The question of the richness (or sparseness) of conscious experience has evoked ongoing debate and discussion. Claims for both richness and sparseness are supported by empirical data, yet they are often indirect, and alternative explanations have been put forward. Recently, it has been suggested that current experimental methods limit participants' responses, thereby preventing researchers from assessing the actual richness of perception. Instead, free verbal reports were presented as a possible way to overcome this limitation. As part of this approach, a novel paradigm of freely reported words was developed using a new metric, intersubjective agreement (IA), with experimental results interpreted as capturing aspects of conscious perception. Here, we challenge the validity of freely reported words as a tool for studying the richness of conscious experience. We base our claims on two studies (each composed of three experiments), where we manipulated the richness of percepts and tested whether IA changed accordingly. Five additional control experiments were conducted to validate the experimental logic and examine alternative explanations. Our results suggest otherwise, presenting four challenges to the free verbal report paradigm: first, impoverished stimuli did not evoke lower IA scores. Second, the IA score was correlated with word frequency in English. Third, the original positive relationship between IA scores and rated confidence was not found in any of the six experiments. Fourth, a high rate of nonexisting words was found, some of which described items that matched the gist of the scene but did not appear in the image. We conclude that a metric based on freely reported words might be better explained by vocabulary conventions and gist-based reports than by capturing the richness of perception.

The role of the parietal cortex in perceptual awareness and in resolving perceptual ambiguity is unsettled. Early influential transcranial magnetic stimulation studies have revealed differences in conscious perception following parietal stimulation, fuelling the notion that parietal cortex causally contributes to resolving perceptual ambiguity. However, central to this conclusion is the reliability of the method employed. Several prior studies have revealed opposing effects, such as shortening, lengthening, or no effect on multistable perceptual transitions following parietal stimulation. Here we addressed the reliability of continuous theta-burst stimulation (cTBS) on parietal cortex on the perception of bistable stimuli. We conducted three cTBS experiments that were matched to prior experiments in terms of stimuli, stimulation protocol, and target site, and used a higher number of participants. None of our cTBS experiments replicated prior cTBS results. The only experiment using individual functional localizers led to weak effects, while the two others led to null results. Individual variability of motor cortex cTBS did not predict parietal cTBS effects. In view of recent reports of highly variable cTBS effects over motor cortex, our results suggest that cTBS is particularly unreliable in modulating bistable perception when applied over parietal cortex.

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

A central project for the neuroscience of consciousness is to reveal the neural basis of consciousness. For the past 20-odd years, this project has been conceptualized in terms of minimal sufficiency. Recently, a number of authors have suggested that the project is better conceived in mechanistic terms as the search for difference-makers. In this paper, I (i) motivate this mechanistic alternative to minimal sufficiency, (ii) develop it further by clarifying debates about the prospects of leveraging mutual manipulability to distinguish constitutive difference-makers from those that are merely causal, and (iii) explore the implications this has for recent debates concerning the status of the prefrontal cortex. I argue that adopting a mechanistic approach to the neuroscience of consciousness suggests that the prefrontal cortex is part of the neural mechanisms underlying consciousness even if it is not strictly speaking a necessary part.

Consciousness arguably presents a "hard problem" for scholars. An influential position asserts that the "problem" is rooted in ontology-it arises because consciousness "is" distinct from the physical. "Problem intuitions" are routinely taken as evidence for this view. In so doing, it is assumed that (i) people do not consider consciousness as physical and (ii) their intuitions faithfully reflect what exists (or else, intuitions would not constitute evidence). New experimental results challenge both claims. First, in some scenarios, people demonstrably view consciousness as a physical affair that registers in the body (brain). Second, "problem intuitions" are linked to psychological biases, so they cannot be trusted to reflect what consciousness is. I conclude that the roots of the "hard problem" are partly psychological. Accordingly, its resolution requires careful characterization of the psychological mechanisms that engender "problem intuitions."

Attributing a visual motion signal to its correct source-be that external object motion, self-motion, or some combination of both-seems effortless, and yet often involves disentangling a complex web of motion signals. Existing literature focuses on either translational motion (heading) or eye movements, leaving much to be learnt about the influence of a wider range of self-motions, such as active head rotations, on visual motion perception. This study investigated how active head rotations affect visual motion detection thresholds, comparing conditions where visual motion and head-turn direction were either congruent or incongruent. Participants judged the direction of a visual motion stimulus while rotating their head or remaining stationary, using a fixation-locked Virtual Reality display with integrated head-movement recordings. Thresholds to perceive visual motion were higher in both active-head rotation conditions compared to stationary, though no differences were found between congruent or incongruent conditions. Participants also showed a significant bias to report seeing visual motion travelling in the same direction as the head rotation. Together, these results demonstrate active head rotations increase visual motion perceptual thresholds, particularly in cases of incongruent visual and active vestibular stimulation.

