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How is the information-processing architecture of the human brain organised, and how does its organisation support consciousness? Here, we combine network science and a rigorous information-theoretic notion of synergy to delineate a 'synergistic global workspace', comprising gateway regions that gather synergistic information from specialised modules across the human brain. This information is then integrated within the workspace and widely distributed via broadcaster regions. Through functional MRI analysis, we show that gateway regions of the synergistic workspace correspond to the human brain's default mode network, whereas broadcasters coincide with the executive control network. We find that loss of consciousness due to general anaesthesia or disorders of consciousness corresponds to diminished ability of the synergistic workspace to integrate information, which is restored upon recovery. Thus, loss of consciousness coincides with a breakdown of information integration within the synergistic workspace of the human brain. This work contributes to conceptual and empirical reconciliation between two prominent scientific theories of consciousness, the Global Neuronal Workspace and Integrated Information Theory, while also advancing our understanding of how the human brain supports consciousness through the synergistic integration of information.
The human brain consists of billions of neurons which process sensory inputs, such as sight and sound, and combines them with information already stored in the brain. This integration of information guides our decisions, thoughts, and movements, and is hypothesized to be integral to consciousness. However, it is poorly understood how the brain regions responsible for processing this integration are organized in the brain. To investigate this question, Luppi et al. employed a mathematical framework called Partial Information Decomposition (PID) which can distinguish different types of information: redundancy (available from many regions) and synergy (which reflects genuine integration). The team applied the PID framework to the brain scans of 100 individuals. This allowed them to identify which brain regions combine information from across the brain (known as gateways), and which ones transmit it back to the rest of the brain (known as broadcasters). Next, Luppi et al. set out to find how these regions compared in unconscious and conscious individuals. To do this, they studied 15 healthy volunteers whose brains were scanned (using a technique called functional MRI) before, during, and after anaesthesia. This revealed that the brain integrated less information when unconscious, and that this reduction happens predominantly in gateway rather than broadcaster regions. The same effect was also observed in the brains of individuals who were permanently unconscious due to brain injuries. These findings provide a way of understanding how information is organised in the brain. They also suggest that loss of consciousness due to brain injuries and anaesthesia involve similar brain circuits. This means it may be possible to gain insights about disorders of consciousness from studying how people emerge from anaesthesia.
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Encéfalo , Estado de Conciencia , Imagen por Resonancia Magnética , Humanos , Estado de Conciencia/fisiología , Encéfalo/fisiología , Encéfalo/diagnóstico por imagen , Masculino , Adulto , Femenino , Adulto Joven , Red en Modo Predeterminado/fisiologíaRESUMEN
Psychological network approaches propose to see symptoms or questionnaire items as interconnected nodes, with links between them reflecting pairwise statistical dependencies evaluated on cross-sectional, time-series, or panel data. These networks constitute an established methodology to visualise and conceptualise the interactions and relative importance of nodes/indicators, providing an important complement to other approaches such as factor analysis. However, limiting the representation to pairwise relationships can neglect potentially critical information shared by groups of three or more variables (higher-order statistical interdependencies). To overcome this important limitation, here we propose an information-theoretic framework to assess these interdependencies and consequently to use hypergraphs as representations in psychometrics. As edges in hypergraphs are capable of encompassing several nodes together, this extension can thus provide a richer account on the interactions that may exist among sets of psychological variables. Our results show how psychometric hypergraphs can highlight meaningful redundant and synergistic interactions on either simulated or state-of-the-art, re-analysed psychometric datasets. Overall, our framework extends current network approaches while leading to new ways of assessing the data that differ at their core from other methods, enriching the psychometrics toolbox, and opening promising avenues for future investigation.
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Striking progress has been made in understanding cognition by analyzing how the brain is engaged in different modes of information processing. For instance, so-called synergistic information (information encoded by a set of neurons but not by any subset) plays a key role in areas of the human brain linked with complex cognition. However, two questions remain unanswered: (a) how and why a cognitive system can become highly synergistic; and (b) how informational states map onto artificial neural networks in various learning modes. Here we employ an information-decomposition framework to investigate neural networks performing cognitive tasks. Our results show that synergy increases as networks learn multiple diverse tasks, and that in tasks requiring integration of multiple sources, performance critically relies on synergistic neurons. Overall, our results suggest that synergy is used to combine information from multiple modalities-and more generally for flexible and efficient learning. These findings reveal new ways of investigating how and why learning systems employ specific information-processing strategies, and support the principle that the capacity for general-purpose learning critically relies on the system's information dynamics.
