Neuroscience of Consciousness

Hallucinatory experiences, defined as perception in the absence of external stimuli, can occur in both pathological and non-pathological states and can be broadly phenomenologically divided into those of a simple and a complex nature. Non-pathological visual hallucinations can be induced experimentally using a variety of stimulation conditions. To assess whether these techniques drive a shared underlying hallucinatory mechanism, despite these differences, we compared two methods: flicker and perceptual deprivation (Ganzfeld). Specifically, we measured the frequency and complexity of the hallucinations produced by these techniques. We utilised button press, retrospective drawing, interviews, and questionnaires to quantify hallucinatory experience in 20 participants. With both experimental techniques, we found that simple hallucinations were more common than complex hallucinations. We also found that on average, flicker was more effective than Ganzfeld at eliciting a higher number of hallucinations, though Ganzfeld hallucinations were longer than flicker hallucinations. There was no interaction between experimental condition and hallucination complexity, suggesting that the increased bottom-up visual input in flicker increased both simple and complex hallucinations similarly. A correlation was observed between the total proportional time spent hallucinating in flicker and Ganzfeld, which was replicated in a retrospective questionnaire measure of experienced intensity, suggesting a shared hallucinatory mechanism between the two methodologies. We attribute these findings to a shared low-level core hallucinatory mechanism, such as excitability of visual cortex, which is amplified in flicker compared to Ganzfeld due to heightened bottom-up input.

One proposed function of imagery is to make thoughts more emotionally evocative through sensory simulations. Here we report a novel test of this theory utilizing a special population with no visual imagery: Aphantasia. After using multi-method verification of aphantasia, we show that this condition, but not the general population, is associated with a flat-line physiological response to frightening written, but not perceptual scenarios, supporting imagerys critical role in emotion.

Research on mental visual imagery typically relies on vividness ratings. However, vividness is ill-defined as it lacks an objective reference. Here, we present survey results that suggest vividness is nevertheless a robust measure. It explains individual differences of a broad range of subjective experiences, from the detail of mental imagery, the propensity to report having other internally generated visual experiences, and the vividness of visual dreams. Critically, simple vividness ratings can replace the protracted questionnaires commonly used for this purpose and reduce methodological issues with these instruments. We further find that vividness is closely linked with the experience of "seeing" mental images or projecting them into the external world. People who report seeing mental images with their eyes shut are also more likely to experience externally projected imagery. Nevertheless, many people report having mental depictions but without seeing. Overall, our results indicate we should redefine visual aphantasia to distinguish individuals with faint or unseen visual images from those completely lacking a pictorial representation.

Visual hallucinations (VHs) are perceptions of objects or events in the absence of the sensory stimulation that would normally support such perceptions. Although all VHs share this core characteristic, there are substantial phenomenological differences between VHs that have different aetiologies, such as those arising from neurological conditions, visual loss, or psychedelic compounds. Here, we examine the potential mechanistic basis of these differences by leveraging recent advances in visualising the learned representations of a coupled classifier and generative deep neural network - an approach we call computational (neuro)phenomenology. Examining three aetiologically distinct populations in which VHs occur - neurological conditions (Parkinsons Disease and Lewy Body Dementia), visual loss (Charles Bonnet Syndrome, CBS), and psychedelics - we identify three dimensions relevant to distinguishing these classes of VHs: realism (veridicality), dependence on sensory input (spontaneity), and complexity. By selectively tuning the parameters of the visualisation algorithm to reflect influence along each of these phenomenological dimensions we were able to generate synthetic VHs that were characteristic of the VHs experienced by each aetiology. We verified the validity of this approach experimentally in two studies that examined the phenomenology of VHs in neurological and CBS patients, and in people with recent psychedelic experience. These studies confirmed the existence of phenomenological differences across these three dimensions between groups, and crucially, found that the appropriate synthetic VHs were representative of each groups hallucinatory phenomenology. Together, our findings highlight the phenomenological diversity of VHs associated with distinct causal factors and demonstrate how a neural network model of visual phenomenology can successfully capture the distinctive visual characteristics of hallucinatory experience.

