Neuroscience of Consciousness

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.

The use of meditation as a tool to improve human wellbeing is receiving considerable scientific interest. However, most existing research has focused on concentration-based practices. One powerful alternative is jhana meditation, which leads to states characterised by self-reinforcing bliss, potentially useful for a variety of clinical and scientific domains. However, our understanding of these states is limited by small amounts of data and poor access to experts. To enable new insights, here we release the largest to date and first open-access dataset of electroencephalographic and physiological recordings in expert Jhana meditators. This includes 100+ hours of data in N=26 subjects across three retreats, alongside a detailed description and example code illustrating analysis of the data. This open dataset release can enable wider collaboration and has the potential to move us closer to an understanding of endogenously generated altered states of consciousness.

AO_SCPLOWBSTRACTC_SCPLOWSpontaneous thoughts constitute most of everyday inner experience, yet long-standing methodological challenges obscure a thorough exploration of their content and neurophysiological underpinnings. Traditional approaches relying on thought probes impose strict constraints on phenomenological reports, whereas online verbal reports disrupt the natural flow of experience while interfering neural signals with motor artifacts. Here, we designed and tested an alternative approach to assess the neural basis of spontaneous thoughts combining delayed verbal retrospective free reports (RFR) with automated phenomenological ratings generated by large language models (LLMs). Twenty-two participants performed an eyes-closed free-thinking task, providing reports that were evaluated along ten phenomenological dimensions by four state-of-the-art LLMs and a panel of human raters. Machine-learning models (ML) were then trained to decode LLM-derived ratings from EEG spectral, complexity, and connectivity features. Our analyses showed that inter-rater agreement among LLMs exceeded that of human raters whereas ML models achieved above-chance accuracy for the prediction of emotional valence. These findings provide support for the use of LLMs for a scalable phenomenological annotation of spontaneous thoughts and suggest that their affective dimensions can be decoded from concurrent EEG activity.

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.

Intense aesthetic experiences are among the most complex responses arising from the interaction of mind, brain, and context. Observations from fMRI suggest that when viewers feel highly moved by artworks, the underlying neural states differ from those accompanying less intense responses, particularly through recruitment of the DMN. Using electroencephalography and Bayesian category-specific cumulative link mixed models, we investigated whether such putative peak aesthetic responses exhibit threshold-specific neurodynamics rather than linear scaling with intensity. Twenty-two Chilean participants viewed 113 diverse local artworks whilst rating how moved they felt on a four-point scale. We analysed both canonical oscillatory power ({theta}-{gamma}) and aperiodic components (offset and exponent) during the contemplation window and the post-elicitor window. Threshold-specific effects were found: spectral features differentiated the highest rating category from moderate responses, rather than scaling uniformly across all intensity levels. During artwork visualisation, power in the {beta}1 and {beta}2 bands, as well as the interaction of {beta}1 with the 1/f exponent, predicted the transition to the most intense response; during the post-elicitor window, the aperiodic 1/f exponent predicted the transition from very low to higher-intensity responses. Modelling individual differences in spectral signatures (in the and {gamma} bands) credibly improved predictive performance (approximate leave-one-out cross-validation; elpd_loo), suggesting that neural variability reflects meaningful mechanistic heterogeneity in aesthetic processing rather than mere noise. These findings speak to a broader question, how the brain marks the intensity of conscious experience, and, more specifically, support the hypothesis that being intensely moved constitutes a qualitatively distinct neural state, characterised by specific configurations of oscillatory dynamics and cortical excitability that modulate the transition from low and moderate to peak engagement.

