Using a novel turbulence framework that quantifies vorticity (local synchrony) and extends metastability to space and time, the study shows that LSD and psilocybin produce consistent yet discriminable compression of the brain’s functional hierarchy, most notably altering the default mode network. These results quantify how two psychedelics modulate hierarchical brain dynamics and support their proposed mechanistic role relevant to therapeutic applications.
Psychedelic drugs show promise as safe and effective treatments for neuropsychiatric disorders, yet their mechanisms of action are not fully understood. A fundamental hypothesis is that psychedelics work by dose-dependently changing the functional hierarchy of brain dynamics, but it is unclear whether different psychedelics act similarly. Here, we investigated the changes in the brain’s functional hierarchy associated with two different psychedelics (LSD and psilocybin). Using a novel turbulence framework, we were able to determine the vorticity, that is, the local level of synchronization, that allowed us to extend the standard global time-based measure of metastability to become a local-based measure of both space and time. This framework produced detailed signatures of turbulence-based hierarchical change for each psychedelic drug, revealing consistent and discriminate effects on a higher level network, that is, the default mode network. Overall, our findings directly support a prior hypothesis that psychedelics modulate (i.e., “compress”) the functional hierarchy and provide a quantification of these changes for two different psychedelics. Implications for therapeutic applications of psychedelics are discussed.
Previous research has suggested that classic psychedelic drugs can produce therapeutic effects for conditions such as treatment-resistant depression and addiction, but the neural mechanisms underlying these effects remain incompletely understood. A prominent mechanistic hypothesis — articulated in frameworks such as REBUS (RElaxed Beliefs Under pSychedelics) and the entropic/anarchic brain account — proposes that psychedelics relax the brain's hierarchical processing by reducing the precision of high-level priors, thereby permitting increased bottom-up information flow. The authors frame this study in terms of that hypothesis and note that 5-HT2A receptor agonism, a common pharmacological action of classic psychedelics, plausibly alters large-scale neuronal synchrony and canonical rhythms in ways that could underpin such hierarchical relaxation and associated subjective phenomena (for example, ego dissolution).
Papers cited by this study that are also in Blossom
Atasoy, S., Leor, R., Kaelen, M. et al. · Scientific Reports (2017)
Atasoy, S., Vohryzek, J., Deco, G. et al. · Progress in Brain Research (2018)
Bogenschutz, M. P., Forcehimes, A. A., Pommy, J. A. et al. · Journal of Psychopharmacology (2015)
Carhart-Harris, R. L. · Neuropharmacology (2018)
Cruzat and colleagues analysed two independent, placebo-controlled fMRI datasets in healthy volunteers to characterise how LSD and psilocybin modulate the brain's functional hierarchy. The LSD dataset comprised sessions from 20 recruited participants, of whom 15 remained for analysis after exclusions for motion or other issues; LSD (75 μg i.v. bolus in 10 mL saline) and saline placebo were delivered in a balanced within-subjects design, with resting-state scans performed before and after a music block and eyes-closed instructions. The psilocybin dataset began with 15 participants and, after motion exclusion, included 9 participants; each subject underwent two 12-min eyes-closed resting-state scans on separate days and received either psilocybin (2 mg i.v. in 10 mL saline, infused over 60 s) or placebo in a counterbalanced order. Imaging parameters differed modestly between studies (LSD: TR = 2000 ms, 35 slices; psilocybin: TR = 3000 ms, 33 slices). Pre-processing and denoising used the CONN toolbox and SPM12 with standard steps including removal of initial volumes, realignment, slice-timing correction, grey-matter template normalisation and 6 mm smoothing. The analysis combined two complementary approaches inspired by turbulence theory. The model-free approach computed four measures derived from a local Kuramoto order parameter: amplitude turbulence (local synchronisation, Rλ(x,t)), information transfer (spatial decay of time correlations of Rλ as a function of Euclidean distance r), information cascade flow (time-lagged correlation of Rλ at adjacent scales), and the information cascade (average cascade flow across scales). Spatial scales were indexed by λ values from 0.01 (~100 mm) to 0.21 (~5 mm) in steps of 0.03; higher λ indicates shorter spatial distance. Node-level variability of R (standard deviation across time) and Kolmogorov-Smirnov distance (KSD) were used to compare the distributional similarity of node-wise turbulence between psychedelic and placebo states. The Schaefer 1,000-parcel atlas defined nodes and Euclidean parcel distances. The model-based approach constructed whole-brain dynamical models whose local node dynamics followed the normal form of a supercritical Hopf bifurcation (Stuart–Landau). Structural connectivity used tractography-based connectomes from the Human Connectome Project and an exponential distance rule. Models were fitted by minimising the Euclidean distance between empirical and simulated functional connectivity as a function of inter-node distance FC(r), identifying an optimal global coupling G. In silico perturbations were applied by randomly altering each node's bifurcation parameter a within [-0.02, 0]; model sensitivity (susceptibility) was quantified as the change in the mean modulus of the local order parameter between perturbed and unperturbed simulations, averaged across nodes and trials, while information encoding capability was defined as the trial-wise standard deviation of that perturbation-induced change. Statistical comparisons used permutation-based paired t-tests (alpha = 0.05) with FDR correction for the model-free measures, Wilcoxon rank-sum tests for susceptibility and information capability, and KSD for distributional comparisons at node level.