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Encéfalo , Cognición , Aprendizaje , Modelos Neurológicos , Redes Neurales de la Computación , Humanos , Aprendizaje/fisiología , Cognición/fisiología , Encéfalo/fisiología , Biología Computacional , Neuronas/fisiologíaRESUMEN
Disentangling how cognitive functions emerge from the interplay of brain dynamics and network architecture is among the major challenges that neuroscientists face. Pharmacological and pathological perturbations of consciousness provide a lens to investigate these complex challenges. Here, we review how recent advances about consciousness and the brain's functional organisation have been driven by a common denominator: decomposing brain function into fundamental constituents of time, space, and information. Whereas unconsciousness increases structure-function coupling across scales, psychedelics may decouple brain function from structure. Convergent effects also emerge: anaesthetics, psychedelics, and disorders of consciousness can exhibit similar reconfigurations of the brain's unimodal-transmodal functional axis. Decomposition approaches reveal the potential to translate discoveries across species, with computational modelling providing a path towards mechanistic integration.
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Encéfalo , Estado de Conciencia , Humanos , Estado de Conciencia/fisiología , Encéfalo/fisiología , Animales , Cognición/fisiologíaRESUMEN
Understanding how different networks relate to each other is key for understanding complex systems. We introduce an intuitive yet powerful framework to disentangle different ways in which networks can be (dis)similar and complementary to each other. We decompose the shortest paths between nodes as uniquely contributed by one source network, or redundantly by either, or synergistically by both together. Our approach considers the networks' full topology, providing insights at multiple levels of resolution: from global statistics to individual paths. Our framework is widely applicable across scientific domains, from public transport to brain networks. In humans and 124 other species, we demonstrate the prevalence of unique contributions by long-range white-matter fibers in structural brain networks. Across species, efficient communication also relies on significantly greater synergy between long-range and short-range fibers than expected by chance. Our framework could find applications for designing network systems or evaluating existing ones.
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BACKGROUND: There is growing evidence for the therapeutic effects of the psychedelic drug psilocybin for major depression. However, due to the lack of safety data on combining psilocybin with selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs) and concerns that there may be a negative interaction on efficacy, participants enrolling in psychedelic trials are usually required to discontinue SNRI/SNRIs prior to enrolling. AIMS: Using data from a recent clinical trial examining the comparative efficacy the psychedelic drug psilocybin (P) combined with approximately 20 h of psychological support to a 6-week (daily) course of the SSRI escitalopram plus matched psychological support for major depressive disorder, we explored the effects of discontinuing SSRI/SNRIs prior to study enrolment on study outcomes. METHODS: Exploratory post hoc analyses using linear mixed effects model were performed to investigate the discontinuation effect on various validated depression symptom severity scales and well-being. The impact of SSRI/SNRIs discontinuation on the acute psychedelic experience was also explored. RESULTS/OUTCOMES: In the psilocybin group, there was a reduced treatment effect on all outcome measures for SSRI/SNRIs discontinuers compared with unmedicated patients at trial entry. However, no effects of discontinuation on measures of the acute psychedelic experience were found. CONCLUSION: Discontinuation of SSRI/SNRIs before psilocybin might diminish response to treatment; however, as we did not test SSRI/SNRI continuation in our trial, we cannot infer such causation. Moreover, the exploratory nature of the analyses makes them hypothesis generating, and not confirmatory. A controlled trial of SSRI/SNRI discontinuation versus continuation prior to psilocybin is urgently required.