Lucid dreaming (LD), during which the dreamer is aware that they are dreaming, is frequently induced in laboratory settings by delivering sensory cues during rapid eye movement (REM) sleep. These cues should be incorporated into ongoing dreams and can trigger reflective awareness. This approach relies on the continuity between waking experiences and dream content. In sleep laboratories, participants often dream of the experimental setting itself (lab dreaming), providing a predictable context in which lucidity may emerge. The present studies leveraged this phenomenon by explicitly training participants to associate the sleep laboratory with reflective awareness prior to sleep. Across three studies (total N = 101), participants completed a morning nap following verbal LD instructions and presleep audio designed to prime recognition of the laboratory context in dreams. In addition, conditions included immersive virtual reality (VR) rehearsal of the laboratory environment, VR combined with haptic stimulation (HS) during REM sleep, or VR containing subtle fake system errors intended to prompt reflective checking. LD frequency was assessed through external ratings of signal-verified LD (SVLD) dream reports. Lucidity rates were high across all conditions, with approximately 40-45% of dreams externally rated as lucid and 11%-32% SVLDs occurring in every group. However, neither VR rehearsal, haptic stimulation, nor implicit VR errors increased lucidity relative to the baseline laboratory induction procedure. Exploratory analyses investigated the overlap between laboratory dreaming, false awakenings (FAs), and lucidity. These findings suggest that explicit training focused on the predictable context of the sleep laboratory may already provide a powerful pathway to lucidity, with additional technological manipulations offering limited benefit under a single-nap protocol. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/711049v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@191373corg.highwire.dtl.DTLVardef@c1490corg.highwire.dtl.DTLVardef@1a2c193org.highwire.dtl.DTLVardef@52c5d1_HPS_FORMAT_FIGEXP M_FIG C_FIG

Visual hallucinations (VHs) occur across psychedelic states and diverse psychiatric and neurological conditions, yet their phenomenology remains difficult to characterise. Empirical research on VHs is hindered by the lack of large-scale phenomenological datasets, which limits both mechanistic accounts and the systematic characterisation of when and how they arise. Stroboscopic light stimulation (SLS) viewed with closed eyes provides a reliable, non-pharmacological method of inducing VHs in healthy populations. These hallucinations typically consist of vivid colours and dynamic geometric patterns that resemble simple VHs described in both psychedelic and clinical contexts, suggesting partially overlapping neural mechanisms. We developed and applied an unsupervised computer-vision pipeline to analyse a large dataset of 10,598 drawings made following exposure to hallucination-inducing SLS. These drawings were produced by attendees of Dreamachine, a large-scale public installation designed to elicit stroboscopically induced visual hallucinations (SIVHs). We extracted feature embeddings with a self-supervised deep vision transformer, then applied dimensionality reduction and density-based clustering to identify recurrent visual motifs in a data-driven manner. The majority of drawings contained geometric forms, consistent with prior observations of simple VHs under SLS. However, we also identified novel and underreported geometric formations, such as concentric squares, crosses, hyperbolic patterns, and other geometries. Our results show how an unsupervised computer-vision pipeline can organise large, openly shared phenomenological datasets into interpretable classes. By mapping the diversity of simple geometric VHs at scale, this work places new constraints on existing theoretical accounts and motivates targeted experimental work linking SLS parameters, neural dynamics, and geometric visual hallucinations.

Dreams are universal yet deeply personal experiences. While memory and personal concerns influence dream content, the impact of other individual, generalizable traits remains poorly understood. To address this gap, we built a multimodal dataset including dream and wakefulness reports, alongside demographic, psychometric, cognitive, and sleep-related measures in a large adult cohort. Natural language processing characterized the semantic features that quantitatively distinguish dream from wakefulness reports, with this distinction significantly modulated by individual-specific factors. Longitudinal and cross-sample analyses further demonstrated that major external events, such as the COVID-19 pandemic, affect dream content, leaving lasting traces. Overall, the findings highlight a dynamic interplay between stable individual traits and external events in shaping dream experiences, offering novel insights into the cognitive and emotional architecture of dreaming.

