TY  - JOUR
AU  - Tadić, Bosiljka
AU  - Anđelković, Miroslav
AU  - Boshkoska, Biljana Mileva
AU  - Levnajić, Zoran
PY  - 2016
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/1322
AB  - Human behaviour in various circumstances mirrors the corresponding brain connectivity patterns, which are suitably represented by functional brain networks. While the objective analysis of these networks by graph theory tools deepened our understanding of brain functions, the multi-brain structures and connections underlying human social behaviour remain largely unexplored. In this study, we analyse the aggregate graph that maps coordination of EEG signals previously recorded during spoken communications in two groups of six listeners and two speakers. Applying an innovative approach based on the algebraic topology of graphs, we analyse higher-order topological complexes consisting of mutually interwoven cliques of a high order to which the identified functional connections organise. Our results reveal that the topological quantifiers provide new suitable measures for differences in the brain activity patterns and inter-brain synchronisation between speakers and listeners. Moreover, the higher topological complexity correlates with the listeners concentration to the story, confirmed by self-rating, and closeness to the speakers brain activity pattern, which is measured by network-to-network distance. The connectivity structures of the frontal and parietal lobe consistently constitute distinct clusters, which extend across the listeners group. Formally, the topology quantifiers of the multi-brain communities exceed the sum of those of the participating individuals and also reflect the listeners rated attributes of the speaker and the narrated subject. In the broader context, the presented study exposes the relevance of higher topological structures ( besides standard graph measures) for characterising functional brain networks under different stimuli.
T2  - PLOS One
T1  - Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications
VL  - 11
IS  - 11
DO  - 10.1371/journal.pone.0166787
ER  - 

@article{
author = "Tadić, Bosiljka and Anđelković, Miroslav and Boshkoska, Biljana Mileva and Levnajić, Zoran",
year = "2016",
abstract = "Human behaviour in various circumstances mirrors the corresponding brain connectivity patterns, which are suitably represented by functional brain networks. While the objective analysis of these networks by graph theory tools deepened our understanding of brain functions, the multi-brain structures and connections underlying human social behaviour remain largely unexplored. In this study, we analyse the aggregate graph that maps coordination of EEG signals previously recorded during spoken communications in two groups of six listeners and two speakers. Applying an innovative approach based on the algebraic topology of graphs, we analyse higher-order topological complexes consisting of mutually interwoven cliques of a high order to which the identified functional connections organise. Our results reveal that the topological quantifiers provide new suitable measures for differences in the brain activity patterns and inter-brain synchronisation between speakers and listeners. Moreover, the higher topological complexity correlates with the listeners concentration to the story, confirmed by self-rating, and closeness to the speakers brain activity pattern, which is measured by network-to-network distance. The connectivity structures of the frontal and parietal lobe consistently constitute distinct clusters, which extend across the listeners group. Formally, the topology quantifiers of the multi-brain communities exceed the sum of those of the participating individuals and also reflect the listeners rated attributes of the speaker and the narrated subject. In the broader context, the presented study exposes the relevance of higher topological structures ( besides standard graph measures) for characterising functional brain networks under different stimuli.",
journal = "PLOS One",
title = "Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications",
volume = "11",
number = "11",
doi = "10.1371/journal.pone.0166787"
}

Tadić, B., Anđelković, M., Boshkoska, B. M.,& Levnajić, Z.. (2016). Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications. in PLOS One, 11(11).
https://doi.org/10.1371/journal.pone.0166787

Tadić B, Anđelković M, Boshkoska BM, Levnajić Z. Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications. in PLOS One. 2016;11(11).
doi:10.1371/journal.pone.0166787 .

Tadić, Bosiljka, Anđelković, Miroslav, Boshkoska, Biljana Mileva, Levnajić, Zoran, "Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications" in PLOS One, 11, no. 11 (2016),
https://doi.org/10.1371/journal.pone.0166787 . .