Nature reviews. Neuroscience
July 1, 2022
Anil K. Seth, Tim Bayne
836 citations
Four prominent theoretical approaches to consciousness are reviewed: higher-order theories, global workspace theories, re-entry and predictive processing theories, and integrated information theory. Each theory's key characteristics are described, including which aspects of consciousness they explain, their neurobiological commitments, and supporting empirical data. The review considers how empirical debates might distinguish among these theories and outlines three ways theories need to be developed for rigorous testing. Iterative development, testing, and comparison of these theories is expected to deepen understanding of consciousness.
Scientific Reports
April 19, 2017
Michael Schartner, Robin Carhart‐Harris, Adam B. Barrett et al.
450 citations
Measures of neural signal diversity, such as entropy and Lempel-Ziv complexity, are higher during wakeful rest than during anesthesia. In this study, these measures were computed for spontaneous magnetoencephalographic signals from humans under psilocybin, ketamine, and LSD. All three psychedelics produced reliably higher signal diversity, even after controlling for spectral changes, with the most pronounced increase in temporal (single-channel LZ complexity) rather than spatial diversity. Selective correlations emerged between changes in signal diversity and the intensity of psychedelic experience. This is the first time these measures have been applied to the psychedelic state and have yielded values exceeding normal waking consciousness, suggesting that psychedelic phenomenology constitutes an elevated level of consciousness.
Philosophy and the Mind Sciences
December 30, 2020
Jakob Hohwy, Anil K. Seth
162 citations
The search for the neural correlates of consciousness needs a systematic, principled foundation to give putative correlates greater predictive and explanatory value. The predictive processing framework for brain function is proposed as a promising candidate because it addresses three general challenges to identifying neural correlates and satisfies two constraints common to many theories of consciousness. Implementing the search through this lens can yield detailed, systematic mappings between neural substrates and phenomenological structure. The framework, precisely because it is not itself a theory of consciousness, has significant potential for advancing the neuroscience of consciousness.
bioRxiv (Cold Spring Harbor Laboratory)
November 2, 2020
Pedro A. M. Mediano, Fernando E. Rosas, Christopher Timmermann et al.
39 citations
preprint
Psychedelics reliably increase brain entropy (neural signal diversity), an effect linked to psychological changes and opposite to the decrease seen during loss of consciousness. This study investigated how context—specifically stimulus manipulation—modulates that entropy increase. Participants under LSD or placebo experienced eyes-closed versus eyes-open conditions, or no stimulus, music, or video. Brain entropy rose with LSD across all conditions but was largest with eyes closed. Entropy changes consistently matched subjective ratings of the psychedelic experience, except during video viewing, suggesting competition between external stimuli and internal LSD-induced imagery. The findings provide quantitative evidence that context shapes neural dynamics during psychedelic experiences, supporting the practice of eyes-closed psychedelic psychotherapy, and challenge simplistic views of brain entropy as a direct measure of conscious level.
bioRxiv (Cold Spring Harbor Laboratory)
January 4, 2019
David J. Schwartzman, Michael Schartner, Benjamin B. Ador et al.
31 citations
preprint
Stroboscopic stimulation—flashing light—can induce altered states of consciousness without drugs, increasing the intensity and range of subjective experiences, including simple and complex visual hallucinations. These experiences were accompanied by rises in EEG signal diversity, measured by Lempel-Ziv complexity, that exceeded levels seen during wakeful rest. The results align with previous findings from psychedelic studies and support the idea that neural signal diversity reflects the richness of subjective experience across different states of consciousness.
Frontiers in Human Neuroscience
January 3, 2024
Keisuke Suzuki, Anil K. Seth, David J. Schwartzman
20 citations
Visual hallucinations differ substantially depending on their cause, such as neurodegenerative disease, visual loss, or psychedelic drugs. Using a deep neural network approach called computational (neuro)phenomenology, researchers identified three key dimensions that distinguish these hallucinations: realism (how true-to-life they seem), spontaneity (how much they depend on sensory input), and complexity. By tuning the network along these dimensions, they generated synthetic hallucinations characteristic of each cause. Two studies with patients having Parkinson's disease, Lewy body dementia, or Charles Bonnet syndrome, and people with recent psychedelic experience, confirmed that these synthetic images matched the phenomenology reported by each group. The findings show that a neural network model can capture the distinctive visual features of hallucinations from different origins.
bioRxiv (Cold Spring Harbor Laboratory)
July 16, 2019
Lionel Barnett, Suresh Muthukumaraswamy, Robin Carhart‐Harris et al.
