Author

E. Tagliazucchi

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Animal Behavior & Cognition· 1 Biophysics· 1 Neuroscience· 1 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:clustering· 2 Assay:imaging· 2 Approach:machine learning (classical)· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Approach:experimental assay· 1

Frequent Co-Authors

C. Pallavicini· 3 shared L. A. de la Fuente· 3 shared F. Carrillo· 2 shared F. Cavanna· 2 shared F. Zamberlan· 2 shared S. Muller· 2 shared A. M. Garcia· 1 shared A. Sanchez Ferran· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 32 mutual co-author links

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3 shared papersAnimal Behavior & Cognition

C. Pallavicini

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Author profile →

4 papers

Recent·Most cited

Acute effects of psilocybin on the dynamics of gaze fixations during visual aesthetic perception

S. Muller, F. Cavanna, L. A. de la Fuente, N. Bruno, T. D'Amelio, C. Pallavicini, E. Tagliazucchi

This study examines how psilocybin affects eye movements during aesthetic perception, finding that high doses lead to more localized visual exploration and reduced fixation entropy.

bioRxiv · Oct 27, 2023Animal Behavior & Cognition

Natural language signatures of psilocybin microdosing

C. Sanz, F. Cavanna, S. Muller, L. A. de la Fuente, F. Zamberlan, M. Palmucci, L. Janeckova, M. Kuchar, F. Carrillo, A. M. Garcia, C. Pallavicini, E. Tagliazucchi

This study uses natural language analysis to detect psilocybin microdosing effects, finding significant differences in speech metrics between active and placebo conditions.

bioRxiv · Feb 20, 2022Pharmacology & Toxicology

Data augmentation based on dynamical systems for the classification of brain states

Y. Sanz Perl, C. Pallacivini, I. Perez Ipina, M. L. Kringelbach, G. Deco, H. Laufs, E. Tagliazucchi

This paper uses whole-brain computational models to generate synthetic data for brain state classification, achieving comparable accuracy to empirical data.

bioRxiv · Jan 8, 2020Biophysics

Over eight hundred cannabis strains characterized by the relationship between their psychoactive effects, perceptual profiles, and chemical compositions

L. A. de la Fuente, F. Zamberlan, A. Sanchez Ferran, F. Carrillo, E. Tagliazucchi, C. Pallavicini

The paper characterizes over 800 cannabis strains by linking psychoactive effects, perceptual profiles, and chemical compositions using machine learning and user-reported data.

bioRxiv · Sep 8, 2019 · PreprintNeuroscience