Sample sizes after exclusions were 15 participants for LSD and 9 for psilocybin. Using the model-free turbulence measures, both psychedelics produced increases in turbulent signatures compared with placebo, but with drug-specific spatial profiles. LSD increased turbulence across all spatial scales examined, with the largest effects at longer distances (smaller λ values corresponding to long-range scales). Psilocybin showed significant turbulence increases primarily at longer-range scales (reported as λ < 0.06). The authors explored the slope of mean turbulence across λ and observed that both drugs produced a monotonic decrease in that slope at longer spatial scales. Information transfer — the spatial decay slope of time correlations of the local synchronisation — was significantly increased under both psychedelics across all spatial scales, indicating flatter decay and therefore greater long-range information transmission. Information cascade flow (correlation of scale λ with λ − ∆λ at consecutive times) was significantly elevated by LSD at all λ values, whereas psilocybin increased cascade flow primarily at higher spatial scales (i.e. long distances/low λ). Averaged across scales, the information cascade measure was significantly increased under both drugs. For LSD, increases in turbulence, information transfer and information cascade did not correlate with subjective report measures; for psilocybin, only increases in information cascade correlated with ego-dissolution ratings (details reported in supplementary figures according to the text). At the node level, computation of absolute differences in node-level turbulence (example shown at λ = 0.12) and counting of nodes in the upper 15% quantile per resting-state network revealed different network signatures: LSD-related changes were most prominent in the somatomotor (SOM) and dorsal attention network (DAN), while psilocybin-related changes were concentrated in the default mode network (DMN), frontoparietal network (FPN), and ventral network (VEN). In the model-based perturbational analyses, whole-brain Hopf models were fitted separately to each empirical brain state (LSD vs placebo; psilocybin vs placebo) using structural connectivity and FC(r). Systematic in silico perturbations produced two principal effects assessed at λ = 0.18: susceptibility — the model's sensitivity to perturbation — was significantly decreased under both LSD and psilocybin compared with their respective placebos; conversely, information encoding capability — the trial-wise variability in perturbation response — was significantly increased under the psychedelic conditions (reported p < 0.001, two-sided Wilcoxon rank-sum test). The extracted text indicates the susceptibility decrease and information capability increase were consistent across compounds.
