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)
October 7, 2024
George Blackburne, Rosalind McAlpine, Marco S. Fabus et al.
8 citations
preprint
A high dose of the psychedelic drug 5-MeO-DMT radically reorganizes low-frequency brain activity in 29 healthy individuals. Inhaling 12 mg of vaporized synthetic 5-MeO-DMT caused neural activity flows to become incoherent, heterogeneous, viscous, fleeting, and nonrecurring, ceasing typical traveling waves across the cortex. This reorganization led to slower, more stable, low-dimensional broadband activity with increased energy barriers to rapid global shifts. The findings provide the first detailed empirical account of how 5-MeO-DMT alters human brain dynamics, revealing novel cortical slow wave behaviors.
bioRxiv Preprint Server
June 25, 2021
Claudia Pascovich, Santiago Castro-Zaballa, Pedro A. M. Mediano et al.
7 citations
preprint
Neural complexity, measured by the Lempel-Ziv compression algorithm, is lowest during NREM sleep and similar during REM sleep and wakefulness in cats with intracranial electrodes. Under subanesthetic doses of ketamine (5, 10, and 15 mg/kg), complexity follows an inverted U-shaped curve in some electrodes, especially in prefrontal cortex, rising at low doses and falling as doses approach anesthetic levels. Variability in the ketamine dose-response across cats and cortices is larger than sleep-stage differences, revealing distinct local dynamics. These results replicate findings in humans and other species, showing neural complexity is sensitive to conscious state changes and dose-dependent ketamine effects.
medRxiv
September 11, 2024
M. Nikolič, Pedro A. M. Mediano, Tom Froese et al.
6 citations
preprint
Psilocybin, a classic psychedelic, alters perception, cognition, and emotion by activating 5-HT2A receptors and reducing serotonin reuptake. In a placebo-controlled crossover study with 20 healthy individuals, electroencephalography tracked brain activity changes over 24 hours after oral psilocybin (0.26 mg/kg). Acutely, absolute power decreased in alpha and beta bands but increased in delta and gamma frequencies; alpha power decreased occipitally between 1 and 3 hours, and beta decreased frontally at 3 hours. Global functional connectivity in the alpha band dropped acutely, while Lempel-Ziv complexity increased at 1 and 1.5 hours.
Research Square
October 26, 2022
Rubén Herzog, Pedro A. M. Mediano, Fernando E. Rosas et al.
6 citations
Psychedelic drugs like LSD, which activate serotonin 2A receptors, dramatically alter subjective experience and offer a window into the neurobiology of consciousness. A key signature of these drugs is increased entropy—or randomness—in spontaneous brain activity, but why this occurs was unclear. Using a computational model of serotonin's effects on the whole brain, researchers reproduced the entropy increase seen in living brains, providing the first model-based explanation. Entropy rose across all brain regions but was most pronounced in visual and occipital areas. Surprisingly, this pattern was not tied to the density of serotonin receptors but instead linked to the brain's structural connectivity network. The findings clarify how psychedelics reconfigure brain activity.
bioRxiv
February 1, 2022
Hardik Rajpal, Pedro A. M. Mediano, Fernando E. Rosas et al.
5 citations
preprint
Schizophrenia and drug-induced states from LSD and ketamine both increase neural signal diversity, but they differ in how information flows in the brain. In schizophrenia, transfer entropy from the front to the back of the brain is increased, whereas under both drugs it is reduced overall. These differences can be modeled by altering Bayesian inference within a predictive processing framework: drug effects correspond to reduced precision of prior beliefs, while schizophrenia corresponds to increased precision of sensory information. The findings clarify similarities and differences between these altered states, with potential implications for understanding consciousness and developing mental health treatments.
Andrea I. Luppi, Pedro A. M. Mediano, Fernando E. Rosas et al.
