in other clinical groups (e.g., anesthesia, minimally conscious states) offer an opportunity to investigate awareness in people with severe AD. In this article we demonstrate the feasibility of using Transcranial magnetic stimulation (TMS) combined with EEG, event related potentials (ERPs) and fMRI to assess awareness in severe AD. TMS-EEG was performed in six healthy older controls and three people with severe AD. The perturbational complexity index (PCIST) was calculated as a measure of capacity for conscious awareness. People with severe AD demonstrated a PCIST around or below the threshold for consciousness, suggesting reduced capacity for consciousness. ERPs were recorded during a visual perception paradigm. In response to viewing faces, two patients with severe AD provisionally demonstrated similar visual awareness negativity to healthy controls. Using a validated fMRI movie-viewing task, independent component analysis in two healthy controls and one patient with severe AD revealed activation in auditory, visual and fronto-parietal networks. Activation patterns in fronto-parietal networks did not significantly correlate between the patient and controls, suggesting potential differences in conscious awareness and engagement with the movie. Although methodological issues remain, these results demonstrate the feasibility of using objective measures of awareness in severe AD. We raise a number of challenges and research questions that should be addressed using these biomarkers of awareness in future studies to improve understanding and care for people with severe AD.

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.

From the origins to the stream of consciousness and its neural correlates

There are now dozens of very different theories of consciousness, each somehow contributing to our understanding of its nature. The science of consciousness needs therefore not new theories but a general framework integrating insights from those, yet not making it a still-born "Frankenstein" theory. First, the framework must operate explicitly on the stream of consciousness, not on its static description. Second, this dynamical account must also be put on the evolutionary timeline to explain the origins of consciousness. The Cognitive Evolution Theory (CET), outlined here, proposes such a framework. This starts with the assumption that brains have primarily evolved as volitional subsystems of organisms, inherited from primitive (fast and random) reflexes of simplest neural networks, only then resembling error-minimizing prediction machines. CET adopts the tools of critical dynamics to account for metastability, scale-free avalanches, and self-organization which are all intrinsic to brain dynamics. This formalizes the stream of consciousness as a discrete (transitive, irreflexive) chain of momentary states derived from critical brain dynamics at points of phase transitions and mapped then onto a state space as neural correlates of a particular conscious state. The continuous/discrete dichotomy appears naturally between the brain dynamics at the causal level and conscious states at the phenomenal level, each volitionally triggered from arousal centers of the brainstem and cognitively modulated by thalamocortical systems. Their objective observables can be entropy-based complexity measures, reflecting the transient level or quantity of consciousness at that moment.

Decoding perceptual awareness across the brain with a no-report fMRI masking paradigm

Does perceptual awareness arise within the sensory regions of the brain or within higher-level regions (e.g., the frontal lobe)? To answer this question, researchers traditionally compare neural activity when observers report being aware versus being unaware of a stimulus. However, it is unclear whether the resulting activations are associated with the conscious perception of the stimulus or the post-perceptual processes associated with reporting that stimulus. To address this limitation, we used both report and no-report conditions in a visual masking paradigm while participants were scanned using functional MRI (fMRI). We found that the overall univariate response to visible stimuli in the frontal lobe was robust in the report condition but disappeared in the no-report condition. However, using multivariate patterns, we could still decode in both conditions whether a stimulus reached conscious awareness across the brain, including in the frontal lobe. These results help reconcile key discrepancies in the recent literature and provide a path forward for identifying the neural mechanisms associated with perceptual awareness.

Early and late electrophysiological correlates of gradual perceptual awareness in- and outside the Attentional Blink window

There is an ongoing debate on the neural correlates of consciousness (NCC) in the attentional blink (AB). Theoretical accounts propose that NCC during the attentional blink occur late in the processing hierarchy and that this quality is specific to the AB. We investigated this question by recording event-related potentials during an AB experiment with faces as T2. We analyzed ERPs to T2 stimuli inside (short lag) and outside (long lag) the AB window after carefully calibrating T2 stimuli to ensure equal visibility ratings across lags. We found that the N170, the visual awareness negativity (VAN), and the P3b showed an increased amplitude for seen compared to unseen face stimuli regardless of stimulus lag and that all these components scale linearly with subjective visibility. These findings suggest similar early and late mechanisms of graded perceptual awareness within and outside the AB across perceptual (N170, VAN) and post-perceptual (P3b) processing stages.

