Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms - Oku, Amanda Yumi Ambriola; Barreto, Candida; Bruneri, Guilherme; Brockington, Guilherme; Fujita, Andre; Sato, João Ricardo (Frontiers in Computational Neuroscience, 2022)
Hyperscanning is a promising tool for investigating the neurobiological underpinning of social interactions and affective bonds. Recently, graph theory measures, such as modularity, have been proposed for estimating the global synchronization between brains. This paper proposes the bootstrap modularity test as a way of determining whether a pair of brains is coactivated. This test is illustrated as a screening tool in an application to fNIRS data collected from teacher-child interaction. In this application, graph hub centrality measures identify that the dyad's synchronization is critically explained by the relation between teacher's language and number processing and the child's phonological processing.