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Trastorno Depresivo Mayor , Escitalopram , Alucinógenos , Psilocibina , Inhibidores Selectivos de la Recaptación de Serotonina , Humanos , Psilocibina/administración & dosificación , Psilocibina/farmacología , Psilocibina/efectos adversos , Trastorno Depresivo Mayor/tratamiento farmacológico , Adulto , Masculino , Inhibidores Selectivos de la Recaptación de Serotonina/administración & dosificación , Inhibidores Selectivos de la Recaptación de Serotonina/efectos adversos , Inhibidores Selectivos de la Recaptación de Serotonina/farmacología , Femenino , Alucinógenos/administración & dosificación , Alucinógenos/efectos adversos , Alucinógenos/farmacología , Escitalopram/administración & dosificación , Escitalopram/farmacología , Persona de Mediana Edad , Resultado del Tratamiento , Quimioterapia CombinadaRESUMEN
Recent research is revealing how cognitive processes are supported by a complex interplay between the brain and the rest of the body, which can be investigated by the analysis of physiological features such as breathing rhythms, heart rate, and skin conductance. Heart rate dynamics are of particular interest as they provide a way to track the sympathetic and parasympathetic outflow from the autonomic nervous system, which is known to play a key role in modulating attention, memory, decision-making, and emotional processing. However, extracting useful information from heartbeats about the autonomic outflow is still challenging due to the noisy estimates that result from standard signal-processing methods. To advance this state of affairs, we propose a novel approach in how to conceptualise and model heart rate: instead of being a mere summary of the observed inter-beat intervals, we introduce a modelling framework that views heart rate as a hidden stochastic process that drives the observed heartbeats. Moreover, by leveraging the rich literature of state-space modelling and Bayesian inference, our proposed framework delivers a description of heart rate dynamics that is not a point estimate but a posterior distribution of a generative model. We illustrate the capabilities of our method by showing that it recapitulates linear properties of conventional heart rate estimators, while exhibiting a better discriminative power for metrics of dynamical complexity compared across different physiological states.
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Sistema Nervioso Autónomo , Corazón , Frecuencia Cardíaca/fisiología , Teorema de Bayes , Sistema Nervioso Autónomo/fisiología , Encéfalo/fisiologíaRESUMEN
To explain how the brain orchestrates information-processing for cognition, we must understand information itself. Importantly, information is not a monolithic entity. Information decomposition techniques provide a way to split information into its constituent elements: unique, redundant, and synergistic information. We review how disentangling synergistic and redundant interactions is redefining our understanding of integrative brain function and its neural organisation. To explain how the brain navigates the trade-offs between redundancy and synergy, we review converging evidence integrating the structural, molecular, and functional underpinnings of synergy and redundancy; their roles in cognition and computation; and how they might arise over evolution and development. Overall, disentangling synergistic and redundant information provides a guiding principle for understanding the informational architecture of the brain and cognition.
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Encéfalo , Cognición , HumanosRESUMEN
BACKGROUND: To investigate the association between pre-trial expectancy, suggestibility, and response to treatment in a trial of escitalopram and investigational drug, COMP360, psilocybin, in the treatment of major depressive disorder (ClinicalTrials.gov registration: NCT03429075). METHODS: We used data (n = 55) from our recent double-blind, parallel-group, randomized head-to-head comparison trial of escitalopram and investigational drug, COMP360, psilocybin. Mixed linear models were used to investigate the association between pre-treatment efficacy-related expectations, as well as baseline trait suggestibility and absorption, and therapeutic response to both escitalopram and COMP360 psilocybin. RESULTS: Patients had significantly higher expectancy for psilocybin relative to escitalopram; however, expectancy for escitalopram was associated with improved therapeutic outcomes to escitalopram, expectancy for psilocybin was not predictive of response to psilocybin. Separately, we found that pre-treatment trait suggestibility was associated with therapeutic response in the psilocybin arm, but not in the escitalopram arm. CONCLUSIONS: Overall, our results suggest that psychedelic therapy may be less vulnerable to expectancy biases than previously suspected. The relationship between baseline trait suggestibility and response to psilocybin therapy implies that highly suggestible individuals may be primed for response to this treatment.
