Wein, Simon and Schueller, A. and Tome, A. M. and Malloni, W. M. and Greenlee, Mark W. and Lang, Elmar W. (2022) Forecasting brain activity based on models of spatiotemporal brain dynamics: A comparison of graph neural network architectures. NETWORK NEUROSCIENCE, 6 (3). pp. 665-701. ISSN 2472-1751,
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Comprehending the interplay between spatial and temporal characteristics of neural dynamics can contribute to our understanding of information processing in the human brain. Graph neural networks (GNNs) provide a new possibility to interpret graph-structured signals like those observed in complex brain networks. In our study we compare different spatiotemporal GNN architectures and study their ability to model neural activity distributions obtained in functional MRI (fMRI) studies. We evaluate the performance of the GNN models on a variety of scenarios in MRI studies and also compare it to a VAR model, which is currently often used for directed functional connectivity analysis. We show that by learning localized functional interactions on the anatomical substrate, GNN-based approaches are able to robustly scale to large network studies, even when available data are scarce. By including anatomical connectivity as the physical substrate for information propagation, such GNNs also provide a multimodal perspective on directed connectivity analysis, offering a novel possibility to investigate the spatiotemporal dynamics in brain networks.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | STATE FUNCTIONAL CONNECTIVITY; IN-DIFFUSION MRI; LOW-FREQUENCY; GRANGER CAUSALITY; SPHERICAL-DECONVOLUTION; FMRI; FLUCTUATIONS; TRACTOGRAPHY; ACQUISITION; STRATEGIES; Brain connectivity; Graph neural networks; Structure-function relationship; Directed connectivity |
| Subjects: | 100 Philosophy & psychology > 150 Psychology 500 Science > 570 Life sciences |
| Divisions: | Human Sciences > Institut für Psychologie > Lehrstuhl für Psychologie I (Allgemeine Psychologie I und Methodenlehre) - Prof. Dr. Mark W. Greenlee Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 10 Oct 2023 14:25 |
| Last Modified: | 10 Oct 2023 14:25 |
| URI: | https://pred.uni-regensburg.de/id/eprint/56456 |
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