The why of the phenomenal aspect of consciousness: Its main functions and the mechanisms underpinning it

What distinguishes conscious information processing from other kinds of information processing is its phenomenal aspect (PAC), the-what-it-is-like for an agent to experience something. The PAC supplies the agent with a sense of self, and informs the agent on how its self is affected by the agent's own operations. The PAC originates from the activity that attention performs to detect the state of what I define "the self" (S). S is centered and develops on a hierarchy of innate and acquired values, and is primarily expressed via the central and peripheral nervous systems; it maps the agent's body and cognitive capacities, and its interactions with the environment. The detection of the state of S by attention modulates the energy level of the organ of attention (OA), i.e., the neural substrate that underpins attention. This modulation generates the PAC. The PAC can be qualified according to five dimensions: qualitative, quantitative, hedonic, temporal and spatial. Each dimension can be traced back to a specific feature of the modulation of the energy level of the OA.

Bidirectionally connected cores in a mouse connectome: towards extracting the brain subnetworks essential for consciousness

Where in the brain consciousness resides remains unclear. It has been suggested that the subnetworks supporting consciousness should be bidirectionally (recurrently) connected because both feed-forward and feedback processing are necessary for conscious experience. Accordingly, evaluating which subnetworks are bidirectionally connected and the strength of these connections would likely aid the identification of regions essential to consciousness. Here, we propose a method for hierarchically decomposing a network into cores with different strengths of bidirectional connection, as a means of revealing the structure of the complex brain network. We applied the method to a whole-brain mouse connectome. We found that cores with strong bidirectional connections consisted of regions presumably essential to consciousness (e.g. the isocortical and thalamic regions, and claustrum) and did not include regions presumably irrelevant to consciousness (e.g. cerebellum). Contrarily, we could not find such correspondence between cores and consciousness when we applied other simple methods that ignored bidirectionality. These findings suggest that our method provides a novel insight into the relation between bidirectional brain network structures and consciousness.

Consciousness as the Temporal Propagation of Information

Our ability to understand the mind and its relation to the body is highly dependent on the way we define consciousness and the lens through which we study it. We argue that looking at conscious experience from an information-theory perspective can help obtain a unified and parsimonious account of the mind. Today's dominant models consider consciousness to be a specialized function of the brain characterized by a discrete neural event. Against this background, we consider subjective experience through information theory, presenting consciousness as the propagation of information from the past to the future. We examine through this perspective major characteristics of consciousness. We demonstrate that without any additional assumptions, temporal continuity in perception can explain the emergence of volition, subjectivity, higher order thoughts, and body boundaries. Finally, we discuss the broader implications for the mind-body question and the appeal of embodied cognition.

Decoding internally generated transitions of conscious contents in the prefrontal cortex without subjective reports

A major debate about the neural correlates of conscious perception concerns its cortical organization, namely, whether it includes the prefrontal cortex (PFC), which mediates executive functions, or it is constrained within posterior cortices. It has been suggested that PFC activity during paradigms investigating conscious perception is conflated with post-perceptual processes associated with reporting the contents of consciousness or feedforward signals originating from exogenous stimulus manipulations and relayed via posterior cortical areas. We addressed this debate by simultaneously probing neuronal populations in the rhesus macaque (Macaca mulatta) PFC during a no-report paradigm, capable of instigating internally generated transitions in conscious perception, without changes in visual stimulation. We find that feature-selective prefrontal neurons are modulated concomitantly with subjective perception and perceptual suppression of their preferred stimulus during both externally induced and internally generated changes in conscious perception. Importantly, this enables reliable single-trial, population decoding of conscious contents. Control experiments confirm significant decoding of stimulus contents, even when oculomotor responses, used for inferring perception, are suppressed. These findings suggest that internally generated changes in the contents of conscious visual perception are reliably reflected within the activity of prefrontal populations in the absence of volitional reports or changes in sensory input.

The role of the prefrontal cortex in conscious perception is debated because of its involvement in task relevant behaviour, such as subjective perceptual reports. Here, the authors show that prefrontal activity in rhesus macaques correlates with subjective perception and the contents of consciousness can be decoded from prefrontal population activity even without reports.

Indicators and criteria of consciousness: ethical implications for the care of behaviourally unresponsive patients

BACKGROUND

Assessing consciousness in other subjects, particularly in non-verbal and behaviourally disabled subjects (e.g., patients with disorders of consciousness), is notoriously challenging but increasingly urgent. The high rate of misdiagnosis among disorders of consciousness raises the need for new perspectives in order to inspire new technical and clinical approaches.

