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Journal articleSubramani V, Nest T, Pascarella A, et al., 2026,
LSD reconfigures cortical dynamics through faster brain rhythms and increased fractal dimension.
, Commun Biol, Vol: 9Lysergic acid diethylamide (LSD) profoundly alters conscious experience, yet the electrophysiological mechanisms by which it reshapes neural dynamics remain incompletely understood. A hallmark of psychedelic states is widespread cortical desynchronization, typically inferred from reductions in spectral power, but whether such effects reflect genuine weakening of neural oscillations or are confounded by shifts in oscillatory peak frequencies remains unresolved. We combine source-resolved magnetoencephalography (MEG), spectral parameterization, temporal complexity metrics, and interpretable machine learning in an LSD versus placebo design, with and without music. We show that LSD induces robust, spatially structured increases in alpha and beta peak frequencies alongside genuine attenuation of oscillatory power, with partly dissociable cortical patterns. Beyond rhythmic activity, LSD is associated with flattening of the aperiodic 1/f spectral slope and increased neural signal fractality and complexity, preferentially affecting sensory, language, emotion, and imagery-related networks while sparing motor cortex. Machine-learning analyses identify peak-frequency shifts, aperiodic parameters, and complexity measures as key discriminators of the psychedelic state. Music does not robustly amplify these neural signatures and instead shows a trend toward attenuation. These findings provide an electrophysiological account of how LSD reorganizes large-scale human brain dynamics and highlight features that may differentiate its neural signature from other psychedelics.
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Journal articleCarhart-Harris RL, 2026,
The entropic brain today.
, Brain, Vol: 149, Pages: 3362-3378Introduced in 2014 and revised in 2018, the entropic brain hypothesis has accrued a wealth of supportive evidence. The hypothesis states that-along a dimension of 'the size of phenomenal consciousness'-expansive states reliably exhibit increased brain entropy, whereas the inverse applies for states of no or reduced consciousness. Examples of expansive states include expert meditation, flicker-light stimulation, near-death-like experiences, atypical breathing, REM sleep, the pre-ictal aura, unmedicated early psychosis and psychedelic drug states. Examples of states of no or reduced consciousness with low brain entropy, include disorders of consciousness, deep sleep, the anaesthetized state, seizure, post-stroke, ageing, cognitive impairment and neurodegenerative illness. It is shown that the entropic brain has convergent, correlative, predictive, discriminative and external validity. Regarding its predictive validity, increased brain entropy under psilocybin (in a supportive context) predicts subsequent improvements in mental health (improved well-being 1-month post-dose). Regarding its discriminative validity, changes in brain entropy selectively index the 'breadth of subjective experience' versus alternative dimensions, such as arousal. Regarding portability/external validity, an entropy-related function is applied in generative artificial intelligence. In conclusion, the entropic brain is a useful model of conscious states.
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Journal articleErritzoe D, 2026,
Sex-related differences in outcomes following psilocybin or escitalopram: a Bayesian secondary analysis
, Psychopharmacology, ISSN: 0033-3158Rationale: Major depressive disorder (MDD) shows marked sex differences in prevalence, symptomatology, and treatment response. However, females remain underrepresented in many clinical trials, and sex-specific treatment outcomes are rarely examined.Objectives: This study reanalyzed data from a randomized controlled trial comparing psilocybin and escitalopram for MDD to evaluate sex differences across multiple psychological domains.Methods: We conducted a post hoc Bayesian analysis of a six-week, double-blind trial in adults with moderate-to-severe MDD (N=59; 20 female; psilocybin n=30, 11 female; escitalopram n=29, 9 female). Post-treatment depression, anhedonia, anxiety, thought suppression, and well-being were modeled by sex, treatment, sex-by-treatment interaction, and baseline score. Sexual dysfunction, measured post-treatment only, was analyzed ordinally. Prior-sensitivity analyses used narrower and wider priors.Results: No outcome showed an overall sex difference across treatments. Within psilocybin, females had lower post-treatment anxiety than males (STAI adjusted difference = -8.77, 95% CrI = -15.73 to -1.73; BFany = 11.18), although the estimate varied across priors and the narrowest prior included zero. The sex-by-treatment interaction was inconclusive (difference=-8.62, 95% CrI=-18.36 to 1.30; BFany=2.55). A directional female advantage in anhedonia with escitalopram was unsupported by Bayes factors. No sex differences emerged on depression scales. Among males, sexual dysfunction was lower with psilocybin than with escitalopram. Within escitalopram, females reported less sexual dysfunction than males.Conclusions: This reanalysis identified sex-related patterns in anxiety under psilocybin but no clear treatment-specific interaction. Findings support adequately powered, sex-balanced trials incorporating hormonal and reproductive factors.