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Trastorno Depresivo Mayor , Escitalopram , Psilocibina , Sugestión , Humanos , Psilocibina/farmacología , Psilocibina/administración & dosificación , Psilocibina/uso terapéutico , Masculino , Adulto , Femenino , Trastorno Depresivo Mayor/tratamiento farmacológico , Método Doble Ciego , Persona de Mediana Edad , Escitalopram/farmacología , Alucinógenos/farmacología , Alucinógenos/administración & dosificación , Anticipación Psicológica/efectos de los fármacos , Resultado del Tratamiento , Citalopram/uso terapéutico , Citalopram/farmacología , Citalopram/administración & dosificaciónRESUMEN
Recent findings have shown that psychedelics reliably enhance brain entropy (understood as neural signal diversity), and this effect has been associated with both acute and long-term psychological outcomes, such as personality changes. These findings are particularly intriguing, given that a decrease of brain entropy is a robust indicator of loss of consciousness (e.g., from wakefulness to sleep). However, little is known about how context impacts the entropy-enhancing effect of psychedelics, which carries important implications for how it can be exploited in, for example, psychedelic psychotherapy. This article investigates how brain entropy is modulated by stimulus manipulation during a psychedelic experience by studying participants under the effects of lysergic acid diethylamide (LSD) or placebo, either with gross state changes (eyes closed vs open) or different stimuli (no stimulus vs music vs video). Results show that while brain entropy increases with LSD under all of the experimental conditions, it exhibits the largest changes when subjects have their eyes closed. Furthermore, brain entropy changes are consistently associated with subjective ratings of the psychedelic experience, but this relationship is disrupted when participants are viewing a videoâpotentially due to a "competition" between external stimuli and endogenous LSD-induced imagery. Taken together, our findings provide strong quantitative evidence of the role of context in modulating neural dynamics during a psychedelic experience, underlining the importance of performing psychedelic psychotherapy in a suitable environment.
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Alucinógenos , Humanos , Alucinógenos/farmacología , Dietilamida del Ácido Lisérgico , Encéfalo , Mapeo Encefálico , PsicoterapiaRESUMEN
N,N-Dimethyltryptamine (DMT) is a serotonergic psychedelic that induces a rapid and transient altered state of consciousness when inhaled or injected via bolus administration. Its marked and novel subjective effects make DMT a powerful tool for the neuroscientific study of consciousness and preliminary results show its potential role in treating mental health conditions. In a within-subjects, placebo-controlled study, we investigated a novel method of DMT administration involving a bolus injection paired with a constant-rate infusion, with the goal of extending the DMT experience. Pharmacokinetic parameters of DMT estimated from plasma data of a previous study of bolus intravenous DMT were used to derive dose regimens necessary to keep subjects in steady levels of immersion into the DMT experience over an extended period of 30 min, and four dose regimens consisting of a bolus loading dose and a slow-rate infusion were tested in eleven healthy volunteers (seven male, four female, mean age ± SD = 37.09 ± 8.93 years). The present method is effective for extending the DMT experience in a stable and tolerable fashion. While subjective effects were maintained over the period of active infusion, anxiety ratings remained low and heart rate habituated within 15 min, indicating psychological and physiological safety of extended DMT. Plasma DMT concentrations increased consistently starting 10 min into DMT administration, whereas psychological effects plateaued into the desired steady state, suggesting the development of acute psychological tolerance to DMT. Taken together, these findings demonstrate the safety and effectiveness of continuous IV DMT administration, laying the groundwork for the further development of this method of administration for basic and clinical research.
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Alucinógenos , Trastornos Mentales , Femenino , Humanos , Masculino , Administración Intravenosa , Estado de Conciencia , Alucinógenos/farmacología , N,N-Dimetiltriptamina , Adulto , Persona de Mediana EdadRESUMEN
Integrating independent but converging lines of research on brain function and neurodevelopment across scales, this article proposes that serotonin 2A receptor (5-HT2AR) signalling is an evolutionary and developmental driver and potent modulator of the macroscale functional organization of the human cerebral cortex. A wealth of evidence indicates that the anatomical and functional organization of the cortex follows a unimodal-to-transmodal gradient. Situated at the apex of this processing hierarchy-where it plays a central role in the integrative processes underpinning complex, human-defining cognition-the transmodal cortex has disproportionately expanded across human development and evolution. Notably, the adult human transmodal cortex is especially rich in 5-HT2AR expression and recent evidence suggests that, during early brain development, 5-HT2AR signalling on neural progenitor cells stimulates their proliferation-a critical process for evolutionarily-relevant cortical expansion. Drawing on multimodal neuroimaging and cross-species investigations, we argue that, by contributing to the expansion of the human cortex and being prevalent at the apex of its hierarchy in the adult brain, 5-HT2AR signalling plays a major role in both human cortical expansion and functioning. Owing to its unique excitatory and downstream cellular effects, neuronal 5-HT2AR agonism promotes neuroplasticity, learning and cognitive and psychological flexibility in a context-(hyper)sensitive manner with therapeutic potential. Overall, we delineate a dual role of 5-HT2ARs in enabling both the expansion and modulation of the human transmodal cortex.