BackgroundIntegrated Information Theory (IIT) predicts gradual consciousness changes, while Global Workspace Theory (GWT) emphasizes discrete threshold events. We tested whether sleep stage transitions exhibit these distinct patterns using quantitative EEG analysis. MethodsWe analyzed 622 sleep stage transitions from 12 healthy adults (Wake[-&gt;]N1, N1[-&gt;]N2, N2[-&gt;]N3, REM[-&gt;]Wake) using the Consciousness Gradient Index (CGI = {surd}({varphi} x {rho}) x 10). We employed two approaches: (1) an adaptive method selecting transition-specific metrics (alpha power, spindle density, spectral entropy), and (2) control analyses applying uniform metrics (spectral entropy, Lempel-Ziv complexity) across all transitions. ResultsThe adaptive approach showed N1[-&gt;]N2 as the steepest transition (slope = -2.161, d = 2.814, p < 0.001). However, control analyses revealed this pattern to be metric-dependent. With spectral entropy applied uniformly, all transitions showed near-zero slopes (0.001-0.004), with N1[-&gt;]N2 ranking 3rd in magnitude. With Lempel-Ziv complexity, N1[-&gt;]N2 showed the smallest magnitude (0.001). Neither control supported N1[-&gt;]N2 as uniquely steep. ConclusionsThe apparent "dual architecture" resulted from selecting metrics based on known neurophysiological changes at each transition, creating circular reasoning. Control analyses using unbiased metrics showed no meaningful consciousness changes during any transition. This study demonstrates the importance of validation with uniformly-applied metrics and serves as a methodological warning about metric selection effects in consciousness research. The adaptive CGI framework successfully detected known neurophysiological changes but did not reveal fundamental differences in consciousness transition mechanisms.

Experiences in which the sense of the body becomes distorted offer a unique window into how the brain constructs the bodily self. Despite their clinical relevance in conditions such as depersonalization and body-image disorders, large-scale brain dynamics underlying unusual bodily experiences (UBEs) remain poorly understood, and no prior study has examined them systematically across wakefulness and sleep. Here, we analyzed a high-density EEG dataset including 36 UBE episodes, such as floating sensations, distorted body boundaries, and out-of-body experiences, recorded across rapid eye-movement (REM) sleep, light sleep, sleep arousals, and wakefulness during meditation (N=20). We quantified the temporal irreversibility of neural dynamics, a marker of cortical hierarchical organization, and complemented these analyses with whole-brain signal complexity measures following a within-subject design. UBEs were consistently associated with a global reduction in neural irreversibility and cortical hierarchical differentiation relative to non-UBEs and wakefulness, along with a concurrent increase in whole-brain complexity to levels comparable to wakefulness. Together, these findings suggest that UBEs reflect a neural state combining high informational richness with a transient flattening of cortical hierarchy, a profile that resembles that observed in psychedelic states. Key pointsO_LIUBEs are associated with a global flattening of brain hierarchy measured by EEG. C_LIO_LIUBEs are associated with increased global EEG complexity, resembling the psychedelic state. C_LI

Effortful cognition is typically associated with controlled, task-constrained neural processing, whereas effortless awareness may require a more flexible, internally driven mode of brain organization. Critical brain dynamics provide a principled framework for characterizing this shift, as systems near criticality are thought to balance stability and flexibility, allowing efficient information processing without excessive control. Transcendental Meditation (TM), characterized by a shift from effortful mental engagement to effortless awareness, offers a natural model for testing this possibility. Here, we investigated whether critical brain dynamics track TM as a global meditative state, or instead reflect moment-to-moment fluctuations in subjective effortlessness. We combined high-density electroencephalography (EEG) with time-resolved phenomenological reports using Temporal Experience Tracing (TET). Experienced TM practitioners (N = 33) and matched controls (N = 33) completed resting-state recordings before and after a 30-minute TM or silent counting control task. Long-range temporal correlations (LRTCs) were quantified using detrended fluctuation analysis, while functional excitation/inhibition (fEI) balance was used to estimate directional deviations from criticality. State-based analyses showed that TM increased alpha and beta LRTCs relative to pre- and post-resting state within meditators, but revealed no robust between-group differences in either LRTCs or fEI balance. In contrast, neurophenomenological analyses showed that subjective effortlessness was robustly associated with increased theta, alpha, beta, and broadband LRTCs, with significantly stronger relationships in meditators than controls. Restricting analyses to low-effort periods further revealed higher beta LRTCs in meditators, a difference missed by conventional state comparisons. These findings identify scale-free neural dynamics as a candidate marker of "letting go" during meditation.

