Hauptseite > Publikationsdatenbank > Dynamic causal modeling computational pipeline for resting-state fMRI data: the structure and main modules for DCM and PEB analysis > print

001     1017429
005     20231027201848.0
024 7 _ |a 10.34734/FZJ-2023-04125
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037 _ _ |a FZJ-2023-04125
100 1 _ |a Silchenko, Alexander
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111 2 _ |a INM Retreat
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|d 2023-10-17 - 2023-10-18
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245 _ _ |a Dynamic causal modeling computational pipeline for resting-state fMRI data: the structure and main modules for DCM and PEB analysis
260 _ _ |c 2023
336 7 _ |a Conference Paper
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336 7 _ |a INPROCEEDINGS
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500 _ _ |a Acknowledgments: This work was supported by the Deutsche Forschungsgemeinschaft (DFG, EI 816/11-1), the National Institute of Mental Health (R01-MH074457), the Helmholtz Portfolio Theme Supercomputing and Modeling for the Human Brain, and the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreements 720270 (HBP SGA1), 785907 (HBP SGA2), and 826421 (VirtualBrainCloud).
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700 1 _ |a Bettazzi, Edoardo
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700 1 _ |a Eickhoff, Simon
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700 1 _ |a Tahmasian, Masoud
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700 1 _ |a Hoffstaedter, Felix
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856 4 _ |u https://juser.fz-juelich.de/record/1017429/files/Silchenko_Poster_INM_IBI_Retreat_2023.pdf
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