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Article: Language as a Window Into the Altered State of Consciousness Elicited by Psychedelic Drugs.

Tagliazucchi, Enzo

2022 Volume 13, Page(s) 812227

Abstract: Psychedelics are drugs capable of eliciting profound alterations in the subjective experience of the users, sometimes with long-lasting consequences. Because of this, psychedelic research tends to focus on human subjects, given their capacity to ... ...

Abstract	Psychedelics are drugs capable of eliciting profound alterations in the subjective experience of the users, sometimes with long-lasting consequences. Because of this, psychedelic research tends to focus on human subjects, given their capacity to construct detailed narratives about the contents of their consciousness experiences. In spite of its relevance, the interaction between serotonergic psychedelics and language production is comparatively understudied in the recent literature. This review is focused on two aspects of this interaction: how the acute effects of psychedelic drugs impact on speech organization regardless of its semantic content, and how to characterize the subjective effects of psychedelic drugs by analyzing the semantic content of written retrospective reports. We show that the computational characterization of language production is capable of partially predicting the therapeutic outcome of individual experiences, relate the effects elicited by psychedelics with those associated with other altered states of consciousness, draw comparisons between the psychedelic state and the symptomatology of certain psychiatric disorders, and investigate the neurochemical profile and mechanism of action of different psychedelic drugs. We conclude that researchers studying psychedelics can considerably expand the range of their potential scientific conclusions by analyzing brief interviews obtained before, during and after the acute effects. Finally, we list a series of questions and open problems that should be addressed to further consolidate this approach.
Language	English
Publishing date	2022-03-22
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2587355-6
ISSN	1663-9812
ISSN	1663-9812
DOI	10.3389/fphar.2022.812227
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Article ; Online: Time is a river which sweeps consciousness along, but consciousness is the river: Comment on "Is temporo-spatial dynamics the "common currency" of brain and mind? In Quest of "Spatiotemporal Neuroscience"" by Georg Northoff et al.

Tagliazucchi, Enzo

Physics of life reviews

2019 Volume 33, Page(s) 75–77

MeSH term(s)	Brain ; Consciousness ; Neurosciences ; Rivers
Language	English
Publishing date	2019-09-27
Publishing country	Netherlands
Document type	Journal Article ; Comment
ZDB-ID	2148883-6
ISSN	1873-1457 ; 1571-0645
ISSN (online)	1873-1457
ISSN	1571-0645
DOI	10.1016/j.plrev.2019.09.010
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Article ; Online: Contribution of low-level image statistics to EEG decoding of semantic content in multivariate and univariate models with feature optimization.

Holm, Eric Lützow / Slezak, Diego Fernández / Tagliazucchi, Enzo

NeuroImage

2024 , Page(s) 120626

Abstract: Spatio-temporal patterns of evoked brain activity contain information that can be used to decode and categorize the semantic content of visual stimuli. However, this procedure can be biased by low-level image features independently of the semantic ... ...

Abstract	Spatio-temporal patterns of evoked brain activity contain information that can be used to decode and categorize the semantic content of visual stimuli. However, this procedure can be biased by low-level image features independently of the semantic content present in the stimuli, prompting the need to understand the robustness of different models regarding these confounding factors. In this study, we trained machine learning models to distinguish between concepts included in the publicly available THINGS-EEG dataset using electroencephalography (EEG) data acquired during a rapid serial visual presentation paradigm. We investigated the contribution of low-level image features to decoding accuracy in a multivariate model, utilizing broadband data from all EEG channels. Additionally, we explored a univariate model obtained through data-driven feature selection applied to the spatial and frequency domains. While the univariate models exhibited better decoding accuracy, their predictions were less robust to the confounding effect of low-level image statistics. Notably, some of the models maintained their accuracy even after random replacement of the training dataset with semantically unrelated samples that presented similar low-level content. In conclusion, our findings suggest that model optimization impacts sensitivity to confounding factors, regardless of the resulting classification performance. Therefore, the choice of EEG features for semantic decoding should ideally be informed by criteria beyond classifier performance, such as the neurobiological mechanisms under study.
Language	English
Publishing date	2024-04-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	1147767-2
ISSN	1095-9572 ; 1053-8119
ISSN (online)	1095-9572
ISSN	1053-8119
DOI	10.1016/j.neuroimage.2024.120626
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Zs.A 3664: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
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Article ; Online: The signatures of conscious access and its phenomenology are consistent with large-scale brain communication at criticality.

Tagliazucchi, Enzo

Consciousness and cognition

2017 Volume 55, Page(s) 136–147

Abstract: Conscious awareness refers to information processing in the brain that is accompanied by subjective, reportable experiences. Current models of conscious access propose that sufficiently strong sensory stimuli ignite a global network of regions allowing ... ...