Subjective experiences are hard to capture quantitatively without losing depth and nuance, and subjective report analyses are time-consuming, their interpretation contested. We describe Temporal Experience Tracing, a method that captures relevant aspects of the unified conscious experience over a continuous period of time. The continuous multidimensional description of an experience allows us to computationally reconstruct common experience states. Applied to data from 852 meditations - from novice (n=20) and an experienced (n=12) meditators practising Breathing, Loving-Kindness and Open-Monitoring meditation - we reconstructed four recurring experience states with an average duration of 6:46 min (SD = 5:50 min) and their transition dynamics. Three of the experience states assimilated the three meditation styles practiced, and a fourth experience state represented a common low-motivational, off-task state for both groups. We found that participants in both groups spent more time in the task-related experience state during Loving Kindness meditation than other meditation styles and were less likely to transition into an off-task experience state during Loving Kindness meditation than during Breathing meditation. We demonstrate that drawing the dynamics of experience enables the quantitative analysis of subjective experiences, transforming the time dimension of the stream of consciousness from narrative to measurable.

Lucid dreaming (LD), during which the dreamer becomes aware of the dream state, offers a unique opportunity for a variety of applications, including motor practice, personal well-being, and nightmare therapy. However, these applications largely depend on a dreamers ability to control their dreams. While LD research has traditionally focused on induction techniques to increase dream frequency, the equally crucial skill of dream control remains underexplored. This study provides an initial investigation into the mechanisms of dream control and its potential influencing factors. We specifically examined whether a complex motor skill--juggling--could be performed within a lucid dream, creating a particularly challenging lucid dream task, which calls for a high level of dream control. Eight healthy participants (aged 24-50) underwent overnight polysomnography (PSG) at the University of Berns Institute for Sports Science, provided detailed dream reports, and completed questionnaires assessing dream control, self-efficacy, personality traits, mindfulness, motivation, and intention setting. Of these, four participants experienced lucid dreams, and of these, two demonstrated high dream control with successful LD juggling attempts. Trait differences between non-lucid and lucid dreamers in the lab were examined, with a focus on low-to-no dream control versus high dream control among the lucid dreamers. The two lucid dream juggling attempts are described in detail, providing insight into the challenges of executing complex tasks within a lucid dream. While this study lacks in sample size, it highlights the potential roles of many psychological traits, such as belief, motivation, and self-efficacy, in shaping dream control abilities. This study helps to lay the groundwork for future research aimed at investigating lucid dream control and therefore optimizing LD applications in therapy, sports training, and cognitive science.

Why does an angry face feel uncomfortable? The answer is that it signals a threat. However, a face is only part of an encounter, and distance, facial stimulus type, and gaze may shape discomfort regardless of perceived anger. To separate these cues, we conducted three within-subjects virtual reality experiments. In each experiment, 24 adults viewed avatars at intimate, personal, and social distances (30, 100, and 300 cm, respectively) and rated the faces perceived anger and their own discomfort; head movement was recorded in Experiments 2 and 3. In Experiment 1, the expression (angry, neutral) and facial color (natural, red) were crossed with distance; in Experiment 2, a featureless mannequin served as a nonface comparison; and in Experiment 3, the gaze direction (direct, averted) was manipulated. Expression primarily determined perceived anger, whereas distance predominantly determined discomfort: A nearby neutral face was uncomfortable despite low perceived anger (Experiment 1). A neutral human face was more uncomfortable than a mannequin, although both received similarly low perceived-anger ratings (Experiment 2). Direct gaze increased the discomfort without changing perceived anger (Experiment 3). Backward head movement exhibited a similar pattern, with participants leaning back more from human faces than from the mannequin. These results indicate that the discomfort associated with an angry face is not merely explained by perceived anger. Instead, social discomfort was differentially associated with interpersonal distance and gaze direction and differed between the human-face and mannequin conditions.

