ArticleNeuroImage2021
Inter-subject and inter-parcellation variability of resting-state whole-brain dynamical modeling.
Article in NeuroImage, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Effective workflow from multimodal MRI data to model-based prediction.Scientific reports · 2025Article
- Adolescent maturation of cortical excitation-inhibition ratio based on individualized biophysical network modeling.Science advances · 2025Article
- Structural Balance of Resting-state Brain Network in Attention Deficit Hyperactivity Disorder.Basic and clinical neuroscience · 2025Article
- Arbor-TVB: a novel multi-scale co-simulation framework with a case study on neural-level seizure generation and whole-brain propagation.Frontiers in computational neuroscience · 2025Article
- Article
- On the robustness of the emergent spatiotemporal dynamics in biophysically realistic and phenomenological whole-brain models at multiple network resolutions.Frontiers in network physiology · 2025Article
- Comparison of whole-brain task-modulated functional connectivity methods for fMRI task connectomics.Communications biology · 2024Article
- Comparison of whole-brain task-modulated functional connectivity methods for fMRI task connectomics.bioRxiv : the preprint server for biology · 2024Article
- Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics.Nature communications · 2024Article
- Review
- An exploratory computational analysis in mice brain networks of widespread epileptic seizure onset locations along with potential strategies for effective intervention and propagation control.Frontiers in computational neuroscience · 2024Article
- Temporal fingerprints of cortical gyrification in marmosets and humans.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Whole-brain dynamical modelling for classification of Parkinson's disease.Brain communications · 2023Article
- An atlas of trait associations with resting-state and task-evoked human brain functional organizations in the UK Biobank.Imaging neuroscience (Cambridge, Mass.) · 2023Article
- Enhanced simulations of whole-brain dynamics using hybrid resting-state structural connectomes.Frontiers in computational neuroscience · 2023Article
- Data and model considerations for estimating time-varying functional connectivity in fMRI.NeuroImage · 2022Article
- Towards an efficient validation of dynamical whole-brain models.Scientific reports · 2022Article
- A tale of two gradients: differences between the left and right hemispheres predict semantic cognition.Brain structure & function · 2022Article
- Pattern of frustration formation in the functional brain network.Network neuroscience (Cambridge, Mass.) · 2022Article
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Authors and funding
8 authors.
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Abstract
Modern approaches to investigate complex brain dynamics suggest to represent the brain as a functional network of brain regions defined by a brain atlas, while edges represent the structural or functional connectivity among them. This approach is also utilized for mathematical modeling of the resting-state brain dynamics, where the applied brain parcellation plays an essential role in deriving the model network and governing the modeling results. There is however no consensus and empirical evidence on how a given brain atlas affects the model outcome, and the choice of parcellation is still rather arbitrary. Accordingly, we explore the impact of brain parcellation on inter-subject and inter-parcellation variability of model fitting to empirical data. Our objective is to provide a comprehensive empirical evidence of potential influences of parcellation choice on resting-state whole-brain dynamical modeling. We show that brain atlases strongly influence the quality of model validation and propose several variables calculated from empirical data to account for the observed variability. A few classes of such data variables can be distinguished depending on their inter-subject and inter-parcellation explanatory power.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.