MAIN BODY

We take as a starting point a recently introduced list of operational indicators of consciousness that facilitates its recognition in challenging cases like non-human animals and Artificial Intelligence to explore their relevance to disorders of consciousness and their potential ethical impact on the diagnosis and healthcare of relevant patients. Indicators of consciousness mean particular capacities that can be deduced from observing the behaviour or cognitive performance of the subject in question (or from neural correlates of such performance) and that do not define a hard threshold in deciding about the presence of consciousness, but can be used to infer a graded measure based on the consistency amongst the different indicators. The indicators of consciousness under consideration offer a potential useful strategy for identifying and assessing residual consciousness in patients with disorders of consciousness, setting the theoretical stage for an operationalization and quantification of relevant brain activity.

CONCLUSIONS

Our heuristic analysis supports the conclusion that the application of the identified indicators of consciousness to its disorders will likely inspire new strategies for assessing three very urgent issues: the misdiagnosis of disorders of consciousness; the need for a gold standard in detecting consciousness and diagnosing its disorders; and the need for a refined taxonomy of disorders of consciousness.

Inattentive Perception, Time, and the Incomprehensibility of Consciousness

Cerebral energy supply is insufficient to support continuous neuronal processing of the plethora of time-constant objects that we are aware of. As a result, the brain is forced to limit processing resources to (the most relevant) cases of change. The neuronally generated world is thus temporally discontinuous. This parallels the fact that, in all relevant microscopic fundamental equations of nature, temporal change plays a dominant role. When a scientist calculates a "solution" to such an equation, integration over time is an essential step. The present Hypothesis expresses that the step from neuronal activity to phenomenal content of consciousness is reflective of a (phenomenal) "solution:" the main source of the incomprehensibility of consciousness is proposed to result from the introduction of phenomenal time-constant entities. These are "filled-in" via integration, even though neuronal data only exists for changes to these entities. In this way, a temporally continuous picture of the world phenomenally appears. Qualia are "initial conditions," which are required for integration and cannot be deduced from present data. Phenomenal "identity" (vs. "high similarity") is related to qualia. Inattentive visual perception, which is only rarely investigated, offers insights into these relationships. Introspectively, unattended vision appears rich because percepts are cumulated over long time spans, whereas attentive perception relies purely on present neuronal signals. The present Hypothesis is that a brief neuronal activity can signify long-lasting and constant phenomenal content of consciousness. Experimental support is presented that comes from discrepancies between neuronal activity and perception: transient neuronal responses to sustained stimuli, "filling-in," change blindness, identity vs. close resemblance.

The Neural Correlates of Access Consciousness and Phenomenal Consciousness Seem to Coincide and Would Correspond to a Memory Center, an Activation Center and Eight Parallel Convergence Centers

An increasing number of authors suggest that the neural correlates of consciousness (NCC) have no selective, executive, or metacognitive function. It is believed that attention unconsciously selects the contents that will become conscious. Consciousness would have only the fundamental function of transforming the selected contents into a format easily used by high-level processors, such as working memory, language, or autobiographical memory. According to Dehaene, the neural correlates (NC) of access consciousness (AC; cognitive consciousness) constitute a widespread network in the frontal, parietal, and temporal cortices. While Tononi localized the correlates of phenomenal consciousness (PC; subjective consciousness) to a posterior “hot zone” in the temporo-parietal cortex. A careful examination of the works of these two groups leads to the conclusion that the correlates of access and PC coincide. The two consciousnesses are therefore two faces of the same single consciousness with both its cognitive and subjective contents. A review of the literature of the pathology called “neglect” confirms that the common correlates include 10: a memory center, an activation center, and eight parallel centers. From study of the “imagery” it can be deduced that these eight parallel centers would operate as points of convergence in the third person linking the respective eight sensory-motor-emotional areas activated by external perceptions and the corresponding memories of these perceptions deposited in the memory center. The first four centers of convergence appear in the most evolved fish and gradually reach eight in humans.