The content of consciousness (cC) constitutes an essential part of human life and is at the very heart of the hard problem of consciousness. The cC of a person (e.g., study participant) has been examined indirectly by evaluating the persons behavioral reports, bodily signs, or neural signals. However, the measures do not reflect the full spectrum of the persons cC. In this paper, we define a method, called "CHANging Consciousness Epistemically" (CHANCE), to consciously experience a cC that would be identical to that experienced by another person, and thus directly know the entire spectrum of the others cC. In addition, the ontologically subjective knowledge about a persons cC may be considered epistemically objective and scientific data. The CHANCE method comprises two empirical steps: (1) identifying the minimally sufficient, content-specific neural correlates of consciousness (mscNCC) and (2) reproducing a specific mscNCC in different brains.

Sleep deprivation amplifies emotional reactivity to brief, overt threats in the external environment. However, its effects on emotional responses to prolonged, ambiguous threat remain unclear. In this pre-registered study, we combined virtual reality, psychophysiology and multidimensional experience sampling to test the hypothesis that sleep deprivation disrupts emotional adaptation to sustained or resolving threat. Following a night of restful sleep or total sleep deprivation, healthy young adults navigated an immersive virtual world that alternated between ambiguously threatening and non-threatening contexts. Despite initial increases in emotional arousal, sleep-rested individuals quickly downregulated affective responses to ambiguous threat, reflecting efficient adaptation to the aversive virtual environment. Sleep-deprived individuals, by contrast, were unable to overturn elevated arousal responses, and exhibited a breakdown of goal-orientated, emotional control. Interestingly, resting heart rate variability, an index of affective regulatory capacity, mitigated arousal responses to ambiguous threat after sleep deprivation. These findings suggest that insufficient sleep prevents an adaptive renormalisation of emotional arousal during prolonged and ambiguous threat, giving rise to a maladaptive state of anxiety.

Our awareness of dreams, hallucinations, and illusions reflects an intriguing human capacity to recognize potentially false perceptions, known as the Sense of Reality (SoR). Though central to mental health, the study of SoR has been hindered by the subjective nature of hallucinatory experiences. Here we employed a novel virtual reality paradigm simulating virtual hallucinations, mirroring the phenomenology of clinical hallucinations. Combining psychophysics, physiological recordings, and computational modeling in one exploratory (n = 31) and one preregistered experiment (n = 32), we found that SoR varied with virtual hallucination magnitude and domain. SoR judgments were associated with distinct motor, pupillary, and cardiac responses, allowing classification of virtual hallucination exposure. We present a computational model in which SoR judgments arise from comparing current sensory input to an internal model of the world. Our results shed light on the age-old question how do we know what is real?

Identifying neural signatures of consciousness remains a central challenge in neuroscience. Sleep offers a tractable model for comparing brain activity in the presence or absence of subjective experience while minimizing behavioral responsiveness confounds. Using overnight 256 electrode high-density EEG in 140 participants and a serial-awakening paradigm, we analyzed 699 non-rapid eye movement (NREM) sleep stage 2 and 3 awakenings (351 dreaming experience, 348 no experience). Features from the 60s preceding awakening included regional spectral power, lagged-coherence connectivity, graph-theoretic metrics and gamma-to-alpha power ratios. Dreaming experiences were associated with shifts in posterior spectral balance, particularly reduced alpha and delta power and increased gamma-related measures, together with altered large scale network organization. In participant-level cross-validated machine-learning analyses, all classifiers performed above chance, with the best ensemble model reaching an ROC-AUC of 0.80 and average precision of 0.80. These findings identify reproducible posterior electrophysiological and network-level signatures of conscious states during NREM sleep.