Abstract	Conscious awareness refers to information processing in the brain that is accompanied by subjective, reportable experiences. Current models of conscious access propose that sufficiently strong sensory stimuli ignite a global network of regions allowing further processing. The immense number of possible experiences indicates that activity associated with conscious awareness must be highly differentiated. However, information must also be integrated to account for the unitary nature of consciousness. We present a computational model that identifies conscious access with self-sustained percolation in an anatomical network. We show that the amount of integrated information (Φ) is maximal at the critical threshold. To the extent that self-sustained percolation relates to conscious access, the model supports a link between information integration and conscious access. We also identify a posterior "hotspot" of regions presenting high levels of information sharing. Finally, competitive activity spreading qualitatively describes the results of paradigms such as backward masking and binocular rivalry.
Language	English
Publishing date	2017-10
Publishing country	United States
Document type	Journal Article
ZDB-ID	1106647-7
ISSN	1090-2376 ; 1053-8100
ISSN (online)	1090-2376
ISSN	1053-8100
DOI	10.1016/j.concog.2017.08.008
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Article ; Online: Revisiting the Mechanisms of Charge Transport in Solutions of Redox-Active Molecules Using Computer Simulations: When and Why Do Analytical Theories Fail?

Perez Sirkin, Yamila A / Tagliazucchi, Mario

The journal of physical chemistry. B

2023 Volume 127, Issue 13, Page(s) 2968–2978

Abstract: ... electron-transfer rates, i.e., the most relevant conditions for energy-storage applications. Under these conditions ...

Abstract	Understanding charge transport is essential for the development of energy-storage applications. This work introduces a new theoretical methodology to model diffusive charge transport in solutions of redox-active molecules by combining Langevin dynamics for the spatial degrees of freedom and a master-equation formalism to describe the electron-hopping events between redox molecules. The model is used to analyze the effects of the concentration of the redox molecules and the strength of the intermolecular interactions on the charge-transport mechanism. In the past, the rate of charge transport has been modeled with the analytical Dahms-Ruff equation; however, this is a mean-field equation, whose range of validity has not been tested with less approximate theories. We show that the Dahms-Ruff equation fails to quantitatively predict the diffusion coefficient for charge transport for large concentrations of the redox species and high bimolecular electron-transfer rates, i.e., the most relevant conditions for energy-storage applications. Under these conditions, the diffusion coefficient for charge transport obtained from simulations is larger than that predicted from the Dahm-Ruff equation because of the formation of transient clusters of redox molecules. Also, intermolecular interactions, which are not taken into account by the Dahms-Ruff equation, play a central role in the charge transport of redox species. We show that the apparent diffusion coefficient experiences a maximum with respect to the strength of the intermolecular attractions. This maximum is traced back to the formation of clusters and their two opposite effects on the diffusion coefficient: electron hopping is fast within a cluster but inefficient between neighboring clusters.
Language	English
Publishing date	2023-03-23
Publishing country	United States
Document type	Journal Article
ISSN	1520-5207
ISSN (online)	1520-5207
DOI	10.1021/acs.jpcb.2c06956
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Article ; Online: Genomic and microenvironmental heterogeneity shaping epithelial-to-mesenchymal trajectories in cancer.

Malagoli Tagliazucchi, Guidantonio / Wiecek, Anna J / Withnell, Eloise / Secrier, Maria

Nature communications

2023 Volume 14, Issue 1, Page(s) 789

Abstract: ... hybrid E/M and mesenchymal phenotypes. We show that the hybrid state is relatively stable and linked ...

Abstract	The epithelial to mesenchymal transition (EMT) is a key cellular process underlying cancer progression, with multiple intermediate states whose molecular hallmarks remain poorly characterised. To fill this gap, we present a method to robustly evaluate EMT transformation in individual tumours based on transcriptomic signals. We apply this approach to explore EMT trajectories in 7180 tumours of epithelial origin and identify three macro-states with prognostic and therapeutic value, attributable to epithelial, hybrid E/M and mesenchymal phenotypes. We show that the hybrid state is relatively stable and linked with increased aneuploidy. We further employ spatial transcriptomics and single cell datasets to explore the spatial heterogeneity of EMT transformation and distinct interaction patterns with cytotoxic, NK cells and fibroblasts in the tumour microenvironment. Additionally, we provide a catalogue of genomic events underlying distinct evolutionary constraints on EMT transformation. This study sheds light on the aetiology of distinct stages along the EMT trajectory, and highlights broader genomic and environmental hallmarks shaping the mesenchymal transformation of primary tumours.
MeSH term(s)	Humans ; Epithelial-Mesenchymal Transition/genetics ; Neoplasms/genetics ; Neoplasms/pathology ; Antineoplastic Agents ; Phenotype ; Genomics ; Tumor Microenvironment/genetics
Chemical Substances	Antineoplastic Agents
Language	English
Publishing date	2023-02-11
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-36439-7
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Article ; Online: Entropy production of multivariate Ornstein-Uhlenbeck processes correlates with consciousness levels in the human brain.