From internal models toward metacognitive AI

In several papers published in Biological Cybernetics in the 1980s and 1990s, Kawato and colleagues proposed computational models explaining how internal models are acquired in the cerebellum. These models were later supported by neurophysiological experiments using monkeys and neuroimaging experiments involving humans. These early studies influenced neuroscience from basic, sensory-motor control to higher cognitive functions. One of the most perplexing enigmas related to internal models is to understand the neural mechanisms that enable animals to learn large-dimensional problems with so few trials. Consciousness and metacognition-the ability to monitor one's own thoughts, may be part of the solution to this enigma. Based on literature reviews of the past 20 years, here we propose a computational neuroscience model of metacognition. The model comprises a modular hierarchical reinforcement-learning architecture of parallel and layered, generative-inverse model pairs. In the prefrontal cortex, a distributed executive network called the "cognitive reality monitoring network" (CRMN) orchestrates conscious involvement of generative-inverse model pairs in perception and action. Based on mismatches between computations by generative and inverse models, as well as reward prediction errors, CRMN computes a "responsibility signal" that gates selection and learning of pairs in perception, action, and reinforcement learning. A high responsibility signal is given to the pairs that best capture the external world, that are competent in movements (small mismatch), and that are capable of reinforcement learning (small reward-prediction error). CRMN selects pairs with higher responsibility signals as objects of metacognition, and consciousness is determined by the entropy of responsibility signals across all pairs. This model could lead to new-generation AI, which exhibits metacognition, consciousness, dimension reduction, selection of modules and corresponding representations, and learning from small samples. It may also lead to the development of a new scientific paradigm that enables the causal study of consciousness by combining CRMN and decoded neurofeedback.

V1 as an egocentric cognitive map

We typically distinguish between V1 as an egocentric perceptual map and the hippocampus as an allocentric cognitive map. In this article, we argue that V1 also functions as a post-perceptual egocentric cognitive map. We argue that three well-documented functions of V1, namely (i) the estimation of distance, (ii) the estimation of size, and (iii) multisensory integration, are better understood as post-perceptual cognitive inferences. This argument has two important implications. First, we argue that V1 must function as the neural correlates of the visual perception/cognition distinction and suggest how this can be accommodated by V1's laminar structure. Second, we use this insight to propose a low-level account of visual consciousness in contrast to mid-level accounts (recurrent processing theory; integrated information theory) and higher-level accounts (higher-order thought; global workspace theory). Detection thresholds have been traditionally used to rule out such an approach, but we explain why it is a mistake to equate visibility (and therefore the presence/absence of visual experience) with detection thresholds.

Minimal physicalism as a scale-free substrate for cognition and consciousness

Theories of consciousness and cognition that assume a neural substrate automatically regard phylogenetically basal, nonneural systems as nonconscious and noncognitive. Here, we advance a scale-free characterization of consciousness and cognition that regards basal systems, including synthetic constructs, as not only informative about the structure and function of experience in more complex systems but also as offering distinct advantages for experimental manipulation. Our "minimal physicalist" approach makes no assumptions beyond those of quantum information theory, and hence is applicable from the molecular scale upwards. We show that standard concepts including integrated information, state broadcasting via small-world networks, and hierarchical Bayesian inference emerge naturally in this setting, and that common phenomena including stigmergic memory, perceptual coarse-graining, and attention switching follow directly from the thermodynamic requirements of classical computation. We show that the self-representation that lies at the heart of human autonoetic awareness can be traced as far back as, and serves the same basic functions as, the stress response in bacteria and other basal systems.

Perceptual awareness negativity: a physiological correlate of sensory consciousness

Much research on the neural correlates of consciousness (NCC) has focused on two evoked potentials, the P3b and the visual or auditory awareness negativity (VAN, AAN). Surveying a broad range of recent experimental evidence, we find that repeated failures to observe the P3b during conscious perception eliminate it as a putative NCC. Neither the VAN nor the AAN have been dissociated from consciousness; furthermore, a similar neural signal correlates with tactile consciousness. These awareness negativities can be maximal contralateral to the evoking stimulus, are likely generated in underlying sensory cortices, and point to the existence of a generalized perceptual awareness negativity (PAN) reflecting the onset of sensory consciousness.

Deep learning and the Global Workspace Theory

Recent advances in deep learning have allowed artificial intelligence (AI) to reach near human-level performance in many sensory, perceptual, linguistic, and cognitive tasks. There is a growing need, however, for novel, brain-inspired cognitive architectures. The Global Workspace Theory (GWT) refers to a large-scale system integrating and distributing information among networks of specialized modules to create higher-level forms of cognition and awareness. We argue that the time is ripe to consider explicit implementations of this theory using deep-learning techniques. We propose a roadmap based on unsupervised neural translation between multiple latent spaces (neural networks trained for distinct tasks, on distinct sensory inputs and/or modalities) to create a unique, amodal Global Latent Workspace (GLW). Potential functional advantages of GLW are reviewed, along with neuroscientific implications.