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Corteza Cerebral , Receptor de Serotonina 5-HT2A , Adulto , Humanos , Encéfalo , Corteza Cerebral/fisiología , Cognición/fisiología , NeuroimagenRESUMEN
Recent research has provided a wealth of evidence highlighting the pivotal role of high-order interdependencies in supporting the information-processing capabilities of distributed complex systems. These findings may suggest that high-order interdependencies constitute a powerful resource that is, however, challenging to harness and can be readily disrupted. In this paper, we contest this perspective by demonstrating that high-order interdependencies can not only exhibit robustness to stochastic perturbations, but can in fact be enhanced by them. Using elementary cellular automata as a general testbed, our results unveil the capacity of dynamical noise to enhance the statistical regularities between agents and, intriguingly, even alter the prevailing character of their interdependencies. Furthermore, our results show that these effects are related to the high-order structure of the local rules, which affect the system's susceptibility to noise and characteristic time scales. These results deepen our understanding of how high-order interdependencies may spontaneously emerge within distributed systems interacting with stochastic environments, thus providing an initial step toward elucidating their origin and function in complex systems like the human brain.
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The immune system is a central component of organismic function in humans. This paper addresses self-organization of biological systems in relation to-and nested within-other biological systems in pregnancy. Pregnancy constitutes a fundamental state for human embodiment and a key step in the evolution and conservation of our species. While not all humans can be pregnant, our initial state of emerging and growing within another person's body is universal. Hence, the pregnant state does not concern some individuals but all individuals. Indeed, the hierarchical relationship in pregnancy reflects an even earlier autopoietic process in the embryo by which the number of individuals in a single blastoderm is dynamically determined by cell- interactions. The relationship and the interactions between the two self-organizing systems during pregnancy may play a pivotal role in understanding the nature of biological self-organization per se in humans. Specifically, we consider the role of the immune system in biological self-organization in addition to neural/brain systems that furnish us with a sense of self. We examine the complex case of pregnancy, whereby two immune systems need to negotiate the exchange of resources and information in order to maintain viable self-regulation of nested systems. We conclude with a proposal for the mechanisms-that scaffold the complex relationship between two self-organising systems in pregnancy-through the lens of the Active Inference, with a focus on shared Markov blankets.
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Recent research has demonstrated the potential of psychedelic therapy for mental health care. However, the psychological experience underlying its therapeutic effects remains poorly understood. This paper proposes a framework that suggests psychedelics act as destabilizers, both psychologically and neurophysiologically. Drawing on the 'entropic brain' hypothesis and the 'RElaxed Beliefs Under pSychedelics' model, this paper focuses on the richness of psychological experience. Through a complex systems theory perspective, we suggest that psychedelics destabilize fixed points or attractors, breaking reinforced patterns of thinking and behaving. Our approach explains how psychedelic-induced increases in brain entropy destabilize neurophysiological set points and lead to new conceptualizations of psychedelic psychotherapy. These insights have important implications for risk mitigation and treatment optimization in psychedelic medicine, both during the peak psychedelic experience and during the subacute period of potential recovery.
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Objectives: To perform a Bayesian reanalysis of a recent trial of psilocybin (COMP360) versus escitalopram for Major Depressive Disorder (MDD) in order to provide a more informative interpretation of the indeterminate outcome of a previous frequentist analysis. Design: Reanalysis of a two-arm double-blind placebo controlled trial. Participants: Fifty-nine patients with MDD. Interventions: Two doses of psilocybin 25mg and daily oral placebo versus daily escitalopram and 2 doses of psilocybin 1mg, with psychological support for both groups. Outcome measures: Quick Inventory of Depressive Symptomatology-Self-Report (QIDS SR-16), and three other depression scales as secondary outcomes: HAMD-17, MADRS, and BDI-1A. Results: Using Bayes factors and 'skeptical priors' which bias estimates towards zero, for the hypothesis that psilocybin is superior by any margin, we found indeterminate evidence for QIDS SR-16, strong evidence for BDI-1A and MADRS, and extremely strong evidence for HAMD-17. For the stronger hypothesis that psilocybin is superior by a 'clinically meaningful amount' (using literature defined values of the minimally clinically important difference), we found moderate evidence against it for QIDS SR-16, indeterminate evidence for BDI-1A and MADRS, and moderate evidence supporting it for HAMD-17. Furthermore, across the board we found extremely strong evidence for psilocybin's non-inferiority versus escitalopram. These findings were robust to prior sensitivity analysis. Conclusions: This Bayesian reanalysis supports the following inferences: 1) that psilocybin did indeed outperform escitalopram in this trial, but not to an extent that was clinically meaningful--and 2) that psilocybin is almost certainly non-inferior to escitalopram. The present results provide a more precise and nuanced interpretation to previously reported results from this trial, and support the need for further research into the relative efficacy of psilocybin therapy for depression with respect to current leading treatments. Trial registration number: NCT03429075.