Using two independent, placebo-controlled fMRI datasets, the researchers applied turbulence-inspired, model-free and model-based analyses to test the hypothesis that classic psychedelics relax hierarchical processing in the brain. Across methods and compounds, the psychedelic state was characterised by generally increased turbulent dynamics and enhanced information transmission across spatial and temporal scales. The authors interpret these results as consistent with prior observations that psychedelics increase entropy of spontaneous brain activity, broaden the repertoire of connectivity states and enhance global connectivity between high-level networks and the rest of the brain. The turbulence framework is presented as offering mechanistic insight into how information transfers across space and time in whole-brain dynamics; increased turbulence and flatter spatial-decay slopes were taken to indicate enhanced long-range information transfer, which the authors link to recruitment of long-distance cortical connections thought important for conscious processing. Network-level patterns differed by drug: psilocybin affected high-level networks (DMN, FPN, VEN), while LSD produced more pronounced changes in somatomotor and dorsal attention networks, suggesting that different psychedelics perturb hierarchical processing in partly distinct ways. The authors note that changes in setting (for example, music) might interact with turbulence but that this was outside the present study's scope. From the perturbational modelling, the investigators report that whole-brain dynamics under psychedelics are less susceptible to external perturbations yet display greater information encoding capacity. They caution that susceptibility is a measure of a system's ability to be perturbed rather than a direct index of complexity; by contrast, information capability reflects how external inputs are encoded and relates more closely to established complexity metrics. The authors situate their perturbative approach as complementary to observational analyses, arguing that data-constrained whole-brain models permit systematic exploration of mechanistic responses to targeted perturbations. They further relate their findings to previous perturbation work in the LSD state that reported increased variability in perturbational responses and slower recovery to baseline, noting their results advance understanding by focusing on information processing characteristics. Overall, the study concludes that classic psychedelics produce a patterned increase in turbulence-related metrics that may be mechanistically linked to their effects on conscious experience and information processing. The authors present these findings as both enriching the understanding of the psychedelic state and demonstrating the utility of turbulence-inspired metrics for characterising brain function more broadly.
To quantify the functional hierarchy under the acute effects of different psychedelics (LSD, and psilocybin), we applied a novel turbulence framework to two psychedelic datasets in human participants. We used the power of both whole-brain model-free and model-based approaches to characterise the hierarchy for the different compounds. For the model-free approach, we estimated the levels of turbulence, information transfer, information cascade flow, and information cascade. For the modelbased approach, we estimated the susceptibility and information encoding capability measures. Below we briefly summarise the participants, study settings, data acquisition and pre-processing protocols.
We used a novel turbulence frameworkto investigate changes in brain hierarchy induced by different psychedelic drugs measured with fMRI in healthy volunteers from two different datasets. Participants received intravenous injections of lysergic acid diethylamide (LSD) (N=15) or psilocybin (N=9), and placebo in two separate studies. Experimental designs differed but all were placebo controlled (saline injection) with participants blinded to condition. Here we focused on the effects of psychedelics on the brain's turbulent dynamics based on the recent demonstration that the brain exhibits a turbulent dynamic intrinsic backbone that facilitates large-scale network communication. Within the model-free framework, we studied changes in information transmission flow across spatial and temporal scales using four distinct measures: turbulence, information transfer, information cascade flow, and information cascade. These analyses were performed based on the Kuramoto order parameter describing the local degree of synchronization of a brain region, n, as a function of space, 𝑥̅ , and time t, at a given scale λ. The scale of the local synchronization is defined by the parameter λ, which determines the spatial distance where the synchronization is assessed. We explored scales ranging from 0.01 (~100 mm) to 0.21 (~5 mm), in steps of 0.03, where high values of λ denote short distances in the brain and vice versa. Compared with placebo, psychedelics induce significant increases in turbulence (Figure). In the LSD condition, these increases were found across all spatial scales but were more pronounced at the longer ones. In contrast, the effects in psilocybin were observed only at longer distances in the brain (λ < 0.06). Complementarily, we calculated a linear fit to the mean turbulence at each λ and captured the slopes of each condition representing its level of turbulence at each spatial scale. Figureresumes the measures of information transmission through time and space calculated by changes in turbulence on each different scale. Both psychedelics monotonically decrease the slope at longer spatial scales. We