Dream recall varies substantially both between individuals and from night to night within the same individual. Although nocturnal awakenings are thought to facilitate the encoding and later retrieval of dream experiences, it remains unclear whether dream recall is shaped primarily by awakening frequency or by more specific awakening characteristics, including duration, sleep stage, and timing within the night. Here, we analyzed two cohorts: cohort 1 consisted of 708 adults spanning the full range of dream recall frequency, assessed across three waves with home sleep recordings and questionnaire-based dream recall frequency measures; cohort 2 consisted of 124 adults with high dream recall frequency, assessed across multiple nights with home sleep recordings and daily dream reports. Using multilevel models with within-between decomposition, we examined trait-like and state-like associations between awakening measures and dream recall outcomes. At the trait level, both questionnaire-based dream recall frequency in cohort 1 and daily dream recall (i.e., a sense of having dreamed) in cohort 2 were associated with a specific nocturnal awakening profile: more habitual long REM awakenings and short NREM awakenings, with REM awakening effects remaining robust after adjustment for sleep duration. At the state level, in cohort 2, nights with more short and medium REM awakenings than usual increased the likelihood of morning dream recall, whereas nights with more long REM awakenings than usual increased the likelihood of morning dream content recall (i.e., remembering dream content). These findings support the arousal-retrieval and functional state-shift models, while highlighting important nuances in the associations between nocturnal awakenings and different dream recall outcomes.

Empathy, a key element of social interaction, involves both cognitive and affective processes and is commonly investigated through measures such as empathic accuracy and affective physiological synchrony. While physiological synchrony offers a continuous measure of affective processes, empathic accuracy typically relies on discrete self-reports, leaving their temporal relationship largely unexplored. Advancing this line of research requires datasets that integrate time-continuous self-reports with physiological signals, yet such datasets--particularly those focusing on the empathizee--remain limited. To fill this gap, we present EMPAC (Empathy Measurement: Physiological, Affective, and Cognitive), a multimodal dataset constructed. To create empathy-eliciting stimuli, professional actors performed emotionally intense, pseudo-autobiographical narratives while their physiological signals (e.g., ECG, EDA) and continuous self-reported emotional states were recorded. We then conducted two observer experiments using these video recordings. In Experiment 1, to validate the stimuli as empathy-eliciting materials, observers continuously rated emotional intensity without being informed of the specific emotion portrayed, following the protocol of previous studies on time-series empathic accuracy. Yet this approach sometimes revealed a gap between the emotion category portrayed by the target and that perceived by the observers. In Experiment 2, we introduced a revised procedure in which the target emotion category was disclosed prior to viewing, revealing that specifying the target emotion led to a different relationship between individual empathy traits and empathic accuracy than observed in Experiment 1. EMPAC thus provides a rich, temporally aligned resource for investigating empathy dynamics in naturalistic settings and for evaluating methodological variations in empathic accuracy paradigms.

Human recognition of objects as animate or inanimate is fast and accurate. However, this task may be challenging for objects with animal-like properties (e.g., presence of eyes/face), albeit being inanimate (e.g., a cow-mug). Lookalike objects provide an opportunity to examine how visual perception resolves categorical ambiguities and whether it exhibits an intrinsic bias to see animacy. During electroencephalography (EEG), we presented healthy humans with images of objects at a regular, rapid frequency (6 Hz), where every five exemplars of a standard category (animate or inanimate), an exemplar of the other oddball category was shown (1.2 Hz). In some conditions, oddball-stimuli were replaced by lookalikes. Periodic visual stimulation should give rise to a distinctive EEG response at 6 Hz. Moreover, if the oddball category elicits a different neural response than the standard category, a distinct response should be observed at 1.2 Hz. This categorization response was found for animate-oddballs among inanimate objects, and vice versa. It was also found for lookalike-oddballs presented among animate or inanimate objects, but it was significantly higher in the first case, implying that lookalike objects were perceived as more similar to inanimate than animate objects. The degree of animal resemblance modulated the amplitude of neural response to lookalikes, without however changing the category boundary. These results--also replicated in an artificial model of human vision--demonstrate that animal resemblance of objects is registered in visual perception, but it does not alter the critical ability to distinguish between what is truly alive and what is not.