10 citations
preprint
Psychedelic drugs such as LSD, psilocybin, and low-dose ketamine reduce directed functional connectivity—the flow of information—across the brain, as measured by Granger causality in source-localised MEG recordings. This breakdown in organised information flow supports the idea that the psychedelic state disrupts normal patterns of neural communication. With LSD specifically, directed connectivity decreased while undirected connectivity (measured by correlation and coherence) increased, an opposite movement that highlights the importance of using multiple connectivity measures when analyzing time-resolved neuroimaging data. The non-psychedelic anticonvulsant tiagabine was included for comparison.
Pedro A.M. Mediano, Fernando E. Rosas, Andrea I. Luppi et al.
10 citations
A new method called Complexity via State-space Entropy Rate (CSER) estimates neural signal complexity with better temporal resolution and spectral decomposition than the standard Lempel-Ziv complexity (LZ) approach. CSER matches LZ in distinguishing conscious states but offers two key advantages: it can break complexity down by frequency bands, and it provides temporal resolution about 100 times finer. Using MEG, EEG, and ECoG data from humans and monkeys, CSER revealed that gamma-band activity primarily drives complexity changes across states of consciousness. In an auditory mismatch negativity experiment, CSER detected early entropy increases roughly 20 milliseconds before the standard event-related potential. This method enables finer-grained study of how signal complexity relates to cognitive processes and conscious states.
bioRxiv (Cold Spring Harbor Laboratory)
March 11, 2025
Devon Stoliker, Leonardo Novelli, Moein Khajehnejad et al.
8 citations
preprint
Psychedelics like psilocybin alter consciousness by reorganizing brain connectivity in a context-sensitive way. In the largest psychedelic neuroimaging dataset to date, 62 adults underwent functional MRI and EEG before and after ingesting 19 mg of psilocybin, during rest and naturalistic stimuli. Under psilocybin, brain signals during eyes-closed conditions became similar to those during eyes-open conditions, with increased global functional connectivity in associative regions and decreased connectivity in sensory areas. Machine learning linked subjective effects to structured neural activity patterns. Stronger self-dissolving effects were associated with more distinct neural representations and next-day mindset changes, revealing a state of 'embeddedness' where networks that usually segregate internal and external processing integrate coherently, aligning neural dynamics with context.
bioRxiv Preprint Server
July 16, 2025
Borjan Milinkovic, Anil K. Seth, Lionel Barnett et al.
2 citations
preprint
Consciousness depends on neural activity across many scales. A new measure, dynamical independence (DI), quantifies these multi-scale relationships. Applying DI to EEG data from people under three anaesthetics, the authors found that propofol and xenon—which abolish conscious report—produce more emergent but highly variable dynamic structure, indicating fragmented macroscopic organisation. Ketamine, which preserves dream-like states, shows reduced overall emergence but partial preservation of macroscopic structure similar to wakefulness. Regional brain contributions varied. The results reveal drug-specific reconfigurations of emergent dynamics, dissociate the amount of emergence from its organisation, and caution against equating emergence with consciousness level.
bioRxiv Preprint Server
November 3, 2017
Keisuke Suzuki, Warrick Roseboom, David J. Schwartzman et al.
2 citations
preprint
A tool called the Hallucination Machine simulates visual hallucinatory experiences using deep convolutional neural networks and panoramic virtual reality videos of natural scenes. It induces visual phenomenology qualitatively similar to classical psychedelics, but does not evoke the temporal distortion commonly associated with altered states. This technique allows researchers to study altered consciousness without the confounding physiological and cognitive effects of psychoactive substances or psychopathological conditions, offering a valuable method for consciousness science and psychiatry.
bioRxiv (Cold Spring Harbor Laboratory)
February 18, 2026
Ethan Grove, Trevor Hewitt, Anil K. Seth et al.
1 citation
Visual hallucinations (VHs) occur in psychedelic states and various psychiatric and neurological conditions, but their phenomenology is hard to characterize due to a lack of large-scale datasets. Stroboscopic light stimulation (SLS) with closed eyes reliably induces VHs in healthy people, producing vivid colors and dynamic geometric patterns similar to simple VHs in other contexts. Researchers developed an unsupervised computer-vision pipeline to analyze 10,598 drawings made after hallucination-inducing SLS at a public installation. Most drawings contained geometric forms, consistent with prior observations, but novel patterns like concentric squares, crosses, and hyperbolic shapes also appeared. The pipeline organized the drawings into interpretable classes, mapping the diversity of simple geometric VHs and placing new constraints on theoretical accounts.