computed the information transfer measure, which denotes how information travels across space at a given spatial scale. We found that psychedelics significantly increase information transfer across all spatial scales in the brain, favouring information transmission. Figureshows boxplots of the statistically significant differences between conditions that passed the permutation-based paired t-test with p < 0.05. We performed the exact computations presented in Figure, but now for the information cascade measurement. Figuresummarize the behaviour of this measure at different spatial scales. LSD and psilocybin present a similar slope-scale relationship at shorter spatial scales (larger lambdas), while their differ at the shorter ones suggesting that psilocybin is more sensitive to differences in the degree of information transmission across scales. We then characterized the transmission of information across spatial and temporal scales using the information cascade flow measurement described as the correlation of the signal at a given scale λ, with the signal at a lower scale λ -∆λ, in consecutive time steps, t + ∆t. As shown in Figure, we found that LSD significantly increased information cascade flow at all λ scales compared with placebo, while psilocybin also did so at higher spatial scales, i.e., lower λ denoting long distances in the brain. Finally, we found evidence of significantly increased information cascade under the psychedelic state compared with placebo (Figure). This measure characterises the global degree of information transmission across scales and is obtained by averaging the information cascade flow across all λ scales. The increases in turbulence, information transfer and information cascade observed under LSD did not correlate with the subjective experience reports. For psilocybin, we observed that only the increases in information cascade correlated with ratings on ego-dissolution (see Supp Figures). Furthermore, we calculated the node variability of the local synchronization defined as the standard deviation across time of the local Kuramoto order parameter for each condition. We calculated the similarity of the node-level turbulence between each psychedelic compound and the counterpart placebo using the Kolmogorov-Smirnov distance (KSD) between them at each spatial scale. Figureshows that the difference between conditions is more prominent at lower λ scales for both psychedelic drugs. For each condition, we then computed the absolute difference of the node-level turbulence between the psychedelic state and the placebo at λ=0.12. Figurerenders this absolute difference onto the brain's cortex. Subsequently, we picked the nodes for each comparison of the upper 15% quantile, identified the resting-state network to which they belong, and counted the number of nodes per network. This strategy allowed us to describe the precise signature of turbulence-based hierarchical change for each psychedelic drug, revealing how each one impacts the dynamics of the networks. As can be seen in Figure, differences between LSD and placebo were mainly found in the somatomotor (SOM) and dorsal attention networks (DAN), and between psilocybin and placebo in the default mode network (DMN), frontoparietal (FPN), and ventral network (VEN). We applied a whole-brain computational modeling approach based on the sensitivity of these models to react to external in silico perturbations and their capability to offer insights into the mechanisms underlying the global complexity and dynamical stability of brain activity(see the methods section). For each of the four brain states (LSD vs. placebo, and psilocybin vs. placebo), we constructed a whole-brain dynamical model based on the normal form of a supercritical Hopf bifurcation. The model was coupled to the structural connectivity obtained through DTI and used the exponential distance rule (EDR) of anatomical connections as a costof-wiring principle. Each model was fitted to optimally reproduce the empirical spatiotemporal dependencies of each brain state characterized using the functional connectivity (FC) measure as a function of the global coupling parameter G. For each G and condition, we performed 100 simulations and calculated the fitting performance as the Euclidean distance between the empirical and the simulated FC. The minimum distance between the empirical and the simulated FC defines the optimal operating point of the model. Then, to evaluate how each model-based brain state reacts to external stimuli, we systematically applied in silico perturbations and quantified the functional consequences of these perturbations using the susceptibility and information capability measures. Perturbations were implemented by randomly changing the bifurcation parameter of each brain area an in the model within the range [-0.02:0]. The susceptibility measure reflects the sensitivity of the whole-brain model to react to external perturbations. It is defined by the difference between the perturbed and unperturbed mean of the modulus of the local order parameter across time (𝑅 ̃λ𝑠 (𝑥̅ , 𝑡) and 𝑅 λ 𝑠 (𝑥̅ , 𝑡), respectively), averaged over all brain nodes. Complementarily, the information capability denotes the capacity of the brain to encode external perturbations in brain dynamics and is defined as the standard deviation across trials of the susceptibility measure. Figureshows that LSD and psilocybin significantly decrease susceptibility. Complementarily, the information encoding capacity significantly increases following the psychedelic drug administration, compared to placebo (p < 0.001, two-sided Wilcoxon rank sum test). The results for both measures were estimated at λ = 0.18.