Visual working memory (vWM) is often linked to conscious experience and visual imagery, but it is typically described as a system that stores separate, independent items. These assumptions are difficult to reconcile, given the unified nature of conscious experience. Here, we test the hypothesis that vWM relies on at least two distinct representations: an underlying, unconscious memory trace and a consciously accessible, integrated representation. A total of 216 participants performed a change-detection task, in which they rated their perceptual awareness of the memory display during the maintenance interval. Critically, we manipulated the statistical properties of the displays (average item size and size variability) to probe sensitivity to unified ensemble-level structure. Results revealed a dissociation between subjective and objective measures. Perceptual awareness increased for displays with larger, more variable items, whereas objective performance improved for displays with smaller, less variable items. Despite this difference, subjective awareness still predicted performance, and even incorrect responses showed consistent biases rather than random guesses. Importantly, individual differences in imagery vividness (VVIQ) were selectively associated with subjective awareness and estimation bias, but not with objective correctness. These precision biases were further shaped by display statistics, suggesting that multiple representations can guide behavior. Together, our findings support a reinterpretation of vWM performance in which task responses can draw on both unconscious and consciously accessible representations. One possible explanation for these behavioral patterns is that subjective experience reflects integrated, ensemble-like representations, while objective performance depends more strongly on item-specific information. Public significance statementsWorking memory allows us to temporarily hold and use information, and differences in this ability are closely linked to broader cognitive skills such as intelligence. This study shows that these differences may not depend only on how much information people can store, but also on how they experience it: some individuals appear to rely more on consciously accessible, image-like representations, especially when memory is uncertain or prone to error. By demonstrating that subjective experience and the vividness of imagery can shape behavior independently of objective accuracy, these findings suggest that how we use memory may be as important as how much we can store, with implications for understanding individual differences in cognition.

Insight is commonly studied in laboratory paradigms as a sudden shift in understanding accompanied by characteristic "Aha!" experiences. However, such paradigms may not capture the full phenomenological range of insight as it occurs in naturalistic contexts. This study examined insight experiences across psychedelic, everyday-life, and laboratory settings to characterise context-related differences in insight phenomenology and identify which dimensions predict perceived belief change. Using a within-subject, cross-sectional design, participants reported insight experiences across four contexts: psychedelic experiences, everyday-life insights, Compound Remote Associates problem-solving, and ambiguous image-based tasks. For each context, participants rated insights across multiple phenomenological dimensions. Ordinal mixed-effects models examined context effects and predictors of belief change. Psychedelic insights were rated higher than everyday insights across most dimensions, particularly intensity, meaning, ineffability, and belief change. In contrast, laboratory-based insights received substantially lower ratings, especially for meaning, belief change, and drive. Naturalistic-laboratory differences were largest for dimensions related to personal significance and transformation, particularly meaning and belief change, whereas core "Aha!" features such as confidence and pleasure showed smaller differences. Across naturalistic contexts, perceived meaning was the strongest predictor of belief change, with additional contributions from intensity and ineffability. After accounting for these phenomenological dimensions, context was not independently associated with belief change. These findings suggest that laboratory paradigms capture core features of insight but underrepresent dimensions related to personal meaning and belief updating. They further indicate that insight-related belief change depends less on context itself than on how the insight is experienced.

Study ObjectivesTo quantify high-resolution video-based eye kinematics across sleep macro- and microstructure and determine their coupling with pupil-based and cortical arousal markers. MethodsWe recorded polysomnography and utilized infrared video-based eye-tracking in 17 healthy adults. Computer vision was employed to extract eye position and speed, which were related to pupil size (subcortical arousal marker) and EEG spectral slope (cortical arousal marker) across sleep stages, rapid eye movement (REM) substates, and K-complexes. ResultsEye kinematics varied significantly across sleep stages (p<0.001), except for horizontal pupil position (p=0.192). Video-based eye position and speed are sufficient to classify stages with above chance level accuracy (47%). Eye movement speed positively correlated with pupil size during non-REM sleep (R[&ge;]0.21, p<0.001) and with spectral slope during wakefulness and REM sleep (R[&ge;]0.11, p<0.018). These strengths of the correlations differ depending on the direction of the eye movement. Phasic REM exhibited faster eye movements, larger pupil size (p<0.001), and a flatter spectral slope (p=0.014) compared to tonic REM, indicating elevated subcortical and cortical arousal. K-complexes were accompanied by increased eye movement speed (p<0.05) and a steeper spectral slope (p[&le;]0.010), suggesting a transient shift toward a sleep-protective cortical state despite concurrent oculomotor activation. ConclusionsVideo-based eye-tracking reveals that eye movements are quantitatively coupled to brain-wide arousal fluctuations in a state-dependent manner. This methodology provides a ground-truth framework for resolving fine-grained eye dynamics during sleep, offering a high-fidelity tool for sleep phenotyping and clinical assessment. Statement of significanceTraditional sleep monitoring relies on low-resolution electrical signals that often confound true eye movements with brain or muscle activity. This study uses high-resolution video tracking to establish a physical ground truth for eye kinematics across human sleep. We demonstrate that eye movements are coupled with both cortical and subcortical arousal levels in a state-dependent manner, providing a clearer neurophysiological distinction between, for example, sleep substates like tonic and phasic REM. This framework reveals how the eyes serve as a non-invasive window into the brains internal arousal state. Such insights address critical gaps in understanding sleep microarchitecture and offer a novel pathway for developing high-fidelity biomarkers for neurological disorders, such as Parkinsons disease, characterized by disrupted sleep-related arousal.

