Author

M. L. Kringelbach

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

Biology Disciplines

Click to filter author papers

Biophysics· 2 Physiology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 3 Approach:statistical model· 3 Research Focus:clustering· 2 Approach:deep learning· 2 Assay:electrophysiology· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Research Focus:dimensionality reduction· 1

Frequent Co-Authors

G. Deco· 2 shared A. Gazzaley· 1 shared A. Goriely· 1 shared A. I. Luppi· 1 shared C. Pallacivini· 1 shared C. Timmermann· 1 shared D. Bor· 1 shared D. Candia-Rivera· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBiophysics

G. Deco

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Multilevel irreversibility reveals higher-order organisation of non-equilibrium interactions in human brain dynamics

R. Nartallo-Kaluarachchi, L. Bonetti, G. Fernandez-Rubio, P. Vuust, G. Deco, M. L. Kringelbach, R. Lambiotte, A. Goriely

This paper introduces a framework to quantify irreversibility in brain network dynamics across multiple levels and identifies higher-order organizational patterns in human brain interactions.

bioRxiv · May 2, 2024 · PreprintBiophysics

The entropic heart: Tracking the psychedelic state via heart rate dynamics

F. E. Rosas, P. A. M. Mediano, C. Timmermann, A. I. Luppi, D. Candia-Rivera, R. Abbasi-Asl, A. Gazzaley, M. L. Kringelbach, S. D. Muthukumaraswamy, D. Bor, S. Garfinkel, R. Carhart-Harris

This paper uses Bayesian methods to analyze heart rate dynamics during psychedelic experiences, finding increased entropy and variability linked to subjective and neural effects.

bioRxiv · Nov 7, 2023 · PreprintPhysiology

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