Gilson, Matthieu / Tagliazucchi, Enzo / Cofré, Rodrigo

Physical review. E

2022 Volume 107, Issue 2-1, Page(s) 24121

Abstract: Consciousness is supported by complex patterns of brain activity which are indicative of irreversible nonequilibrium dynamics. While the framework of stochastic thermodynamics has facilitated the understanding of physical systems of this kind, its ... ...

Abstract	Consciousness is supported by complex patterns of brain activity which are indicative of irreversible nonequilibrium dynamics. While the framework of stochastic thermodynamics has facilitated the understanding of physical systems of this kind, its application to infer the level of consciousness from empirical data remains elusive. We faced this challenge by calculating entropy production in a multivariate Ornstein-Uhlenbeck process fitted to Functional magnetic resonance imaging brain activity recordings. To test this approach, we focused on the transition from wakefulness to deep sleep, revealing a monotonous relationship between entropy production and the level of consciousness. Our results constitute robust signatures of consciousness while also advancing our understanding of the link between consciousness and complexity from the fundamental perspective of statistical physics.
MeSH term(s)	Humans ; Consciousness ; Entropy ; Brain ; Wakefulness ; Thermodynamics
Language	English
Publishing date	2022-10-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	2844562-4
ISSN	2470-0053 ; 2470-0045
ISSN (online)	2470-0053
ISSN	2470-0045
DOI	10.1103/PhysRevE.107.024121
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Article ; Online: Predicting the outcome of psilocybin treatment for depression from baseline fMRI functional connectivity.

Copa, Débora / Erritzoe, David / Giribaldi, Bruna / Nutt, David / Carhart-Harris, Robin / Tagliazucchi, Enzo

Journal of affective disorders

2024 Volume 353, Page(s) 60–69

Abstract: Background: Psilocybin is a serotonergic psychedelic drug under assessment as a potential therapy for treatment-resistant and major depression. Heterogeneous treatment responses raise interest in predicting the outcome from baseline data.: Methods: A ...

Abstract	Background: Psilocybin is a serotonergic psychedelic drug under assessment as a potential therapy for treatment-resistant and major depression. Heterogeneous treatment responses raise interest in predicting the outcome from baseline data. Methods: A machine learning pipeline was implemented to investigate baseline resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI) as a predictor of symptom severity in psilocybin monotherapy for treatment-resistant depression (16 patients administered two 5 mg capsules followed by 25 mg, separated by one week). Generalizability was tested in a sample of 22 patients who participated in a psilocybin vs. escitalopram trial for moderate-to-severe major depression (two separate doses of 25 mg of psilocybin 3 weeks apart plus 6 weeks of daily placebo vs. two separate doses of 1 mg of psilocybin 3 weeks apart plus 6 weeks of daily oral escitalopram). The analysis was repeated using both samples combined. Results: Functional connectivity of visual, default mode and executive networks predicted early symptom improvement, while the salience network predicted responders up to 24 weeks after treatment (accuracy≈0.9). Generalization performance was borderline significant. Consistent results were obtained from the combined sample analysis. Fronto-occipital and fronto-temporal coupling predicted early and late symptom reduction, respectively. Limitations: The number of participants and differences between the two datasets limit the generalizability of the findings, while the lack of a placebo arm limits their specificity. Conclusions: Baseline neurophysiological measurements can predict the outcome of psilocybin treatment for depression. Future research based on larger datasets should strive to assess the generalizability of these predictions.
MeSH term(s)	Humans ; Psilocybin/pharmacology ; Psilocybin/therapeutic use ; Depression ; Escitalopram ; Magnetic Resonance Imaging ; Depressive Disorder, Major/diagnostic imaging ; Depressive Disorder, Major/drug therapy
Chemical Substances	Psilocybin (2RV7212BP0) ; Escitalopram (4O4S742ANY)
Language	English
Publishing date	2024-02-27
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	135449-8
ISSN	1573-2517 ; 0165-0327
ISSN (online)	1573-2517
ISSN	0165-0327
DOI	10.1016/j.jad.2024.02.089
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Article ; Online: Propofol Reversibly Attenuates Short-Range Microstate Ordering and 20 Hz Microstate Oscillations.