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Journal articleRosas FE, Mediano PAM, Luppi AI, et al., 2026,
Four faces of information in natural systems
, Nature Reviews Physics, Vol: 8, Pages: 654-666The idea of ‘information’ has been instrumental to advances in multiple fields of physics and natural science more broadly. However, despite — or perhaps because of — its pervasiveness, this key notion is used in such a wide range of settings that it is unclear whether there is coherence underpinning all these applications. Instead of advocating for a monolithic perspective, we posit that information has come to bear a number of different technical interpretations, which are usually not sufficiently disambiguated. Following this idea, in this Perspective, we put forward a pluralistic approach towards information, wherein multiple technical interpretations coexist — each bringing its own affordances and restrictions. We outline four different technical senses in which information is currently used in scientific research, which we describe as the engineering, statistical, thermodynamic and ontological ‘faces’ of information. Disambiguating the domain and scope of these faces may help to avoid misinterpretations. We also highlight the complementarity of distinct, yet equally valid applications of an information lens for natural systems.
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Journal articleSuresh P, Kins J, Levkovskyy L, et al., 2026,
Moving beyond 5-HT2A: language models map neurotransmitter receptors to experiential semantics.
, Psychopharmacology (Berl)RATIONALE: Psychedelics exhibit rapid, durable therapeutic effects across diverse psychiatric conditions, yet their broad-spectrum psychoactivity poses challenges for clinical translation. OBJECTIVES: As a proof-of-concept, we aimed to quantify associations between 19 neurotransmitter receptors and the subjective effects of 21 psychedelic drugs with broadly assayed binding profiles. METHODS: We used a custom Global Vectors for Word Representation (GloVe)-based semantic embedding model trained on 4,496 firsthand experience reports and integrated it with receptor affinities to identify candidate receptor-linked semantic patterns related to distinct psychoactive effects without imposing predefined categorization systems. RESULTS: While 5-HT2A predictably associates with classic facets of psychedelic experience, our analysis reveals novel associations, including 5-HT1A and 5-HT1B with 'Cognitive Disruption', H1 with 'Interdimensional Communication', and 5-HT7a and 5-HT1E with 'Visual Complexity'.
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Journal articleRichardson B, O'Byrne J, Bruno V, et al., 2026,
410. Comparative neurophysiological signatures of psychedelics, stimulants and anesthetics in rodent cortical activity
, International Journal of Neuropsychopharmacology, Vol: 29, Pages: i82-i83, ISSN: 1461-1457<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>Psychedelics induce altered states of consciousness (AOC) with profound perceptual, cognitive, and emotional shifts, often linked to positive therapeutic outcomes. Although serotonergic psychedelics such as psilocybin, LSD, and 5-MeO-DMT share receptor targets, they differ in behavioral and neural effects. How these compounds alter cortical dynamics relative to other consciousness-modulating agents, including dopaminergic stimulants and anesthetics, remains unclear.</jats:p> </jats:sec> <jats:sec> <jats:title>Aims & Objectives</jats:title> <jats:p>We aimed to delineate the compound-specific neurophysiological signatures of serotonergic psychedelics, dopaminergic stimulants, and anesthetics by examining cortical oscillations, muscular activity, signal complexity, and spectral entropy.</jats:p> </jats:sec> <jats:sec> <jats:title>Method</jats:title> <jats:p>Rodents received i.p. injections of psilocybin (6 mg/kg), LSD (0.2 mg/kg), 5-MeO-DMT (10 mg/kg), lisuride (0.5 mg/kg), d-amphetamine (5 mg/kg), or propofol (100 mg/kg). Electrocorticography (ECoG) and electromyography (EMG) recorded cortical and muscular activity. Analyses included absolute and relative power across canonical delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13Hz), beta (13-30Hz), and gamma (30-40 Hz) bands, Lempel-Ziv complexity (LZ) and Higuchi fractal dimension (HFD) to assess signal diversity, and spectral entropy to quantify frequency-specific unpredictability. Principal component and clustering analyses identified compound-specific patterns.</jats:p> </jats:sec>
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Journal articleKroupi E, Araujo H, Oosterveld C, et al., 2026,
Higher signal diversity, network dysregulation, and increased well-being under DMT administration: An EEG study.