Two-dimensional accounts of consciousness that distinguish global integration from functional diversity are empirically supported [1,2] but lack a formal phase-structure: they do not specify the nature of the transition between the two regimes, the order parameter that governs it, or the quantitative predictions that follow. We provide this structure. We propose that the dimensionality of the neural correlation structure, operationalised as the Participation Ratio of the covariance eigenspectrum, constitutes a second, independent order parameter D that governs a phase transition distinct from global integration {Phi}. Formalised through a Landau-Ginzburg free energy functional F[{Phi}, D], this transition defines a Redundant Integrated State {Delta} (high {Phi}, low D) in which globally integrated mental function is present but phenomenal experience is absent, a thermodynamic phase, not a point on a continuum. The framework generates three falsifiable predictions absent from prior work: (i) a power-law scaling D* [~] |{Phi} - {Phi}_c|^{nu} with measurable critical exponent{nu} ; (ii) a diverging susceptibility {chi}_D = {partial}D/{partial}{Phi} at the consciousness threshold, quantifiable from perturbational EEG; (iii) an explicit dissociation between MCS and VS patients in the ({Phi}, D) space, with MCS predicted to occupy state {Delta}. These predictions are directly testable with existing methodology and are not generated by any current theory of consciousness.

Across contemplative traditions, deeper states of meditation are described as states of heightened clarity, vividness, and stillness of mind, yet what this clarity corresponds to in the brain has remained difficult to specify. The functional signal-to-noise ratio (f-SNR) framework frames mental clarity as a measurable property of neural signals: the degree to which brain activity tracks the causes of sensory signals rather than endogenous, irrelevant fluctuations. It predicts that deepening meditation should raise f-SNR, expressing sensory events more faithfully in neural signals against ongoing background activity. We tested this prediction across different levels of meditative depth. Twenty-nine experienced Vipassana practitioners meditated while auditory tones were presented, periodically reporting their depth of meditation. f-SNR was quantified from event-related potentials (ERPs) in a fronto-central P3 window and from single-trial decodability of auditory tone-evoked activity against no-tone background EEG. High-depth states were associated with greater ERP signal-to-noise ratio, stronger single-trial signal consistency, and improved decodability of auditory tones. These results suggest that meditative depth is expressed in the reproducibility and stimulus-background separability of sensory responses, consistent with deep meditation enhancing the brain's functional signal-to-noise ratio by improving the clarity of sensory signals and reducing endogenous noise.

Social media users often feel that time vanishes while scrolling, but real feeds confound novelty, rewards, social signals, and self-paced control, leaving the driver of this distortion unclear. We tested whether self-paced visual exploration is sufficient to compress subjective time by comparing active scrolling with passive, yoked viewing and a static baseline. Twenty-three adults viewed sequences of natural images under three within-subject conditions: Scrolling (self-paced mouse clicks), Watching (a passive, yoked replay of their own scrolling sequence), and a Baseline (a static image). Participants estimated the elapsed duration of each block. Subjective duration was most compressed under Scrolling (48% of elapsed time), followed by Watching (51%) and Baseline (65%). Two sources separated these effects. Adding back the empty inter-image fixations brought the image-rich conditions to within seconds of the Baseline, showing that observers barely counted the blank gaps; the Scrolling--Watching difference, by contrast, was independent of these shared gaps, isolating self-paced control as a second source of compression. Electrophysiology linked that control to anticipatory neural states and the timing of early visual responses, with no amplified encoding of individual images. The results favor an attention-weighted account of timing, on which subjective duration tracks how much attention reaches the clock, a resource that a self-paced stream and its uncounted gaps both draw away.