5 citations
preprint
Consciousness can be understood not as a single unified thing but as composed of distinct information-theoretic elements. A new approach called Integrated Information Decomposition (ΦID) shifts from measuring how much integrated information a system has to analyzing its composition. This provides a formal way to determine whether consciousness is an emergent phenomenon based on that composition. Two organisms can have the same amount of integrated information yet differ in its composition. A new measure, ΦR, and the ΦR-ing rate quantify how efficiently an entity uses information for conscious processing. This decomposition identifies qualitatively different 'modes of consciousness,' enabling mapping between phenomenology and information-theoretic structure, starting with selfhood.
Sci Rep
September 15, 2022
Rubén Herzog, Pedro A. M. Mediano, Fernando E. Rosas et al.
3 citations
A scientific paper was retracted because a typo in the script used to calculate differential entropy made the reported entropy estimations invalid. The corrected calculations no longer show the expected increase in brain signal diversity or complexity that the original analysis had claimed.
bioRxiv (Cold Spring Harbor Laboratory)
October 7, 2023
Kenneth Shinozuka, Katarina Jerotic, Pedro A. M. Mediano et al.
2 citations
preprint
Serotonergic psychedelics such as LSD, psilocybin, and DMT alter consciousness and show therapeutic potential for depression and addiction, but their mechanisms remain unclear. A systematic review and meta-analysis across three levels—phenomenology, neuroimaging, and pharmacology—reveals that medium and high doses of LSD produce significantly stronger visionary restructuring than psilocybin. Neuroimaging shows psychedelics generally strengthen connectivity between brain networks while weakening connectivity within networks. Pharmacologically, LSD triggers more inositol phosphate formation at the 5-HT2A receptor than DMT or psilocin, but no significant differences emerged in receptor selectivity among the drugs. The findings highlight high heterogeneity and risk of bias, underscoring the need for standardized methods.
Hum Brain Mapp
January 1, 2026
Henrik Röhr, Daniel A Atad, Fynn-Mathis Trautwein et al.
1 citation
Meditation can deliberately alter the sense of self, allowing comparison between an active and suspended self. In 41 experienced meditators, magnetoencephalography recordings distinguished a state of reduced sense of self (self-boundary dissolution) from rest and a control meditation state. Machine learning using source band power and Lempel-Ziv complexity features predicted mental states with above-chance accuracy. The best performance, classifying self-boundary dissolution versus rest using Lempel-Ziv complexity, achieved average accuracy of about 0.64 for within-participant prediction and about 0.57 for across-participant prediction. This neural marker could support decoded neurofeedback for clinical treatments of self disorders or meditation training.
October 1, 2025
Daniel Andrew Atad, Pedro A. M. Mediano, Fynn-Mathis Trautwein et al.
1 citation
preprint
The sense of being a bounded self can be attenuated or dissolved while awareness remains. Analyzing magnetoencephalography data from 46 long-term meditators, the study found that both meditation conditions (self-boundary dissolution and maintenance) increased broadband entropy rate and directed information transfer compared to rest, driven mainly by high-frequency activity. Localized reductions in information transfer from the anterior cingulate to posterior cingulate and in high-beta entropy rate in sensorimotor and posterior-medial cortices differentiated the two meditation conditions. Reduced orbitofrontal cortex entropy rate and reduced information transfer from occipital, cingulate, limbic, and subcortical areas correlated strongly with self-boundary dissolution phenomenology. Together with a previously reported neural correlate of reduced high-beta power in the posterior-medial cortex, these two neural correlates explained over half the variance in phenomenological dissolution scores (R² = 0.52).
Elife
July 18, 2024
Andrea I. Luppi, Pedro A. M. Mediano, Fernando E. Rosas et al.
1 citation
Loss of consciousness significantly disrupts the brain's ability to integrate information. In a study involving functional MRI analysis, it was revealed that gateway regions in a 'synergistic global workspace' correspond to the default mode network, while broadcaster regions align with the executive control network. This integration breakdown occurs during general anaesthesia or disorders of consciousness, with recovery restoring functionality. The findings enhance understanding of consciousness by bridging Global Neuronal Workspace and Integrated Information Theory, highlighting the critical role of brain networks in maintaining conscious experience.
bioRxiv (Cold Spring Harbor Laboratory)
Hanna M. Tolle, Andrea I. Luppi, Timothy Lawn et al.
