daniele marinazzo
Affiliations: | 2003-2008 | Physics | University of Bari, Italy |
| 2008-2001 | CNRS, Paris, Île-de-France, France | ||
| 2011- | Data Analysis | Ghent University, Ghent, Vlaanderen, Belgium |
Area:
computational neuroscience, statistical physics, complex systems, networksWebsite:
https://users.ugent.be/~dmarinaz/Google:
"https://scholar.google.com/citations?user=OJbWSLoAAAAJ&hl=en"Mean distance: 106866
Parents
Sign in to add mentor| Sebastiano Stramaglia | grad student | 2003-2007 | University of Bari |
| Lyle J. GRAHAM | post-doc | 2008-2011 |
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Publications
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| Nuzzi D, Pellicoro M, Angelini L, et al. (2020) Synergistic information in a dynamical model implemented on the human structural connectome reveals spatially distinct associations with age. Network Neuroscience (Cambridge, Mass.). 4: 910-924 |
| Stramaglia S, Scagliarini T, Daniels BC, et al. (2020) Quantifying Dynamical High-Order Interdependencies From the O-Information: An Application to Neural Spiking Dynamics. Frontiers in Physiology. 11: 595736 |
| Scagliarini T, Faes L, Marinazzo D, et al. (2020) Synergistic Information Transfer in the Global System of Financial Markets. Entropy (Basel, Switzerland). 22 |
| Aerts H, Schirner M, Dhollander T, et al. (2020) Modeling brain dynamics after tumor resection using The Virtual Brain. Neuroimage. 213: 116738 |
| Colenbier N, Van de Steen F, Uddin LQ, et al. (2020) Disambiguating the role of blood flow and global signal with partial information decomposition. Neuroimage. 116699 |
| Valdés-Sosa M, Ontivero-Ortega M, Iglesias-Fuster J, et al. (2020) Objects seen as scenes: Neural circuitry for attending whole or parts. Neuroimage. 116526 |
| Nuzzi D, Pellicoro M, Angelini L, et al. (2020) Synergistic information in a dynamical model implemented on the human structural connectome reveals spatially distinct associations with age Network Neuroscience. 4: 910-924 |
| Krohova J, Faes L, Czippelova B, et al. (2019) Multiscale Information Decomposition Dissects Control Mechanisms of Heart Rate Variability at Rest and During Physiological Stress. Entropy (Basel, Switzerland). 21 |
| Almgren H, Van de Steen F, Razi A, et al. (2019) The effect of global signal regression on DCM estimates of noise and effective connectivity from resting state fMRI. Neuroimage. 116435 |
| Van de Steen F, Krebs RM, Colenbier N, et al. (2019) Effective connectivity modulations related to win and loss outcomes. Neuroimage. 116369 |