Journal
ENTROPY
Volume 23, Issue 9, Pages -Publisher
MDPI
DOI: 10.3390/e23091204
Keywords
Granger causality; random graphs; spectral radius; brain connectivity; autism spectrum disorder
Categories
Funding
- CAPES [001]
- FAPESP [2018/21934-5, 2018/04654-9]
- CNPq [303855/2019-3]
- Alexander von Humboldt Foundation
- Academy of Medical Sciences-Newton Fund
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This study focuses on inferring Granger causality between networks' time series to understand information flow, proposing a theoretical framework for modeling time-varying graphs, showing that the spectral radius can be a reasonable estimate of some random graph model parameters, and demonstrating differences in G-causality intensity between brain hemispheres of controls and children diagnosed with ASD.
Graphs/networks have become a powerful analytical approach for data modeling. Besides, with the advances in sensor technology, dynamic time-evolving data have become more common. In this context, one point of interest is a better understanding of the information flow within and between networks. Thus, we aim to infer Granger causality (G-causality) between networks' time series. In this case, the straightforward application of the well-established vector autoregressive model is not feasible. Consequently, we require a theoretical framework for modeling time-varying graphs. One possibility would be to consider a mathematical graph model with time-varying parameters (assumed to be random variables) that generates the network. Suppose we identify G-causality between the graph models' parameters. In that case, we could use it to define a G-causality between graphs. Here, we show that even if the model is unknown, the spectral radius is a reasonable estimate of some random graph model parameters. We illustrate our proposal's application to study the relationship between brain hemispheres of controls and children diagnosed with Autism Spectrum Disorder (ASD). We show that the G-causality intensity from the brain's right to the left hemisphere is different between ASD and controls.
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