1 citation
preprint
A geometric deep learning model called graphTRIP predicts post-treatment depression severity from pretreatment clinical and brain imaging data. Trained on a clinical trial comparing psilocybin and escitalopram, it achieves strong predictive accuracy (r = 0.75) and generalizes to an independent dataset. The model links better outcomes to reduced functional coupling within serotonin systems and broader serotonergic integration with sensory-motor networks. Causal analysis shows a group-level advantage of psilocybin over escitalopram but identifies individuals with specific stress-related neuromodulatory profiles who may benefit more from escitalopram, advancing precision medicine and biomarker discovery in depression.
May 13, 2026
Robin Carhart-Harris, Richard J. Zeifman, Lorenzo Pasquini et al.
preprint
The paper argues that the term 'plasticity' in neuroscience refers to induced changes in brain function or structure, which differs from the dictionary definition of plasticity as the ability to be shaped or molded. Many biomarkers of neuroplasticity actually index processes that bias phenotypic canalization, the opposite of phenotypic plasticity, creating a paradox. The authors question extrapolating from these biomarkers to improved mental health, as the relationship is context dependent. They propose a new construct, 'mediational and recalibrative plasticity' (MR-P), which aligns with plasticity proper and can describe and predict phenotypic changes relevant to mental health.
Transl Psychiatry
November 13, 2025
Kenneth Shinozuka, Katarina Jerotic, Pedro A. M. Mediano et al.
correction
This correction notice addresses errors in a previously published article that presented three systematic reviews and meta-analyses examining the pharmacology, neuroimaging, and phenomenology of psychedelics. The correction does not provide new findings or data but serves to amend the original publication.
arXiv (Cornell University)
August 6, 2020
Rodrigo Cofré, Rubén Herzog, Pedro A. M. Mediano et al.
Altered states of consciousness provide a key opportunity to understand how global brain activity changes relate to different subjective experiences. This paper advocates a research program that bridges bottom-up generative models of whole-brain activity with top-down signatures proposed by theories of consciousness. It defines altered states, discusses relevant brain-activity signatures, and introduces whole-brain models to explore the mechanisms of altered consciousness from the bottom-up. The authors argue that systematic investigation of altered states via bottom-up modeling may help clarify the biophysical, informational, and dynamical foundations of consciousness.
arXiv Preprint Archive
April 13, 2026
Adam B. Barrett, Borjan Milinkovic, Pedro A. M. Mediano et al.
The integrated information theory of consciousness (IIT) proposes a mathematical formula, derived from fundamental properties of conscious experience, to describe the quantity and quality of consciousness for any physical system. This article clarifies common misunderstandings. A high value of the measure Φ does not mean 'more consciousness'; Φ might be replaced with a suite of quantities for a multidimensional characterization. IIT implies a distinct panpsychism where space and time are tiled with substrates of proto-consciousness, which the authors find unproblematic. Φ is not well-defined for real physical systems and has never been computed on one; only proxies have been computed, not approximations. For IIT to align with fundamental physics, a reformulation in continuous fields would be needed.
Neuroimage
June 1, 2023
Joel Frohlich, Tim Bayne, Julia S Crone et al.
Consciousness likely cannot begin before the establishment of thalamocortical connectivity at 26 weeks gestation, as this system is necessary for subjective experience according to most theoretical frameworks. To determine when consciousness emerges after this point, the authors advocate developing a sensory perturbational complexity index (sPCI) using auditory, visual, or olfactory cortical perturbations—rather than electromagnetic ones—to estimate the perinatal brain's state of consciousness. Techniques such as fMRI, EEG, and MEG can be used in both newborn and fetal studies, with the womb offering a more controlled environment than the cradle for such investigations.
Neuroimage
February 11, 2023
Andrea I. Luppi, Pedro A. M. Mediano, Fernando E. Rosas et al.