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Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma Campaign, here we provide our framework and vision to understand the diverse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state-of-the-art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness; which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges.
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Lesiones Encefálicas , Estado de Conciencia , Humanos , Estado de Conciencia/fisiología , Trastornos de la Conciencia/diagnóstico por imagen , Lesiones Encefálicas/complicaciones , Neuroimagen , Simulación por ComputadorRESUMEN
The recent link discovered between generalized Legendre transforms and non-dually flat statistical manifolds suggests a fundamental reason behind the ubiquity of Rényi's divergence and entropy in a wide range of physical phenomena. However, these early findings still provide little intuition on the nature of this relationship and its implications for physical systems. Here we shed new light on the Legendre transform by revealing the consequences of its deformation via symplectic geometry and complexification. These findings reveal a novel common framework that leads to a principled and unified understanding of physical systems that are not well-described by classic information-theoretic quantities.
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Psychedelic drugs, including lysergic acid diethylamide (LSD) and other agonists of the serotonin 2A receptor (5HT2A-R), induce drastic changes in subjective experience, and provide a unique opportunity to study the neurobiological basis of consciousness. One of the most notable neurophysiological signatures of psychedelics, increased entropy in spontaneous neural activity, is thought to be of relevance to the psychedelic experience, mediating both acute alterations in consciousness and long-term effects. However, no clear mechanistic explanation for this entropy increase has been put forward so far. We sought to do this here by building upon a recent whole-brain model of serotonergic neuromodulation, to study the entropic effects of 5HT2A-R activation. Our results reproduce the overall entropy increase observed in previous experiments in vivo, providing the first model-based explanation for this phenomenon. We also found that entropy changes were not uniform across the brain: entropy increased in all regions, but the larger effect were localised in visuo-occipital regions. Interestingly, at the whole-brain level, this reconfiguration was not well explained by 5HT2A-R density, but related closely to the topological properties of the brain's anatomical connectivity. These results help us understand the mechanisms underlying the psychedelic state and, more generally, the pharmacological modulation of whole-brain activity.
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Alucinógenos , Alucinógenos/farmacología , Entropía , Encéfalo/fisiología , Dietilamida del Ácido Lisérgico/farmacología , Estado de ConcienciaRESUMEN
Psychedelics have attracted medical interest, but their effects on human brain function are incompletely understood. In a comprehensive, within-subjects, placebo-controlled design, we acquired multimodal neuroimaging [i.e., EEG-fMRI (electroencephalography-functional MRI)] data to assess the effects of intravenous (IV) N,N-Dimethyltryptamine (DMT) on brain function in 20 healthy volunteers. Simultaneous EEG-fMRI was acquired prior to, during, and after a bolus IV administration of 20 mg DMT, and, separately, placebo. At dosages consistent with the present study, DMT, a serotonin 2A receptor (5-HT2AR) agonist, induces a deeply immersive and radically altered state of consciousness. DMT is thus a useful research tool for probing the neural correlates of conscious experience. Here, fMRI results revealed robust increases in global functional connectivity (GFC), network disintegration and desegregation, and a compression of the principal cortical gradient under DMT. GFC × subjective intensity maps correlated with independent positron emission tomography (PET)-derived 5-HT2AR maps, and both overlapped with meta-analytical data implying human-specific psychological functions. Changes in major EEG-measured neurophysiological properties correlated with specific changes in various fMRI metrics, enriching our understanding of the neural basis of DMT's effects. The present findings advance on previous work by confirming a predominant action of DMT-and likely other 5-HT2AR agonist psychedelics-on the brain's transmodal association pole, i.e., the neurodevelopmentally and evolutionarily recent cortex that is associated with species-specific psychological advancements, and high expression of 5-HT2A receptors.