Technological advances raise new puzzles and challenges for cognitive science and the study of how humans think about and interact with artificial intelligence (AI). For example, the advent of large language models and their human-like linguistic abilities has raised substantial debate regarding whether or not AI could be conscious. Here, we consider the question of whether AI could have subjective experiences such as feelings and sensations ('phenomenal consciousness'). While experts from many fields have weighed in on this issue in academic and public discourse, it remains unknown whether and how the general population attributes phenomenal consciousness to AI. We surveyed a sample of US residents ( = 300) and found that a majority of participants were willing to attribute some possibility of phenomenal consciousness to large language models. These attributions were robust, as they predicted attributions of mental states typically associated with phenomenality-but also flexible, as they were sensitive to individual differences such as usage frequency. Overall, these results show how folk intuitions about AI consciousness can diverge from expert intuitions-with potential implications for the legal and ethical status of AI.

The Integrated Information Theory is a theoretical framework that aims to elucidate the nature of consciousness by postulating that it emerges from the integration of information within a system, and that the degree of consciousness depends on the extent of information integration within the system. When consciousness is lost, the core complex of consciousness proposed by the Integrated Information Theory disintegrates, and Φ measures, which reflect the level of integrated information, are expected to diminish. This study examined the predictions of the Integrated Information Theory using the global brain network acquired via functional magnetic resonance imaging during various tasks and sleep. We discovered that the complex located within the frontoparietal network remained constant regardless of task content, while the regional distribution of the complex collapsed in the initial stages of sleep. Furthermore, Φ measures decreased as sleep progressed under limited analysis conditions. These findings align with predictions made by the Integrated Information Theory and support its postulates.

[This corrects the article DOI: 10.1093/nc/niae017.].

In search for the neural correlates of consciousness (NCCs), it is important to isolate the true NCCs from their prerequisites, consequences, and co-occurring processes. To date, little is known about how attention affects the event-related potential (ERP) correlates of auditory awareness and there is contradictory evidence on whether one of them, the late positivity (LP), is affected by response requirements. By implementing a GO-NOGO design with target and nontarget stimuli, we controlled for feature-based attention and response requirements in the same experiment, while participants rated their awareness using a perceptual awareness scale. The results showed a prolonged auditory awareness negativity (AAN) for aware trials, which was influenced neither by attention nor by response requirement. The LP was affected by both attention and response requirements. Consistent with the levels of processing hypothesis, the LP was related to consciousness as a correlate of the processing of higher-level stimulus features, likely requiring access to a "global workspace." Our findings further suggest that AAN is a proper ERP correlate of auditory consciousness and thus a true NCC in the auditory modality.

Identifying the neuronal markers of consciousness is key to supporting the different scientific theories of consciousness. Neuronal markers of consciousness can be defined to reflect either the brain signatures underlying specific conscious content or those supporting different states of consciousness, two aspects traditionally studied separately. In this paper, we introduce a framework to characterize markers according to their dynamics in both the "state" and "content" dimensions. The 2D space is defined by the marker's capacity to distinguish the conscious states from non-conscious states (on the -axis) and the content (e.g. perceived versus unperceived or different levels of cognitive processing on the -axis). According to the sign of the - and -axis, markers are separated into four quadrants in terms of how they distinguish the state and content dimensions. We implement the framework using three types of electroencephalography markers: markers of connectivity, markers of complexity, and spectral summaries. The neuronal markers of state are represented by the level of consciousness in (i) healthy participants during a nap and (ii) patients with disorders of consciousness. On the other hand, the neuronal markers of content are represented by (i) the conscious content in healthy participants' perception task using a visual awareness paradigm and (ii) conscious processing of hierarchical regularities using an auditory local-global paradigm. In both cases, we see separate clusters of markers with correlated and anticorrelated dynamics, shedding light on the complex relationship between the state and content of consciousness and emphasizing the importance of considering them simultaneously. This work presents an innovative framework for studying consciousness by examining neuronal markers in a 2D space, providing a valuable resource for future research, with potential applications using diverse experimental paradigms, neural recording techniques, and modeling investigations.