Anesthetics and plants: no pain, no brain, and therefore no consciousness

Plants have a rich variety of interactions with their environment, including adaptive responses mediated by electrical signaling. This has prompted claims that information processing in plants is similar to that in animals and, hence, that plants are conscious, intelligent organisms. In several recent reports, the facts that general anesthetics cause plants to lose their sensory responses and behaviors have been taken as support for such beliefs. These lipophilic substances, however, alter multiple molecular, cellular, and systemic functions in almost every organism. In humans and other animals with complex brains, they eliminate the experience of pain and disrupt consciousness. The question therefore arises: do plants feel pain and have consciousness? In this review, we discuss what can be learned from the effects of anesthetics in plants. For this, we describe the mechanisms and structural prerequisites for pain sensations in animals and show that plants lack the neural anatomy and all behaviors that would indicate pain. By explaining the ubiquitous and diverse effects of anesthetics, we discuss whether these substances provide any empirical or logical evidence for "plant consciousness" and whether it makes sense to study the effects of anesthetics on plants for this purpose. In both cases, the answer is a resounding no.

Anaesthetics and plants: from sensory systems to cognition-based adaptive behaviour

Plants are not only sensitive to exogenous anaesthetics, but they also produce multitudes of endogenous substances, especially when stressed, that often have anaesthetic and anelgesic properties when applied to both humans and animals. Moreover, plants rely on neurotransmitters and their receptors for cell-cell communication and integration in a similar fashion to the use of neural systems in animals and humans. Plants also use their plant-specific sensory systems and neurotransmitter-based communication, including long-distance action potentials, to manage stress via cognition-like plant-specific behaviour and adaptation.

Dissociating neural correlates of consciousness and task relevance during auditory processing

In recent years, several ERP components have been identified as potential neural correlates of consciousness (NCC), including early negativities and late positivities. Based on experiments in the visual modality, it has recently been shown that awareness is often confounded with reporting it, possibly overestimating the NCC. It is unknown whether similar constraints also exist in the auditory modality. In order to address this gap, we presented spoken words in a sustained inattentional deafness paradigm. Electrophysiological responses were obtained in three physically identical experimental conditions that differed only with respect to the participants' instructions. Participants were either left uninformed or informed about the presence of spoken words while confronted with an auditory distractor task (U/I condition), informed about the words while exposed to the same task as before (I condition), or requested to respond to the now task-relevant speech stimuli (TR condition). After completion of the U/I condition, only informed participants reported awareness of the words. In ERPs, awareness of words in the U/I and I condition was accompanied by an anterior auditory awareness negativity (AAN). Only when stimuli were task-relevant, i.e., during the TR condition, late positivities emerged. Taken together, these results indicate that early negativities but not late positivities index awareness across sensory modalities. Thus, they provide evidence for a recurrent processing framework, which highlights the importance of early sensory processing in conscious perception.

Science-Driven Societal Transformation, Part I: Worldview

Humanity faces serious social and environmental problems, including climate change and biodiversity loss. Increasingly, scientists, global policy experts, and the general public conclude that incremental approaches to reduce risk are insufficient and transformative change is needed across all sectors of society. However, the meaning of transformation is still unsettled in the literature, as is the proper role of science in fostering it. This paper is the first in a three-part series that adds to the discussion by proposing a novel science-driven research-and-development program aimed at societal transformation. More than a proposal, it offers a perspective and conceptual framework from which societal transformation might be approached. As part of this, it advances a formal mechanics with which to model and understand self-organizing societies of individuals. While acknowledging the necessity of reform to existing societal systems (e.g., governance, economic, and financial systems), the focus of the series is on transformation understood as systems change or systems migration—the de novo development of and migration to new societal systems. The series provides definitions, aims, reasoning, worldview, and a theory of change, and discusses fitness metrics and design principles for new systems. This first paper proposes a worldview, built using ideas from evolutionary biology, complex systems science, cognitive sciences, and information theory, which is intended to serve as the foundation for the R&D program. Subsequent papers in the series build on the worldview to address fitness metrics, system design, and other topics.