High-level brain functions are thought to arise from coordinated activity across neural systems, but this has been hard to test empirically. Using a framework called Integrated Information Decomposition, which quantifies emergence in dynamical systems, the authors analyzed functional MRI data and found that emergent and hierarchical neural dynamics are significantly reduced in chronically unresponsive patients with severe brain injury. Emergence capacity was positively correlated with hierarchical organization in brain activity. Combining network control theory and whole-brain modeling, the authors show that reduced emergent and hierarchical dynamics in these patients can be explained by disruptions in the structural connectome. The results suggest that chronic unresponsiveness after severe brain injury may stem from structural damage to neural infrastructure needed for emergent brain dynamics.
arXiv Preprint Archive
August 6, 2020
Rodrigo Cofré, Rubén Herzog, Pedro A. M. Mediano et al.
Altered states of consciousness, such as those experienced during dreaming or meditation, offer a way to study how large-scale brain activity relates to different subjective experiences. This paper advocates a research program that combines bottom-up generative models of whole-brain activity, based on known properties of neural tissue, with top-down signatures proposed by theories of consciousness. The authors define altered states, discuss relevant brain-activity signatures, and introduce whole-brain models to explore the mechanisms behind these states. They argue that systematically investigating altered states through bottom-up modeling can clarify the biophysical, informational, and dynamical foundations of consciousness.
arXiv Preprint Archive
February 12, 2019
Adam B. Barrett, Pedro A. M. Mediano
Integrated Information Theory (IIT) defines consciousness as a fundamental property of physical systems, measured by the quantity Phi. For IIT to be credible, Phi must be uniquely defined and always well-defined. This article identifies three ways in which the current formulation of Phi fails these standards, making the measure ambiguous or ill-defined in certain cases, and discusses potential solutions to address these foundational issues.
Entropy (Basel, Switzerland)
December 25, 2018
Pedro A. M. Mediano, Anil K. Seth, Adam B. Barrett
Integrated Information Theory (IIT) is a prominent theory of consciousness that centers on measures quantifying how much a system generates more information than the sum of its parts. This article provides clear descriptions of six distinct candidate measures of integrated information and explores their properties through simulations on networks of eight interacting nodes with Gaussian linear autoregressive dynamics. The results reveal striking diversity in the measures' behavior—no two measures show consistent agreement across all analyses. A subset of the measures appears to reflect some form of dynamical complexity, meaning simultaneous segregation and integration between system components. These findings help guide the operationalization of IIT and advance development of measures with more general applicability.
arXiv Preprint Archive
June 25, 2018
Pedro A. M. Mediano, Anil K. Seth, Adam B. Barrett
Integrated Information Theory (IIT) proposes that consciousness arises from a system generating more information than the sum of its parts, but multiple measures of this integrated information (Φ) exist with little comparative testing. This article describes six candidate measures and simulates them on eight-node networks with Gaussian linear autoregressive dynamics. No two measures agreed consistently across all analyses, and only a subset genuinely reflected dynamical complexity—simultaneous segregation and integration between components. The findings guide operationalization of IIT and development of more generally applicable measures of integrated information.
Ignacio Cea, Niccolò Negro, Pedro A. M. Mediano et al.
preprint
The Integrated Information Theory (IIT) 4.0 defines minimal conscious entities called 'monads' as single-unit systems with maximal integrated information (phi_s*). This paper argues that IIT's own formalism cannot apply to monads because it requires any candidate substrate of consciousness to consist of at least two non-overlapping, non-empty, jointly exhaustive parts—the Plurality requirement. Monads violate this requirement, making the equations for calculating system integrated information undefined. The authors call for clarification or revision from IIT proponents regarding the status of phi-monads as ontologically fundamental building blocks and minimal substrates of consciousness.
George Blackburne, Alberto Liardi, Jeremy I Skipper et al.
preprint
The relationship between subjectivity and its physical substrate can be understood through compatibilist emergence, which accounts for how nature can host new dynamical laws at higher scales. The autopoietic character of life may require and promote the kind of emergence necessary, though not sufficient, for consciousness.