Afterimages are illusory, visual conscious perceptions. A widely accepted theory is that afterimages are caused by retinal signaling that continues after the physical disappearance of a light stimulus. However, afterimages have been reported without preceding visual, sensory stimulation (e.g. conditioned afterimages and afterimages induced by illusory vision). These observations suggest the role of top-down brain mechanisms in afterimage conscious perception. Therefore, some afterimages may share perceptual features with sensory-independent conscious perceptions (e.g. imagery, hallucinations, and dreams) that occur without bottom-up sensory input. In the current investigation, we tested for a link between the vividness of visual imagery and afterimage conscious perception. Participants reported their vividness of visual imagery and perceived sharpness, contrast, and duration of negative afterimages. The afterimage perceptual features were acquired using perception matching paradigms that were validated on image stimuli. Relating these perceptual reports revealed that the vividness of visual imagery positively correlated with afterimage contrast and sharpness. These behavioral results support shared neural mechanisms between visual imagery and afterimages. However, we cannot exclude alternative explanations, including demand characteristics and afterimage perception reporting inaccuracy. This study encourages future research combining neurophysiology recording methods and afterimage paradigms to directly examine the neural mechanisms of afterimage conscious perception.

Mystical-like states of consciousness may arise through means such as psychedelic substances, but may also occur unexpectedly during near-death experiences (NDEs). So far, research studies comparing experiences induced by serotonergic psychedelics and NDEs, along with their enduring effects, have employed between-subject designs, limiting direct comparisons. We present results from an online survey exploring the phenomenology, attribution of reality, psychological insights, and enduring effects of NDEs and psychedelic experiences (PEs) in individuals who have experienced both at some point during their lifetime. We used frequentist and Bayesian analyses to determine significant differences and overlaps (evidence for null hypotheses) between the two. Thirty-one adults reported having experienced both an NDE (i.e. NDE-C scale total score ≥27/80) and a PE (intake of lysergic acid diethylamide, psilocybin/mushrooms, ayahuasca, -dimethyltryptamine, or mescaline). Results revealed areas of overlap between both experiences for phenomenology, attribution of reality, psychological insights, and enduring effects. A finer-grained analysis of the phenomenology revealed a significant overlap in mystical-like effects, while low-level phenomena (sensory effects) were significantly different, with NDEs displaying higher scores of disembodiment and PEs higher scores of visual imagery. This suggests psychedelics as a useful model for studying mystical-like effects induced by NDEs, while highlighting distinctions in sensory experiences.

Internal feeling states such as pain, hunger, and thirst are widely assumed to be drivers of behaviours essential for homeostasis and animal survival. Call this the 'causal assumption'. It is becoming increasingly apparent that the causal assumption is incompatible with the standard view of motor action in neuroscience. While there is a well-known explanatory gap between neural activity and feelings, there is also a disjuncture in the reverse direction-what role, if any, do feelings play in animals if not to cause behaviour? To deny that feelings cause behaviours might thus seem to presage epiphenomenalism-the idea that subjective experiences, including feelings, are inert, emergent and, on some views, non-physical properties of brain processes. Since epiphenomenalism is antagonistic to fundamental commitments of evolutionary biology, the view developed here challenges the standard view about the function of feelings without denying that feelings have a function. Instead, we introduce the 'sense making sense' hypothesis-the idea that the function of subjective experience is not to cause behaviour, but to explain, in a restricted but still useful sense of 'explanation'. A plausible framework is derived that integrates commonly accepted neural computations to blend motor control, feelings, and explanatory processes to make sense of the way feelings are integrated into our sense of how and why we do and what we do.

