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Forecasting brain activity based on models of spatiotemporal brain dynamics: A comparison of graph neural network architectures

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Wein, Simon ; Schüller, A. ; Tomé, A. M. ; Malloni, W. M. ; Greenlee, M. W. ; Lang, E. W.
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Date of publication of this fulltext: 28 Sep 2022 06:21


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 ...


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