, Brain Res, Vol: 1892N,N-Dimethyltryptamine (DMT), a potent serotonin-2A receptor agonist, elicits intense psychedelic experiences and has become a focus of interest in neuroscience and mental health research. While EEG studies of psychedelics typically report reduced alpha power, increased delta power, and enhanced signal complexity-primarily assessed using Lempel-Ziv complexity (LZc)-less is known about DMT's effects on other complexity metrics, EEG-based connectivity, and emotional correlates. This study investigated the effects of intravenous DMT versus saline placebo in 13 healthy participants using EEG. We analyzed spectral power, brain signal complexity, and functional connectivity, and examined their associations with emotional responses and subjective intensity ratings. Four complexity measures were evaluated: Lempel-Ziv-Welch (LZW) complexity, Higuchi fractal dimension (HFD), permutation entropy (PE), and waveform complexity (WC). Connectivity was assessed using weighted symbolic mutual information (wSMI), with network segregation and efficiency inferred from clustering coefficient and path length. Emotional correlates included beta-to-alpha ratio (BAR, an indicator of arousal) and frontal alpha asymmetry (FAA, an indicator of well-being). DMT significantly reduced broadband wSMI connectivity, segregation, and efficiency, particularly in alpha and beta bands in posterior and frontoparietal regions. Complexity metrics positively correlated with subjective intensity; HFD and PE were the most sensitive, revealing increased complexity in beta/gamma and decreased complexity in delta/theta/alpha bands under DMT. BAR and FAA both increased under DMT, correlating with perceived intensity. These findings suggest that DMT induces greater neural unpredictability and emotional arousal, consistent with the Entropic Brain theory. The results highlight a dynamic brain state that may support therapeutic brain network reorganization relevant for psychiatric treatment.
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Journal articleCarhart-Harris RL, Rosenblat JD, 2026,
Psychedelics Trials and Outcomes-A Closer Look.
, JAMA Psychiatry, Vol: 83, Pages: 990-991 -
Journal articleHancock F, Kee R, Rosas F, et al., 2026,
A complexity-science framework for studying flow: using media to probe brain-phenomenology dynamics.
, Neuroimage, Vol: 338Consciousness spans a range of phenomenological experiences, from effortless immersion to disengaged monotony, yet how such phenomenology emerges from brain activity is not well understood. Flow, a phenomenological experience frequently elicited by interactive media, has drawn attention for its links to performance and wellbeing, but existing neural accounts rely on single-region or small-network analyses that overlook the brain's distributed and dynamic nature. Complexity science offers tools that capture brain-wide dynamics, but this approach has rarely been applied to flow or to its natural comparisons: boredom and frustration. Consequently, it remains unclear whether tools drawn from complexity science can objectively discriminate between these phenomenological experiences while also clarifying their neural basis. To address this uncertainty, we induced each phenomenological experience with a difficulty-titrated video game during functional magnetic resonance imaging and collected concurrent behavioral and self-report data. Our complex systems analyses revealed that flow, in this experimental setup, shows an inverse relationship to global entropy with moderate explanatory power, and is not explained by either synchronization or metastability, whereas boredom and frustration exhibit different configurations of brain-dynamics metrics. Notably, these findings integrate previously separate prefrontal and network-synchrony observations within a single dynamical systems framework and identify complexity-based markers with the potential to map the neural underpinnings of media-related benefits.
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Journal articleAustin B, Kurtin DL, Herlinger K, et al., 2026,
Investigating hierarchical control among functional networks disrupted by Opioid Use Disorder using effective connectivity
, Imaging Neuroscience, ISSN: 2837-6056Opioid use disorder (OUD) poses a significant public health challenge. Developing a better understanding of the brain mechanisms and potential markers of OUD would facilitate the development of therapeutic interventions. While we recently showed that between-network connectivity is disrupted in people with OUD compared with healthy controls, it remains unclear what mechanisms may drive these disruptions and how dysfunctional interactions propagate across large scale functional networks. To advance the mechanistic understanding of the disrupted processes in OUD, this study used Effective Connectivity (EC) to quantify disrupted hierarchical control among functional networks governing cognition, attention, and reward. We also explored whether whole-brain patterns of EC were effective markers to distinguish people with severe OUD from controls. We hypothesised that the ventromedial network (VMN) would drive dysfunction in cognitive and attentional networks in people with OUD. Task-fMRI data was collected from healthy controls (HC; n=22) and OUD participants on methadone maintenance treatment (OUD; n=25), during a heroin cue reactivity (CR) and monetary incentive delay (MID) task. Following brain parcellation (214 regions) and network assignment (7 functional networks), EC was quantified using large scale nonlinear Granger causality. Dimensionality reduction was performed using uniform manifold approximation and projection, followed by hierarchical density-based spatial clustering of applications with noise to assess whether EC patterns could form clusters corresponding to group labels.Contrary to our hypothesis, the VMN did not drive dysfunction in cognitive and attentional networks. Instead, edges with significantly stronger EC in HC vs OUD participants were within and between the control, somatomotor, and default mode networks. EC patterns were unable to form distinct clusters that corresponded to clinical groups; instead, clusters separated by task. Little evidence w
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