In daily life, we can not only estimate confidence in our inferences ('I'm sure I failed that exam'), but can also estimate whether those feelings of confidence are good predictors of decision accuracy ('I feel sure I failed, but my feeling is probably wrong; I probably passed'). In the lab, by using simple perceptual tasks and collecting trial-by-trial confidence ratings visual metacognition research has repeatedly shown that participants can successfully predict the accuracy of their perceptual choices. Can participants also successfully evaluate 'confidence in confidence' in these tasks? This is the question addressed in this study. Participants performed a simple, two-interval forced choice numerosity task framed as an exam. Confidence judgements were collected in the form of a 'predicted exam grade'. Finally, we collected 'meta-metacognitive' reports in a two-interval forced-choice design: trials were presented in pairs, and participants had to select that in which they thought their confidence (predicted grade) best matched their accuracy (actual grade), effectively minimizing their quadratic scoring rule (QSR) score. Participants successfully selected trials on which their metacognition was better when metacognitive performance was quantified using area under the type 2 ROC (AUROC2) but not when using the 'gold-standard' measure m-ratio. However, further analyses suggested that participants selected trials on which AUROC2 is lower in part via an extreme-confidence heuristic, rather than through explicit evaluation of metacognitive inferences: when restricting analyses to trials on which participants gave the same confidence rating AUROC2 no longer differed as a function of selection, and likewise when we excluded trials on which extreme confidence ratings were given. Together, our results show that participants are able to make effective metacognitive discriminations on their visual confidence ratings, but that explicit 'meta-metacognitive' processes may not be required.

Recent years have seen the rise of several theories saying that the prefrontal cortex (PFC) is a neural correlate of visual consciousness (NCC). Especially popular here are theories saying that the PFC is the 'content NCC' for vision, i.e. it contains those brain areas that are not only necessary for consciousness, but also determine 'what' it is that we visually experience (e.g. whether we experience green or red). This article points out how this "upper-deck" form of PFC theory is at odds with the character of visual experience: on the one hand, visual consciousness appears to contain copious amounts of content, with many properties (such as object, shape, or color) being simultaneously represented in many parts of the visual field. On the other hand, the functions that the PFC carries out (e.g. attention and working memory) are each dedicated to processing only a relatively small subset of available visual stimuli. In short, the PFC probably does not produce enough or the right kind of visual representations for it to supply all of the content found in visual experience, in which case the idea that the PFC is the content NCC for vision is probably false. This article also discusses data thought to undercut the idea that visual experience is informationally rich (inattentional blindness, etc.), along with theories of vision according to which "ensemble statistics" are used to represent features in the periphery of the visual field. I'll argue that these lines of evidence fail to close the apparently vast gap between the amount of visual content represented in the visual experience and the amount represented in the PFC.

To investigate mechanisms underlying loss of consciousness, it is important to extend methods established in humans to rodents as well. Perturbational complexity index (PCI) is a promising metric of "capacity for consciousness" and is based on a perturbational approach that allows inferring a system's capacity for causal integration and differentiation of information. These properties have been proposed as necessary for conscious systems. Measures based on spontaneous electroencephalography recordings, however, may be more practical for certain clinical purposes and may better reflect ongoing dynamics. Here, we compare PCI (using electrical stimulation for perturbing cortical activity) to several spontaneous electroencephalography-based measures of signal diversity and integrated information in rats undergoing propofol, sevoflurane, and ketamine anesthesia. We find that, along with PCI, the spontaneous electroencephalography-based measures, Lempel-Ziv complexity (LZ) and geometric integrated information (Φ), were best able to distinguish between awake and propofol and sevoflurane anesthesia. However, PCI was anti-correlated with spontaneous measures of integrated information, which generally increased during propofol and sevoflurane anesthesia, contrary to expectations. Together with an observed divergence in network properties estimated from directed functional connectivity (current results) and effective connectivity (earlier results), the perturbation-based results seem to suggest that anesthesia disrupts global cortico-cortical information transfer, whereas spontaneous activity suggests the opposite. We speculate that these seemingly diverging results may be because of suppressed encoding specificity of information or driving subcortical projections from, e.g., the thalamus. We conclude that certain perturbation-based measures (PCI) and spontaneous measures (LZ and Φ) may be complementary and mutually informative when studying altered states of consciousness.

The contents of awareness can substantially change without any modification to the external world. Such effects are exemplified in binocular rivalry, where a different stimulus is presented to each eye causing instability in perception. This phenomenon has made binocular rivalry a quintessential method for studying consciousness and the necessary neural correlates for awareness. However, to conduct research on binocular rivalry usually requires self-reports of changes in percept, which can produce confounds and exclude states and contexts where self-reports are undesirable or unreliable. Here, we use a novel multivariate spatial filter dubbed 'Rhythmic Entrainment Source Separation' to extract steady state visual evoked potentials from electroencephalography data. We show that this method can be used to quantify the perceptual switch-rate of participants during binocular rivalry and therefore may be valuable in experimental contexts where self-reports are methodologically problematic or impossible, particularly as an adjunct. Our analyses also reveal that 'no-report' conditions may affect the deployment of attention and thereby neural correlates, another important consideration for consciousness research.