Hermann, Gesine / Tödt, Inken / Tagliazucchi, Enzo / Todtenhaupt, Inga Karin / Laufs, Helmut / von Wegner, Frederic

Brain topography

2024 Volume 37, Issue 2, Page(s) 329–342

Abstract: Microstate sequences summarize the changing voltage patterns measured by electroencephalography, using a clustering approach to reduce the high dimensionality of the underlying data. A common approach is to restrict the pattern matching step to local ... ...

Abstract	Microstate sequences summarize the changing voltage patterns measured by electroencephalography, using a clustering approach to reduce the high dimensionality of the underlying data. A common approach is to restrict the pattern matching step to local maxima of the global field power (GFP) and to interpolate the microstate fit in between. In this study, we investigate how the anesthetic propofol affects microstate sequence periodicity and predictability, and how these metrics are changed by interpolation. We performed two frequency analyses on microstate sequences, one based on time-lagged mutual information, the other based on Fourier transform methodology, and quantified the effects of interpolation. Resting-state microstate sequences had a 20 Hz frequency peak related to dominant 10 Hz (alpha) rhythms, and the Fourier approach demonstrated that all five microstate classes followed this frequency. The 20 Hz periodicity was reversibly attenuated under moderate propofol sedation, as shown by mutual information and Fourier analysis. Characteristic microstate frequencies could only be observed in non-interpolated microstate sequences and were masked by smoothing effects of interpolation. Information-theoretic analysis revealed faster microstate dynamics and larger entropy rates under propofol, whereas Shannon entropy did not change significantly. In moderate sedation, active information storage decreased for non-interpolated sequences. Signatures of non-equilibrium dynamics were observed in non-interpolated sequences, but no changes were observed between sedation levels. All changes occurred while subjects were able to perform an auditory perception task. In summary, we show that low dose propofol reversibly increases the randomness of microstate sequences and attenuates microstate oscillations without correlation to cognitive task performance. Microstate dynamics between GFP peaks reflect physiological processes that are not accessible in interpolated sequences.
MeSH term(s)	Humans ; Brain/physiology ; Propofol ; Electroencephalography ; Alpha Rhythm ; Cluster Analysis
Chemical Substances	Propofol (YI7VU623SF)
Language	English
Publishing date	2024-01-16
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1078442-1
ISSN	1573-6792 ; 0896-0267
ISSN (online)	1573-6792
ISSN	0896-0267
DOI	10.1007/s10548-023-01023-1
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Article ; Online: Orientational Pathways during Protein Translocation through Polymer-Modified Nanopores.

Gonzalez Solveyra, Estefania / Perez Sirkin, Yamila A / Tagliazucchi, Mario / Szleifer, Igal

ACS nano

2024 Volume 18, Issue 15, Page(s) 10427–10438

Abstract: Protein translocation through nanopores holds significant promise for applications in biotechnology, biomolecular analysis, and medicine. However, the interpretation of signals generated by the translocation of the protein remains challenging. In this ... ...

Abstract	Protein translocation through nanopores holds significant promise for applications in biotechnology, biomolecular analysis, and medicine. However, the interpretation of signals generated by the translocation of the protein remains challenging. In this way, it is crucial to gain a comprehensive understanding on how macromolecules translocate through a nanopore and to identify what are the critical parameters that govern the process. In this study, we investigate the interplay between protein charge regulation, orientation, and nanopore surface modifications using a theoretical framework that allows us to explicitly take into account the acid-base reactions of the titrable amino acids in the proteins and in the polyelectrolytes grafted to the nanopore surface. Our goal is to thoroughly characterize the translocation process of different proteins (GFP, β-lactoglobulin, lysozyme, and RNase) through nanopores modified with weak polyacids. Our calculations show that the charge regulation mechanism exerts a profound effect on the translocation process. The pH-dependent interactions between proteins and charged polymers within the nanopore lead to diverse free energy landscapes with barriers, wells, and flat regions dictating translocation efficiency. Comparison of different proteins allows us to identify the significance of protein isoelectric point, size, and morphology in the translocation behavior. Taking advantage of these insights, we propose pH-responsive nanopores that can load proteins at one pH and release them at another, offering opportunities for controlled protein delivery, separation, and sensing applications.
MeSH term(s)	Nanopores ; Polymers/chemistry ; Polyelectrolytes ; Proteins/chemistry ; Protein Transport
Chemical Substances	Polymers ; Polyelectrolytes ; Proteins
Language	English
Publishing date	2024-04-01
Publishing country	United States
Document type	Journal Article
ISSN	1936-086X
ISSN (online)	1936-086X
DOI	10.1021/acsnano.3c11318
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