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| Hauptseite > Publikationsdatenbank > Optimizing Current Imaging Pipelines by Whole-Brain Dynamical Models |
| Hauptseite > Publikationsdatenbank > Optimizing Current Imaging Pipelines by Whole-Brain Dynamical Models |
| Talk (non-conference) (Invited) | FZJ-2022-00494 |
2021
Abstract: Investigation of the resting-state brain dynamics involves mathematical modeling of brain activity by whole-brain dynamical models. The structural and functionalbrain connectomes extracted from the neuroimaging data are essentially employed for the model derivation and validation. At this the brain is represented as afunctional network of brain regions defined by a brain atlas (or brain parcellation), while edges represent the structural or functional connectivity among them.There is however no consensus and golden standard for the approaches and parameters of the neuroimaging data processing, which in most cases remain at the levelof best practice. In this project we investigate how such parameters of the data processing can influence the modeling results. In particular, we considered severalbrain parcellations and densities of the whole-brain tractography to evaluate the inter-subject and inter-parcellation variability of the model fitting and itsdependence on a few indices calculated from empirical data. Such data indices can be used to accounting for the variation of the modeling results across simulationconditions and individual subjects, which can help to find optimal data processing and mechanisms for improved personalized modeling of the resting-state braindynamics.
Keyword(s): Health and Life (1st) ; Others (2nd) ; Medicine (2nd)
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