.

A recent advancement in consciousness science has been the introduction of a multidimensional framework of consciousness. This framework has been applied to global states of consciousness, including psychedelic states and disorders of consciousness, and the consciousness of non-human animals. The multidimensional framework enables a finer parsing of both various states of consciousness and forms of animal consciousness, paving the way for new scientific investigations into consciousness. In this paper, the multidimensional model is expanded by constructing temporal profiles. This expansion allows for the modelling of changes in consciousness across the life cycles of organisms and the progression over time of disorders of consciousness. The result of this expansion is 2-fold: (i) it enables new modes of comparison, both across stages of development and across species; (ii) it proposes that more attention be given to the various types of fluctuations that occur in patients who are suffering from disorders of consciousness.

The loss of consciousness (LOC) during seizures is one of the most striking features that significantly impact the quality of life, even though the neuronal network involved is not fully comprehended. We analyzed the intracerebral patterns in patients with focal drug-resistant epilepsy, both with and without LOC. We assessed the localization, lateralization, stereo electroencephalography (SEEG) patterns, seizure duration, and the quantification of contacts exhibiting electrical discharge. The degree of LOC was quantified using the Consciousness Seizure Scale. Thirteen patients (40 seizures) with focal drug-resistant epilepsy underwent SEEG. In cases of temporal lobe epilepsy (TLE, 6 patients and 15 seizures), LOC occurred more frequently in seizures with mesial rather than lateral temporal lobe onset. On the other hand, in cases of frontal lobe epilepsy (7 patients; 25 seizures), LOC was associated with pre-frontal onset, a higher number of contacts with epileptic discharge compared to the onset count and longer seizure durations. Our study revealed distinct characteristics during LOC depending on the epileptogenic zone. For temporal lobe seizures, LOC was associated with mesial seizure onset, whereas in frontal lobe epilepsy, seizure with LOC has a significant increase in contact showing epileptiform discharge and a pre-frontal onset. This phenomenon may be correlated with the broad neural network required to maintain consciousness, which can be affected in different ways, resulting in LOC.

Modern medicine has been shaken by the surge of psychedelic science that proposes a new approach to mitigate mental disorders, such as depression and post-traumatic stress disorder. Clinical trials to investigate whether psychedelic substances can treat psychiatric conditions are now underway, yet less discussion gravitates around their use in neurological disorders due to brain injury. One suggested implementation of brain-complexity enhancing psychedelics is to treat people with post-comatose disorders of consciousness (DoC). In this article, we discuss the rationale of this endeavour, examining possible outcomes of such experiments by postulating the existence of an optimal level of complexity. We consider the possible counterintuitive effects of both psychedelics and DoC on the functional connectivity of the default mode network and its possible impact on selfhood. We also elaborate on the role of computational modelling in providing complementary information to experimental studies, both contributing to our understanding of the treatment mechanisms and providing a path towards personalized medicine. Finally, we update the discourse surrounding the ethical considerations, encompassing clinical and scientific values.

The neurobiology of conscious experience is one of the fundamental mysteries in science. New evidence suggests that transcranial magnetic stimulation of the parietal cortex does not modulate bistable perception. What does this mean for the neural correlates of consciousness, and how should we search for them?

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

Self-esteem, the evaluation of one's own worth or value, is a critical aspect of psychological well-being and mental health. In this paper, we propose an active inference account of self-esteem, casting it as a sociometer or an inferential capacity to interpret one's standing within a social group. This approach allows us to explore the interaction between an individual's self-perception and the expectations of their social environment.When there is a mismatch between these perceptions and expectations, the individual needs to adjust their actions or update their self-perception to better align with their current experiences. We also consider this hypothesis in relation with recent research on affective inference, suggesting that self-esteem enables the individual to track and respond to this discrepancy through affective states such as anxiety or positive affect. By acting as an inferential sociometer, self-esteem allows individuals to navigate and adapt to their social environment, ultimately impacting their psychological well-being and mental health.