Here we used two independent fMRI datasets of healthy participants receiving moderate to high doses of LSD or Psilocybin in placebo-controlled designs to determine the psychedelic-specific modulation of the brain's dynamic functional hierarchy and assess its impact on information processing. Our framework comprised model-free and model-based approaches inspired by signatures of turbulence in complex systems. Using this approach, we aimed to test a leading hypothesis of the brain action of psychedelics, i.e., that they relax the properties of canonical systems in the brainencoding internal models or assumptions. Results revealed generally consistent increases in turbulent signatures across the psychedelics. Serotonin 2A receptor agonism is a defining pharmacological property of the 'classic' psychedelicsand LSD and psilocybin are perhaps the most familiar examples. At the population and systems level, psychedelics have been shown to increase the entropy of spontaneous brain activity, broaden the repertoire of connectivity statesand enhance global connectivity between high-level networks and the rest of the brain. The merit of turbulence related metrics, however, is the information they confer about information transfer in the brain and their relevance to complexity sciencewhich offers a rich and developing language for understanding the properties of complex systems. Using a model-free approach, we first explored the global information transmission characteristics. This approach is grounded in the innovative and sophisticated framework for analyzing whole-brain dynamics, recently developed by, through which they revealed that the healthy human brain shows turbulent dynamics. Summarizing the results, compared with placebo, both psychedelics promoted greater information transmission in the brain, in both the spatial and temporal domains. Specifically, significant increases were observed in turbulence, information transfer across scales, information cascade flow, and information cascade. The present framework could equally well be described in terms of the local Kuramoto order parameter and its use for characterising information transmission, i.e., as a generalisation of the concept of metastability in neuroscience, pioneered by Shanahan and Kuramoto. Nevertheless, such a description does not capture the generality of the principles governing brain dynamics and most, if not all, physical systems. The turbulence framework offers a characterization of the dynamics underlying different brain states and provides a principled, mechanistic way to describe information transmission across spacetime. Thus, irrespective of the type of psychedelic, the psychedelic state appears to show a clear trend towards a greater transmission of informationcharacterized by increases in turbulence and information transfer valuesthrough long-range spatial scales, i.e., smaller lambdas. Long-range cortical connections have long been thought to be crucial for the emergence of consciousness. In fact, it has been shown that long-range connections are associated with enhanced cognitive processing in healthy participants; whereas a decrease in global information processing and largescale functional connectivity appears to be a robust signature of reduced conscious levels. These findings suggest that the recruitment of longdistance connections plays a fundamental role in the flow of information through the cortex, allowing communication between different brain areas and ultimately supporting the emergence of conscious awareness. It is tempting to speculate that increase long-range information transfer under psychedelics relates to their purported ability to facilitate psychological insightconsistent with the etymology of the term "psychedelic" -i.e., "mind -revealing". We explored node-level changes in turbulence to identify the primary brain areas driving the turbulent dynamic core and thus involved in changing the whole-brain dynamics underlying each psychedelic state. Noteworthily, we found that brain regions belonging to the somatomotor and dorsal attention network showed the most critical differences in the LSD-induced brain state; and for psilocybin the default mode, frontoparietal and ventral networks showed the greatest differences. These results highlight the specificfunctional changes to the functional hierarchy, revealing that psilocybin directly impact on high-level networks, whereas LSD have stronger effects on primary visual-sensory areas. Given that the level of turbulence is increased for both LSD and psilocybin at the different spatial scales, we speculate that changes in the setting such as music may increase turbulence and therefore increase the observed effect. However, this out of the scope of the present paper and deserves thorough investigation. Furthermore, we used a model-based approach to investigate how whole-brain dynamics underlying each brain state impacts the brain's capacity to encode external perturbations. To do so, we built a wholebrain model based on the normal form of a supercritical Hopf bifurcation, simulating the empirical fMRI statistical dependencies. We applied in silico external perturbations to evaluate how each model-based brain state reacts to (simulated) external perturbations. We