Granger Causality among Graphs and Application to Functional Brain Connectivity in Autism Spectrum Disorder
Carregando...
Autores
Orientador
Co-orientadores
Citações na Scopus
Tipo de documento
Artigo Científico
Data
2021
Arquivos
Título da Revista
ISSN da Revista
Título do Volume
Resumo
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.
Palavras-chave
Titulo de periódico
Entropy
URL da fonte
Título de Livro
URL na Scopus
Idioma
Português
URL permanente
Notas
Membros da banca
Área do Conhecimento CNPQ
CIENCIAS EXATAS E DA TERRA::MATEMATICA::MATEMATICA APLICADA
CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA
CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAO
ENGENHARIAS::ENGENHARIA BIOMEDICA
CIENCIAS DA SAUDE
CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA
CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAO
ENGENHARIAS::ENGENHARIA BIOMEDICA
CIENCIAS DA SAUDE