Trance states include various practices characterized by a modulation of consciousness, but with their own specific characteristics and induction techniques. They have been very seldom scientifically studied, and their phenomenological similarities and differences are poorly documented. This paper will focus on two types of Western trances developed after the leaders were trained in traditional shamanic communities: the auto-induced cognitive trance (AICT) and the Mahorikatan trance (MT). Twenty-five AICT and 26 MT participants who were able to self-induce the trance state completed questionnaires about their trance practice (e.g. context of the first trance episode, frequency of practice, and consequences on personal life) and the phenomenological characteristics (i.e. emotional, physical, and cognitive) of the trance episodes they experienced. These characteristics were compared to explore similarities and differences between the two trance states. AICT and MT are characterized by the expression of different emotions, modification of various perceptions, a feeling of unicity (i.e. being completely oneself), and an expansion of consciousness. AICT participants commonly reported body movements, vocalizations, as well as increased creativity, visions of entities and/or places, and feeling of interaction with the environment. MT participants commonly reported a feeling of body dissolution. Most participants in both groups reported positive effects of their trance practice on their personal life. These results helped characterize AICT and MT, as well as their similarities and differences. Further studies should continue to explore the characteristics of such trance states, as well as their potential clinical applications.

Psychedelic therapy has seen a resurgence of interest in the last decade, with promising clinical outcomes for the treatment of a variety of psychopathologies. In response to this success, several theoretical models have been proposed to account for the positive therapeutic effects of psychedelics. One of the more prominent models is "RElaxed Beliefs Under pSychedelics," which proposes that psychedelics act therapeutically by relaxing the strength of maladaptive high-level beliefs encoded in the brain. The more recent "CANAL" model of psychopathology builds on the explanatory framework of RElaxed Beliefs Under pSychedelics by proposing that canalization (the development of overly rigid belief landscapes) may be a primary factor in psychopathology. Here, we make use of learning theory in deep neural networks to develop a series of refinements to the original CANAL model. Our primary theoretical contribution is to disambiguate two separate optimization landscapes underlying belief representation in the brain and describe the unique pathologies which can arise from the canalization of each. Along each dimension, we identify pathologies of either too much or too little canalization, implying that the construct of canalization does not have a simple linear correlation with the presentation of psychopathology. In this expanded paradigm, we demonstrate the ability to make novel predictions regarding what aspects of psychopathology may be amenable to psychedelic therapy, as well as what forms of psychedelic therapy may ultimately be most beneficial for a given individual.

[This corrects the article DOI: 10.1093/nc/niae001.].

Here we build on recent findings which show that greater alignment between our subjective experiences (how we feel) and physiological states (measurable changes in our body) plays a pivotal role in the overall psychological well-being. Specifically, we propose that the alignment or 'coherence' between affective arousal (e.g. how excited we 'feel') and autonomic arousal (e.g. heart rate or pupil dilation) may be key for maintaining up-to-date uncertainty representations in dynamic environments. Drawing on recent advances in interoceptive and affective inference, we also propose that arousal coherence reflects interoceptive integration, facilitates adaptive belief updating, and impacts our capacity to adapt to changes in uncertainty, with downstream consequences to well-being. We also highlight the role of meta-awareness of arousal, a third level of inference, which may permit conscious awareness, learning about, and intentional regulation of lower-order sources of arousal. Practices emphasizing meta-awareness of arousal (like meditation) may therefore elicit some of their known benefits via improved arousal coherence. We suggest that arousal coherence is also likely to be associated with markers of adaptive functioning (like emotional awareness and self-regulatory capacities) and discuss mind-body practices that may increase coherence.

Auto-induced cognitive trance (AICT) is a modified state of consciousness derived from shamanic tradition that can be practised by individuals after specific training. The aim of this work was to characterize the phenomenological experiences of AICT, using text mining analysis. Free recalls of subjective experiences were audio-recorded in 27 participants after five pseudo-randomized experimental sessions: ordinary conscious resting state, with auditory stimulation and with an imaginary mental task, as well as during AICT with and without auditory stimulation. Recordings were transcribed, normalized total word counts were calculated for each condition, and analyses of content were performed using IRaMuTeQ software. Results showed that the length of the participants' reports was higher for AICT compared to the other conditions, and that the content could be categorized into four classes of discourse: AICT memory, AICT, ordinary conscious states, and AICT with and without stimulation. AICT was also characterized by specific content compared to rest, auditory stimulation, and imagination conditions. Content analysis of the narrative revealed nine categories encompassing the presence of nature, people, animals, positive and negative features, sensory perceptions, body modifications, metacognition, and difficulty of describing thoughts. Among these categories, AICT is specifically characterized by reports related to the presence of nature, animals, body modifications, as well as the difficulty of describing thoughts. These results suggest that a richer phenomenology was reported during AICT, compared to the other conditions, and that AICT constitutes a class of discourse on its own, with a clear dissociation from the other conditions.