Ghent University Academic Bibliography

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Hemodynamic response function (HRF) variability confounds resting-state fMRI functional connectivity

Rangaprakash Deshpande, Guo-Rong Wu, Daniele Marinazzo (UGent) , Xiaoping Hu and Gopikrishna Deshpande

(2018) MAGNETIC RESONANCE IN MEDICINE.
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- journalArticle
- open access
Predicting functional networks from region connectivity profiles in task-based versus resting-state fMRI data

Javier Rasero, Hannelore Aerts (UGent) , Marlis Ontivero Ortega, Jesus M. Cortes, Sebastiano Stramaglia and Daniele Marinazzo (UGent)

(2018) PLOS ONE. 13(11).
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Dilution of ferromagnets via a random graph-based strategy

Marco Alberto Javarone and Daniele Marinazzo (UGent)

(2018) COMPLEXITY.
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- journalArticle
- open access
Connectome sorting by Consensus Clustering increases separability in group neuroimaging studies

Javier Rasero, Ibai Diez, Jesus M Cortes, Daniele Marinazzo (UGent) and Sebastiano Stramaglia

(2018) Network Neuroscience. p.1-36
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- journalArticle
- open access
Modeling brain dynamics in brain tumor patients using the virtual brain

Hannelore Aerts (UGent) , Michael Schirner, Ben Jeurissen, Dirk Van Roost (UGent) , Eric Achten (UGent) , Petra Ritter and Daniele Marinazzo (UGent)

(2018) ENEURO. 5(3).
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- journalArticle
Parameterized hemodynamic response function data of healthy individuals obtained from resting-state functional MRI in a 7T MRI scanner

D. Rangaprakash, Guo-Rong Wu, Daniele Marinazzo (UGent) , Xiaoping Hu and Gopikrishna Deshpande

(2018) DATA IN BRIEF. 17. p.1175-1179
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- journalArticle
- A1
Variability and reliability of effective connectivity within the core default mode network: A multi-site longitudinal spectral DCM study

Hannes Almgren (UGent) , Frederik Van de Steen (UGent) , Simone Kühn, Adeel Razi, Karl Friston and Daniele Marinazzo (UGent)

(2018) NeuroImage.
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- journalArticle
- A2
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Consensus clustering approach to group brain connectivity matrices

Javier Rasero, Mario Pellicoro, Leonardo Angelini, Jesus M Cortes, Daniele Marinazzo (UGent) and Sebastiano Stramaglia

(2017) NETWORK NEUROSCIENCE. 1(3). p.242-253
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- journalArticle
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Multiscale granger causality

Luca Faes, Giandomenico Nollo, Sebastiano Stramaglia and Daniele Marinazzo (UGent)

(2017) PHYSICAL REVIEW E . 96(4).
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- A1
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Ising model with conserved magnetization on the human connectome : implications on the relation structure-function in wakefulness and anesthesia

S Stramaglia, M Pellicoro, L. Angelini, E Amico, H Aerts, JM Cortés, S Laureys and Daniele Marinazzo (UGent)

(2017) CHAOS. 27(4).

Academic Bibliography

Hemodynamic response function (HRF) variability confounds resting-state fMRI functional connectivity

Predicting functional networks from region connectivity profiles in task-based versus resting-state fMRI data

Dilution of ferromagnets via a random graph-based strategy

Connectome sorting by Consensus Clustering increases separability in group neuroimaging studies

Modeling brain dynamics in brain tumor patients using the virtual brain

Parameterized hemodynamic response function data of healthy individuals obtained from resting-state functional MRI in a 7T MRI scanner

Variability and reliability of effective connectivity within the core default mode network: A multi-site longitudinal spectral DCM study

Consensus clustering approach to group brain connectivity matrices

Multiscale granger causality

Ising model with conserved magnetization on the human connectome : implications on the relation structure-function in wakefulness and anesthesia

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