PLoS ONE
December 4, 2025
Jonathan Robinson, Andrew W. Corcoran, Christopher J. Whyte et al.
1 citation
Active inference, a framework for modeling how sentient agents behave, is being tested as necessary for changes in conscious content. In an adversarial collaboration, active inference will be contrasted with two other theories that do not require it for consciousness. This study protocol describes an adaptation of the motion-induced blindness paradigm: an active condition where participants direct their gaze toward a target after it disappears from consciousness and report its reappearance, versus a passive condition where participants fixate centrally while the stimulus array moves in a replay of active eye-tracking data. Two experiments will compare target reappearance across conditions to evaluate active inference's contribution to conscious awareness.
December 13, 2024
Trevor Hewitt, Ioanna Amaya, Romy Beauté et al.
preprint
Exposure to rapid and bright stroboscopic light can induce vivid visual hallucinations of color and geometric forms, a phenomenon first documented by Purkinje over 200 years ago. Despite centuries of scientific, therapeutic, and cultural interest, fundamental questions remain about its phenomenology, physiological origins, and potential clinical applications. This narrative review summarizes the historical research on stroboscopic light stimulation, its use in recreational and lay-therapeutic settings, and discusses the phenomenology of these experiences. It also examines current perspectives on the neural mechanisms that may underlie stroboscopically induced experiences and outlines directions for future research.
medRxiv Preprint Server
June 17, 2026
Danny Nacker, Luise Kalus, Anil K. Seth et al.
preprint
Supervised stroboscopic light stimulation (SLS) was safe, tolerable, and feasible in adults with depressive symptoms, but efficacy was not established. In a staged program, 31 participants tested 11 SLS parameter sets; no severe adverse reactions occurred, and mean discomfort was low (0.49 out of 10). A subsequent randomized trial assigned 84 participants to four weekly 31-minute sessions of SLS or a low-phenomenology control. Retention was 83.3% (70 of 84 participants), with higher retention in the intervention arm (39 of 42) than the control arm (31 of 42). Exploratory depressive-symptom changes suggested a possible signal on the BDI-II but do not confirm efficacy. The next step is a Phase 2a feasibility trial with a locked protocol.
arXiv Preprint Archive
February 25, 2025
Romy Beauté, David J. Schwartzman, Guillaume Dumas et al.
Stroboscopic light stimulation on closed eyes typically induces simple visual hallucinations—vivid, geometric, and colorful patterns. An analysis of 862 open-ended reports from the Dreamachine immersive experience, using large language models and topic modeling, confirmed these simple hallucinations and also revealed altered states of consciousness and complex hallucinations. This computational approach enables systematic study of subjective experiences beyond standard questionnaires, capturing subtle patterns not readily identified through closed-form questions. The findings broaden understanding of stroboscopically induced phenomena and demonstrate the potential of natural language processing in computational neurophenomenology.
arXiv Preprint Archive
October 9, 2024
Christopher J. Whyte, Andrew W. Corcoran, Jonathan Robinson et al.
Subjective experience is multifaceted, making consciousness hard to study because traditional theories often focus on isolated aspects like perception or wakefulness and are difficult to compare. This work starts from active inference—a first-principles framework that models behavior as approximate Bayesian inference—and builds toward a minimal theory of consciousness derived from shared features of computational models under active inference. Reviewing models applied to consciousness, the authors argue that these models imply a small set of theoretical commitments pointing to a minimal, testable theory of consciousness.
arXiv Preprint Archive
September 30, 2024
Lancelot da Costa, Anil K. Seth, Karl Friston et al.
A Rosetta Stone hypothesis from predictive processing proposes that beliefs serve as a central hub linking phenomenology, behavior, and neural dynamics. If phenomenology is a function of beliefs, then specific predictions follow for subjective similarity judgments, cognitive metabolic cost, subjective cognitive effort, and time perception. The connection between beliefs and neural dynamics completes the generative passage for neurophenomenology, while the belief-behavior link is already well-documented. Testing these predictions will inform the validity of the central assumption and advance the neurophenomenology research program.