Light is a fundamental regulator of human physiology and behaviour. Whether prior light exposure shapes subsequent higher-order cognition and mood beyond the period of exposure remains unknown. We tested this in a within-subject, randomised crossover experiment in which 24 healthy young adult males completed a multimodal cognitive battery following 2 x15 min of full-spectrum light (FL; median 1,029 melanopic equivalent daylight illuminance [mEDI]) or standard indoor light (SL; median 234 mEDI), with all testing conducted under identical dim illumination. FL improved Digit-Symbol Substitution Test accuracy and promoted digit-directed gaze reallocation, consistent with more efficient associative encoding. On the Balloon Analogue Risk Task, FL reduced reward-seeking behaviour and suppressed backward-referencing gaze transitions linking current and prior-trial reward information. Mood declined following SL but remained stable after FL. Sustained attention, vigilance, and subjective sleepiness were unaffected. Our findings identify pre-task FL exposure as a selective primer of higher-order cognition and mood, independent of alertness.

Music is a fundamental medium for human communication, yet it remains unclear whether it enables genuine alignment of internally felt emotions beyond mere emotion perception. Creative expression may be central to this process: when performers improvise with creative intent, they engage in self-expression that could draw listeners into closer emotional and physiological resonance. Here, dual-electrocardiography was recorded across 37 performer-listener dyads while performers generated live improvisations under conventional, unconventional, or creative instructions. We show that creative improvisation enhances dyadic emotional alignment for both valence and arousal, and increases cardiac synchronization. Performer-listener alignment was strongest when performers felt and expressed emotions were themselves aligned, and when listeners showed a gradual arousal buildup. Creativity also elicited higher sublimity, lower unease and vitality, and greater diversity of selected emotional labels. These findings establish creativity as a mechanism through which music achieves one of its most celebrated functions: the creation of shared human experience.

Brain waves are ubiquitous phenomena of human brain activity. As they propagate, they coordinate neural communication, shaping conscious perception. Understanding how brain waves unfold across space and time is thus critical for uncovering the neural mechanisms that support and suppress consciousness. Here, we analyzed data from the Human Connectome Project alongside multiple independent human datasets of various states of consciousness collected during non-rapid eye movement sleep, propofol anesthesia, and psychedelic states produced by lysergic acid diethylamide, N,N-dimethyltryptamine, psilocybin, nitrous oxide, and ketamine. We then applied complex principal component analysis to map spatiotemporal propagation patterns of blood oxygen level-dependent activity across the human brain, under these diverse states of consciousness. We identified four dominant motifs of wave propagation: a global synchronized wave supporting unimodal-transmodal propagation, an anti-correlated unimodal-transmodal wave, an anti-correlated task-positive/task-negative wave, and an anti-correlated visual-somatomotor wave. Among them, the global wave exhibited the most pronounced state-dependent reconfiguration: in diminished states (sleep and anesthesia), the time needed for the wave to propagate across brain regions consistently increased and the distribution of regional contributions to the waves power became more spatially concentrated and heterogeneous across individuals, indicating slower, more fragmented, and less stereotyped dynamics. In contrast, propagation duration decreased under psychedelic states, reflecting accelerated global wave dynamics alongside a trend towards more spatially distributed and uniform regional contributions, consistent with a more integrated global wave propagation pattern. Beyond this global mode, diminished states slowed propagation primarily along the unimodal-transmodal axis, whereas psychedelic states selectively accelerated propagation along the task-positive/task-negative axis. Together, our findings reveal that diminished (sleep and anesthesia) and psychedelic states alter the spatiotemporal structure of wave propagation across the brain in opposite and distinct ways, providing a unifying account of how macroscale brain dynamics are dynamically reshaped under pharmacological and endogenous perturbations of consciousness.