found that the brain is less sensitive to external perturbations under psychedelics as shown by the susceptibility measure. Conversely, consistent increases in the brain's information encoding capacity were observed across all psychedelics suggesting that the brain becomes more selective and enhances specificity when dealing with information processing. It is important to note that the susceptibility measure is not a measure of complexity but rather a measure of the ability of a system to be perturbed, and neither a measure of the ensuing complexity of the response (as in TMS-PCI studies). In contrast, the information capacity measures the ability of the system to encode external inputs, and such is closer related to complexity measures such as Lempel-Ziv- Welch (LZw), automatic complexity evaluator (ACE), and synchrony coalition entropy (SCE) (used and defined by Schartner and colleagues. First proposed by, the perturbative approach has been increasingly applied to investigate brain function due to its potential to relate local neural activity changes to global brain dynamics and reveal the underlying detailed causal mechanisms. This approach is a suitable complement to observational approaches that are typically descriptive and correlative, thus do not offer insights into the underlying mechanisms. Data constrained whole-brain models are key to studying perturbation-induced changes in neural activity, as they allow parameter optimization and targeted perturbation to be systematically explored in different brain regions. Perturbations in dynamical models of whole-brain activity have been shown to dissociate different brain states, providing a robust metric and computational tool capable of characterizing and unravelling brain states. While a previous study compared perturbation-induced changes in brain dynamics in the LSD state versus placebo using a similar model-based approach 41 , it did not focus on the information processing characteristics of brain states. Still, as in the present study, this previous one did show greater variability in the perturbational responses in the LSD condition compared to placebo 41 . This variability refers to what we call here information encoding capability, a measure that captures how the external perturbations are encoded in whole-brain dynamics. The previous study also reported that brain dynamics under LSD took longer to recover to baseline activity after perturbation. Psychedelic drugs appear to broadens the brain's dynamical repertoireand enhances global functional connectivity by shifting the brain's global working point towards a more globally connected profile. The present study's findings are consistent with this characterization and advance on it by suggesting that psychedelics also promote a greater spread of neural activity and associated increase in information transfer and 'mixing', across domains and scales throughout the brain. Taken together, our findings show that psychedelics exhibits a particular pattern of (generally increased) turbulent dynamics that may relate to their characteristic effects on conscious experience. While helping to enrich our understanding of the brain basis of the psychedelic state, these findings also deepen our understanding of the functional relevance of turbulence related metrics in relation to brain function more broadly.
Create a free account to open full-text PDFs.
Carhart-Harris, R. L., Giribaldi, B., Watts, R. et al. · New England Journal of Medicine (2021)
Carhart-Harris, R. L., Leech, R., Shanahan, M. et al. · Frontiers in Human Neuroscience (2014)
Carhart-Harris, R. L., Muthukumaraswamy, S., Roseman, L. et al. · PNAS (2016)
Carhart-Harris, R. L., Bolstridge, M., Rucker, J. et al. · Lancet Psychiatry (2016)
Carhart-Harris, R. L., Erritzoe, D., Williams, T. et al. · PNAS (2012)
Griffiths, R. R., Johnson, M. W. · Journal of Psychopharmacology (2016)
Hartogsohn, I. · Frontiers in Human Neuroscience (2018)
Jobst, B. M., Atasoy, S., Ponce-Alvarez, A. et al. · NeuroImage (2021)
Johnson, M. W., Griffiths, R. R., Hendricks, P. S. et al. · Neuropharmacology (2018)
Johnson, M. W., Hendricks, P. S., Barrett, F. S. et al. · Pharmacology and Therapeutics (2019)
Lord, L. D., Expert, P., Atasoy, S. et al. · NeuroImage (2019)
Luppi, A. I., Carhart-Harris, R. L., Roseman, L. et al. · NeuroImage (2021)
Millière, R. · Frontiers in Human Neuroscience (2017)
Nichols, D. E. · Pharmacological Reviews (2016)
Nour, M. R., Evans, J., Nutt, D. J. et al. · Frontiers in Human Neuroscience (2016)
Osmond, H. · Annals of the New York Academy of Sciences (2010)
Preller, K. H., Burt, J. B., Adkinson, B. et al. · eLife (2018)
Roseman, L., Nutt, D. J., Carhart-Harris, R. L. · Frontiers in Pharmacology (2018)
Tagliazucchi, E., Roseman, L., Kaelen, M. et al. · Current Biology (2016)
Varley, T. F., Carhart-Harris, R., Roseman, L. et al. · NeuroImage (2020)
Yaden, D. B., Griffiths, R. R. · ACS Pharmacology and Translational Science (2020)
Papers in Blossom that reference this study
Socoró-Garrigosa, M., Sanz Perl, Y., Kringelbach, M. L. et al. · Annals of the New York Academy of Sciences (2025)
Shinozuka, K., Jerotic, K., Mediano, P. A. M. et al. · Translational Psychiatry (2024)
Hipólito, I., Mago, J., Rosas, F. E. et al. · Psyarxiv (2022)