Nonduality is a foundational but conceptually elusive notion across several contemplative traditions. Nondual traditions challenge the assumption that a subject-object structure characteristic of ordinary experience is an intrinsic feature of conscious awareness. However, little remains known about the neurocognitive mechanisms associated with such experiential state. Here, we investigated how Open Presence (OP) meditation, a form of non-dual mindfulness practice, modulates bodily self-representation and large-scale brain functional organization. We combined the Full-Body Illusion Experience (FBIE), a virtual reality paradigm manipulating bodily self-processing, with resting-state functional connectivity gradient analyses in expert meditators (>10,000 hours of practice) and meditation novices. We hypothesized that OP would attenuate bodily self susceptibility as measured by FBIE and increase large-scale integration of functional brain networks, consistent with prior findings linking reduced self-boundaries and ego-dissolution to increased connectome integration. Seventy-five participants (28 experts, 47 novices) underwent fMRI scanning during OP meditation. Brain network organization was assessed using connectivity gradients and network dispersion/ eccentricity metrics. Group differences were evaluated using bootstrap statistics and support vector classification. Compared with novices, expert practitioners showed reduced global network eccentricity during OP, particularly within dorsal attention, ventral attention, and frontoparietal networks, suggesting greater large-scale integration of functional networks. These neural patterns were positively correlated with FBIE self-report measures and negatively with cognitive defusion scores, a construct thought to reflect reduced self-grasping toward thoughts and mental contents. Together, these findings suggest that nondual meditation is associated with alterations in self-representation and increased large-scale functional integration, providing candidate neural markers of nondual awareness.

Alexithymia is the inability to identify and describe emotions, associated with an increased risk of somatic and psychiatric disease. Alexithymia is also characterized by reduced subjective sleep quality. However, it is not well-known if this reduction in sleep quality reflects physiological changes in sleep, a specific alteration in perceived sleep quality not captured by objective metrics, or a non-specific spillover of the negative affective style which characterizes alexithymia. In BSETS, a large (N=228) EEG study of naturalistic sleep, we found that alexithymia symptoms are associated with worse habitual (AIS) and current (GSQS) subjective sleep quality ({beta}AIS=0.207, pAIS=0.002, {beta}GSQS=0.203, pGSQS=0.002). However, we observed no significant association between alexithymia and EEG-based sleep efficiency ({beta}=- 0.017, p=0.791). The association with subjective sleep quality was almost completely attenuated when controlling for either depressive symptoms (PHQ-9, {beta}AIS=0.001, pAIS=0.982, {beta}GSQS=0.044, pGSQS=0.486) or trait neuroticism (ZKPQ, BFI-44, {beta}AIS=0.057, pAIS=0.442, {beta}GSQS=0.048, pGSQS=0.514). A possible exception is the Difficulty Identifying Feelings alexithymia dimension, reflecting complaints about the labeling of interoceptive experiences, which was associated with lower subjective sleep quality even after covariate control. This pattern of findings suggests that alexithymia is characterized only by alterations of subjective sleep quality, and even these reflect a non-specific increase in negative affect which influences self-reports of sleep quality, rather than a specific reduction in perceived sleep quality itself.

Neural correlates of consciousness are often evaluated along single dimensions, such as large-scale integration or metabolic activity, yet it remains unclear whether either is sufficient, or whether conscious states require the joint satisfaction of multiple biological constraints. Here, we evaluate the prediction that conscious states occupy a regime defined by the co-occurrence of sufficient metabolic support and preserved perturbational complexity. We performed a targeted cross-study synthesis of published benchmarks from [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) and transcranial magnetic stimulation combined with electroencephalography (TMS-EEG). Metabolic values and perturbational complexity index (PCI) values were mapped across disorders of consciousness, sleep, and anaesthesia into a shared two-dimensional state space. Across independent cohorts, a lower bound near ~42-46% of normal cortical metabolism and a complexity threshold near PCI* {approx} 0.31 consistently separate unconscious from conscious conditions. Of 16 conditions with complete data, all 9 conscious states occupied the joint regime (above both thresholds), while all 7 unconscious states fell below at least one threshold (Fishers exact test, p = 8.74 x 10-5). The sole off-diagonal placement -- NREM sleep, with preserved metabolism but reduced complexity -- was unconscious, supporting the prediction that metabolic support alone is insufficient without preserved integrative dynamics. These findings support a joint metabolic-integrative constraint on consciousness and motivate a testable prediction: reportable experience should not occur outside this regime. Direct evaluation will require prospective within-subject multimodal studies combining FDG-PET and TMS-EEG.