Mind Blanking (MB) is a mental state characterized by the experience of a seemingly empty mind. This apparent emptiness challenges the theoretical view of a continuous and content-full stream of thought, leading to the question of how it is possible to capture MB events in the first place. MB research has relied largely on probe-caught experience-sampling, during which participants are interrupted at random times to report their mental state. This approach risks missing some MB events as they may occur between probes. Self-caught paradigms, on the other hand, allow participants to report MB upon spontaneously realizing it, relying on meta-awareness. To date, it is not clear whether these two methods capture the same phenomenon neuronally. Here, we investigated whether probe-caught MB (pMB) and self-caught MB (sMB) converge on their behavioral properties and brain correlates. Twenty-two participants underwent 3T fMRI scanning while performing both a pMB and a sMB experience-sampling task. We compared the behavioral properties, BOLD activations and time-varying functional connectivity (FC) across the two approaches. We found that reporting frequencies of pMB and sMB were significantly correlated across individuals, and both MB reports were uniformly distributed over time, pointing towards a behavioral convergence across approaches. However, we observed a divergence in BOLD activations, as sMB recruited significantly greater activation in the dorsal anterior cingulate cortex (dACC) compared to pMB, likely reflecting the meta-awareness and metacognitive monitoring required for self-detecting a MB. Lastly, time-varying FC analysis revealed a convergence, with both pMB and sMB FC resembling a hyperconnectivity pattern compared to other content-full mental states, pointing towards low arousal FC. Together, our results show that sMB and pMB converge on overlapping neurobehavioral correlates. This positions the self-caught method as a complementary tool for studying MB without external interruption, while highlighting the role of meta-awareness in self-report detection.

Flow, as defined by Mihalyi Csikszentmihalyi (1975), is a holistic sensation experienced when individuals are fully immersed in an activity, resulting in a mental state characterized by a diminished sense of self and altered perception of time. To investigate the global neural dynamics underlying flow, we employed EEG microstate analysis to capture the spatial and temporal properties of dominant transient global brain states (Lehmann et al., 1998). In a study involving 43 participants playing the video game Thumper for 25 minutes, we extracted three four-minute EEG segments from each session corresponding to reported experiences of flow, boredom, and frustration, as determined by self-reports and performance metrics. Across conditions, six distinct microstate topographies (A-F) accounted for most of the global variance. Given that reduced self-referential processing is a key feature of flow, we hypothesized that flow would modulate the properties of microstates C and E, which have been associated with brain regions resembling the default mode network (DMN). Compared to boredom and frustration, the flow condition showed significantly decreased global explained variance, mean duration, time coverage, and occurrence frequency of microstate E, as well as reduced mean duration and time coverage of microstate C. These findings suggest that microstates associated with self-referential processing are shorter and less frequent during flow than during boredom and frustration. This supports the notion that the flow experience modulates global brain dynamics, particularly within the DMN. Furthermore, our results align with previous research reporting reduced DMN activity during meditative and psychedelic states, reinforcing the idea of diminished self-awareness in such conditions.

Super-Recognisers show exceptional ability in face recognition, providing a natural model of how perceptual systems optimise for individuating visually similar stimuli in variable viewing conditions. However, the neural representations supporting this extreme perceptual expertise are unknown. Here, we tested whether Super-Recognisers (n = 23) differed from typical recognisers (n = 21) in the dimensional organisation of neural face identity coding. We recorded 64-channel electroencephalography while participants viewed random and rapidly-presented sequences containing 10 naturally varying images of 40 unfamiliar identities. Using time-resolved representational similarity analysis we measured the geometry of identity representations, their consistency across observers, and how clearly they specified face identity. Although neural expression of identity information was robust in both groups, we found three key differences between Super-Recognisers and typical recognisers. First, the geometry of face identity representations differed between groups. Second, Super-Recognisers showed greater inter-individual consistency in representational geometry. Third, Super-Recognisers' neural signals discriminated between face identities more strongly than those of typical recognisers. Differences in the coding of broader face categories (sex, age, ethnicity) were notably weaker, suggesting that the observed group differences reflected fine-scale differences in identity coding rather than global reshaping of representational geometry. Strikingly, all three differences emerged within a common mid-latency interval (~300-500ms), implicating higher-stages of face processing associated with representations that are sensitive to face familiarity and link between perceptual and semantic domains. Together, these findings indicate that individual differences in face recognition ability reflect higher-level differences in neural identity coding, rather than enhanced early sensory processing.